Summary of your 'study carrel' ============================== This is a summary of your Distant Reader 'study carrel'. The Distant Reader harvested & cached your content into a collection/corpus. It then applied sets of natural language processing and text mining against the collection. The results of this process was reduced to a database file -- a 'study carrel'. The study carrel can then be queried, thus bringing light specific characteristics for your collection. These characteristics can help you summarize the collection as well as enumerate things you might want to investigate more closely. Eric Lease Morgan May 27, 2019 Number of items in the collection; 'How big is my corpus?' ---------------------------------------------------------- 711 Average length of all items measured in words; "More or less, how big is each item?" ------------------------------------------------------------------------------------ 799 Average readability score of all items (0 = difficult; 100 = easy) ------------------------------------------------------------------ 6 Top 50 statistically significant keywords; "What is my collection about?" ------------------------------------------------------------------------- 273 DOI 172 Comput 69 Proceedings 59 model 52 Computational 42 Linguistics 37 Conference 31 network 27 word 22 IEEE 19 image 17 datum 17 LSTM 16 internet 15 system 15 Proc 14 table 14 language 14 IPV9 14 Fig 13 feature 13 Network 13 CNN 12 web 12 PMC 11 topic 11 Figure 11 ACM 10 user 10 algorithm 10 Wikipedia 10 POS 10 GPU 10 Association 9 figure 9 address 9 University 9 SVM 9 RNN 9 Language 8 software 8 node 8 Twitter 8 International 7 time 7 relation 7 event 7 Python 6 sentence 6 sense Top 50 lemmatized nouns; "What is discussed?" --------------------------------------------- 20620 model 17891 datum 12608 % 12457 network 11580 system 10971 word 10818 method 9694 time 9290 number 9190 result 9061 feature 8107 information 7608 set 7415 value 6964 algorithm 6829 table 6377 approach 6282 analysis 6181 work 5958 task 5881 user 5775 figure 5721 performance 5599 language 5545 example 5447 study 5426 function 5328 case 5243 size 5108 level 5086 paper 5056 dataset 5013 type 4962 image 4826 node 4770 problem 4722 process 4587 training 4326 experiment 4196 software 4178 research 4084 structure 4079 sentence 4047 application 3945 test 3937 state 3798 data 3741 parameter 3737 order 3725 point Top 50 proper nouns; "What are the names of persons or places?" -------------------------------------------------------------- 21727 al 17930 . 13410 et 13290 DOI 7957 peerj 6914 PeerJ 6799 Sci 6497 Comput 4958 M 4359 � 4313 − 4078 S 3877 A 3851 J 3799 International 3797 C 3680 Journal 3417 Conference 3343 IEEE 2656 Computational 2573 T 2498 Figure 2460 University 2398 K 2385 Y 2318 Linguistics 2301 Proceedings 2289 Fig 2282 D 2247 M. 2243 L 2231 Association 2140 R 2113 J. 2102 Science 2083 Computer 2078 B 2046 Network 2027 F 1983 N 1949 j 1946 e 1876 s 1867 Research 1824 ACM 1771 m 1771 S. 1750 P 1725 Language 1724 algorithm Top 50 personal pronouns nouns; "To whom are things referred?" ------------------------------------------------------------- 35157 we 16578 it 5564 they 5019 i 2657 them 1046 you 1044 us 819 he 588 itself 502 one 312 themselves 278 me 229 she 178 him 83 em 79 http://www.bmw.com/com/en/insights/technology/connecteddrive/2013/a_to_z/index.html 70 λ 62 ours 51 de- 49 u 44 http://dl.acm.org/citation.cfm?id=1855768.1855772 41 α 40 n 33 ourselves 32 s 31 ’s 31 her 28 y 25 us- 21 theirs 20 toki 17 mine 16 himself 15 ui 15 ia 13 wr 13 myself 12 w′ 11 yt 11 ti 10 mj 10 in- 10 # 9 hi- 9 di- 8 δ∗c 8 http://creativecommons.org/licenses/by/4.0/ 8 herself 7  7 π Top 50 lemmatized verbs; "What do things do?" --------------------------------------------- 143062 be 28653 use 19537 have 13002 base 9484 show 7808 do 5125 provide 5109 propose 4894 give 4862 follow 4523 find 4446 perform 4423 make 4409 include 4147 learn 3825 represent 3794 compare 3619 see 3526 consider 3399 obtain 3325 generate 3295 define 3240 describe 3105 train 3068 set 2997 take 2991 present 2969 apply 2886 improve 2878 contain 2794 require 2582 allow 2563 identify 2549 need 2476 select 2463 create 2409 evaluate 2312 increase 2240 achieve 2213 page 2196 compute 2164 predict 2157 add 2136 accord 2098 indicate 2002 analyze 1999 reduce 1988 extract 1987 produce 1967 relate Top 50 lemmatized adjectives and adverbs; "How are things described?" --------------------------------------------------------------------- 14644 not 8426 also 8391 more 7995 - 7503 other 7083 different 6565 such 6533 only 6092 high 6024 well 5593 first 5038 then 4960 large 4883 same 4207 false 4191 new 3991 most 3954 however 3768 true 3673 good 3642 available 3304 low 3099 small 2918 many 2864 non 2802 full 2799 semantic 2753 e.g. 2717 specific 2620 as 2583 similar 2581 single 2526 neural 2472 possible 2345 social 2311 therefore 2308 thus 2280 very 2258 second 2168 multiple 2073 several 2073 random 2012 average 1989 real 1966 important 1944 multi 1933 even 1911 human 1851 simple 1842 further Top 50 lemmatized superlative adjectives; "How are things described to the extreme?" ------------------------------------------------------------------------- 2476 good 1432 most 780 high 623 least 413 large 336 Most 279 low 267 near 212 bad 199 close 187 small 183 short 106 late 90 simple 73 big 69 long 63 strong 54 great 46 Least 37 fast 35 early 27 http://www.w3.org/tr/xmlhttprequ 17 weak 17 old 17 easy 15 topmost 15 dense 10 ter 8 wide 8 holy 8 hard 7 new 7 furth 7 farth 6 heavy 6 e 6 deep 5 steep 5 slow 5 poor 5 lb 4 thin 4 rich 4 http://dx.doi.org/10.7717/peerj-cs.257 4 few 4 cheap 3  3 unitt 3 g 3 fine Top 50 lemmatized superlative adverbs; "How do things do to the extreme?" ------------------------------------------------------------------------ 2559 most 395 least 214 well 55 highest 6 x 6 greatest 5 worst 3 lowest 2 long 2 hard 2 fast 1 β∗ 1 x|β 1 transcriptome 1 text.2 1 shortest 1 s1.modest 1 near 1 mrnas 1 llkknanaext 1 j)}18 1 easiest 1 base.1 1 aa2—no Top 50 Internet domains; "What Webbed places are alluded to in this corpus?" ---------------------------------------------------------------------------- 16042 dx.doi.org 7378 peerj.com 3161 doi.org 1930 github.com 1491 dl.acm.org 957 www.w3.org 897 www.vosviewer.com 897 creativecommons.org 709 www.semanticsoftware.info 436 arxiv.org 324 www.nime.org 316 n2t.net 314 ec.bioscientifica.com 271 papers.nips.cc 266 www.conti-online.com 256 ccl.northwestern.edu 240 www.media.volvocars.com 237 ieeexplore.ieee.org 234 repository.tudelft.nl 210 www.ics.uci.edu 204 tools.ietf.org 200 purl.org 196 www.creativecommons.org 195 thomsonreuters.com 193 agreeordie.com 183 www.ietf.org 183 www.bmw.com 178 www2.mercedes-benz.co.uk 176 doi 175 www.force11.org 170 en.wikipedia.org 168 www.usenix.org 161 snap.stanford.edu 156 googleblog.blogspot.com 155 www.sdn.sap.com 152 lirias.kuleuven.be 145 www.ncbi.nlm.nih.gov 142 www.mitpressjournals.org 141 security.stackexchange.com 137 aisel.aisnet.org 133 www.attana.com 128 code.enthought.com 125 cnets.indiana.edu 124 joinup.ec.europa.eu 123 www.informationweek.com 121 www.nytimes.com 120 blogs.msdn.com 119 jena.apache.org 117 www.slate.com 117 www.aclweb.org Top 50 URLs; "What is hyperlinked from this corpus?" ---------------------------------------------------- 3441 http://peerj.com 3255 http://peerj.com/computer-science/ 562 http://peerj.com/academic-boards/editors/ 521 http://www.semanticsoftware.info/semantic-scientific-literature-peerj-2015-supplements 410 http://creativecommons.org/licenses/by/4.0/ 314 http://ec.bioscientifica.com 208 http://creativecommons.org/licenses/by-nc/4.0/ 203 http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/mendeley/fig6_map.txt&network=http://www.leydesdorff.net/mendeley/fig6_net.txt&n_lines=10000&label_size=1.0&label_size_variation=0.34 203 http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/mendeley/fig5_map.txt&network=http://www.leydesdorff.net/mendeley/fig5_net.txt&n_lines=10000&label_size=1.0&label_size_variation=0.34 196 http://www.creativecommons.org/licenses/by/4.0/ 177 http://www2.mercedes-benz.co.uk/content/unitedkingdom/mpc/mpc_unitedkingdom_website/en/home_mpc/passengercars/home/corporate_sales0/fleet/leasing/our_advantages/Safety.0009.html 176 http://doi 172 http://www.media.volvocars.com/global/en-gb/media/pressreleases/49875/volvo-cars-reveals-world-class-safety-and-support-features-to-be-introduced-in-the-all-new-xc90-in-2 168 http://creativecommons.org/licenses/by-nc-nd/4.0/ 162 http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/mendeley/fig2_map.txt&network=http://www.leydesdorff.net/mendeley/fig2_net.txt&n_lines=10000 162 http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/mendeley/fig1_map.txt&network=http://www.leydesdorff.net/mendeley/fig1_net.txt&n_lines=10000 161 http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/mendeley/fig3_map.txt&network=http://www.leydesdorff.net/mendeley/fig3_net.txt&n_lines=1000 154 http://www.sdn.sap.com/irj/scn/go/portal/prtroot/docs/library/uuid/20c957bc-01bb-2c10-0bb1-ed8c458b5b09?QuickLink=index&overridelayout=true&45896020704110 149 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6280217&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6280217 143 http://www.conti-online.com/www/pressportal_com_en/themes/press_releases/1_topics/automated_driving_en/pr_2012_12_18_automated_driving_en.html 133 http://dx.doi.org/10.7717/ 132 http://www.attana.com/wp-content/uploads/2013/02/TN03-01-Immobilization-of-Antibodies-on-the-Attana-Carboxyl-Sensor-Chip-Surface.pdf 123 http://joinup.ec.europa.eu/asset/dcat_application_profile/asset_release/dcat-application-profile-data-portals-europe-final 123 http://cnets.indiana.edu/groups/nan/webtraffic/click-dataset/ 122 http://www.informationweek.com/mobile/mobile-devices/ces-2012-vmware-shows-android-based-virtual-machines/d/d-id/1102135? 122 http://www.conti-online.com/www/pressportal_com_en/themes/initiatives/channel_mobility_study_en/ov_mobility_study2013_en/ 121 http://repository.tudelft.nl/assets/uuid:c34edcab-2734-4cd9-b060-67371eb3bab0/Supplementary_Material_Gerhard_Marquart.zip 117 http://www.slate.com/articles/technology/technology/2014/10/google_self_driving_car_it_may_never_actually_happen.html 115 http://www.wellcome.ac.uk/stellent/groups/corporatesite/@policy_communications/documents/web_document/wtp051762.PDF 115 http://blogs.msdn.com/b/vcblog/archive/2014/12/08/visual-studio-2015-preview-work-in-progress-security-feature.aspx 112 http://thomsonreuters.com/en/products-services/pharma-life-sciences/life-science-research/world-drug-index.html/ 112 http://repository.tudelft.nl/assets/uuid:c34edcab-2734-4cd9-b060-67371eb3bab0/Thesis_Report_Gerhard_Marquart.pdf 110 http://www.nature.com/sdata/data-policies/repositories 106 http://creativecommons.org/publicdomain/zero/1.0/ 103 http://www.datacenterknowledge.com/archives/2008/09/24/microsoft-uses-solar-panels-in-new-data-center/ 102 http://www.gov.uk/government/uploads/system/uploads/attachment_data/file/370866/T4_Guidance_11-14.pdf 102 http://blog.trendmicro.com/trendlabs-security-intelligence/exploring-control-flow-guard-in-windows-10/ 100 http://www.force11.org/datacitationimplementation 99 http://www.eurofot-ip.eu/download/library/deliverables/eurofotsp120121212v11dld113_final_report.pdf 99 http://owners.honda.com/vehicles/information/2014/Accord-Coupe/features/Forward-Collision-Warning/3 98 http://www.bmw.com/com/en/newvehicles/x/x5/2013/showroom/driver_assistance/park_assistant.html#t=l 97 http://www.cumminspower.com/www/literature/technicalpapers/PT-9019-Cell-Tower-Applications-en.pdf 96 http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks 95 http://www.mscience.com.au/upload/pages/fortebio/octet_platform_brochure_low-rez.pdf?1439858924 94 http://www.bsi.bund.de/cae/servlet/contentblob/471456/publicationFile/30746/standard_1004.pdf 93 http://www.daimler.com/dccom/0-5-1210218-1-1210321-1-0-0-1210228-0-0-135-0-0-0-0-0-0-0-0.html 92 http://dx.doi.org/10.6084/m9.figshare.1515944 91 http://github.com/geojson/geojson-ld/blob/8f08cf2df2e61de3a666ed90be43a14eada4cc03/time.md 91 http://github.com/fakenmc/pphpc/tree/netlogo 91 http://code.enthought.com/projects/traits/docs/html/tutorials/traits_ui_scientific_app.html Top 50 email addresses; "Who are you gonna call?" ------------------------------------------------- 25 forcnet@googlegroups.com 19 ferrarae@isi.edu 12 openaccess@ed.ac.uk 7 xusp686@163.com 7 mlap@inf.ed.ac.uk 7 alika_wang@mail.ru 7 13386036170@189.cn 6 wjg_xit@126.com 6 563937848@qq.com 5 yoav.goldberg@gmail.com 5 yangyh26@qq.com 5 oms@bsut.by 5 mcjzp139@139.com 5 liu.bao.long@hotmail.com 5 berenger.bramas@inria.fr 5 1341369601@qq.com 4 wzhsh1681@163.com 4 sunhong@usst.edu.cn 4 steedman@inf.ed.ac.uk 4 schleicher@dsg.tuwien.ac.at 4 sateli@semanticsoftware.info 4 michal.rozenwald@gmail.com 4 lextoet@gmail.com 4 ivan.baxter@ars.usda.gov 4 haoqili@usc.edu 4 elsadih@wit.edu 4 835092445@qq.com 4 498194312@qq.com 4 407171251@qq.com 4 277019826@qq.com 3 yujun@xatu.edu.cn 3 xiaomeibai@outlook.com 3 tpataky@shinshu-u.ac.jp 3 szenasi.sandor@nik.uni-obuda.hu 3 subukata@cs.osakafu-u.ac.jp 3 siva.reddy@ed.ac.uk 3 roiri@ie.technion.ac.il 3 r-ghavami@sbu.ac.ir 3 mbiro@ulb.ac.be 3 kiattisak.m@rsu.ac.th 3 kathpaliaaditi@gmail.com 3 jason.saleem@louisville.edu 3 inquiries@cislmu.org 3 ihsanalichd@siswa.um.edu.my 3 frank.foerster@uni-wuerzburg.de 3 evangelia.zacharaki@centralesupelec.fr 3 dariuszplewczynski@gmail.com 3 cyw901@163.com 3 chensp@usst.edu.cn 3 alk23@cam.ac.uk Top 50 positive assertions; "What sentences are in the shape of noun-verb-noun?" ------------------------------------------------------------------------------- 48 data is available 43 model does not 32 data are available 29 results are not 26 model is able 23 algorithm obtained values 23 approach does not 23 method does not 22 model is also 22 models do not 21 algorithm does not 20 model is not 19 approach is not 18 work is also 16 features are not 16 method is not 16 model is more 16 system does not 16 systems do not 14 algorithm is not 14 data are not 14 data is not 14 methods do not 13 approach is also 13 models are also 12 information is available 12 information is not 12 method is more 12 methods are not 11 algorithm is able 11 algorithm is better 11 network based language 11 results are very 11 system is not 11 work is not 10 data set gsmn 10 method is able 10 model performs better 10 network is not 10 results are available 10 users do not 10 values are not 9 approach is similar 9 data using spark 9 model is better 9 results are also 9 results were not 9 work was partially 8 algorithm is more 8 algorithm is simple Top 50 negative assertions; "What sentences are in the shape of noun-verb-no|not-noun?" --------------------------------------------------------------------------------------- 8 results are not directly 3 approach is not always 3 data is not available 3 features are not helpful 3 method is not only 3 network is not thoroughly 3 results are not comparable 3 table contains no geographic 2 algorithm is not only 2 algorithms are not able 2 approach is not common 2 approaches are not directly 2 data is not only 2 features are not detectable 2 information is not available 2 methods are not faulty 2 model does not explicitly 2 model has no knowledge 2 model is not sensitive 2 models are not able 2 models do not significantly 2 results are not available 2 results were not overly 2 systems have not yet 2 user has not yet 2 users are not aware 2 users were not able 2 words are not necessary 2 work is not directly 1 % are not enthusiastic 1 % are not sig- 1 % had no detectable 1 % were not able 1 % were not eligible 1 algorithm has no dependency 1 algorithm has no parallel 1 algorithm is not accurate 1 algorithm is not always 1 algorithm is not applicable 1 algorithm is not as 1 algorithm is not merely 1 algorithm is not much 1 algorithm is not work 1 algorithm was not suitable 1 algorithms are no strangers 1 algorithms are not efficient 1 algorithms are not entirely 1 algorithms are not only 1 algorithms are not successful 1 algorithms are not suitable Sizes of items; "Measures in words, how big is each item?" ---------------------------------------------------------- 40292 work_xp5ehtk7w5gx5cv7hwqaqf7rvm 31085 work_fkn6grwf7be5hmmu5cqetl6dzm 30543 work_kcfnc6khsraxhcor4ocz3g7ixm 27802 work_7hmcw6dxwjborfxvzwffuce4wq 26806 work_tw4wakfkzbfmvcyhbrwr7qmcc4 22672 work_y2wdmmp76vgxzolncbcl4sfin4 22298 work_jhgdjhqkh5dknobbgykk37oz4y 22081 work_cc75k3nhgzfdtkmohnfvvfarqy 21340 work_4abvrmst2vgavg2uywzcd5rmua 20879 work_pijwwvfoivdarkphykmuwwhuyi 20583 work_zg4qriee75dphc3uvx6own7gka 20184 work_cxgelzja2ve7blgq5bwv2zoshy 20076 work_7wyyn4jlmzflvnev4k7qonrx2i 18636 work_tkn7xe72drcwdmb4dnl5as5iii 18627 work_ztwbqgudijgzxlxrphrkhfclui 18598 work_dksywpuce5hyvazldbmanbc62i 18291 work_dzeata5onzf7rp26j2quaotjza 17819 work_im2qrukbnra2vdfxqduhays26i 17650 work_6fchrrabknd3vnvyxpbbhrm72a 17568 work_ztklkdhf5fexjdonz6dgaysziq 17535 work_vd6oruexsvf4fikunggshpi4vm 17222 work_4jc6r4nqhfdotlm3egq4retkha 17146 work_nfb3nb2bjzgehk6wxpj525oqka 17096 work_sylvnwgcdjbulhidyf7lrawwri 16959 work_aid2rvqau5dnffyxvubsm7mhya 16562 work_bwyl5aldazcytler7culcro2sm 16204 work_gcygeykq7ffsnenhntlew223ma 16072 work_mety3a2v7zdilbbgj4lw5lxvte 16020 work_kt5jsmzxpfef3fivjs6s6tzd4m 15839 work_i2qf3vbj7bampklw365wxgijja 15506 work_l3z5e7xzgfegbmvfa6eryggaaq 15457 work_y6y774uctjetvarldheqeoenfy 15442 work_m7bikytkibezlorb42jgqtvbsi 15373 work_bumlyld32nartpx6c5uawr5dxu 15345 work_7z3ossdi4rddjfj5xuw5l6m5eq 15201 work_qrknnrsfj5d3xinxeligze6g4i 15092 work_rd3cilvao5avtowjpe2c6looxq 15062 work_4q5hm7aepvhlhh2i7onh5jcije 15042 work_5jbqrz54ujdzrhn3nbecrse62u 14965 work_6egrw63wyfcczp2iyrguf2koaq 14928 work_4jahkqj3yzfxjggdfr7jx3jif4 14773 work_qzjy63q6cbfzlfevurt7tyno7m 14700 work_qxcof3it6vhyxbcv4b7vyzzs4m 14679 work_nfqwywp3onayzkcizcm2w6ysqi 14668 work_lbym4kns2nhrrcgrs5qrckanai 14527 work_kc3hrngeqbdsfc4atlsx5umlti 14433 work_3jqyjxcrlveslbwv26j5kxcd4m 14327 work_vaxtuleo6nfo7eq2dpcoadhgxa 14279 work_lxfkgxtl7za4dgjpbee5atxncy 14157 work_les4de22qzd4pkbxjnruyovkn4 14124 work_x6dykc6hezhvlnovvg2d6vmdxe 14018 work_5o44bzxzyzdwdmbx5hz3b4svtq 14018 work_hscp7elrtfakfkfv4zzrbyj23q 13974 work_n3xwttbopngatcfdmiu7tbqtxu 13965 work_5i3h5iv2yrhdznh444ehpmhe7a 13815 work_ijabiykaibfnhbma2tyfindlu4 13802 work_e6jamuapavb4jnm3pcyykhj3ba 13746 work_hzbgotiuhjazhgnm4aubvyb7pu 13733 work_kxuqkxr44vclndiw24jbsscsae 13728 work_jvoiujigvff45klae5xermbbae 13721 work_zmw4nyamdvhgbjpenjnarukk7m 13667 work_6qxc4oe23veqhn7qioxt5srhlu 13619 work_w73hiptz3bcxri5xhr47jx335e 13538 work_h35ppmoemvbgdnrofwufellqvq 13487 work_d2vjeeo4qjeyhn4ekhqacy6q3u 13458 work_oavbptqpunch5jy27k3m3zb5yi 13429 work_ae7j2j76jbaubdvmkzdpm2hype 13425 work_455dmcqiznh7th3y2oqmbuw6wu 13335 work_dzfda62vxjemvos4a6kit6z3iu 13199 work_qivwkxnmazbqll5lutx7ibnvke 13164 work_wsiwqbod3nbyvm3dffvduzocri 13162 work_eabupqevvbdzbepciteahrkls4 13127 work_zg62yupdxbb5tb2624egapptde 13091 work_fawdarttj5h2rku4pl5w34q76i 12995 work_hqes4liwkjbipfnjiwg72ck2oe 12984 work_sytjzbtv25fdlo34wpz4crxwue 12879 work_tww7cprsyzdg5fsft2jhn6hweq 12805 work_4tui5szsfzgg5pmnwcq4aw3mwi 12763 work_blzi5mheefd3fhpgc2sbrofqdy 12754 work_fljh2g733fa2fnxmkvwa4p3kby 12718 work_3jstltojlnahjhwxdidtdnycqy 12717 work_oxyhki32wvhqhkc7hia2kg2azu 12695 work_ap6lbi5lozcalg6ytbkyybau6a 12566 work_evnw3zjkvvd63mc2eu2m2ej6gm 12489 work_rnvsfzs6ffgp7d7tryvjj7kggi 12468 work_5brlhve5rrfp5k3ki4c4vyrm2i 12451 work_ptt4wjnlafbitn5ku5cpz22awy 12366 work_afsxvcg3kfhxbgf5td2lfziyua 12301 work_tyhqgdkjnzax3gvmp2ffowkomi 12231 work_okvvxviedrfdxmxumhunbaqdf4 12209 work_3bm3dechy5didpwd3zolcdcwti 12144 work_r6leqo5ppjbtbo47mcs26brbx4 12124 work_3qibjvwhv5hrzhnlia3sdxdgvq 12095 work_ryxojgna3vbkfek5l2onbkh3vu 12044 work_gocqmq4fknd2fjg2ixbgjj53nu 12039 work_s6nrg5wnavdkrjcrx45chwcn2a 12015 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work_jlmpiucycfc6rdblexk6obfor4 -13.0 work_q6u36m2psnc3rpytggbjzexftu -117.0 work_y6y774uctjetvarldheqeoenfy -106.0 work_jvoiujigvff45klae5xermbbae -10.0 work_pp4msfxqizentabvmvas5sabne work_2iy7olcp6bgspd4hfeinespmbm work_5y7zlwyzhfcunhtjekvohrwboy work_6fazzelrfneund7qlj4jpzclhy work_jfciwbeeifgkvl2k7eogkom2di Item summaries; "In a narrative form, how can each item be abstracted?" ----------------------------------------------------------------------- work_22tktt3z4fczfipon3agmpyoeq network of services to allow users to directly publish small Linked Data statements kinds of services are complementary and together allow us to query nanopublications Keywords Nanopublications, Semantic Web, Linked data, Semantic publishing contrast to the existing Linked Data publishing paradigms, semantic micro-contributions context of Linked Data publishing (including Solid and Blockchain-based approaches). existing nanopublication publishing ecosystem to provide query services and intuitive user interfaces that allow for quick and easy publishing of small Linked Data contributions in a existing Linked Data technologies, one based on the grlc API generator and the other 4. positive evaluation results on the above-mentioned query services and user interface. this new approach is to allow end-users to directly publish Linked Data snippets in the sets of services on top of the existing nanopublication network to query and access the in the npa:graph links the nanopublication to its public key if the signature was found work_235n7dcftbgpplqreihoa3x6uy Shift-Reduce Constituent Parsing with Neural Lookahead Features Transition-based constituent parsers are fast and accurate, performing incremental parsing using a sequence of state transitions in linear time. Accordingly, our model should predict the constituent hierarchy for each word rather than simple more difficult compared to simple sequence labelling, since two sequences of constituent hierarchies must be predicted for each word in the input Second, for high accuracies, global features from the full sentence are necessary since constituent hierarchies contain rich structural information. LSTM, in the same way a neural language model decoder generates output sentences for machine translation (Bahdanau et al., 2015). 1. Compared with full parsing, the constituent hierarchies associated with each word have no forced learn global features from the sentence; and the decoder layer predicts constituent hierarchies according to the encoder layer features, by using the attention mechanism (Bahdanau et al., 2015) to compute work_23qh3ethwvhxtazlivq7izfvwa new generation of network IPV9 address representation The network number field of address of class A, B the IP address, and write the number of network prefix IPv6 USES 128-bit addresses (2128 bits), which is IPv6 addresses consist of global routing prefixes, B. IPv6 address representation method "d" represents the 8-bit value of the IPv4 address and is IPV9 not only expands the length of IP address, but specify IPV9 packet sender address, using variable bit, and the destination address of IPV9 packet is B. Text representation of IPV9 addresses represent IPV9 address, including "bracket decimal", addresses to be compatible in IPV9.Such as: Since IPV9 has an address length of 256 bits, address prefix is used to represent the network On the representation of IPV9 address prefix, original Ipv6 address of 16 bits, in hexadecimal; Each "d" represents the original IPv4 address of 8 bits, in work_27d5tr326feydgcx32t4nhl424 A Novel Feature-based Bayesian Model for Query Focused Multi-document Supervised learning methods and LDA based topic propose a novel supervised approach that can incorporate rich sentence features into Bayesian topic both topic model and feature based supervised learning methods. topic models have widely been applied in multidocument summarization in that Bayesian approaches can offer clear and rigorous probabilistic interpretations for summaries(Daume and Marcu, use of both useful text features and the latent semantic structures from by LDA topic model. of combining topic model with feature based supervised learning. feature based Bayesian model S-sLDA for multidocument summarization. Haghighi and Vanderwende (2009) proposed topicsum and hiersum which use a LDA-like topic model step in combining topic model with supervised feature based regression for sentence scoring in summarization. The problem of Celikyilmaz and HakkaniTurs model is that topic model and feature based regression are two separate processes and the score of work_2dimm6xerfcsnc7w5ji6qhdb7y Design and Implementation of Music Recommendation System Based on Hadoop recommendation algorithm, this paper introduces k-means clustering algorithm to improve the recommendation Collaborative Filtering; Recommendation Algorithm; Hadoop recommendation algorithm is based on several users that are 1) Construct users song data representation matrix. user-song matrix, the similarity algorithm is used to value of a song that a similar user has heard while the target recommendation algorithm based on user collaborative algorithm to calculate the cluster center point of user label for users in each cluster.This step is divided into a number of calculating user similarity, generating recommended results. recommended algorithm layer uses Hadoop cluster for recommends different songs to different users, which user-based collaborative filtering recommendation algorithm distributed collaborative filtering recommendation algorithm, user-based collaborative filtering algorithm, the clustering and the recommendation algorithm after the the recommendation algorithm by using the song tag for recommendation algorithm based on item and user[J].Information work_2dw3vuoprfdbdnrfirx5jj7jme Modi, A, Titov, I, Demberg, V, Sayeed, A & Pinkal, M 2017, ''Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction'', Transactions of the Association for Computational Linguistics, vol. https://www.research.ed.ac.uk/portal/en/publications/modeling-semantic-expectation-using-script-knowledge-for-referent-prediction(01c319a9-4ee1-4b73-af5a-9ac0aad76603).html suggesting that human expectations at different levels of representation have separable effects on prediction and, as a consequence, that the modelling do not provide a computational model for estimating referent predictability. only structural linguistic features for predicting referents; the other uses general script-independent selectional preference features. We use the InScript corpus to develop computational models for the prediction of discourse referents (DRs) and to evaluate their prediction accuracy. to the Mechanical Turk experiment (Figure 2), our referent prediction model is asked to guess the upcoming DR. knowledge improves predictions of upcoming referents and that the script model is the best among We also used the estimated models to predict referring expression type work_2edq4sbs6readbovfgzcxl5ojy With FPGA implementation & synthesize of 64-bit Wallace Tree CSA based Radix-8 , hardware design area (number of logic elements) designs for Radix-8 based multiplier unit including: Radix-8 Booth, Wallace Tree Karatsuba Multiplier, CSA Based Radix-8 Booth Multiplier, 64-bit Wallace design alternatives of Radix-8 based multiplier, Section carry propagation delay and the number of bits in Delay-Area analysis of CSA vs CLA implementations (8–64 bit) A. Radix-8 CSA Based Booth Multiplier A. Radix-8 CSA Based Booth Multiplier Design of Radix-8 Booth 32-bit multiplier Multiplier using a 32-bit CSA based radix-8 Booth for Design of 64-bit CSA Based Radix-8 Booth, Wallace Tree Karatsuba multiplier. either using 64-bit CSA Based Radix-8 Booth, KSA C. Sequential 64-Bit CSA Based Radix-8 Booth Design of CSA based Radix-8 Booth 64-bit multiplier. the 64-bit Wallace Tree CSA based Radix-8 Booth Tree CSA Based Radix-8 Booth Multiplier (WCBM) Tree CSA Based Radix-8 Booth Multiplier (WCBM) work_2ha3mubt3zcffhnqhokzofd3ai A spatial data infrastructure (SDI) is a framework of geospatial data, metadata, users search engine was added to the SDI stack to enhance the CSW catalogue discovery abilities of the search engine, to return relevant and reliable content to SDI users. Keywords Data discovery, Catalogue Service for the Web, Metadata, WorldMap, Geoportal, Search pairing the CSW with a search engine platform within the SDI software stack. An SDI is a framework of geospatial data, metadata, users and tools which provides a The catalogue, based on the CSW standard, lets users to discover data and services in an www.elastic.co/), two popular open source search engine web platforms, both based on layers metadata using a search engine rather than the OGC catalogue, enabling more Enhancing discovery in spatial data infrastructures using a search engine Enhancing discovery in spatial data infrastructures using a search engine Enhancing discovery in spatial data infrastructures using a search engine work_2iy7olcp6bgspd4hfeinespmbm work_2lytvedz4zhc3ne5onhq7issre the protocol format of the information server''s network, a obtained by decimal network query server. The architecture of RFID tag information query location query service based on decimal network is a The network architecture of RFID tag information query service mainly includes the decimal network Internet information query service technology system.  RF information query of Decimal network and  RF information query of Decimal network and implementation of RFID tag information query service visits between decimal network information query the Internet information server and label coding format network, expert module, information server The process of Internet accessing to a decimal network based on the d-ons protocol. f) The information server of decimal network f) The information server of decimal network queries the Internet server for product information. g) The query server returns product information. decimal network information query service with direct information to the query server of decimal network to work_2mdy3t4xane2hdgqagdmp6jlju Keywords Necktie knots, Formal language, Automata, Chomsky hierarchy, Generating functions and Fink & Mao (1999) defined a formal language for describing tie-knots, encoding the this language to enumerate all tie-knots that could reasonably be tied with a normal-sized Fink and Mao, together with an analysis of the asymptotic complexity class of the tie-knots A tie-knot has to be tied by winding and tucking one of the two blades around the other: move to tuck the blade U nder the tie itself.2 The notation proposed by Fink & Mao (2000) We can write a context-free grammar for the arbitrary depth tuck tie-knots. of generality, we can assume that a tie-knot starts by putting the active blade in region R: For our necktie-knot grammars, the sizes are the winding lengths of the ties, and it is • The generating function for Fink and Mao necktie-knots is • The generating function for single tuck necktie-knots is work_2mp36ujpvjcgdc3qzaxexknpvi A Method to Access a Decimal Network (IPV9) Resource Technology of China and The Decimal Network Developed a complete set of decimal network Keywords-Decimal Network; CHN; Domain Name; existing Internet network, the IPV9 .chn domain name network can be accessed by setting up the existing need to set the network DNS and point to the IPV9 resources of the decimal network in the current Internet network and Sharing Center setting interface. browser address bar to access the IPV9 site, as shown MOBILE ACCESS .CHN WEBSITE phone to display the setting interface, as shown in Mobile phone Setting Interface interface of network parameter setting appears, and phone and enter http://www.xand.chn in the browser You can access IPV9 network resources by simply WLAN, and the network setting interface appears, as and the DNS setting interface appears, as shown in character domain names, the decimal network system to access decimal network resources through personal work_2p32le2xefgk7mdiaxsaftmnmu Keywords Computational science, Open science, Publication, Reproducible, Replicable, https://elifesciences.org/elife-news/inside-elife-forking-software-used-elife-papers-github Replicating a published result means writing and then running new software based on the description of a computational model or method provided in the original publication, the best of our knowledge, no major journal accepts replications in computational science ReScience is an openly-peer-reviewed journal that targets computational research and range of computational sciences (see http://rescience.github.io/board/) and more than must consider it reproducible and a valid replication of the original work. valuable experience concerning the reproducibility and replicability of computational work example, request that authors make their software work on a standard computational answer questions by authors and reviewers about the ReScience publishing process. Figure 1 (A) The ReScience publication chain starts from an original research article by authors A, published in a journal, in conference proceedings, or as a preprint. the replication is published, and feedback is given to original authors (and editors) to inform them the work_2pr3au7mozfx3bfmyg4bc4yo7u kernel learning (MKL) based gene regulatory network (GRN) inference approach MKL-GRNI: A parallel multiple kernel learning approach for supervised inference of largescale gene regulatory networks. interaction data using advanced multiple kernel learning (MKL) library provided by In yet another study for network inference using kernel data integration (Yamanishi, Multiple kernel Learning approach has also been applied to the domain of drugtarget interaction network inference and drug bioactivity prediction. Algorithm 1 MKL-GRNI Parallel approach for supervised inference of large-scale gene regulatory Multiple kernel learning is based on integrating many features of objects such as genes, To test the parallel MKL algorithm on multiple datasets, we downloaded gene expression approach with other methods that infer gene interactions from single and integrated MKL-GRNI: A parallel multiple kernel learning approach for supervised inference of large-scale gene regulatory networks MKL-GRNI: A parallel multiple kernel learning approach for supervised inference of large-scale gene regulatory networks work_2qq6wxmizbfornkrysxkp6vpqu times from different annotation schemes by measuring overlap of intervals on the timeline. Figure 1: Annotation of the expression Saturdays since March 6 following the SCATE schema. (2004), Bethard and Parker (2016) proposed Semantically Compositional Annotation of Time Expressions (SCATE). propose a new evaluation metric to compare time normalizations annotated in both the ISO 8601 format of We apply the interval-based evaluation metric introduced in Section 3 to the AQUAINT and TimeBank datasets, treating the TimeML annotations as the SCATE annotations cover different time intervals that TimeML has a recall of only 92% of the time intervals identified by SCATE in the AQUAINT corpus The SCATE annotation represents the full expression and, consequently, produces the correct time interval [1986-01Unsurprisingly, TimeML has a lower recall of the time intervals from the SCATE annotations Our 2-Softmax model (Figure 3) splits the output space of labels into two sets: non-operators and work_2sjrdf2ktjborjpbns3i4rort4 Improvement and Realization of CamShift Algorithm Based MotionImage Tracking tracking algorithm, this paper integrates SURF feature Keywords-Motion Image; CamShift Algorithm; SURF; Video tracking is the key technology for motion target detection result to realize the tracking.This method can mainstream motion object tracking methods with good detection and tracking of moving objects in the UAV video. research shows that the target object tracking method based The CamShift algorithm performs target object In the video target tracking by drone, the Camshift algorithm [3],comparing to other tracking methods, has The tracking of the characteristics of the target object extract the points of interest using SURF detection method, object tracking of drone video, this paper proposes the detection to realize the tracking of motion object in UAV method can effectively track and locate the target object in moving target tracking algorithm based on improved Camshift [J]. Image feature point extraction and matching based on SIFT work_2sn25vxvsrbzrjcp6ps7nehcte Combining Minimally-supervised Methods for Arabic Named Entity Supervised methods can achieve high performance on NLP tasks, such as Named Entity Recognition (NER), but new annotations classifier and another one using distant learning techniques, and then combined them using amount of annotated data is available for many languages, including Arabic (Zaghouani, 2014), changing the domain or expanding the set of classes always requires domain-specific experts and new annotated data, both of which demand time and effort. we report our results from testing the recently proposed Independent Bayesian Classifier Combination Saha and Ekbal (2013) studied classifier combination techniques for various NER models under order to automatically develop an Arabic NE annotated corpus, which is used later to train a state-ofthe-art supervised classifier. The SSL classifier performs better than distant learning in detecting NEs minimal supervision approaches using various classifier combination methods leads to better results for Named entity recognition through classifier combination. work_2tflktf2hvbkja6rltueqe3w4q Research on Vehicle Detection Method Based on Background Modeling background modeling method base on frame difference, and compares it with the statistical average background model and Gaussian distribution background modeling method. Keywords-Vehicle Detection; Background Modeling; This article uses the background difference method. difference method needs to establish a background reference models are the statistical average method and the Gaussian A. Statistical average method background model is to obtain the gray average value ofN frames of images in The Gaussian distribution background model was first The Gaussian distribution background model was first background models with single Gaussian distribution and the background image as a Gaussian random process, and model based on the inter-frame difference method. method uses the background of the current frame and the By using the statistical average method, the background used averaging methods and Gaussian distribution model Detection Based on Background Difference Algorithm [J]. model and three-frame difference method[D]. work_2timpskoaza73ntj374tkxmaty Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective the first systematic study on predicting the outcome of cases tried by the European Court How to cite this article Aletras etal (2016), Predicting judicial decisions of the European Court of Human Rights: a Natural Language section of a case best predicts the actual court''s decision, which is more consistent with the case, which is a decision to the effect that a violation of some Convention article Table 1 Articles of the Convention and number of cases in the data set. right that each article protects and the number of cases in our data set. by the parties or to the legal reasons provided by the Court itself on the merits of a case 23 Enforcement of domestic judgments and reasonable time court, applicant, article, judgment, case, law, proceeding, work_2tzdxx7pkvbbbb62pwqubu6nfe Word segmentation can be very challenging, especially for languages without explicit word boundary delimiters, such as Chinese, Japanese and Vietnamese. with large character sets and high segmentation frequencies, such as Chinese, Japanese and Vietnamese specific settings that can be applied to improve segmentation accuracy for each language group. Word segmentation can be modelled as a characterlevel sequence labelling task (Xue, 2003; Chen et non-segmental multiword tokens for languages like Table 3: Tag set for universal word segmentation. We use one set of parameters for all the experiments as we aim for a simple universal model, although fine-tuning the hyperparameters on individual languages might result in al., 2016) are used for all the word segmentation experiments.3 In total, there are 81 datasets in 49 languages that vary substantially in size. contains word segmentation, POS tagging, morphological analysis and dependency parsing models in word segmentation model targeting languages without space delimiters like Chinese and Japanese. work_2vd5wfkfpfgqtm4e6elvfcktem In this paper, we consider whether brokerage in an intraorganizational communication network and type of work role interact a joint effect on performance along with work role in a study of also suggest that interdependent roles requiring broad, organizationwide collaboration, and communication with others, brokerage is how brokerage affects performance in two distinct work roles by condition in structural network analysis is the independent–interdependent nature of work roles, even though 1The organization''s work role structures and innovation activities were studied extensively at two-year research project The contingent effect of work roles on brokerage in professional organizations The contingent effect of work roles on brokerage in professional organizations The contingent effect of work roles on brokerage in professional organizations The contingent effect of work roles on brokerage in professional organizations The contingent effect of work roles on brokerage in professional organizations The contingent effect of work roles on brokerage in professional organizations work_33nbguho3jgb5kkpigcjwnzm64 finding unknown real and integer parameters in dynamical models of biological Keywords Differential Evolution, Parameter optimization, Mathematical modeling, (2016), A software for parameter optimization with Differential Evolution Entirely Parallel method. DEEP method was developed to solve the inverse problem of mathematical modeling. and maximal number of iterations Gmax are the main control parameters of the method. of different algorithmic parameters on method convergence was discussed in Kozlov & function is better, and a randomly selected value is less than the predefined parameter for real to integer are implemented in DEEP method as described in Kozlov et al. problem based on real biological model of gap gene regulatory network (Kozlov et al., Figure 1 Comparison of number of objective function evaluations for DEEP and MEIGOR on reduced Evolution of three objective functions during parameter fitting (C). The parallelization of objective function calculation implemented in DEEP method work_35n7f6rilnfzdevpa7noi3pla4 Keywords Ensemble method, Deep learning, Helmet-wearing detection, Face detection A deep learning-based ensemble method for helmet-wearing detection. Once (YOLO) algorithm to accurately detect helmet wear in images with an average of algorithms to improve the ability of helmet-wearing detection in complex scenes. RCNN performs well for relatively large objects, but when detecting small faces or helmets, Faster RCNN for detecting faces and helmet-wearing. The detection results of Faster RCNN for faces are shown in Figs. Obviously, the Faster RCNN model has lower accuracy for small faces. data that the detection capabilities of the Faster RCNN and Tiny Face models have their Accuracy of base algorithms for helmet detection ensemble framework by combining Faster RCNN and Tiny Face+CNN together with ROC for helmet-wearing detection, we can integrate a complementary model with it to get Safety helmet wearing detection based on image processing and machine learning. Safety helmet wearing detection method of improved work_35tjy7sldnhtrdrp4eqtj2nuw4 Research on Enterprise Application Integration Platform ESB as the core, transforms enterprise information integration establishes the idea of basic data management, so as to achieve enterprise integration platform based on SOA. data information for all application systems of the integration platform, an enterprise service bus (ESB) is establish a data exchange management platform to management platform, as a service provider in the SOA architecture, to provide basic data management management platform will integrate the basic data of exchange platform as the enterprise service bus will the data exchange management platform should also the data exchange management platform should also data exchange platform in the form of XML message, platform are service management and data exchange Main interface of data exchange management platform the enterprise integrated information system based on The basic data management platform service interface platform based on SOA [J]. data sharing and exchange platform based on SOA [J]. work_37wft6eehnazxaxgenjumsuamm and multi-step heuristics for model minimization, our approach is a simple greedy approximation algorithm DMLC (DISTRIBUTEDMINIMUM-LABEL-COVER) that solves this sequence labeling tasks: Part-of-Speech tagging for multiple languages (including lowresource languages), with complete and incomplete dictionaries, and supertagging, a In this work, we tackle the problem of unsupervised sequence labeling using tag dictionaries. Ravi and Knight (2009) explores the idea of performing model minimization followed by EM training to learn taggers. large data and grammar sizes, and does not require the corpus or label set to fit into memory. A more popular approach is to learn from POS-tag dictionaries (Merialdo, 1994; Ravi and Knight, 2009), incomplete dictionaries (Hasan and Ng, 2009; Garrette and word wij we associate a set of possible tags Tij. We from the raw and test data to perform model minimization followed by unsupervised EM training. raw training data along with the word-tag dictionary work_3bm3dechy5didpwd3zolcdcwti uses a significantly different definition as black spots are sections of the road network (statistics, data mining, pattern recognition) to localize accident black spots in these the safety experts'' point of view, the result of the KDE method is the accident density For the black spot candidate localization step, the Density-Based Spatial Clustering of case of spatial black spot localization techniques, the definition of road accident density It is possible to calculate the black spot area and the accident density of a given cluster by researchers that the number of accidents in a given area (section) of the road network road safety engineers, it is not necessary that the accidents of a given black spot have any Analysis of historical road accident data supporting autonomous vehicle control strategies Analysis of historical road accident data supporting autonomous vehicle control strategies Analysis of historical road accident data supporting autonomous vehicle control strategies work_3ecslqollvat3jyruwpjy26lou Modeling Past and Future for Neural Machine Translation are fed to both the attention model and the decoder states, which provides Neural Machine In addition to PRESENT, we address the importance of modeling PAST and FUTURE contents in step, and the RNN state of the FUTURE layer corresponds to source contents of untranslated words. We then feed the PAST and FUTURE information to both the attention model and decoder states. to explicitly model the holistic source summarization by PAST and FUTURE contents at each decoding step. In addition, we use two separate layers to explicitly model translated and untranslated contents, which is updated at each decoding step by subtracting the source content being translated (i.e., attention vector) from the last state (i.e., the untranslated while the PAST layer encodes translated source contents up to the current step. subtract the semantics being translated from the untranslated FUTURE contents at each decoding step. work_3eoycspfm5bwthv6g7zteuo6ky A Graph-based Model for Joint Chinese Word Segmentation and BERT is combined, our model can substantially reduce the performance gap of dependency parsing between joint models and previous joint models mainly adopted a transitionbased parsing framework to integrate the word segmentation, POS tagging, and dependency parsing. Because the segmentation is a characterlevel task and dependency parsing is a word-level and CTB-9, our model achieves state-ofthe-art score in joint CWS and dependency joint POS tagging and dependency parsing model joint inference model for word segmentation, POS F1seg and F1udep are the F1 score for Chinese word segmentation and unlabeled dependency parsing, Owing to the joint decoding of CWS and dependency parsing, we can utilize the characterlevel pre-trained language model BERT. joint Chinese word segmentation and dependency joint decoding between Chinese word segmentation and dependency parsing, our model can use Joint Segmentation, POS Tagging, and Dependency Parsing work_3f7hqg25zfedthvomuvrajfkyq Methods: We proposed a general method to detect mobile applications'' anti-patterns incidence of anti-patterns using the ontology merging on mobile applications. Keywords Mobile applications, Reverse engineering, UML, OntoUML, Anti-patterns, Ontology � Presenting a new method for generating OWL ontology of mobile applications. proposed in the literature to detect mobile applications'' anti-patterns. detect 32 anti-patterns related to inconsistencies between application versions. detected 18 object oriented (OO) anti-patterns in 1,343 Java mobile applications by of semantic anti-patterns will improve the quality of mobile applications. design of mobile applications to detect design anti-patterns, and for making semantic reverse the Java code of mobile applications and generating UML class diagram models. start the detection of the anti-patterns process for the integrated application (Fig. 2). 29 mobile applications and the relation between the different types of anti-patterns. Table 5 shows the detected anti-patterns in each application using the proposed method of detecting anti-patterns in mobile applications. work_3fky2fv4l5b7horsv5frlbujja Keywords Capacitated centered clustering problem, Gaussian mixture models, Dispersion Most of the solving algorithms for the CCCP perform clustering within the search � At each iteration, Gaussian distribution-based clustering performs, for a given point, a values on the computations of GMMs. In order to reduce dispersion of the CCCP data the compression algorithm presented in EM algorithm (see Fig. 2), the number of points assigned to each cluster is obtained. Figure 4 Clustering with (A) standard EM algorithm and (B) DRG meta-heuristic (modified EM Table 2 presents the best results of the DRG meta-heuristic for the considered instances. Table 2 Performance of DRG, VNS, SA, CS, TS and GA on CCCP instances when compared to updated Best-known solutions*: (a) MATLAB, Solution strategy based on Gaussian mixture models and dispersion reduction for the capacitated centered clustering problem Solution strategy based on Gaussian mixture models and dispersion reduction for the capacitated centered clustering problem work_3gi6ydizojeklalau6r3q7nwju a central authority to assign routes to the vehicles, or by means of a learning process Sharing diverse information gets driver agents to learn faster: an application in Our approach is based on using communication to augment the information each agent1 travel times (hence, rewards) received by the agents, regarding their last action performed. MARL based approach, where each agent has to explore in order to gain information. In our approach, after a certain time, the agents have learned a policy to map states to the learning process is accelerated if agents do not have the very same information that CommDevs compute and share the reward information to the driver agents. Sharing diverse information gets driver agents to learn faster: an application in en route trip building Sharing diverse information gets driver agents to learn faster: an application in en route trip building work_3gk6cma2gndppblfkxoyk4sx3m We describe how duration information can be incorporated into an unsupervised Bayesian dependency parser whose only other source of information is the words themselves (without punctuation or parts of speech). syntactic structure for language-learning infants, and motivate the use of word duration 2011) that infants might use word duration as a direct cue to syntactic structure (i.e., without requiring intermediate prosodic structure), because words phrase structure using word duration (and fundamenin a model of language acquisition, gold tags certainly are not. As mentioned, we will be incorporating word duration into unsupervised dependency parsing, producing analyses like the one in Figure 1. dependents may allow us to capture selectional restrictions in POS and words models, or exploit effects of syntactic predictability on dependent duration. Table 2: Performance on wsj10 and swbdnxt10 for models using words and POS tags only. Table 3: Performance on swbdnxt10 for models using words and duration. work_3he56nupl5gqtpkwpkewfgko54 Searchable Re-encryption Cloud Storage Method Based on Markov Chain SReCSM(Searchable Re-encryption Cloud Storage Method) when different size of the data is stored in storage nodes Keywords-Cloud Storage; Markov Chain; Re-encryption; storage is designed to store data in cloud and is widely used mobile device to data, stored in a cloud, leads to poor client  Searchable Re-encryption Cloud Storage Method cloud storage according to data size based on Markov is not Searchable Re-encryption Cloud Storage Method based on the storage cost of the nodes for storing different size file, cloud system, depending on the size of the storage data file, The state space of the cloud storage based on Markov According to the storage cost of data stored in different Re-encryption Cloud Storage Method based on Markov re-encrypted data will be forwarded to the cloud storage state of the storage nodes in the cloud system are different, work_3iywiieamja5tayrhj5mjsm6gy To our knowledge, this is the first purely datadriven approach of probabilistic metaphor acquisition, recognition, and explanation. Existing work on metaphor recognition and interpretation can be divided into two categories: contextoriented and knowledge-driven. the selection association) is widely used in more recent approaches for metaphor recognition and interpretation (Mason, 2004; Shutova, 2010; Shutova et For example, Mason (2004) learns domain-specific selectional preferences and use them to find mappings between concepts from different domains. metaphors by focusing on the nearby verbs of a potential source or target concept. from human-curated knowledge bases like WordNet, known metaphor and idiom sets. more candidate metaphor pairs from billions of sentences in the web corpus: That is, pairs extracted by the "is a" pattern contains at least two types of relations: the literal isA relations and the metaphor relations. We label a sentence in the set as a metaphor if the two nouns connected by BE do not actually have isA relation; or if work_3izv3tjjq5ga7j3fkxkvenujpy guess the human opponent''s emotion word in the EMO20Q game, the agent''s behavior of We describe and experimentally validate a question-asking framework for machine-learned linguistic knowledge about human emotions. Even when the agent fails to guess the human opponent''s emotion word in the EMO20Q agent cannot directly experience emotions as a human would, question-asking can be leveraged for the40 using question-asking to interactivly acquire linguistic knowledge about emotion by a computer dialog agent The key goals of this paper are to use question-asking to observe natural language descriptions of emotion The model we use for the EMO20Q questioner agent is a sequential Bayesian belief update algorithm.205 Of the 110 matches played between the 25 human players, 94 – approximately 85% – terminated successfully with the questioner correctly identifying the emotion that the answerer picked or a word that the the human opponent''s emotion word in the EMO20Q game, the agent''s behavior of searching for knowledge work_3jdx4rpw3ne7pdgamiplej6n4e data statements will help alleviate issues related to exclusion and bias in language technology; lead to better precision in claims A data statement is a characterization of a dataset which provides context to allow developers and users to as data statements bring our datasets and their represented populations into better focus, they should NLP needs data statements (§3) and relate our proposal to current practice (§4). Recent studies have documented the fact that limitations in training data lead to ethically problematic limitations in the resulting NLP systems. NLP papers using datasets for training or test data tend statements should be included in every NLP publication which presents new datasets and in the 2026 the Association for Computational Linguistics (ACL) proposes that data statements be standardized and required components of research papers. ''data statements'' in all publications and documentation for all NLP systems. work_3jhpujlx6zhmzidpnvccudpn5y Research on Comprehensive Training Platform for Software Engineering Based on campus, the C / S model training platform, the use of Android integrated training platform to achieve the Chinese character building of training platform on Android system, software integrated-platform principle, software engineering, computer integrated-platform structure, software project The comprehensive training platform is based on 2) Android-based APP is to imitate the training platform specific function is to provide students a Chinese characters P ANDROID-BASED TRAINING PLATFORM writing and modify the Chinese characters, submit the result, client input Chinese characters and display on the big screen, development of network communication process based on The system training platform uses the TCP through the Android based training platform can experience integrated training platform for writing Chinese characters comprehensive training platform for Chinese character comprehensive training platform for Chinese character engineering and software development of the whole process; train software engineering students other comprehensive work_3jqyjxcrlveslbwv26j5kxcd4m In the architecture based on fog computing and IoT, priority processes of the article include: Features and security needs of fog computing in "Proposed Model", concept of fog computing and IoT protocols used in the proposed model. � Confidentiality: Data must be secured during transmission from the IoT node to the fog In the proposed model, high computing processes are made in fog nodes. since the detected data is encrypted in the fog nodes and sent to the cloud. Fog nodes perform data processing and storage within the local network. requests on the fog nodes and the proposed resource management algorithm. Management of iot sensor data using a fog computing node. A novel IoT-based health and tactical analysis model with fog computing A novel IoT-based health and tactical analysis model with fog computing A novel IoT-based health and tactical analysis model with fog computing work_3jstltojlnahjhwxdidtdnycqy inference methods in different artificial and real-world data sets. and effect to a certain function class: For linear relations with non-Gaussian independent assumption, the effect data may contain information about the relation between cause and approach Regression Error based Causal Inference (RECI) and summarize the algorithm the causal direction in various artificially generated and observed real-world data sets. Generally, ANM performs the best in all data sets. performed evaluations with artificial data sets where the input distribution and the noise performing functions and parameters of the different causal inference methods. In case of RECI, Theorem 1 states an equality of the MSE if the functional relation is linear and, thus, the causal direction can not be inferred. While the cause and noise also have a dependency in the SIM-c data sets, the performance Under the assumption of an independence among the data generating function, the work_3lprnbk47berhkkk2gnttcvhuu Keywords Software citation, CodeMeta, ISO metadata, Metadata, Crosswalk CodeMeta-compliant descriptions of software that is documented using the ISO standards. Mapping ISO 19115-1 geographic metadata standards to CodeMeta. Mapping metadata for software between different schemas and dialects is an important • Related Resource Citations also occur at a specific location in the model, identificationInfo.associatedResource (XPath = /mdb:MD_Metadata/mdb:identificationInfo/*/ The ISO standards provide several specific resource citations for citing software, including: cit:CI_OnlineResource/mdb:MD_Metadata/mdb:identificationInfo/*/mri:citation/ cit:CI_OnlineResource/mdb:MD_Metadata/mdb:identificationInfo/*/mri:citation/ aMultiple CodeMeta terms are mapped to this ISO XML element, some with different attributes. aMultiple CodeMeta terms are mapped to this ISO XML element, some with different attributes. aMultiple CodeMeta terms are mapped to this ISO XML element, some with different attributes. aMultiple CodeMeta terms are mapped to this ISO XML element, some with different attributes. aMultiple CodeMeta terms are mapped to this ISO XML element, some with different attributes. aMultiple CodeMeta terms are mapped to this ISO XML element, some with different attributes. work_3nicn4x7u5bbvf6ajajnu73nbi https://www.research.ed.ac.uk/portal/en/publications/discretestate-variational-autoencoders-for-joint-discovery-and-factorization-of-relations(7b6ff228-0589-4b78-bf5c-289ee79084d8).html relation between two entities, and a factorization model, which reconstructs arguments extractor which predicts a semantic relation between two entities in a specific sentence given The use of a reconstruction-error objective, previously considered primarily in the context of training neural autoencoders (Hinton, 1989; Vincent et also qualitatively evaluate our model by both considering several examples of induced relations (both the semantic relation r = REVIEWED.1 The standard approach to this task is to either rely on human annotated data (i.e., supervised learning) or use 1In some of our examples we will use relation names, although our method, as virtually any other latent variable model, In this work we explore three different factorizations ψ for the decoding component: a tensor factorization model inspired by previous work on relation factorization, a simple selectional-preference that we train the relation classifier (i.e., the encoding model), unlike some of the previous approaches, work_3o2flxcuwjbitlgqg237dzc7da Visualizing Multilevel Networks for the Analysis of Superposed ties are economic relationships (business deals) (2020), visualizes multilevel networks of individuals and organizations. Visualizing Multilevel Networks for the Analysis of Superposed Levels of Collective Agency this trade fair, nodes at the upper level are companies representatives, sellers and buyers of TV programs density of this inter-individual network represents the From an economic sociology perspective, such patterns facilitate the study of multilevel, multiplex and perspective on markets as multilevel networks. these multilevel networks, a relationship between two relation ships between sales representatives contribute to the formation of inter-organizational, contracting ties (Bathelt and Glückler, 2003; Berends C''s company and so seller A is aware of buyer C''s For a general perspective on multilevel networks in an application to a multilevel network of researchers. (Eds), Multilevel Network flavours of multilevel issues for networks", In Lazega, E. Multilevel Network Analysis for Visualizing multilevel networks with post/visualizing-multilevel-networks-with-graphlayouts/ work_3o7sy5d745gbzkgpk76ulfnedm Advanced Dynamic Autonomous Knowledge Learning Method for Distance Interactive Technology; Dynamic Autonomous Knowledge Knowledge acquisition process is the learners to participate distance learning model is a simple information-sharing A. Characteristics of active distance-learning model process of learning, each knowledge sender bears certain learning content, send requests to knowledge giver, when knowledge learning process and receive it down. learning network, it is impossible for knowledge giver to subject at the same time, or send data to same knowledge time of knowledge interaction.  Network learners cannot receive knowledge and send assigned knowledge content to learning object according to request of the knowledge data at the same time only on the that each learner interact with knowledge giver according to time, then let the knowledge giver''s interaction have a free learners complete the knowledge content learning. learners sending interactive data in dynamic changes interaction between learners and knowledge imparter is work_3q27dttkvbgtlcjxliqljpouve Zbrowse: an interactive GWAS results browser Zbrowse: an interactive GWAS results browser viewing of GWAS results with a focus on an ability to compare results across multiple traits Some web applications provide tools for viewing Manhattan plots interactively, but The ZBrowse GWAS results viewer is an interactive application that runs on a local machine needs to select the y­axis column with the significance value against which to plot each SNP. When the user scrolls over points in the plot, a tooltip will display that shows way of the viewing or selecting of points, clicking the plot will temporarily hide the viewer is available in the Data Table tab for analysis of the selected GWAS dataset. Genome wide view of Interactive GWAS Results Browser. Chromosome View tab of the Interactive GWAS Results Browser displaying a peak Annotation tab of the Interactive GWAS Results Browser. work_3q7djukk75c2zkcpzjfjnkd7xu Specifically, we learn to assign complexity levels to solutions based on their linguistic makeup. original FAQ order using Kendall''s τ (values are averages over 100 problem-solution sets). over the positions at which a solution with that complexity can occur and uses this distribution to order Qrm is the number of times a solution with position r is given complexity m over the full corpus. Table 3: Most likely words assigned to varying complexity levels by the permutations-based model. Specifically, we can compute the expected complexity of the solution set for problem i, using the inferred distribution over levels θi: In the previous section, we showed how our models can assign an expected complexity value to a solution text or an entire problem. the ranking model on 240 problem-solution sets; level 1 will be ordered after the solution with complexity 2. work_3qibjvwhv5hrzhnlia3sdxdgvq collection of data mining algorithms which effectively support the crime investigation Fuzzy based binary feature profiling (BFPM) for modus operandi analysis is one An actual crime data set was used in testing the performance of the newly proposed method the fuzzy based binary feature profiling for modus operandi analysis. the fuzzy based binary feature profiling for modus operandi analysis. types, subtypes, crime flows and the special category in Table 1, it results in 21-bit feature The method was tested with a crime data set obtained from Sri Lanka Police. Table 6 Results returned by the fuzzy based binary feature profiling for the modus operandi analysis proposed method on the crime data set. Figure 12 ROC curves returned by the newly proposed method on the 20 classes of crime data set. As the newly proposed method accepts only binary input variables, the data sets which work_3r5hnn4c4fhgvg2epficptavh4 (LSTM)—to use them to predict the stock prices with a high level of accuracy. tool to learn and predict temporal data having long term dependencies. the LSTM model uses historical stock data along with sentiments from news items to Keywords Long Short-Term Memory (LSTM), Explainable AI(XAI), Stock price prediction, the Daily Prediction model and historical data from 2003 obtained from Yahoo finance is to separate rule base data from the text while the RNN-LSTM model is utilized to get the Neural Networks, Support Vector Machines, and Case-Based Reasoning models, they Figure 2 System Architecture of Stock Market Prediction using LSTM and XAI. LSTM CNN model for news headlines As represented in Fig. 9, after training the model and obtaining predictions the explainer Figure 10 Loss LSTM -CNN model for News Headlines. The loss values for the LSTM-CNN model Stock market prediction using LSTM recurrent neural network. Prediction models for Indian Stock market. work_3snzfdkn7bb6hpxhca6z5amcfa Impact study of data locality on task-based applications Impact study of data locality on task-based applications through the Heteroprio different memory nodes can be evaluated without looking at the tasks'' dependencies. Keywords Scheduling, Task-based, Starpu, HPC, Data locality Our first step in managing data locality is to subdivide each bucket into M different tasklists and set up one list for each of the M memory nodes. the tasks of the bucket index b that we consider local to the memory node m. locality of a task regarding the memory nodes and the distribution of the data it uses. Table 1 Examples of memory node selection by the proposed DLAF for different tasks and data configurations. Impact study of data locality on task-based applications through the Heteroprio scheduler Impact study of data locality on task-based applications through the Heteroprio scheduler Impact study of data locality on task-based applications through the Heteroprio scheduler work_3ustg4gq35hhpexpxl6tm3yf5m Semantic Analysis of the Wa Tautology in Subordinate Clauses with Minimal This paper focuses on Type ④ whose language form can In Example (2) which represents Type ④, However, in Type ④, Tautological part Tautological expression will appear when Type part of Type ④ only belongs to subordinate clause (従属句) Tautological express of Type ④ is in Subordinate Clause, there is half in Subordinate Clause, Type ④ can be called "Tautological expression in Subordinate Clause". "Tautological expression in Subordinate Clause". Type ④ as the sentence with the structure of the expression After Example (5), Okamoto(1993) changed the sentence To analyze the contrastive sentence and Tautological part and contrastive sentence is the narrative part. (17) which are contrastive sentences, linguistic meaning of narrative part, Tautology of subject part of Type ④ has no In other words, Tautological expression of Type This example is almost identical in language to Type ②. work_3x65hc7335h7zcr2lpcmjf3t4e The Comparison on the Side Feed Mode of Micro-strip Patch Abstract—The feeding of the micro-strip patch is flexible and In this paper, a single microstrip patch antenna with a center frequency of 2.45GHZ is 1/4 converter sizes of the non-slotted side feed and slotted side modes, electrical size of the slotted feed is smaller. Keywords-HFSS Simulation; Micro-strip Patch; Side-feed; be also affected by micro-strip patch feeding mode. the cell structure of the micro-strip patch antenna with the The size of the slotted micro-strip patch can be also The slotted feed mode is closer to the theoretical value than Slotted patch antenna Slotted patch antenna Slotted patch antenna The theoretical value of the slotted feed size is edge impedance of the slotted feed patch is mainly caused by the edge of the slot and the radiation patch. The slotted radiation patch reduces the electrical size of the Liu Yang.Design of HFSS Antenna [M]. work_3zucn2lewrgwneokzjgjfu4zkq Inspired by the recent success of structure-aware Graph Convolutional Networks (GCNs) for various NLP tasks such as machine translation, compute the dependency parse tree for each utterance in the conversation and use a GCN to capture Our contributions can be summarized as follows: (i) We use GCNs to incorporate structural information for encoding query, history and KB entities in goal-oriented dialogues (ii) We use a sequential attention mechanism to obtain query aware and history aware context representations (iii) GCNs in NLP : Recently, there has been an active interest in enriching existing encode-attenddecode models (Bahdanau et al., 2015) with structural information for various NLP tasks. To the best of our knowledge ours is the first work that uses GCNs to incorporate dependency structural information and the entity-entity graph structure in a single end-to-end neural model for goaloriented dialogue. work_44qds2wxfnh3tncnwfvuffhoau language treebanks; 3) a method for integrating these steps with the density-driven annotation projection method of Rasooli and Collins source of translation data is the Bible, a considerably smaller corpus than the Europarl 2016) and methods that leverage cross-lingual representations of word clusters, embeddings or dictionaries (Täckström et al., 2012; Durrett et al., 2012; • We describe a method for transfer of lexical information from the target language into source When using Europarl data instead of the Bible, our approach gives 83.9% accuracy, a 1.7% absolute improvement over Rasooli and Our experiments showed an improvement in average labeled dependency accuracy for the languages We can use the cluster-based features φ(c)(x,y) on the source language treebanks Table 6: Results for our method using different sources of translation data. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1234–1244, work_455dmcqiznh7th3y2oqmbuw6wu instances for routing and facility location problems with real geographical distance metrics for routing and facility location problems; (3) simulation of nondeterministic inventory control models; (4) importing/exporting and plotting of solutions for large vehicle routing and facility location problems. � generation of test instances for routing and facility location problems with real solving routing and facility location problems (symmetric and asymmetric metrics are The development of location data is important to test solving methods or algorithms for meta-heuristics and solving methods for different vehicle routing/facility location the characteristics of the vehicle routing/facility location problems and their solutions. Figure 10 Coded suite: solution of the NNS-GRASP meta-heuristic for the CVRP instance X-n219-k73.vrp as computed by the function inventory model with a general demand distribution. Development of a coded suite of models to explore relevant problems in logistics Development of a coded suite of models to explore relevant problems in logistics work_45agadeerbhszh2kmiv4s3yymm present the Alternating Guided Filter (AGF) that achieves edge preserving smoothing preserves significant image edges while effectively eliminating small scale details. AGF combines the large scale edge and local intensity preserving properties of the RGF iterative framework results in effective size selective filtering of small scale details combined Figure 3 shows the results of RGF, SiRmed and AGF filtering after the first 3 iteration steps. Notice that all three filter schemes iteratively restore large scale image edges proceeding of respectively AGF, RGF, SiR and SiRmed filtering of Fig. 6A after five iteration steps. Results of (B) AGF, (C) RGF, (D) SiR and (E) SiRmed filtering after 5 iteration Results of RGF filtering of the input image for different values of the variances of the spatial (σs =3, 6 and 9) and range (σr =0.05, 0.1 and local intensity preserving image smoothing properties of the RGF with the large scale edge work_46ftgva4mfasnhpfh7cdkzzequ Cross-Sentence N-ary Relation Extraction with Graph LSTMs contextual representation is learned for the entities, which serves as input to the relation classifier. Figure 1: An example document graph for a pair of sentences expressing a ternary interaction (tumors with work on n-ary relation extraction focused on single sentences (Palmer et al., 2005; McDonald et al., for cross-sentence n-ary relation extraction, based To overcome these challenges, we explore a general relation extraction framework based on graph n-ary relation extraction based on graph LSTMs. Markov models (HMMs), except that discrete hidden states are replaced with continuous vectors, and For multi-task learning, we also considered drug-gene and drug-mutation sub-relations, We compared graph LSTMs with three strong baseline systems: a well-engineered feature-based classifier (Quirk and Poon, 2017), a convolutional neural than prior approaches, and can also improve performance on single-sentence binary relation extraction. ary relation extraction based on graph LSTMs. The work_47lp4am6gndwhjbxhphpyiw2zy these language-model-based encoders are difficult to train due to their large parameter layer perfectly serve our desire to decouple learning contexts and words and devote most computational resources to the contextual encoder. reduce the complexity of the output layer in language models, such as the adaptive softmax, and pre-trained contextual representations to downstream tasks: 1) feature-based and 2) fine-tuning. potential drawback of these subword-level language models, however, is that they produce representations for fragments of words. The continuous output layer has a reduced arithmetic complexity and trainable parameter size. softmax layer in ELMo trained on the One Billion Communication cost To train large neural network models, using multiple GPUs almost becomes output layer, on the other hand, incurs little communication cost across GPUs. 3.2 Open-Vocabulary Training With the continuous output layer, we can conduct training on an arbitrary sequence of words, as the pre-trained word embedding affects the performance of the model. Pre-trained CNN layer as word embedding work_47xmn44k3nccdfwsrtmwbae6ky Process Analysis for Security (STPA-Sec) approach views losses as resulting from In this article, we propose a data-flow-based adaption of the STPA-Sec Keywords Security analysis, Complex interaction, Information-critical system, Data flow structure, Data-flow-based adaption of the System-Theoretic Process Analysis for Security Table 1 Summary of established security analysis approaches other than STPA-based ones. The STPA-based security analysis approach (STPA-Sec) has been used to identify another system-oriented scenario-based approach CHASSIS, the STPA-Sec views the The STPA-Sec only analyzes insecure possibilities related to this action at a functional level helps to identify more data-related threats than using STPA-Sec alone, this diagram based Furthermore, the STPA-Sec approach regards the security issue as one of the key threats In this article, we have proposed a data-flow-based approach for security analysis of Data-flow-based adaption of the System-Theoretic Process Analysis for Security (STPA-Sec) Data-flow-based adaption of the System-Theoretic Process Analysis for Security (STPA-Sec) work_4abvrmst2vgavg2uywzcd5rmua (2017), Challenges as enablers for high quality Linked Data: insights from the Semantic Publishing //2014.eswc-conferences.org/semantic-publishing-challenge.html), in 2015 we mentioned by Information Extraction and Interlinking'''' (Di Iorio et al., 2015) (2015 SemPub Challenge, http://2015.eswc-conferences. producing Linked Data about it (Dimou et al., 2016) (2016 SemPub Challenge, http: http://2014.eswc-conferences.org/semantic-publishing-challenge.html http://2014.eswc-conferences.org/semantic-publishing-challenge.html //2014.eswc-conferences.org/important-dates/call-challenges.html, 2015 Semantic Web • an outline of challenges organized in the field of Linked Data and Semantic Web For Task 1, the participants were asked to extract information from selected CEURWS.org workshop proceedings volumes to enable the computation of indicators for the of the Semantic Publishing Challenge with related datasets in the Linked Data Cloud. Table 3 Task 1 solutions: their primary analysis methods, methodologies, implementations basis and evaluation results. (RML http://rml.io) to define how data extracted from CEUR-WS.org Web pages should In the case of the Semantic Publishing Challenge, the first edition''s tasks were work_4dlhwsemczhz7ptump36z3mt2u The relationship between a driver''s glance orientation and corresponding head rotation in head-glance correspondence while driving, classifier models based on head-rotation (2018), Investigating the correspondence between driver head position and glance location. of glance and head rotation data drawn from a study conducted by the Virginia Tech drivers'' rotate their heads, (b) generate input features for classifiers that predicted glance Figure 4 Principal component analysis (PCA) of dynamic data, using head rotation. Figure 4 Principal component analysis (PCA) of dynamic data, using head rotation. Table 2 Performance measures (AC, accuracy; FS, F1 score; KP, Kappa statistic) across class distributions for the Random Forest and HMM classifiers for dynamic data, forward roadway vs. Figure 7 Drivers'' head angle profiles while glancing to the center stack during the radio tasks (note: Also, predictive power of head rotation data for specific types of glances, such movement correspondence: predicting drivers'' glance location using head rotation work_4dzt4w64yvf3vioq3v655rj5mi particle swarm support vector machine (SVM) method is proposed for detecting and optimization of the SVM algorithm, the grid search method and particle swarm Keywords 5 Ground penetrating radar (GPR), Image segmentation, Feature extraction, Support vector machine (SVM), Grid search method, Particle swarm optimization (PSO) Non-destructive detection of highway hidden layer defects using a ground-penetrating radar and adaptive particle swarm support vector machine. shallow hidden defect classifiers based on the support vector machine (SVM) algorithm. the SVM algorithm, this study optimizes and improves its parameter selection process. method and the particle swarm optimization (PSO) (Yang et al., 2018) algorithm, the Figure 6 Parameter optimization results of the grid search method. Figure 8 Test-set classification results after the grid search optimization of the SVM classifier parameters. The fitness curve of the improved adaptive mutation PSO algorithm for SVM-based approach, the accuracy of the SVM with parameters optimized using mutation PSO work_4edup4wwozbhdb2gbpd24ungsu Improving Topic Models with Latent Feature Word Representations • Topic models take a corpus of documents as input, and jointly cluster: corpus to improve the topic-word distributions in a topic model Latent-feature topic-to-word distributions • In our topic models, we mix the CatE distribution with a multinomial initialise the word-topic variables zdi using the LDA sampler initialise the word-topic variables zdi using the DMM sampler • A topic model learns document-topic and topic-word distributions: • Do the word2vec and Glove word vectors behave differently in topic 20-topic word2vec-DMM on the TMN titles corpus 20-topic word2vec-DMM on the TMN titles corpus Evaluation of 20-topic LDA on the N20 short corpus, • For document classification the latent feature models generally perform corpus to accurately estimate topic-word distributions • More sophisticated latent-feature models of topic-word distributions Conclusions and future work Conclusions and future work Conclusions and future work Conclusions and future work Conclusions and future work work_4frqouxcbjey3jnykpwfln2tba [PDF] Multiple comparative metagenomics using multiset k-mer counting | Semantic Scholar Corpus ID: 7987311Multiple comparative metagenomics using multiset k-mer counting title={Multiple comparative metagenomics using multiset k-mer counting}, On the other hand, de novo methods, that compare the whole sets of sequences, either do not scale up on ambitious metagenomic projects or do not provide… Expand Multiple comparative metagenomics using multiset k-mer counting Figures, Tables, and Topics from this paper Sort by Most Influenced Papers View 6 excerpts, cites background, methods and results View 1 excerpt, cites methods View 1 excerpt, cites methods View 1 excerpt, cites methods View 1 excerpt, cites methods MetaFast: fast reference-free graph-based comparison of shotgun metagenomic data View 2 excerpts, references methods and background View 2 excerpts, references methods and background View 1 excerpt, references methods View 1 excerpt, references methods View 1 excerpt, references background View 1 excerpt, references background View 1 excerpt, references background work_4g77lat4ofeppkced2gc7b6pjq Comparing Bayesian Models of Annotation comparison to gold labels, predictive accuracy for new annotations, annotator characterization, and item difficulty, using four literature comparing models of annotation is limited, focused exclusively on synthetic data (Quoc Our findings indicate that models which include annotator structure generally outperform All Bayesian models of annotation that we describe are generative: They provide a mechanism This model pools all annotators (i.e., assumes they have the same ability; see (2008)—are widely used in the literature on annotation models (Carpenter, 2008; Hovy et al., a small number of items and annotators (statistics in Table 1), the different model complexities result in no gains, all the models performing The unpooled models (D&S and MACE) assume each annotator has their own response parameter. this paper further implies that there are no differences between applying these models to corpus annotation or other crowdsourcing tasks. Multilevel Bayesian models of categorical data annotation. work_4i3v2eiupvdt5gqy5o2tdcvz2e Data-based intervention approach for Complexity-Causality measure. Figure 4 Standard deviation of causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR(1) processes, from Y to X (solid line-circles, black) and X to Y (solid line-crosses, magenta) as Figure 5 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR(100) processes, from Y to X (solid line-circles, black) and X to Y (solid line-crosses, magenta) as the degree of Figure 5 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR(100) processes, from Y to X (solid line-circles, black) and X to Y (solid line-crosses, magenta) as the degree of Figure 8 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR processes Figure 8 Mean causality values estimated using CCC (A), TE (B) and GC (C) for coupled AR processes work_4jahkqj3yzfxjggdfr7jx3jif4 Gastro-CADx, features extracted in the first stage are applied to the discrete wavelet � In the first stage, Gastro-CADx studies several CNN based methods for feature � In the second stage, Gatro-CADx extracts handcrafted features based on textural based methods are useful in extracting texture features from images which is equivalent In experiment II (first stage of Gastro-CADx), DL features are extracted from the Table 4 The classification accuracy for the four CNNs used in Gastro-CADx using Dataset II. Table 4 The classification accuracy for the four CNNs used in Gastro-CADx using Dataset II. using DCT features extracted using AlexNet+ResNet+DenseNet+DarkNet CNNs, where CA features extracted from AlexNet+ResNet+DenseNet CNNs using Dataset I and Next, in the second stage of Gastro-CADx, DCT, and DWT feature extraction Table 8 The Classification Accuracy (%) for the 500 DCT features extracted from different DarkNet-19 CNNs. This is because Gastro-CADx extracted not only spatial features but work_4jc6r4nqhfdotlm3egq4retkha allows for continuously updating the study, we defined a new data collection procedure papers were found in the initial study, which were integrated with the update result set). Additionally, the result set contains 126 papers addressing SPI success factors with an Figure 8 Trend chart of the share of papers that present customized and/or new SPI models. Figure 9 Overview of the classification of publications addressing the standard approaches CMMI and ISO/IEC 15504 (n = 225), and their relation to custom/new models (n = 295). Figure 11 Summary of papers addressing success factors in SPI categorized according the researchand contribution type facets. Figure 12 Summary of the research methods applied to study SPI success factors. agility and SPI, whereas only one paper develops a model on success factors while of However, in our study, we found more than 200 papers addressing standard SPI S5 ((feasibility or experience) and (study or report)) and (SPI or ''''software process improvement'''') work_4mhuno2zhbhupdwgmqajqhbcye words to automatically construct wide coverage lexicons from small seed sets. model the problem of morpho-syntactic lexicon generation as a graph-based semi-supervised learning Our entire framework of lexicon generation, including the label propagation algorithm and the feature extraction module is language independent. Koo et al., 2008; Turian et al., 2010), but a surface morphological transformation feature like suffix:ed:ing possibly indicates a change in the tense their aw''s (obtained from seed lexicon)5 and the unlabeled words U whose attributes are unknown. predicts morphological attributes for words, we provide an intrinsic evaluation where we compare predicted attributes to gold lexicons that have been either read off from a treebank or derived manually. For every language, we create a graph with the features described in §2 with words in the seed lexicon showed that the lexicons thus constructed help improve performance in morphological tagging and dependency parsing, when used as features. work_4oaheysiu5hhvapo7iqe4q6yq4 Typed Entailment Graphs with Global Soft Constraints'', Transactions of the Association for Computational https://www.research.ed.ac.uk/portal/en/publications/learning-typed-entailment-graphs-with-global-soft-constraints(f9e6cde4-6adb-4f78-aeab-44ff87367405).html Learning Typed Entailment Graphs with Global Soft Constraints Learning Typed Entailment Graphs with Global Soft Constraints This paper presents a new method for learning typed entailment graphs from text. Our immediate goal is to learn entailment rules between typed predicates with two arguments, where entailment and paraphrase rules for use in semantic parsing and open domain question-answering, directly learns entailment relations between predicates, these methods aim at predicting the source First, it is standard to learn a separate typed entailment graph for each (plausible) type-pair because arguments provide necessary disambiguation for predicate meaning (Berant et al., 2011, consistent between different typed entailment graphs; LpResolution encourages paraphrase predicates to have the similarity scores and test our model on two entailment rules datasets (§5.2). (2011) annotated all the edges of 10 typed entailment graphs based on the predicates in their corpus. work_4q5hm7aepvhlhh2i7onh5jcije unified access point to the world of nanopublications enabling search over graph Keywords Nanopublication, Scientific data, Graph exploration, Data search, Data citation, Search, access, and explore life science nanopublications on the Web. PeerJ In Fig. 1A we used some prefixes within the nanopublication assertion, namely: dgngda, sio, miriam-gene and lld, that are specific of the life science domain. a DisGeNET (http://rdf.disgenet.org/) gene-disease association; sio identifies a resource graph; (C) network of gene-disease associations created by five nanopublications. user interface to search, access and explore the nanopublications and their relation interface that the user can use to search, access, explore, and cite nanopublications. enables users to search for nanopublications based on topics (e.g., genes, diseases, proteins, NanoWeb aims to provide users unified access to nanopublications and to search and Search, access, and explore life science nanopublications on the Web Search, access, and explore life science nanopublications on the Web work_4tk7vbc46ndwrkklwbvejl4sim Clients'' outcomes from providers'' networks: the role of argue that providers'' relational exclusivity benefits clients because it providers'' network features that benefit the users of their services. Interorganizational networks, Client benefits, Health care. the extent to which providers'' network relations benefit benefits from providers'' network relations. effects of referral network features on the benefits that outcomes from providers'' network relations, showing improving client outcomes from provider networks. exclusivity unlocks the potential of partnering organizations to benefit clients because it improves on patient referral relations in a network of hospital Before examining the determinants of patient referral to hospitals providing better care, it is instructive of patient referral to hospitals with better care quality the effect of relational exclusivity on patient benefit Effect of relational exclusivity on patient referral to hospitals with better thereby helps clients benefit from providers'' network account for clients'' benefits from providers'' networks no patient benefits in hospitals whose network work_4tui5szsfzgg5pmnwcq4aw3mwi optimization problem, we develop a Multi-Objective Simulated Annealing (MOSA) results state that the MOSA performs better than the SA under multi-objective Convolutional Neural Networks (CNNs) differ from multi-layer perceptron models with Multi-objective simulated annealing for hyper-parameter optimization in convolutional two general solution approaches to Multi-Objective Optimization (MOO). Pareto optimal solution with respect to one objective is impossible without worsening at it can be concluded that the MOSA algorithm is able to search the objective space Figure 4 Comparison of MOSA and SA search ability in terms of objective space distribution and the Pareto fronts with (A) random seed: 10, show that the MOSA algorithm is able to search the objective space more effectively than show that the MOSA algorithm is able to search the objective space more effectively than Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks work_4vvn36orfzcjbhebqpiwh44nsa Keywords Polynomial approximation, Discontinuous Galerkin, Mesh generation, High-order a simple first-order voxelization within the coarse elements of the mesh for the DGFEM As such, we need a mesh like in the immersed boundary methods, but a high-order Figure 1 Illustration of the voxelization of a sphere within coarse mesh elements. indicated by the yellow surface while the thick black lines outline the elements of the actual mesh. voxelization within elements follows the Octree refinement towards the sphere and is indicated by the enable high-order material definitions within the mesh elements. areas, but we still need to obtain high-order surface approximations inside the elements • Voxelization (and flooding) within elements of the final mesh to identify color color boundaries in volumes by the voxelization method described above for the mesh. Generation of high order geometry representations in Octree meshes Generation of high order geometry representations in Octree meshes Generation of high order geometry representations in Octree meshes work_4w3odkddrjadtj7ujjam2avyky current Internet was originated in the United States. Internet servers,which is a new generation network Keywords-Network Security; Root Server; Network network/IPV9 network data communication standards world, and the formed network space address naming Any time we access the network, including The 13 root domain name servers read the All parent, root, and subservers of IPv4 are managed by ICANN, an Internet the management of global Internet domain name root servers, domain name systems, and IP addresses. server has more than 1000 Internet domain name United States has controlled the entire Internet by servers are completely controlled by the United States. United States monitors the world through the Internet, of Internet domain names around the world.  The problem of network information security The main features of the future network/IPV9 are as IPv9 network can realize real-name Internet access, next-generation Internet protocol IPv6 proposed by network/IPV9 starts with the address 2^256 power, and work_4wuutuv2lfhhdgl2dgr6ruegii Cross-lingual Projected Expectation Regularization for Weakly Supervised Learning labeled examples, our method yields significant improvements over state-of-the-art supervised methods, achieving best reported numbers to date on Chinese OntoNotes and German CoNLL-03 datasets. (2001) project labels produced by an English tagger to the foreign side of bitext, then use the projected labels to learn a HMM model. Given bitext between English and a foreign language, our goal is to learn a CRF model in the Figure 1: Diagram illustrating the projection of model expectation from English to Chinese. We would like to learn a CRF model in the foreign language that has similar expectations as the Projecting expectations instead of one-best label assignments from English to foreign language can the weakly supervised setting, we simulate the condition of having no labeled training data, and evaluate the model learned from bitext alone. our method, learned over bitext alone, can rival performance of supervised models trained with thousands of labeled examples. work_4ydcpyzirfhf3ma7lkh3dhayqm of out-of-order packets in opportunistic data forwarding and long decoding delay Keywords TCP, Network coding, Opportunistic data forwarding, Multi-hop wireless networks (2016), TCP adaptation with network coding and opportunistic data forwarding in multi-hop wireless networks. In multi-hop wireless networks, data packet collision and link quality variation can opportunistic routing protocols broadcasts the data packets before the selection of nexthop forwarder. congestion control work well with opportunistic data forwarding and network coding. TCPFender and TCP/IP in different topologies of wireless mesh networks, and analyzed the utilize opportunistic data forwarding and network coding, but none of these was designed Opportunistic data forwarding and network coding do not inherently support TCP, so To better support TCP with opportunistic data forwarding and network coding, TCPFender coded packets only include information for the first few TCP data segments of the batch, TCP/IP because opportunistic data forwarding and network coding increase the utilization work_4zamv3kd6bhadgzzpkitxfvryi uses (i) multilingual word clusters and embeddings; (ii) token-level language information; and (iii) language-specific features (finegrained POS tags). POS tags, multilingual word embeddings and multilingual word clusters, and (2) tweaking the behavior of the parser depending on the current input Therefore, we extend the token representation in MALOPA by concatenating learned embeddings of multilingual word clusters, and pretrained ''MultiCCA'' uses a linear operator to project pretrained monolingual embeddings in each language (except English) to the For tagging, we construct the token representation by concatenating the embeddings of the word type (pretrained), the Brown cluster and the input language. The token representation used for parsing includes the embedding of predicted POS tags, which may be incorrect. Table 3: Dependency parsing: labeled attachment scores (LAS) for monolingually-trained parsers and fine-grained POS embeddings, on average outperforms monolingually-trained parsers for target languages with a treebank. work_55utqx7tjrft5ojtbr67ypjdye Comparing Apples to Apple: The Effects of Stemmers on Topic Models First, conflating semantically related words into one word type could improve model fit by intelligently reducing the space In this work we consider two categories of word normalization1 methods: rule-based stemmers, or stemmers primarily reliant on rules converting one affix to another, and context-based methods, or strategies that use dictionaries and other contextual, inflectional, and derivational information to infer the for our data, lemmatizing the corpus took more computational time than training the topic model. fewer possible words; at its extreme, the probability of any corpus under a zero-truncation stemmer no-stemmer treatment t0, we take the difference between topic probabilities, weighted by inverse document frequency (idf) to favor words that are specific While stemming constrains all conflated word types to share one probability in each topic, it does not ensure that those work_577ikynqqjccxpgsyirnrp7bme Within graph-based projective parsing, the thirdorder parser of Koo and Collins (2010) has a runtime of O(n4), just one factor of n more expensive crossing-sensitive grandparent-sibling 1-EndpointCrossing parser proposed here takes O(n4) time, Endpoint-Crossing tree with each edge ~ehm scored The parser finds the maximum scoring 1-EndpointCrossing tree according to the factorization in Section 3 with a dynamic programming procedure reminiscent of Koo and Collins (2010) (for scoring uncrossed edges with grandparent and/or sibling features) and of Pitler et al. Difficulty 1 is solved by adding crossed and uncrossed edges to the tree in distinct sub-problems Uncrossed edges are added only through trapezoid subproblems (that may or may not have a grandparent index), while crossed edges are added in nontrapezoid sub-problems. unconstrained 1-Endpoint-Crossing tree does not include any pruned edges, then whether the parser uses grandparent-sibling factored models for both projective and 1-Endpoint-Crossing parsing are in Tables work_57lneblzxjhgdbzxcmcswlxbxu Domain Adaptation for Syntactic and Semantic Dependency Parsing Using In current systems for syntactic and semantic dependency parsing, people usually define a very high-dimensional feature space to With additional unlabeled target domain data, our method can learn a latent feature representation (LFR) that is beneficial to For example, the relation path between a predicate and an argument is a syntactic feature used in semantic dependency parsing (Johansson and Nugues, 2008). Our DBN model is trained unsupervisedly on original feature vectors of data in both domains: training data from the source domain, and unlabeled data Using the original features, the performance drop on out-of-domain test data is 10.58 section, we introduce how our DBN model represent a data sample as a vector of latent features. data to our DBN model, we learn the LFR for semantic dependency parsing. the training time of our DBN models for both syntactic and semantic parsing. work_57rrnauwwnbp3hjv4m5ye6kck4 Application of Improved BP Neural Network in Hybrid Control Model of Lime model of real time feedback and control parameters. timely feedback to the lime production control system, to achieve the purpose of real-time control of the quality of lime. in hybrid control model of lime quality. The production control process of the rotary kiln is the products quality prediction results and adjusting control correction information, lime rotary kiln control system for The product quality control model flow chart of lime the product quality prediction model is activated according to The control parameters (Y) of the lime rotary kiln are of product quality control. product quality information and control parameters product quality information and control parameters Product quality information and control the production process by the control parameters to adjust the information on the quality of the product data. quality of the products and to achieve timely control work_5brlhve5rrfp5k3ki4c4vyrm2i Keywords Learning curves, Data complexity, Data pruning, Hellinger distance, Bias-variance How to cite this article Zubek and Plewczynski (2016), Complexity curve: a graphical measure of data complexity and classifier performance. In this article, we introduce a new measure of data complexity targeted at sample The problem of measuring data complexity in the context of machine learning is A set of practical measures of data complexity with regard to classification was introduced be used as an universal measure for comparing complexity of different data sets. same setting as when calculating the complexity curve: classifiers were trained on random Figure 3 presents complexity curve and the adjusted error of decision tree classifier on Figure 7 presents conditional complexity curves for all three data sets. Table 4 Areas under conditional complexity curve (AUCC) for microarray data sets along AUC ROC values for different classifiers. complexity curves, PS to data pruning with progressive sampling. work_5btix32qbfgvriqhr7d64hs5mq evaluation study of window-based Distributional Semantic Models on a wide variety of show that our strategy allows us to identify parameter configurations that achieve good performance across different datasets and tasks1. goal: it presents the results of a large-scale evaluation of window-based DSMs on a wide variety of semantic tasks. Bullinaria and Levy (2007) report on a systematic study of the impact of a number of parameters (shape and size of the co-occurrence window, corpus, and evaluated on a number of tasks (including TOEFL and noun clustering on the dataset of corpus, window size, number of context dimensions, use of stemming, lemmatization and stopwords, similarity metric, score for feature weighting. Our study aims at extending their parameter set and evaluation methodology to standard tasks. Comparative clustering experiments showed no substantial differences for cosine similarity; in the rank-based setting, pam consistently outperformed work_5dzi3skd2ngnbczs2uwyz7x3se Research of Email Classification based on Deep Neural Network poor accuracy of email classification based on naive bayes classification algorithm based on DNN, in this paper we Bayes in the accuracy of email classification when the Keywords-Deep Neural Networks; Spam Email; Naive bayes algorithm is a kind of frequently-used email classification based on naive bayes algorithm is low. classification based on naive bayes algorithm, scholars have email classification algorithm based on deep neural network based on deep neural network was shown in Figure 3. Construct a DNN containing multiple hidden layers, set the number of the Spam Base dataset and extract the email features for number of nodes on each layer (hidden_units) ,set training of the algorithm in the email classification(accuracy_score) naive Bayes in the accuracy of email classification when the The application of email classification algorithm based Weight Based on Deep Neural Network," Computer Science, Vol. 43 work_5e3llx7bebbyjotwjnmnxonmk4 sys_1000 wp-p1m-39.ebi.ac.uk wp-p1m-39.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265369843 (wp-p1m-39.ebi.ac.uk) Time: 2021/04/06 17:58:19 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_5eaxej5xgbalnghivmnkptf75m The Remote Control System Based on the Virtual Reality network remote closed-loop control structure based on virtual reference idea to the remote real-time closed-loop control. Keywords-Virtual Reality; Network Time-delay; Remote simulation applied to network remote control structures and closed-loop control make the impact of network latency out Network latency makes remote real-time control has operator to create a virtual simulation environment based on the control objects and target of virtual reality association to the actual control objects and target, that is virtual reality can object response and real-time closed-loop control of the three closed-loop remote control system, the operator can be create a virtual closed-loop architecture and network delay as virtual real controlled object, then make the remote controlled object to achieve the purpose of real-time remote network remote closed-loop control was proposed. of network delay on real-time closed-loop control system of remote real-time closed-loop control. work_5i3h5iv2yrhdznh444ehpmhe7a realizes long (up to 10 NFs) and stateful service chains that achieve line-rate 40 Gbps (2016), SNF: synthesizing high performance NFV service chains. throughput degradation when realizing chains of interconnected, monolithic NFs. The first consolidation attempts targeted application layer (e.g., deep packet inspection) service chain of NFs. Packets in a traffic class are all processed the same way. SNF handles stateful NFs. Using its understanding of each of the per-traffic class chains, SNF then synthesizes equivalent, high-performance NFs for each of the traffic classes. Offloading traffic classification to a commodity OpenFlow switch allows SNF to realize realistic ISP-level chains at 40 Gbps (for most of the frame sizes), while bounding the median the service level where multiple NFs can be chained, we define a TCU as a set of packets, operator uses to specify a service chain to be synthesized by SNF. Software-based SNF: In the ''A chain of routers at the cost of one,'' ''Stateful service work_5i3wjeon5zeghmnvsvaas77wem Heterogeneous Networks and Their Applications: Scientometrics, Name Disambiguation, and Topic Modeling disambiguation, topic modeling, and the measurement of scientific impact to be easily solved Graph-based methods have been used to great effect in NLP, on problems such as word sense disambiguation (Mihalcea, 2005), summarization (Erkan in several applications: the measurement of scientific impact (Section 2), name disambiguation (Section 3), and topic modeling (Section 4). In general, non-heterogeneous measures like h-index or collaboration network Pagerank, which only focus on one type of relationship The heterogeneous network for this problem contains papers, authors, terms, venues, and institutions. Table 4: Performance of different networks and distance measures on the author name disambiguation task. al., 2011), a high-performance author disambiguation method based on the coauthorship graph. graph and topic association based on random walks may consider that the methods of the author disambiguation or topic modeling tasks could be to find work_5jbqrz54ujdzrhn3nbecrse62u To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST), a new methodology model can be used to support identification of fraud in public procurements in Brazil. To fill the gap, this paper describes the Uncertainty Modeling Process for Semantic Technology (UMP-ST), a methodology for defining a probabilistic ontology and using it the procurement fraud use case, but the UMP-ST is applicable to any domain in which UMP-ST, this section reviews related literature on design processes that provided an initial consistent with the ontology engineering and probability elicitation processes described in Figure 1 Uncertainty Modeling Process for Semantic Technology (UMP-ST). Figure 2 Probabilistic Ontology Modeling Cycle (POMC)—Requirements in blue, Analysis & Design As a case study, Carvalho (2011) developed a proof-of-concept probabilistic ontology The first step in defining a PR-OWL probabilistic ontology for the procurement fraud The Uncertainty Modeling Process for Semantic Technology (UMP-ST) addresses an work_5lcn66xezff75mzhcf2ufszade Linguistic sentiment analysis suggests another path forward: one could leverage textual features to predict the valence of evaluative texts Separate sentiment or signed-network models will miss or misread these signals. Many social networks encode person-to-person sentiment information via signed edges between users signs that (1) agree with the predictions of the sentiment model, and (2) form triangles that agree with respectively, and pe is the probability of edge e being positive according to the sentiment model alone. Intuitively, the more the inferred edge sign xe deviates from the prediction pe of the sentiment model, an HL-MRF to predict edge signs based on triangle sentiment model for all blue edges, and the signs of During testing, the network structure of all yellow edges, the sentiment predictions for all yellow Figure 5: Normalized cost λ(i) (defined in Sec. 4.3; logarithmic scale) for deviating from sentiment-model predictions pe, for bins i = 1,...,10 (Wikipedia). work_5mrw3qouhrez7dsxvmhhninjiy Integrated circuits may be vulnerable to hardware Trojan attacks during its design or Design of a Viterbi decoder and possible hardware Trojan models Keywords Coded communication system, Hardware Trojan, Viterbi decoder, Bit error rate and its hardware Trojan models: an FPGA-based implementation study. The work is concentrated toward RTL design of a Viterbi decoder and possible Trojans concept to a RTL level circuit design of the decoder and the Trojan activities. implementation of the Viterbi decoder is achieved and the Trojan effects on the system decoder performance, the decoder was fed with noisy data of different SNRs. Figure 14 shows the BERs obtained for the MATLAB behavioral model, the RTL design Effect of hardware trojans on the performance of a coded communication system. A Viterbi decoder and its hardware Trojan models: an FPGA-based implementation study A Viterbi decoder and its hardware Trojan models: an FPGA-based implementation study work_5o44bzxzyzdwdmbx5hz3b4svtq Keywords Swarm robotics, Automatic design, Behavior trees, Finite state machines, possible to use behavior trees as a control software architecture for robot swarms, as it has return running, Maple produces control software in the form of behavior trees with generated control software in the form of behavior trees by comparing its performance in Maple is an automatic modular design method that generates control software in the form behavior trees can be used as a control architecture in swarm robotics. control software for robot swarms in the form of behavior trees. trees as a control architecture in the automatic modular design for robot swarms, and in the context of the automatic modular design of robot swarms, behavior trees are a AutoMoDe-Chocolate: automatic design of control software for robot swarms. Automatic modular design of robot swarms using behavior trees as a control architecture Automatic modular design of robot swarms using behavior trees as a control architecture work_5omcr5wpnfgplho6goba5fsek4 visualize and map genome-wide data on to map and visualize the genome-wide information, such as GC content, gene and repeat The R package RIdeogram allows users to build high-quality idiograms of It can map continuous and discrete genome-wide data on the The visualization of genome-wide data mapping and comparison allow Keywords Genome, Chromosome, Idiogram, R package, Data visualization that allows to visualize and map whole-genome information on the idiograms based on ideogram Map and visualize the genome-wide data on the idiograms and visualizing, RIdeogram considers the continuous data, such as gene density across the RIdeogram is available through CRAN (https://cran.r-project.org/web/packages/ RIdeogram maps the gene density information on the idiograms as overlaid genome explained using two idiogram graphics, one showing the gene distribution and no species limitations and map genome-wide information on the idiograms for better Supplemental information for this article can be found online at http://dx.doi.org/10.7717/ chromPlot: visualization of genomic data in chromosomal context. work_5q357hhw75ff3ebwvg7x5x4ssu to similar visual approaches such as degree histograms, adjacency Graph analytic triage, Node-neighbor centrality, Standard canonical The degree of each node is the number of links 1. Calculate the centrality (degree) of each node semi–log, inverse, and same degree offsets, are presented in Section ''optional steps of the HB algorithm.'' algorithms only sample the graph data set, while the Figure 2: Visone backbone layout of jazz player data set. of Figure 5 shows which high-degree nodes are some of the highest degree nodes are not connected Figure 6: Sample directed neighbors plot for jazz player data set (Green = In, Red = Out). Figure 8: Backbone layout representation of the Toaster data set. Figure 15: HB chart of third 3,500 connections in Toaster data set. Figure 15: HB chart of third 3,500 connections in Toaster data set. Figure 14: HB chart of second 3,500 connections in Toaster data set. representation allows different node-link data sets, work_5s3bn533p5dixbjmrb6kr6wn5e Anfis Coordination of Changes In Power Oscillation Damper Parameters with proposed Adaptive Neuro Fuzzy coordinated controller is data set, the toolbox function ANFIS constructs a fuzzy graph of check data and ANFIS output for lead time constant. Training Data and ANFIS Output: Lead Time Constant Check Data and ANFIS Output: Lead Time Constant Training Data and ANFIS Output: Lag Time Constant Check Data and ANFIS Output: Lag Time Constant PLOT OF TRAINING DATA AND ANFIS OUTPUT:LAG TIME CONSTANT PLOT OF TRAINING DATA AND ANFIS OUTPUT:LAG TIME CONSTANT PLOT OF CHECK DATA AND ANFIS OUTPUT:LAG TIME CONSTANT PLOT OF CHECK DATA AND ANFIS OUTPUT:LAG TIME CONSTANT PLOT OF TRAINING DATA AND ANFIS OUTPUT:LEAD TIME CONSTANT PLOT OF TRAINING DATA AND ANFIS OUTPUT:LEAD TIME CONSTANT PLOT OF TRAINING DATA AND ANFIS OUTPUT:LEAD TIME CONSTANT PLOT OF CHECK DATA AND ANFIS OUTPUT:LEAD TIME CONSTANT PLOT OF CHECK DATA AND ANFIS OUTPUT:LEAD TIME CONSTANT work_5sg54cik6vhyno33zefmwbmjyy part-of-speech tagging and dependency parsing for truly low-resource languages. Our annotation projection-based approach yields tagging and parsing models for over 100 languages. The best cross-lingual dependency parsing results reported to date were presented by Rasooli and Collins (2015). to cross-lingual POS tagging and dependency parsing are biased toward Indo-European languages, in annotations projected from one or more source sentences through word alignments. Figure 1: An outline of dependency annotation projection, voting, and decoding in our method, using two sources i each vertex v, the projection works by gathering evidence for each tag from all source tokens aligned to Languages with more than 60k tokens (in the training data) are considered source languages, the remaining 6 smaller treebanks (Estonian, Greek, Hungarian, Latin, Romanian, Tamil) are strictly considered targets. sentence pairs, we project POS tags and dependency and dependency parsed target sentence ready to contribute in training a tagger and parser. work_5skuz4byfra4hjw2nr3q35de7u compared with the default system memory allocator, the efficiency of the Recoverable Fixed Length Keywords: High Concurrency, search engine, memory pool, distributor use the New and Delete functions for the allocation and release of each node of the hash table, and the the present search engine system, and the allocation and release of memory of each node in the Map is managed by the distributor in the STL, take over the fixed node memory allocation and release by itself, After analysis, the search engine return the result sat the same time, memory is frequently allocated, the Based on this scene design allocate not free memory pool. Recoverable Fixed Length Memory Pool is Small object distributor, it divided into 4 layers structure. of New/Delete and the memory pool interface function of Allocate/Deallocate. 4.3 Performance test and analysis of allocate not free memory pool work_5u2zpk2fhfbwneryxw4r65giga We suggest a compositional vector representation of parse trees that relies on a recursive Dependency parse-trees encode not only the syntactic structure of a sentence the head word, and the last input is the vector representation of the left-most or the right-most modifier. encoding trees as vectors, and methods for parsing The popular approach for encoding trees as vectors is using recursive neural networks (Goller and Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1159–1168, Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1159–1168, Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1159–1168, work_5uau7ub4i5hn7kt6ojw35x4dxi that supports the major cloud providers, offering scalable management of scientific Keywords Microservices, Cloud computing, Virtual research environments, Application instantiating on-demand VREs on the major cloud providers (''Implementation''). At the lowest level, the Cloud Provider layer manages virtual resources at infrastructure In particular the Cloud Provider manages virtual resources at infrastructure level, and The set of services for a certain community of practice run as container-based microservices, on-demand VREs. In fact, these services may not be available in certain private cloud tools that were parallelized using the PhenoMeNal on-demand VRE on different cloud providers. Figure 6 KubeNow deployment time by cloud provider. The plot shows the deployment time for different cluster sizes (number of nodes) on each of the supported cloud providers. When provisioning on different cloud providers, KubeNow uses the same deployment http://www.infoworld.com/article/3118345/cloud-computing/why-kubernetes-is-winning-the-container-war.html http://www.infoworld.com/article/3118345/cloud-computing/why-kubernetes-is-winning-the-container-war.html http://www.infoworld.com/article/3118345/cloud-computing/why-kubernetes-is-winning-the-container-war.html Available at https://research.csc.fi/cloud-computing (accessed on 16 May Available at https://cloud.google.com/filestore (accessed on Available at https://cloud.google.com/run (accessed on 16 May work_5ugdn7t5sbcplkszshjcthwizq the fractional order Chen chaotic system and discrete wavelet transform is proposed. Keywords: fractional order chaotic system, discrete wavelet transform(DWT), image Poonkuntran and Rajesh proposed a new imperceptible image watermarking scheme proposed a watermarking method based on chaotic map and operation of transform feasible to use discrete wavelet transform(DWT) and chaotic system to encrypt the watermark. Inspired by above analysis, a new image watermarking scheme based on the fractional order Chen Through research, a new image watermarking scheme based on the fractional order Chen chaotic system Image Watermarking Encryption Scheme Based on Fractional Order Chaotic System Image Watermarking Encryption Scheme Based on Fractional Order Chaotic System Image Watermarking Encryption Scheme Based on Fractional Order Chaotic System Image Watermarking Encryption Scheme Based on Fractional Order Chaotic System Image Watermarking Encryption Scheme Based on Fractional Order Chaotic System "Blind image watermarking method based on chaotic key and dynamic work_5w5ug7v47bhlhiu6ds5mrfzzfi reconfiguration abilities of the systems through the synthesis of monitoring programs article presents a new method for the synthesis of monitoring programs and develops Reconfigurable monitoring processes should allow us to gather the data about assume that monitoring systems gather data from objects. Adaptive systems use flexible data processing models (Cabal-Yepez et al., embedded monitoring systems, they equip with reconfigurable data preprocessing modules Monitoring processes are oriented on providing data about the state of the end-users'' both the output data about the state of the network and the conditions of the monitoring, According to Fig. 1, monitoring processes assume gathering data about the target objects The method allows synthesizing programs for objects monitoring in conditions when the In the automata model for program synthesis, the set of input data elements {ds} are 6. /* Build the model of the monitoring program according to the synthesized structure */ work_5xauxfpkpffzjmeon76ftymtxi The Effect of Residual Stress on Coupling Power Loss of VCSEL In this article, the effect of residual stress on active region misalignment of laser light sources for vertical introduced from the residual stress distribution variation for different VCSEL solder joints, i.e. tin-silver (Sn/3.5Ag) and tin-lead (Sn/37Pb) solder joints, are simulated by employing the thermal-elastic-plastic finite element model of MARC The optical coupled power of a VCSEL modulus depends upon residual stress distribution To assemble the VCSEL modulus, SMT uses different solder ball joints, such as Fig.3 Reflow process for VCSEL using Sn/37Pb solder joints. residual stress distribution of Sn/37Pb solder joints used by the VCSEL modulus for the reflow process. Fig.5 Displacement of point A of VCSEL using Sn/37Pb solder joints the reflow process, the VCSEL structure and fiber are jointed. Table.2 Active region displacement (µm)/ Optical coupled power loss for different solder ball grid array joints work_5y7zlwyzhfcunhtjekvohrwboy work_5yrfjqd225fv7jchnnxplfrdgm Levenberg-Marquardt Method Based Iterative Square Root Cubature Kalman Filter and its Applications to Maneuvering Re-entry Target Tracking iterative square root cubature Kalman filter (abbr. algorithm to the state estimation of maneuvering re-entry ISRCKFLM algorithm has better accuracy of state estimation, comparable to Unscented Kalman filter and square root Cubature Kalman filter, according to estimation error analysis Keywords-Nonlinear Filtering; Square Root Cubature Kalman Filter; Levenberg-Marquardt Method; Maneuvering Reentry Targets Tracking The state estimate of maneuver re-entry target is highly estimation of maneuver re-entry target, EKF may produce square root cubature Kalman filter (ISRCKFLM) was we apply the ISRCKFLM algorithm to state estimation of Then we apply the ISRCKFLM algorithm to track re-entry L-M BASED ITERATIVE SQUARE ROOT CUBATURE Iterative square root cubature Kalman filter (ISRCKFLM) is algorithms, we obtain the root mean square errors (RMSEs) SRCKF algorithms, especially, the RMSEs of ISRCKFLM SRCKF on the state estimation of maneuvering re-entry work_5z7jukcuuzcjpf3dkbskq4rrc4 Exploring the Role of Stress in Bayesian Word Segmentation using Adaptor Grammars Exploring the Role of Stress in Bayesian Word Segmentation using Adaptor Bayesian word segmentation model to take advantage of stress cues noticeably improves its investigated the role of stress in word segmentation using computational models, using both neural network and "algebraic" (as opposed to "statistical") approaches (Christiansen et al., 1998; Yang, Bayesian models of word segmentation (Brent, 1999; Goldwater, 2007), however, have who added stress cues to the Bigram model (Goldwater et al., 2009), demonstrating that this leads to Following Cutler and Carter (1987)''s observation that stressed syllables tend to occur at the beginnings of words in English, Jusczyk et al. The earliest computational model for word segmentation incorporating stress cues we are aware of 2005), the high score Yang reported crucially depends on every word token carrying stress, including stress cues for the colloc3-nophon model, we do see work_643a5sia2bchnksdxl2mqbqyka event classes in biographies, based on a probabilistic latent-variable model. and observational data; we present here a latentvariable model that exploits the correlations of event To analyze the latent event classes in Wikipedia biographies, we train our full model (with a logistic normal prior and time as an observable variable) on the full dataset of 242,970 biographies with The latent classes that we learn span a mix of major life events of Wikipedia notable figures (including events that we might characterize as GRADUATING HIGH SCHOOL, BECOMING A CITIZEN, DIVORCE, BEING CONVICTED OF A CRIME, and DYING) and more fine-grained events (such as BEING DRAFTED BY A SPORTS TEAM and BEING INDUCTED INTO THE HALL OF FAME). exists between event classes, we draw on the original work on procedural scripts and schemas (Minsky, 1974; Schank and Abelson, 1977) and narrative chains (Chambers and Jurafsky, 2008; Chambers and Jurafsky, 2009), including more recent advances in the unsupervised learning of frame semantic representations (Modi et al., 2012; O''Connor, work_657azxnanzf5not3eq7kgvht6e A New Method of Improving the Traditional Traffic Identification and Accuracy the application of Support Vector Machine (SVM) in traffic collection and feature generation methods and network traffic Keywords-Support Vector Machine (SVM); Traffic present, the method of network traffic recognition based on classification method based on support vector machine [19], traffic classification based on SVM was introduced, how to paper proposes a network traffic two classification method SVM is a machine learning method that is based on one network traffic classification identification code, statistics C. Support vector machine network traffic identification The network traffic identification based on vector D. P2P traffic classification model based on SVM the entire network traffic identification based on SVM. process of different P2P traffic data, and one support vector A P2P Traffic Classification Method Based on SVM[C]// P2P traffic classification method based on A P2P Network Traffic Classification Method Based on C4.5 work_65iu2434afccfidjkt4v6det2m A Full Decimal Method of Address Assignment for Keyword-Decimal; Future Network; IPV9; Address address assignment for networked computers and 1) External addresses of all networked computers 2) Internal address of all networked computers and numbers, MAC address, and the latest digital domain addressing structure and identification sub-network, the structure of address format prefix and network addressing of the communication Internet interface domain address in the form of a 32-bit decimal number. domains with each address of a binary number from assigned to single network interface, the identifier is of Internet network addresses. the decimal number of the external address are bit of the decimal number of the address is address can be assigned to more than one network full-digital coded address consisted of network access full-digital coded address established through the Internet access, including: domain name, IP address [1] Xie Jianping etc.A method of assigning addresses to network work_6ca2tg546ratlmrt7cjdctbwau dataset1 based on CSI episodes, formalize perpetrator identification as a sequence labeling We formalize the task of identifying the perpetrator in a crime series as a sequence labeling problem. The model predicts for each input whether the perpetrator is mentioned or not. work in natural language processing, computer vision, and more generally multi-modal learning. work uses low-level features (e.g., based on face detection) to establish social networks of main characters in order to summarize movies or perform genre Once the episode is finished and the perpetrator is revealed, the same participant annotates entities in the screenplay referring We formalize the problem of identifying the perpetrator in a crime series episode as a sequence labeling task. As mentioned earlier, the input to our model consists of a sequence of sentences, either spoken utterances or scene descriptions (we do not use speaker model guesses at the start of the episode closely follow the pattern of gold-perpetrator mentions (bottom work_6egrw63wyfcczp2iyrguf2koaq explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any generalor specialpurpose repository as a means to assist users in finding and reusing their data holdings. FAIR guiding principles aimed at publishing data in a format that is Findable, Accessible, data within these objects to be queried in parallel with other data on the Semantic Web. Metadata interoperability—the "FAIR Accessor" and the linked data platform The Linked Data Platform ''''defines a set of rules for HTTP operations on Web resources...to provide an architecture for read-write Linked Data on the Web'''' (https://www.w3.org/TR/ resolve by HTTP GET to documents containing metadata about an individual data component and, a database, a data transformation script, an analytical web service, another FAIR Projector, semantics for a particular data resource, also provides its associated Projector URL. When a FAIR Projector is available, additional DCAT Distributions are included in this metadata document. work_6fazzelrfneund7qlj4jpzclhy work_6fchrrabknd3vnvyxpbbhrm72a that virtual working spaces might be designed to support collaborative creativity in is an effective way to support collaborative creativity in SVEs, (ii) personal spaces Designing spaces to support collaborative creativity in shared virtual environments. Bryan-Kinns, 2019), and integrating personal and group spaces, allowing users to work personal space to be helpful in supporting collaborative music making in SVE, since it H1—Personal space with mobility provides better support for collaboration than personal Bryan-Kinns 2019) in CMM in SVE, providing collaborators with a personal space and between personal and public spaces, which supports collaboration better compared to (2) Time and amount of use of personal space (only in condition Cfix and Caug, as this results indicate that the addition of personal space in Cfix and Cmov possibly led to a weaker (P13A), less separation, better collaboration compared conditions where ''''personal space'''' Compared with rigid personal spaces in Cfix and Cmov, Caug saw more mutual note work_6gjuzkl6kbevxi5nkkalt7xhgm of encoding partial lexicon matches in neural networks and compare it to existing approaches. given only tokenized text and publicly available word embeddings, our system is competitive on the CoNLL-2003 dataset and surpasses the previously reported state of the art (2011b) proposed an effective neural network model that requires little feature engineering and instead learns important features from Figure 2: The convolutional neural network extracts character features from each word. NER performance, we propose a new lexicon encoding scheme and matching algorithm that can make word features into named entity tag scores. features, emb = Collobert word embeddings, caps = capitalization feature, lex = lexicon features from both SENNA Table 6: F1 score results of BLSTM and BLSTM-CNN models with various additional features; emb = Collobert capitalization features to the BLSTM-CNN models degrades performance for CoNLL and mostly Table 6 shows that on the CoNLL-2003 dataset, using features from both the SENNA lexicon and our work_6got5qjl3jemrgxkocpfbmmzvq ngg2, to identify 3′GG gRNA sites from indexed FASTA files. of human protein coding genes have at least one unique, overlapping 3′GG gRNA. tool provides an important ability to identify 3′GG editing sites in any species with an Keywords gRNA, Motif discovery, Python, Open-source, CRISPR/Cas9, 3′GG How to cite this article Roberson (2015), Identification of high-efficiency 3′GG gRNA motifs in indexed FASTA files with ngg2. Overall, I identified greater than 88 million 3′GG gRNA sites in the tested genomes different numbers of 3′GG gRNA sites per genome. Table 2 3′GG gRNA sites per megabase genome size. The number of unique 3′GG gRNA sites in the genomes is encouraging, with an The efficiency of 3′GG gRNA sites in species Identification of high-efficiency 3''GG gRNA motifs in indexed FASTA files with ngg2 Identification of high-efficiency 3''GG gRNA motifs in indexed FASTA files with ngg2 work_6iejq5km6bh3fp7caakywxrp5m high efficient graph partition procedures and triangle motif-based clustering network structures and statistical data with triangle motifs. Keywords Community property, Triangle motif, Large network, Clustering number of the clustered subgraphs from the original large network, and n is the number problem, we combine the graph partition method with the motif-based clustering which are defined as motifs, that is, a set of edges with a small number of nodes. graph partition, we cut the original networks into initial subgraphs under the four clustering procedure, that is, graph partition, modularity refine procedure and motif-based We take the subgraph set of the original network as the input of the motif-based clustering Here, R is the clustering result set, vi is one of the nodes in the subgraph, and w is COMICS: a community property-based triangle motif clustering scheme COMICS: a community property-based triangle motif clustering scheme work_6jll4ersjfbzpo2ra3sito2ydi a set Networked laboratory security system. system uses sensor design nodes to form a ZigBee wireless sensor network to realize the collection of data transmission in the wireless sensor network number of wireless sensor network nodes arranged in composed of three parts: wireless node module, sensor Wireless sensor network node develop a set of wireless sensor networks according to data transmission between the nodes in the network is situation, a routing node is designed in the network to 1) Design of sensor data acquisition module module, and sends the data to the network. abnormality, continue to collect laboratory sensor data. node, so as to join the network and perform data assigned, the terminal node sends data to the node is in another network or whether a coordinator network address and send and receive data through this Monitoring System Based on ZigBee Wireless Sensor Network" ZigBee Sensor Network Technology and Its Application" Radio work_6ljoda22qrewffngplu5frxzny sys_1000 wp-p1m-38.ebi.ac.uk wp-p1m-38.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265376061 (wp-p1m-38.ebi.ac.uk) Time: 2021/04/06 17:58:27 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_6lltcw7mj5effmke754i7v26s4 Such word embeddings have achieved state-of-theart performance on many natural language processing (NLP) tasks, e.g., syntactic parsing (Socher et For example, in dependency parsing, word embeddings could be tailored to capture similarity in terms of context within (2015) have proposed to use canonical correlation analysis (CCA) as a method to learn lowdimensional real vectors, called Eigenwords. This use of CCA to derive word embeddings Figure 3: The CCA-like algorithm that returns word embeddings with prior knowledge encoded based on a similarity graph. Table 1: Results for the word similarity datasets, geographic analogies and NP bracketing. We evaluated the quality of our eigenword embeddings on three different tasks: word similarity, geographic analogies and NP bracketing. into 9 distinct blocks, labeled A through I.) In general, adding prior knowledge to eigenword embeddings does improve the quality of word vectors for FrameNet as a prior knowledge resource for improving the quality of word embeddings is not as helpful work_6m5hm7oumzeynlpkcsrvtr5tey example, in text-to-speech synthesis, one must convert digit sequences (32) into number names (thirtytwo), and appropriately verbalize date and time expressions (12:47 → twelve forty-seven) and abbreviations (kg → kilograms) while handling allomorphy and morphological concord (e.g., Sproat, 1996). This paper continues this tradition by contributing minimally-supervised models for normalization of cardinal number expressions (e.g., ninetyseven). times, dates, measures, or currency expressions without knowing how to verbalize that language''s numbers as well. first FST factors the integer, expressed as a digit sequence, into sums of products of powers of ten (i.e., The core of the approach is an algorithm for inducing language-specific number grammar rules. training example consisted of a digit sequence, gender and case features, and the Russian cardinal number verbalization of that number. Table 3: Accuracies on a test corpus of 1,000 random Russian citation-form number-name examples for the two RNN transducing from integers expressed as digit sequences to the set of possible factorizations for work_6mlcjuckcve7pcpruferfakk64 Keywords Feature selection, Nutritional status, Machine learning, Mediterranean diet, the degree of adherence to the Mediterranean diet through machine-learning techniques. Thus, this study is relevant for understanding how to measure the degree of adherence, The information described below was collected from each selected subject: sociodemographic variables: age, gender, level of education, marital status and relationships of Once the data of the different measurements were obtained, the mid-arm muscle best model in order to ensure whether the performance of a particular ML technique is Figure 2 Summary of the average performance of the experiments: (A) (Accuracy) and (B) (F-measure) of the four ML techniques (RF, SVM, predictive factors of the degree of adherence to the Mediterranean diet through Adherence to Mediterranean diet and bone health. Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques work_6n2v2a3dwvgbndggzshipvmfpy of different approaches to coreference resolution in terms of the structure they operate In particular, we analyze approaches to coreference resolution and point out that they mainly differ in the structures they operate on. we develop a machine learning framework for structured prediction with latent variables for coreference differ in the scope (pairwise, per anaphor, per document, ...) they employ while learning a scoring function for these pairs, and the way the consolidating is focus on accounting for the latent structures underlying coreference resolution approaches. In our framework, we can represent the mention pair model as a labeled graph. The cost function from the mention ranking model naturally extends to the tree case When viewing coreference resolution as prediction of latent structures, entity-based models operate on structures that relate sets of mentions to While antecedent trees give results with the highest precision, a mention ranking model with latent work_6qacatlyhvbifcttz5bojghhhu architecture and Python-based software framework for developing vision algorithms Keywords Computer vision, Computational graph, Publish-subscribe, Robotics, Python, Pipeline, overview of computational systems based on DAGs, the Python data science/computer pool of community-contributed image processing and computer vision algorithms. It allows to develop data processing pipelines, the behavior of algorithm as a computational graph, that is, as a network of functions and data tokens. For example, to visualize the blurred image from the computational graph in Fig. 4 To introduce additional functionality to algorithms expressed as computational graphs and comprise vision processing time sp, overhead from orchestrating the computational graph ocg, 2. EPypes overhead is computed as an excess time in the vision pipeline in addition to the EPypes: a framework for building event-driven data processing pipelines EPypes: a framework for building event-driven data processing pipelines EPypes: a framework for building event-driven data processing pipelines work_6qxc4oe23veqhn7qioxt5srhlu investigate if coupled file change suggestions influence the correctness of the task How to cite this article Ramadani and Wagner (2017), Are suggestions from coupled file changes useful for perfective maintenance tasks? RQ1: How useful are coupled file change suggestions in solving perfective maintenance RQ1.2: Do coupled file change suggestions influence the time needed to solve perfective tasks between the developers who used coupled file change suggestions and those not using and on two tasks using coupled file change suggestions and their related attributes. related to sets of relevant coupled file changes, we define perfective maintenance tasks maintenance task and the set of coupled file changes is presented in Table 3. The complete list of the maintenance tasks, the coupled file changes, the software repository of the difference in the time needed to solve the tasks by the group using coupled file changes the coupled file changes and the attributes as neutral to use in maintenance tasks. work_6tznbs2z2jf6rownybxrorcdsu Nodes are color coded and sized by population density and edges connecting them highlight the density and complexity of human communication and mobility networks. networks are changing over time, and in Senegal there are many large-scale mobility events, relating to different spatio-temporal patterns of human mobility that contrast in overall spatial scale scales and patterns of human mobility, we calculated dominant wavelet functions centered in the scale associated with the dominant wavelet function (centered on Touba) better reveals the punctuated and large-scale mobility events related to religious celebrations (vertical red lines) and Senegal''s daily wavelet functions identifies changes in human mobility relating to the dry and wet Figure 4 Main spatio-temporal patterns of human mobility can be identified by averaging the dominant wavelet functions associated with the wavelets) for analyzing CDR human mobility data. Identifying multiscale spatio-temporal patterns in human mobility using manifold learning Identifying multiscale spatio-temporal patterns in human mobility using manifold learning work_6ymfcev3qva5lpd4wvsschrfkm Application of Chaotic Encryption in RFID Data generated by the chaotic map is used to encrypt the data chaotic sequences, the information of each electronic tag is encrypted with a unique chaotic sequence. data, and a security model based on chaotic encryption paper is mainly to use Logistic chaotic map to generate chaotic sequences to encrypt the data transmitted CHAOTIC SEQUENCE ENCRYPTS RFID parameter value required for chaotic mapping in the data information of each tag uses a unique chaotic generated by the chaotic map is the real field value, and general encryption process of Logistic chaotic map. Parameter value calculation process: In the RFID After the chaotic encryption sequence is transmission are all chaotically encrypted data, and the Read and write control mechanism after chaotic encryption. uses the chaotic encryption sequence generated by the Logistic chaotic map to encrypt the data transmitted by Encryption Based RFID System Information Security[J]. work_6zpvnyjfevhnfiwqfnt3wzyf5y the mean pupil diameter change rate (MPDCR), a measure introduced by Palinko et al. The participants were requested to perform 50 trials of mental arithmetic tasks (multiplications of two numbers), five of which were used as a short training. The mean pupil diameter change (MPDC) for each participant was then obtained The pupil diameter measures (MPD, MPDC, and MPDCR), the blink rates (MBR), and Figure 5 Mean pupil diameter change (MPDC) during the mental multiplication task, for the three Figure 6 Cohen''s dz for the mean pupil diameter change (MPDC) between pairs of levels of difficulty. Figure 7 Mean pupil diameter change rate (MPDCR), for the three levels of difficulty and for seven Figure 9 Mean pupil diameter (MPD) during the mental multiplication task for the third level of Figure 9 Mean pupil diameter (MPD) during the mental multiplication task for the third level of work_75gdtwc2zvf7ta3kal27fs4suu two retrieval-based models, where we output the response which has the highest match with the input context from a set of classifier-picked polite Therefore, our novel polite dialogue models are based on an accurate neural classifier, which Moreover, our approaches allow simply replacing the politeness classifier with any other emotion or personality based language classifier to generate stylistic dialogue for that new style dimension. for effective use in stylistic dialogue response generation, we extend and improve upon the state-of-theart CNN model of Aubakirova and Bansal (2016), model to generate a polite response, we scale the label''s embedding by a score between 0.5 and 1.0, produce polite, neutral and rude responses depending on the prepended label, similar to recent multilabel, multi-space, and zero-shot machine translation work using language identity or style labels (Sennrich et al., 2016a; Johnson et al., 2017; Human To evaluate our models'' ability to generate polite responses without sacrificing dialogue work_75lsf6zn3rhpflwrux7comg6zy HBPF: a Home Blood Pressure Framework with SLA guarantees to follow up hypertensive patients Home Blood Pressure Framework with SLA guarantees to follow up an efficient cloud-based Home Blood Pressure Framework. patients to communicate with their health-care centers, thus facilitating monitoring for framework to follow up hypertensive patients with an SLA guarantee. user-friendly interface is also provided to facilitate following up hypertensive patients. This paper presents HBPF, an efficient cloud-based Home Blood Pressure Framework. HBPF provides a complete, efficient, and cross-platform framework to follow up hypertensive patients with an SLA guarantee. time below one second for 80 000 requests and 28% increase in peak throughput going from one to three virtual machines were obtained. provided to facilitate following up hypertensive patients. Home blood pressure (HBP) consists of patients taking readings at home23 also provides additional facilities to follow up hypertensive patients.130 periodically reminds the patient to send their blood pressure readings. work_77qqyvwmkzehpc4drzvfito2hi The automatic prediction of protein function can provide quick annotations on extensive datasets opening the path for relevant applications, such structure-based protein function prediction, but sufficient data may not yet be available Keywords Enzyme classification, Function predition, Deep learning, Convolutional neural How to cite this article Zacharaki (2017), Prediction of protein function using a deep convolutional neural network ensemble. Most methods use features derived from the amino acid sequence author''s knowledge, deep CNNs have not been used for prediction of protein function so far. enzymatic function prediction, the method is not based on enzyme-specific properties and multi-channel feature set is introduced to a CNN and results are combined by kNN or SVM classification. of amino acids and their arrangement in space (features XD) predict enzymatic function Using pseudo-amino acid composition and support vector machine to predict protein structural class. Predicting enzyme class from protein structure without convolutional architecture for sequence-based protein structure prediction. work_7dbhbon7qnde7pnrlnuwtsy5mu Entity Linking meets Word Sense Disambiguation: a Unified Approach Entity Linking meets Word Sense Disambiguation: a Unified Approach Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical ambiguity of language. on a loose identification of candidate meanings coupled with a densest subgraph heuristic which selects high-coherence semantic interpretations. Our experiments show state-ofthe-art performances on both tasks on 6 different datasets, including a multilingual setting. a densest subgraph heuristic on the available semantic interpretations of the input text to perform a joint 3. We create a graph-based semantic interpretation of the whole text by linking the candidate We consider BabelNet as a directed multigraph which contains both concepts and named entities as its vertices and a multiset of semantic relations as its edges. • The SemEval-2007 task 7 dataset for coarsegrained English all-words WSD (Navigli et al., UKB w2w system,8 a knowledge-based WSD approach (Ponzetto and Navigli, 2010) which exploits work_7drikjhpivhsjj7hgjbx3kyriy Unsupervised Part-Of-Speech Tagging with Anchor Hidden Markov Models These HMMs impose an assumption that each hidden state is associated with an observation state ("anchor word") that can appear under no other state. Because each hidden state is associated with an observation, we can examine the set of such anchor observations to qualitatively evaluate the learned model. In Section 3, we define the model family of anchor HMMs. In Section 4, we derive a matrix decomposition algorithm for estimating the parameters of an anchor A concrete algorithm for factorizing a matrix satisfying Condition 4.1 is given in Figure 1 (Arora model, the algorithm Learn-Anchor-HMM in Figure 2 outputs (π,T,O) up to a permutation on hidden states. We speculate that this is because a Brown model is rather appropriate for the POS tagging task; many words are The anchor condition corresponds to assuming that each POS tag has at least one word that work_7hmcw6dxwjborfxvzwffuce4wq In this article, we propose a method for evaluating feature ranking algorithms. (RFA) curves, which reveal how the relevant features are distributed in the ranking(s). (true positives) and irrelevant features (false positives) with the feature relevance above the starting point for showing the usefulness of a feature ranking evaluation method, as why FFA curves are an appropriate method for comparing feature rankings, nor which and lower quality of feature rankings is reflected in the FFA and RFA curves, and thus When comparing the FFA and RFA curves of different ranking methods, constructed with We construct the curves that base on the feature ranking methods described in Figure 7 Ranking quality assessment for datasets breast-w (A–C) and water (D–F) in terms of the FFA (A and D) and RFA curves (B and E), Error curves for evaluating the quality of feature rankings Error curves for evaluating the quality of feature rankings work_7jjkktfhpnadnpukptzosc5hta recently proposed morphological word representations, we show that our vectors achieve (2013b) proposed simple log-bilinear models to learn continuous representations of words on very large corpora neural language models, where words are represented as sets of features. Recently, several works have proposed different composition functions to derive representations of words Word representations trained on morphologically annotated data were introduced by Cotterell and Schütze (2015). have proposed using subword units to obtain representations of rare words (Sennrich et al., 2016; Luong and Manning, 2016). First, by looking at Table 1, we notice that the proposed model (sisg), which uses subword information, outperforms the baselines on all datasets except and obtain representations for out-of-vocabulary words with our model by summing the vectors of character of our word vectors on the similarity task as a function of the training data size. the language model with pre-trained word representations improves the test perplexity over the baseline LSTM. work_7jtgrdqc4zeb7lul7vifzjglr4 parsing models that predict syntactic structure augmented with semantic predicate-argument relations is challenging to define efficient methods for syntactic and semantic dependency parsing that can exploit • We solve joint inference of syntactic and semantic dependencies with a dual decomposition method, similar to that of Koo et al. A joint model for syntactic and semantic dependency parsing could be defined as: A joint model for syntactic and semantic dependency parsing could be defined as: paper we describe a method that searches over syntactic and semantic dependency structures jointly. paper we describe a method that searches over syntactic and semantic dependency structures jointly. where s srl computes a score for a semantic dependency 〈p,a,r〉 together with its syntactic path where s srl computes a score for a semantic dependency 〈p,a,r〉 together with its syntactic path (2009) defined a joint model that forces the predicate structure to be represented in the syntactic dependency tree, by enriching arcs with semantic information. work_7kttx52hpfgffkvvc235rluscq Previous work coped with the open-domain aspect of algebraic word problems by relying on deterministic state transitions based on verb categorization (Hosseini et al., 2014) or by learning templates called a Quantified Set or Qset to model natural language text quantities and their properties (e.g., ''375 and combining quantities when learning the correspondence between equation trees and text. Inference (word problem w, local set relation model Llocal , global equation model Gglobal ): an ILP-based optimization method to combine extracted Qsets into a list of type-consistent candidate scores equation trees based on the global problem We use an ILP optimization model to generate equation trees involving n base Qsets. desirable candidate equations for a given word problem w using an ILP, which models global considerations such as type consistency and appropriate low models to compute a score for each candidate equation tree generated for an unseen word problem at versus the template-based method on single-equation algebra word problems. work_7ohmgws75fcdhfv77ad7lvpszu Multi Antenna Precoding Algorithm Based on M Spread Spectrum antenna precoding algorithm based on M spread spectrum, precoding before sending signal spread spectrum to simplify Keywords-MIMO; Multi Antenna Technology; Mobile The signal model of MIMO multi antenna system: diversity gain provided by MIMO channel, multiple antennas then the spread spectrum code sequence generated by the spread spectrum code generator is used to modulate the the local spread spectrum code sequence generated from the code generator to expand the spectrum of digital signal. The spread spectrum sequence with high bit rate is used the receiver, the same spread spectrum sequence is used to modulation using the spread spectrum code sequence makes the sequence of spread spectrum code in one frame. Pseudorandom code sequences can be generated by the shift algorithm based on M spread spectrum, and the binary signal spread spectrum communication technology [N]. spread spectrum communication technology [N]. spread spectrum communication technology [N]. work_7p5ztx3635bq5edkve5fwxg25i Application of Incremental Updating Association Mining Algorithm in Geological update the association mining of the inverted index tree. association mining algorithm was applied to the data it is found that the inverted index tree updating association Tree Incremental Updating Association Mining Algorithm Inverted Index Tree Incremental Updating Association Mining of the Inverted Index Tree Incremental Updating Association Mining Algorithm, the association rules are obtained and the Keywords-Inverted Index Tree; Geological Disaster System; Frequent Item Sets; Association Rules association rule algorithms in big data technology incremental association rule updating techniques have updating association mining when the transaction record data ALGORITHM OF INCREMENTAL UPDATING RULE item set combination is the association rule. correlation mining algorithm, Inverted Index Tree Incremental Updating Association mining algorithm tree, Inverted index tree incremental update association the new data processing, the item set inserted IITree. Inverted index tree of updated data association rules between sets of items in large databases[J]. work_7uu52ce5ffbllph3ywz24bap3u Global Internet Come into a New DNS Era Research Center of International Strategic, China Mobile Communication Federation service provided by Domain Name System (DNS). The application of DNS protocols on the Internet the DNS Domain Name System Security Extension of DNS in the "next generation Internet ". get access to Internet data worldwide. platform of network data operations, applications, CHINA''S NETWORK DATA HAS MAJOR conducted in China hosted overseas, and the data the "revolving door"-Open source data, information, duties related to Internet DNS root zone management; real-time monitoring of DNS open source data control of the Internet, strive to develop the DNS Today, any network technology carries data. Network applications generate data; interconnections utilization rate of China''s data centers is less than 50%, technology, discusses Internet security and data development of the Internet domain name system to development of the Internet domain name system to ensure China''s data sovereignty and information work_7vrukcafpzgrvmhu5m3pbiimbe Research on Bounding Volume Boxes Collision Detection Algorithm in Virtual different kinds of bounding boxes collision detection bounding box collision detection algorithm based on spheres continuously, and some classic collision detection algorithms collision detection technology, real-time rendering For the detection of object collision, Unity provides a the traditional bounding box collision detection algorithm build the bounding box tree because the objects in the detection algorithm based on the OBB bounding box, collision detection, the number of basic geometric primitives bounding box overlap test and the cost Cu of updating a collision detection test algorithm, without the need to write the corresponding collision detection algorithm, which collision detection algorithm based on encircling ball and hybrid bounding box algorithm based on the encircling ball Then compare the distance between center and each basic geometric element in the object E, maximum value is that the radius of the bounding sphere, denoted by R. work_7wyyn4jlmzflvnev4k7qonrx2i Decentralized partially observable Markov decision processes (Dec-POMDPs) are general models for decentralized multi-agent decision making under uncertainty. solutions to be generated for significantly longer horizons and larger state-spaces than previous Dec-POMDP methods. Singh, 1999), have explored using higher-level, temporally extended macro-actions (or options ) to represent and solve problems, leading to significant performance improvements in multi-agent case by introducing a Dec-POMDP formulation with macro-actions modeled extended to multi-robot systems: our methods naturally bridge Dec-POMDPs and multirobot coordination, allowing principled decentralized methods to be applied to real domains. To solidify this bridge, we describe a process for creating a multi-robot macro-action DecPOMDP (MacDec-POMDP) model, solving it, and using the solution to produce a set of Dec-POMDPs (Bernstein et al., 2002) generalize POMDPs1 (Kaelbling, Littman, & Cassandra, 1998) and MDPs2 (Puterman, 1994) to the multi-agent, decentralized setting. is, given a current belief state, b, and a policy of option-based macro-actions, µ, the value work_7z3ossdi4rddjfj5xuw5l6m5eq method which uses the induced lexicon to assign positive/negative sentiment scores to unlabeled documents first, a nd t hen u ses those There are many different approaches to sentiment classification in the Natural Language Processing (NLP) literature — from simple lexicon-based When we need to perform sentiment classification in a new domain unseen before, there are usually neither labeled dictionary available to employ induce a sentiment lexicon in the discovered vector space from a very small set of seed words as method specifically for Twitter sentiment classification, while our approach would work for not only the χ2 test on the results of their lexicon-based sentiment classifier) in order to handle the neutral class, word embeddings4 and the ''General Inquirer'' lexicon (Stone et al., 1966) with the sentiment polarity scores collected by Warriner et al. To examine the effectiveness of different machine learning algorithms for building such domainspecific word sentiment classifiers, we attempt to work_a3hd5m5c6naslhdfexvsz5cxna Keywords Biometrics, Iris Recognition, PCA, DWT, Gabor filter, Hough Transformation, of an iris and thereby reduce image resolution and in turn the runtime of the classification PCA + DWT and SVM are used for segmentation, normalization, feature extraction and classification respectively. Iris recognition processing generally consists of the following steps: (i) Image acquisition (ii) Iris segmentation (iii) Normalization (iv) Feature extraction and (v) Classification. A combined PCA and DWT were applied on a fixed size normalized iris for feature Once the circular iris region is successfully segmented from an eye image, normalization is DWT transforms normalized iris image into fourfrequency sub-bands, namely LL, LH, HL and HH. of classification time of two iris templates mostly depend on efficient feature extraction DWT transforms normalized iris image into LL sub-band represents the feature or characteristics of the iris (Acharya et al., 2017; Moni After applying DWT on a normalized iris image the resolution of work_a4s2knqrb5emtnkkpytjown4ya this paper proposes a SLAM method of IMU and vision fusion. This article uses a stereo camera to extract the image ORB threshold, the camera pose is estimated by fusing IMU , Otherwise use feature points to estimate camera pose. binocular vision SLAM with IMU information can estimate the Keyword-Robot; IMU; Stereo Vision; SLAM Camera models generally have four coordinate positions of the camera trajectory and map points are The camera maps the coordinate points of the parameter matrix of the camera, and P is the coordinate purely visual feature point pose estimation method is image coordinate system to solve the rotation matrix R point in the camera coordinate system can be obtained the coordinates of the control point in the camera the reference point in the camera coordinate system are B. Camera pose estimation method based on IMU optimization.The IMU-based camera pose estimation fusion IMU-based robot positioning method is work_aawrwejmaregji2stj32j4azfq as supervised learning, using a large collection of realistic synthetic languages as training data. (hand-engineered or neural features) that correlate with the language''s deeper structure (latent trees). Table 1: Three typological properties in the World Atlas of Language Structures (Dryer and Haspelmath, 2013), and how they the non-IID problem that the available OVS languages may be evolutionarily related.1 We mitigate this issue by training on the Galactic Dependencies treebanks (Wang and Eisner, 2016), a collection of more than 50,000 human-like synthetic 1Properties shared within an OVS language family may appear to be consistently predictive of OVS, but are actually confounds that will not generalize to other families in test data. To score all dependency relation types given the corpus u, we use a feed-forward neural network with the model to predict p∗train from utrain on each training language. Table 3: Average expected loss over 20 UD languages, computed by 5-fold cross-validation. of relation directionality for each training language. work_aayskfc7ajcojb5l63iejmmpvy specialized streams in which multiple deep models are trained separately to segment segmentation of infection manifestations in COVID-19 scans. learning methods for COVID-19 diagnosis and infection segmentation is presented in recognition based on deep models, segmentation of COVID-19-related infection manifestations based on deep models, multi-task pipelines that have the ability to (2020) proposed a deep-learning-based, multi-task, two-stage approach for infection Figure 5 The proposed CNN model for multi-label classification of infection manifestations. features a DeepLab-v3+ model that trains to segment a specific type of manifestations. in X-rays and CT scans, (2) Multi-label recognition of COVID-19 manifestations in For the segmentation task, our training set contains 5,000 COVID-19 images and the https://github.com/shimaaelbana/Classification-and-Segmentation-of-infection-manifestations-in-COVID-19-scans https://github.com/shimaaelbana/Classification-and-Segmentation-of-infection-manifestations-in-COVID-19-scans A multi-task pipeline with specialized streams for classification and segmentation of infection manifestations in COVID-19 scans ... A multi-task pipeline with specialized streams for classification and segmentation of infection manifestations in COVID-19 scans ... work_ae7j2j76jbaubdvmkzdpm2hype the particle swarm optimization (PSO) algorithm. strategy for PSO algorithms is proposed: only the least fit particle and its neighbors Keywords Bak–Sneppen model, Particle swarm optimization, Velocity update strategy sophisticated variants of the algorithm, such as PSOs with time-varying parameters state-of-the art PSOs. Furthermore, the size of the test set is small and does not comprise analysis of the performance, comparing the algorithm with standard PSOs and variations asynchronous and steady state update strategy for PSO in which only the least fit particle Algorithm 1 Steady state particle swarm optimization. Table 7 SS-PSOMoore results: solutions quality, convergence speed and success rates. The preceding tests show that the steady state update strategy when implemented in a PSO times of 49,000 functions evaluations (median values over 10 runs for each algorithm). replaced by random values, in SS-PSO the worst particle and its neighbors are updated and GREEN-PSO: conserving function evaluations in particle swarm optimization. work_afsxvcg3kfhxbgf5td2lfziyua Also, we propose an algorithm to efficiently add delay buffers to selected short paths contamination delay of digital circuits up to a given threshold, beyond satisfying hold time increase the contamination delay to 30% of the circuit critical path length and also without investigates the timing constraints of TS framework and ''Increasing Short Path Delays'' paths of the circuit in ''Min-arc Algorithm for Increasing Short Path Delays.'' Results of our the data by meeting the worst-case propagation delay time of the combinational circuit. the impact of contamination delay on timing speculation framework at circuit level. We introduce Min-arc algorithm for increasing contamination delay of logic circuits up The basic outline of the Min-arc algorithm to increase the short path delay of the circuit threshold, the maximum delay increase affecting a critical path is still within propagation into network graphs as described in ''Min-arc Algorithm for Increasing Short Path Delays''. work_agwx3vvgsne2zexujz6g3vtzje Keywords GPU, CUDA, Inverse heat conduction problem, Heat transfer, Parallelisation, Dataparallel algorithm, Simulation, NVLink, Graphics accelerator, Optimisation How to cite this article Szénási (2017), Solving the inverse heat conduction problem using NVLink capable Power architecture. POWER8 CPUs and NVIDIA''s Pascal GPUs. Data transfer between the host and device speed-up for the GPU implementation (based on other parameters, like population size, Table 1 Runtime values for different population sizes with the GeForce Titan Black cards. Table 3 Runtime of the DHCP solver for different population sizes and CPU core counts (thread the CPU would be faster in the case of small population sizes (where the GPUs cannot take Figure 7 Memory transfer time (µs) for different population sizes with GeForce Titan Black cards. Figure 8 Memory transfer time (µs) for different population sizes with P100 cards. • In the case of the IHCP, the runtime of both the CPU and the GPU implementations work_ahbpjgtgwzc7zhabjlfgv4mshe sys_1000 wp-p1m-39.ebi.ac.uk wp-p1m-39.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265359849 (wp-p1m-39.ebi.ac.uk) Time: 2021/04/06 17:58:07 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_aid2rvqau5dnffyxvubsm7mhya model for the data streams classification, which utilizes the dynamic class weighting Keywords Ensemble learning, Concept drift, Data streams, Adaptive ensemble advanced machine learning methods that can reflect the changing concepts in data streams concepts change over time, dynamic adaptive ensembles present a suitable method that For predictive data modeling applied on the drifting streams, advanced adaptive Ensemble models represent a popular solution for the classification of drifting data of the DDCW model with the selected other streaming ensemble-based classifiers. The DDCW model proved to be suitable for data streams with different concept drifts Table 4 Comparison of accuracy and F1 metrics of evaluated ensemble models on the real data streams. Table 5 Comparison of accuracy and F1 metrics of evaluated ensemble models on the synthetic data streams. Concept drift detection for data stream learning based Classification of the drifting data streams using heterogeneous diversified dynamic class-weighted ensemble work_alqo7jualfh3fkcyozrsuuvk3e Based Approach for Class Specific Feature Selection (SMBA-CSFS), that simultaneously exploits the idea of Sparse Modeling and Class-Specific Feature Selection. A Sparse-Modeling Based Approach for Class Specific Feature Selection. strategy to FS, namely a Sparse-Modeling Based Approach for Class-Specific Feature The sparse-modeling based approach for class-specific feature selection, is based on the Algorithm 1: Sparse-Modeling Based Approach for Class-Specific Feature Selection A General Framework for Class-Specific Feature Selection (GF-CSFS) is described in The proposed SparseModeling Based Approach for Class-Specific Feature Selection (SMBA-CSFS) tries to Figure 1 A Sparse-Modeling Based Approach for Class-Specific Feature Selection. 3. Intra-Class-Specific feature selection: The Sparse-Modeling Based Approach is used for Figure 3 Average ROC curves and the corresponding AUC values on the first 20 features comparing the classification performance among SMBA-CSFS and TFS methods for nine data sets: (A) ALLAML(2), (B) LEUKEMIA(2), (C) CLL_SUB_111(3), (D) GLIOMA(4), (E) LUNG_C(5), (F) LUNG_D(7), https://github.com/DavideNardone/A-Sparse-Coding-Based-Approach-for-Class-Specific-Feature-Selection https://github.com/DavideNardone/A-Sparse-Coding-Based-Approach-for-Class-Specific-Feature-Selection https://github.com/DavideNardone/A-Sparse-Coding-Based-Approach-for-Class-Specific-Feature-Selection https://github.com/DavideNardone/A-Sparse-Coding-Based-Approach-for-Class-Specific-Feature-Selection https://github.com/DavideNardone/A-Sparse-Coding-Based-Approach-for-Class-Specific-Feature-Selection work_anm2hhnwxffalbke2mc7do4ha4 sys_1000 wp-p1m-38.ebi.ac.uk wp-p1m-38.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265374451 (wp-p1m-38.ebi.ac.uk) Time: 2021/04/06 17:58:25 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_ap6lbi5lozcalg6ytbkyybau6a This paper presents a new simplex-type algorithm for Linear Programming with the simplex-type or pivoting algorithms and (ii) Interior Point Methods (IPMs). A new non-monotonic infeasible simplex-type algorithm for Linear Programming. 1984; Arsham, 2007; Pan, 2008; Jurik, 2008; Yeh & Corley, 2009; Elhallaoui et al., 2011; Li, on feasible directions to select the pair of entering and leaving variables, the algorithm This algorithm is called Primal-Dual Interior Point Simplex Algorithm (PDIPSA) (Samaras, and (iii) Primal-Dual Interior Point Simplex Algorithm (PDIPSA). and computes the pair of entering/leaving variables and a new (better) interior point. If iEPSA finds a primal feasible basic solution, then the EPSA is applied to monotonically The main idea behind the first phase is the following: the algorithm is initialized with any basic (infeasible) solution x0exterior and an interior point x Combining interior-point and pivoting algorithms for linear An exterior point simplex algorithm for (general) linear programming problems. work_aptojhcwune4dnb3zom6igwm7e Cross-Document Co-Reference Resolution using Sample-Based Clustering problem in this context is cross-document coreference resolution (CCR): computing equivalence classes of textual mentions denoting It takes as input a set of documents with entity mentions, and computes as output a set of equivalence Cluster-ranking and multi-sieve methods incrementally expand groups of mentions and exploit Similarity computations between mention groups are performed lazily on-demand for the dynamically selected samples. • CROCS, a framework for cross-document coreference resolution using sample-based spectral mention groups ({mij}) obtained in the previous step, we combine the sentences of the mentions to determine the best matching entity in a (using the similarity metric) in a hierarchical fashion to compute the cross-document coreference equivalence classes of mentions. freebase.com entries, for possibly matching entities, to enrich the features of a mention group. It performs a topdown hierarchical bisection process, based on similarity scores among entities, to cluster together coreferring mention groups at each splitting level. work_artm7eh6h5gdbnh3vbgfg4fcga One approach would be to run LDA on the instances for an ambiguous word, then simply interpret topics as induced senses (Brody and Lapata, target word instance, where the sense labels are combination of separate LDA models based on different feature sets (e.g. word tokens, parts of speech, work in that we model sense and topic as two separate latent variables and learn them jointly. context word, we sample a new topic/sense pair for it over topics for global context word token i in instance d as Pr(t(i)g = j|d,t−i,s, ·), where t(i)g = j topic/sense pairs for a local context word token w(i)'' of times sense k and topic j are assigned to some local word tokens. This distribution is considered the final sense assignment distribution for the target word in instance d for generate each word from a topic or sense, with a Topic modelling-based word sense induction. work_asgnsvhx2vhh3pb5hgmtd47ri4 mammals, LH and FSH specifically activate cognate G-protein-coupled receptors that affect characterized the expression profile over the final stages of ovarian maturation of carp gain insight into an evolutionary model of permissive gonadotropin receptor function. These data suggest that carp (Cyprinus carpio) gonad development and maturation gonadotropin receptor activation is a specific feature of Ostariophysi, not all teleosts. (LHCGR), FSH receptor (FSHR), and thyroid-stimulating Table 1 Primers used for cloning carp gonadotropin receptors. Carp and human gonadotropin receptors stimulated CRE-LUC activity in plasmid pCRE-LUC and carp gonadotropin receptors (cFSHR, cLHCGR) or Carp gonadotropin receptors stimulated by A model describing the specificity of gonadotropins binding to their cognate receptors in representative species of fish from different piscine orders. that fish gonadotropin and receptor expression and of the fish gonadotropin receptors, which was previously increased expression of follicle stimulating hormone receptor and The duality of fish gonadotropin receptors: cloning and functional work_asju76efxzdnjbne3dfe7czuly current foreground pixels, to assign provisional labels to foreground pixels, and to record and resolve label equivalences. For the case where the current foreground pixel follows a background pixel (Fig. 1 (b)), if there is no label provisional label m to the current foreground pixel, which is initialized to 1, and establishes the equivalent label set Therefore the current foreground pixel can be assigned any of the labels in the mask. processed, it assigns to the foreground pixels in the line and its neighbor lines (the gray lines in Fig. 2) provisional For each current line, it assigns to the foreground pixels in the line provisional labels and resolves the label In Scan 1-A, our method uses the mask shown in Fig.3 to assign to the current pixel b(x, y), its neighbor above, b(x, equivalences among them, and assign to the current foreground pixel its representative label. work_auqywr3punadtlsyrbktye2xsu Quadrotor Formation Inversion Control Method Based on Unit Quaternion Keyword-Formation Control; Quadrotor; Quaternion; The research of methods of formation control mainly contains leader-follower method, virtual structure, graph theory the controller is designed with different degree of simplification to quadrotor model by feedback linearization and kinetics and kinematics models of the quadrotor are described by quaternion and the intermediate control is introduced. The formation is stabilized by setting the appropriate intermediate control for each UAV. QUADROTOR MODEL BASED ON UNIT QUATERNION According to the information exchange among unmanned aerial vehicles, UAV formation can be in the form of modeling. consistency algorithm, and output to the pose controller, making the UAVs close to the scheduled formation center aggregation. to design the position subsystem controller and the attitude Aiming at the control problem of quadrotor formation, Quadrotors UAVs Dynamics and Formation Flight [J]. Formation control for quadrotor Formation control for quadrotor Formation control of VTOL-UAVs [A]. work_avy3lqnkrzhxtg2fpy5ewyy2li sys_1000 wp-p1m-39.ebi.ac.uk wp-p1m-39.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265367025 (wp-p1m-39.ebi.ac.uk) Time: 2021/04/06 17:58:16 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_axzebh47qfh77lhyykpbcljizu into the satire detection task (Burfoot and Baldwin, 2009), predicting if a given news article is rather than looking at it as a lexical text classification task (Pang and Lee, 2008; Burfoot and Baldwin, 2009), which bases the decision on word-level Instead, we frame the required inferences as a highly-structured latent variable model, trained discriminatively as part of the The model learns commonsense patterns leading to real or satirical decisions The problem of building computational models dealing with humor, satire, irony and sarcasm has attracted considerable interest in the the Natural Language Processing (NLP) and Machine Learning inherently a common-sense reasoning task, as identifying the satirical aspects in narrative text does not inference process jointly assigning values to the latent variables and making the satire decision. Each node in the NRG is assigned a set of competing variables, mapping the node to different categories according to its type. work_ayatblpinzaztdzhilw6yqsi6m Keywords Malware, Ransomware, Performance counters, Classification, Machine learning Most contemporary state-of-theart dynamic analysis techniques detect and classify ransomware that hides itself applications that uses machine learning to classify malicious behavior of malware based previously studied for the analysis and detection of ransomware applications. HPCs to detect Microsoft Windows-based ransomware by analyzing the execution hardware related performance features are extracted from the data set of 160 malware 2019; Victoriano, 2019) related to Android malware detection using machine learning ransomware classification and proposed a learning-based detection strategy. and dynamic or runtime features of executing applications to detect ransomware. HPCs features to detect malware from benign applications. (2016) has presented a machine learning-based malware analysis have used hardware performance counters to detect Android malware, and in another (using signature-based features and hardware performance counters) to detect and classify performance counters-based malware detection. Automatic ransomware detection and analysis based on Anatomy of ransomware malware: detection, analysis and work_b3fht5nxgfg2varvqyybifuwxa Quadrotor Formation Control Method Based on Graph and Consistency Theory consistency theory and puts forward a quadrotor formation between quadrotors, the formation is modeled by graph Keywords-Formation Control; Graph Theory; Consistency Theory; Second-order Integrator; Pilot-follow Method Multiple quadrotors formation control is a control methods are pilot-followed method, virtual structure Graph theory method means to model the formation to position and relative direction of the quadrotors. formation flight of four quadrotors with consistency quadrotors formation, a communication topology solution is graph theory method and pilot-follow method and describes second-order coherence algorithms, the formation of control follower quadrotors can receive information from the pilot. topology of the flight vehicles formation to exist in all these The quadrotor position control comprises the inner and formation control algorithm. formation can be modeled as a directed graph. position and speed information of quadrotor i. Simulation curve of quadrotor formation maneuver quadrotors'' position and speed change curve in Z direction. work_b5xa6yvzjvfo7crqzazx6f62pi Keywords Scholarly data, Topic emergence detection, Empirical study, Research trend detection, Early awareness of the emergence of new research topics can bring significant benefits to & Gibbons (2013) suggested that the development of new topics is encouraged by the crossfertilisation of established research areas and recognised that multidisciplinary approaches novel research topic can be anticipated by a significant increase in the pace of collaboration not always easy to associate clearly identifiable research areas to the resulting topic models. study it is important to be able to associate topics with well-established research areas. Figure 11 Average collaboration pace per year of the sub-graphs related to input topics in both debutant and control groups considering their 20 (A), 40 (B) and 60 (C) most co-occurring topics. Table 4 Collaboration pace of the sub-graphs associated to selected debutant topics versus the average Table 6 The results of the triad census performed on the network associated with the debutant topic ''''semantic web technology'''' removing work_b5zqmaftfja27l2uav7i55veou Multi-Modal Models for Concrete and Abstract Concept Meaning Multi-modal models that learn semantic representations from both linguistic and perceptual input outperform language-only models a means of propagating perceptual information from concrete nouns to more abstract concepts that is more robust than previous approaches. models in these studies corresponds directly to concrete noun concepts, such as chocolate or cheeseburger, and the superiority of the multi-modal over We construct models that acquire semantic representations for four sets of concepts: concrete nouns, perceptual information to abstract nouns and concrete verbs, and is overall preferable to both linear regression and the method of Johns and Jones Figure 1: Boxplot of concreteness distributions for noun and verb concepts in the USF data, with selected example We create evaluation sets of abstract and concrete concepts, and introduce a complementary dichotomy between nouns and verbs, the two POS categories most fundamental to propositional meaning. work_b76j4e4nu5h7lgcro2holgdhqy dataset, as the fine-tuned ResNet deep neural network layers are increased, the best TopKeywords 3D textures, Face recognition system, Histogram of oriented gradients features, Deep Extracting better features are a key process for 3D face recognition 3D texture-based face recognition system using finetuned deep residual networks. developed a residual neural network model base on ResNet for the 3D face recognition This model is fine-tuned with different depths using HOG featured 3D face textures. We trained fine-tuned ResNet models with different depths using HOG based 3D texture representative features of face are extracted from the fine-tuned VGGNet model. HOG features and SVM classifier-based face recognition algorithm is for extracting the HOG features based on 3D face texture images. processing of HOG feature extraction for 3D face image is shown in Figs. layer through the fine-tuning method on 3D face texture recognition research with high work_b773ezdtvzbovc57tbxkayz3ie Compositional Equivalence with Actor Attributes: Positional Analysis of the Florentine intended for multiplex networks – by incorporating actor attributes in the modeling of the network relational structure as diagonal matrices. positional system of the Florentine families network with Business and Marriage ties together known as multiplex networks, and the associated relational structure of such social paper is to extend this type of correspondence by suggesting an effective way to incorporate the attributes of the actors and integration is that social conduct in networks does not always institute a link between individual subjects, and attributebased information about the actors is often play a significant role in the network relational structure and should be incorporated Representing social relations and actor attributes in an integrated system requires a Table 1: Cumulated person hierarchy, , of the Florentine families network of social ties, 5 network structure with the actor attributes work_baa42pags5bzhey4donm65vfce Measurement of Brain Activity Related to Unpleasant Emotion in the study, auditory stimuli applied to subjects in order to arouse unpleasant emotions, changes in blood flow were measured Keywords: near-infrared spectroscopy, unpleasant emotion, prefrontal cortex, auditory stimuli, brain activity In this study, we focus on unpleasant emotions, and analyze blood flow changes measured by NIRS in the prefrontal cortex area related to emotional unpleasant evoked by auditory stimuli. concentration change of channel 15 during 5 trails for the unpleasant emotional stimulus. activity related to only the perception of auditory stimuli, and the unpleasant emotional stimulus caused neural activity waveform for the unpleasant emotional stimulus significantly increased at almost channels. Fig.5 Averaging waveforms unpleasant emotional stimulus presentation at ch 15 In the case of the unpleasant emotional stimulus, a significant increase in concentration of oxy-Hb unpleasant emotional stimulus, significantly increase of oxy-Hb concentration was found in the periphery of work_bcgd7plh7balxooov4i7xjzloe the same time, the 32 -bit address length of IPv4 has The decimal network address prefix uses a CIDR IPV9 addresses are assigned to interfaces, not nodes. The IPV9 address specifies a 256-bit identifier for the The aggregatable global unicast address and cluster The IPV9 aggregatable global unicast address Public topological layer Site topology layer Network interface identifier site-level aggregate identifier is similar to the IPv4 global unicast address ultimately identifies a network as the link layer address of the network interface, or prefix and the 128bit network interface identifier, and to the cluster address, the network sends the message to the address space of IPV9 is reserved for multicast. The multicast address is assigned to multiple network IPV9 MULTICAST ADDRESS FORMAT 64 bits of the IPV9 multicast address mapped to the MULTICAST ADDRESS FORMAT WITH 64BIT GROUP IDENTIFICATION identification of the IPV9 multicast address to 264, work_bd2lkt5lbfh45iivxciwe7av4a Advanced Network, Monitoring and Control, China sovereignty of cyberspace is the "life gate" of the network. China''s cyber sovereignty is subject to the United States, become the key to China''s acquisition of network sovereignty. see the network foundation of digital China from the generations of network data communication standards generations of network data communication standards United States monitors the world through the Internet, United States monitors the world through the Internet, Internet access network sovereignty belongs to the address of the Internet in the United States), we are all key future network test facilities built in the 12th fiveyear plan period that "the Internet based on TCP/IP routing of China''s access network controlled by the computer communication network of the Internet. generation of Internet, the future network file to the network information technology independent Today, our China-led future network/IPV9 3) The future network/IPV9 is an important network / IPv9 next-generation Internet! work_bddby6hpkbcbhepqogem6gmexi distributed among heterogeneous information sources, which can be structured, semistructured or unstructured, and providing the user with a unified view of these data. as a conceptual schema to represent both data sources to be integrated and the global The second issue is how to define mappings between global schema and local sources: Once the query processing activity is performed, data from different sources need to be data integration from heterogeneous sources, also based on ontologies (Calvanese, Lembo external data management systems through semantic mappings that associate SQL queries in the previous activity, is integrated into the global ontology and the mapping table is Local and global ontologies are expressed in OWL-DL (https://www.w3.org/TR/owlfeatures/), whose basic elements are classes c, object properties op and datatype properties The goal of schema matching activity is to generate a set of mapping between local and Query processing for XML data source is supported by a framework, integrated work_bdrh4wlqxbgu5dxs4ezxcr2vgy Estimating free energy differences by computer simulation is useful for a wide variety Implementation of adaptive integration method for free energy calculations of free energy differences; this is a key distinction from other methods and allows AIM free energies were calculated using the fixed λ methods provided by alchemical-analysis. this study, we performed alchemical free energy simulations where the system is changed Computationally, we calculate free energy differences between end states by performing 4. Estimate the free energy difference between the trial and current λ values using the eight trials for each method as a function of simulation time per value of λ. Figure 3 Different simulation times for alanine to valine mutation free energy calculations. AIM requires less samples than fixed λ simulations to smooth the free energy function. As simulation time increases, the average free energy λ—dynamics free energy simulation methods. Free energy methods in molecular simulation. work_beo6544t6be6fg7jquetgu7gsu RobOMP: Robust variants of Orthogonal Matching Pursuit for sparse representations. of CMP by reformulating the active set update under the lens of robust linear regression; We present three different sets of results to validate the proposed robust, sparse block coordinate descent to separately optimize the sparse code, x, and the weight vector, RobOMP estimate the sparse code with parameter K =10. Table 3 Average norm of sparse code errors of MSE–based OMPs and robust alternatives for different only a robust sparse code estimator, but also a statistically efficient one that exploits the Figure 4 Average normalized norm of sparse code error of MSE–based OMPs and robust alternatives Figure 4 Average normalized norm of sparse code error of MSE–based OMPs and robust alternatives Figure 4 Average normalized norm of sparse code error of MSE–based OMPs and robust alternatives given a dictionary D, then, the optimal sparse code, x̂ij, and estimated denoised image, Ẑ, work_besassr4ujgwneb2yqkhk4tsmy 1 Center for Complex Networks and Systems Research, Indiana University, Bloomington, United States Broad access to social media data, however, requires software Here we present the IUNI Observatory on Social Media, an open analytics platform designed to facilitate computational Keywords Social media, Observatory, Twitter, Web science, Network science, Meme diffusion, Computational social science, Big data, API, OSoMe Broad access by the research community to social media platforms is, however, limited information that is spread and collected through online social networks. public tweets to visualize, analyze, and model meme diffusion networks. to social media analysis by providing users with several ready-to-use, Web-based data Because tweet data are time resolved, the evolution of a diffusion or co-occurrence network data-intensive research in the social, behavioral, and economic sciences. In: Proceedings of the 1st ACM conference on online social networks Supporting queries and analyses of large-scale social media data work_bfrt4s7xyrhsbiitubwvkxvyxi sys_1000 wp-p1m-39.ebi.ac.uk wp-p1m-39.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265363880 (wp-p1m-39.ebi.ac.uk) Time: 2021/04/06 17:58:12 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_bghb2jlqpbf6lnr4hpzevghqwq and CNR in HCM, we propose linear function threshold-based C-means (LiFTCM) Keywords Clustering, k-means, Noise rejection, Rough set theory For each cluster, objects distant from its center are rejected as noise. For each cluster, objects distant from its center are rejected as noise. West, 2004) as a rough-set-based C-means clustering, and Peters proposed a refined linear function threshold-based C-means (LiFTCM) by relaxing GRCM. the linear function threshold-based assignment in relaxed GRCM can realize GNR, CNR, linear function threshold-based object-cluster assignment in the proposed LiFTCM. this type of CNR, noise rejection is performed for each cluster by rejecting objects over δc Similar to HCM and GNR, in CNR, the cluster centers are calculated only using the Table 1 Relationship between HCM, GNR, CNR, and rough clustering, and their combinations in noise rejection (CNR) in hard C-means (HCM), we proposed linear function thresholdbased C-means (LiFTCM) by relaxing generalized rough C-means (GRCM) clustering. work_bhexqv46bbfhxibylnf7pundsy An Improved Algorithm of the Collision Detection Based on OBB The bounding box is the most basic collision detection collision detection algorithm classification: From the point Based on space domain collision detection algorithm has Based on space domain collision detection algorithm has bounding box test is a collision detection algorithm is widely sphere, of AABB of OBB bounding box. Based on the method of spherical bounding box of Based on the method of spherical bounding box of collision detection in virtual scene, two irregular objects in met, according to the spherical bounding box collision Axial bounding box AABB is defined as the object its direction the Bounding Box namely OBB ,is to be method , based on OBB bounding box here proposes a disassembling parts of cylindrical bounding box structure first to object bounding box for rough detection, when the bounding box intersect surrounded by its geometry can be work_bj6uvbwk4bch5oknfyzgtne4py method (OPTICAL+) achieved an overall average classification error rate of Common spatial pattern (CSP), Motor imagery (MI), Informative frequency band (IFB) filtered data is fed as the sequence input to the LSTM network for training the model. the filter parameters that would result in the optimal performance of the proposed system. Figure 5 Error rates of the individual subjects for the proposed OPTICAL+ predictor. Figure 8 The error rates of OPTICAL predictor with optimization of the filter parameters and intend to test how the proposed method would perform on other EEG signal classification The proposed method has been able to successfully optimize the filter band parameters EEG signal classification method based on feature priority analysis and CNN. A neural network-based optimal spatial filter design method for motor OPTICAL+: a frequency-based deep learning scheme for recognizing brain wave signals OPTICAL+: a frequency-based deep learning scheme for recognizing brain wave signals work_bjolsjb5sjgodjqh5cmgkbs3ky Keywords Exploratory data analysis, Graph and network visualization, Hierarchical clustering, How to cite this article Alcaide and Aerts (2018), MCLEAN: Multilevel Clustering Exploration As Network. since it allows users to participate in the clustering process by leveraging their visual (Multilevel Clustering Exploration As Network) for grouping and visualizing multiple visual exploratory and clustering method that permits the user to interact with the algorithm a set of examples of visual multilevel clustering and the network transformation of data to Figure 1 Workflow diagram of MCLEAN algorithm, consisting of four steps: (1) graph transformation, (2) node aggregation, (3) community detection and, (4) barcode-tree creation. Figure 4 Network representation of the clustered dataset using a parameter ε of 150 in part (A), 190 in Figure 6 Network representation of the clustered dataset using the distance threshold of 150 in part The barcode-tree (Fig. 7) is a visual representation of cluster arrangement. work_bk4tfao5ljgu3pl27nh63a2y3a correct spatial arrangements for unseen objects if either CNN features or word embeddings of the objects are provided. we leverage the task of predicting the 2D spatial arrangement for two objects under a relationship expressed by either a preposition (e.g., "below" or that represents objects as continuous (spatial) features in an embedding layer and guides the learning task and that by informing it with either word embeddings or CNN features it is able to output accurate predictions about unseen objects, e.g., predicting the spatial arrangement of (man, riding, bike) learn spatial knowledge, we employ the task of predicting the spatial location of an Object ("O") relative to a Subject ("S") under a Relationship ("R"). The embedding layer models our intuition that spatial properties of objects can be, to a certain extent, encoded with a vector of continuous features. Table 4 shows the results of evaluating the embeddings, including those learned in the Prediction task, against the human ratings of spatial similarity (Sect. work_blzi5mheefd3fhpgc2sbrofqdy spider optimization for data clustering using single centroid representation and We found that SSODCSC produces better values for the sum of intra-cluster distances, In our proposed algorithm, social spider optimization for data clustering using single algorithm, SSODCSC, we convert them into dominant male spiders by increasing their that the proposed algorithm produces clustering solutions of better fitness values when Social spider optimization for data clustering using single centroid starts with the Table 3 Clustering results of SSODCSC: Patent corpus5000 datasets. Table 6 Comparison between clustering algorithms in terms of SICD: Patent corpus5000 datasets. Table 7 Comparison of clustering algorithms in terms of accuracy: Patent corpus5000 datasets. The figure specifies inter-cluster distances returned by clustering algorithms when applied on Patent corpus5000 datasets. A novel variant of social spider optimization using single centroid representation and enhanced mating for data clustering A novel variant of social spider optimization using single centroid representation and enhanced mating for data clustering work_bm4dfohilrg3djqxvqjvkrbbte Readings of Portable UV Spectrum Analyzer Data Based on Raspberry Pi quickly read the data from the spectrometer, to meet the actual portable spectrometer has the advantages of fast data reading analyzer control and data processing is the Raspberry Pi The data acquisition of portable UV spectrometer is a and the Raspberry Pi reading spectral data is the process of Data reading sequence diagram of spectrometer The data reading sequence of UV spectrometer is shown How Python reads the Data development package works sent by the raspberry pie to the ultraviolet spectrometer will Figure 5, the Python language reads the data of the ultraviolet spectrum spectrometer through the Python C. How Python reads data works When the raspberry pie is reading the spectrometer data, micro Ultraviolet spectrometer, data reading and so on, using micro-ultraviolet spectrometer read data, and work stable, the photon number read by the raspberry pie from the work_bmh4l4auv5e5hnjsz2hqgca2ma machine live migration can help cloud environment maintainer make full use of node server in the The traditional load balance algorithm is based on task control allocation, when applied to the cloud order to ensure that the load of each node is balanced, the monitor signal is set in the virtual machine and redistribution of the nodes to achieve the strategy of the algorithm, the load balancing technology The load balancing strategy in cloud computing is divided into two types, static state and dynamic probability of receiving a virtual machine migration request is 2:2:3:1,so each node server processing use of virtual machine migration technology, consider how to select the virtual machine from the overload node how to determine the migration destination and coordinate the load of different servers. A kind of load balancing algorithm based on the virtual machine live migration in cloud work_bo6n5wvo4nfipgn3fnvugypu4u annotating such temporal information in clinical of ISO-TimeML (Pustejovsky et al., 2010), developed specifically for the clinical domain, which we THYME project, whose goal is to both create robust gold standards for semantic information in clinical notes, as well as to develop state-of-the-art algorithms to train and test on this dataset. Most critically for temporal reasoning, each clinical note reflects a single time in the patient''s treatment history at which all of the doctor''s statements Clinical notes contain rich temporal information the annotation of events and temporal expressions the THYME-TimeML guideline, an EVENT is anything relevant to the clinical timeline, i.e., anything for temporal annotation in the clinical domain does are identified between the temporal and event expressions present in clinical notes. Our method of addressing both goals in temporal relations annotation is that of the narrative container, discussed in Pustejovsky and Stubbs (2011). time expressions, events, and temporal relations. work_bou4wslvvnhyhj7cn2cnumxhym In this article, a spatial domain watermarking technique is proposed to improve the data � The proposed approach preserves the patient data using a hyped watermarking strategy, process of embedding significant information over a patient''s medical image to provide Figure 2 Digital watermarking techniques based on embedding domain (Rao & Kumari, 2011). In the spatial domain, the watermark is inserted within the original medical image Figure 3 Proposed approach of embedding digital watermarking into medical images. In this article, a robust spatial watermarking algorithm for medical images has been � The proposed approach preserves the watermark and the original image at the same Slantlet based hybrid watermarking technique for medical images. A robust watermarking algorithm for medical images. Watermarking in medical imaging for security and Protection of the patient data against intentional attacks using a hybrid robust watermarking code Protection of the patient data against intentional attacks using a hybrid robust watermarking code work_bqekzgmsnbht5jucugliearktm Current smart city application models mostly assume that data is exclusively paper, we present a methodology and toolset to model available smart city data sources and enable efficient, distributed data access in smart city environments. Keywords Smart city application engineering, Data management, Data migration, Quality of (2017), Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems . that enables efficient and seamless data access for smart city applications by autonomously the SDD framework and evaluate it using a case study in the context of a distributed city most of the data in a smart city context is confined to certain application areas and smart city applications means they are not a priori aware that their data sources might by the Analyzer Manager like request time, data size or a respective cost function against Current smart city application models assume that produced data is managed by and bound work_bumlyld32nartpx6c5uawr5dxu An evolutionary decomposition-based multiobjective feature selection for multi-label classification. methods have been used for multi-label data feature selection (Dendamrongvit, Vateekul & In this article, we propose a decomposition-based method for multi-label feature (1) we address the problem of multi-objective feature selection by solving several singlelabel subproblems, that is, for the first time, decomposition-based evolutionary multiobjective optimization has been used for multi-label classification; (2) we apply a local multi-label classification, multi-objective optimization, and the existing methods for multiobjective multi-label feature selection. we examine existing multi-label feature selection methods that have been proposed for Multi-label feature selection algorithm based on NSGA-II presented a multi-objective PSO-based method for feature selection of multi-label data. 42 Obtain the hamming loss for test data with the selected features of solutions in the final Pareto front. An evolutionary decomposition-based multi-objective feature selection for multi-label classification An evolutionary decomposition-based multi-objective feature selection for multi-label classification work_bwyl5aldazcytler7culcro2sm Keywords Structural bioinformatics, Education, Protein folding, Statistical mechanics, Contact matrix, Protein structure alignment, Designability, Evolution, Contact order, Protein classification puzzle and the contact matrix representation of protein structures, and we propose a simple model structures, on which we propose computational exercises focused on evolutionary Contact matrices are also used as a simplified representation of real protein structures. We can define the sequence structure relationship within the contact energy model of contact interaction energies depend on the protein sequence as Uij =U(Ai,Aj), where Ai self avoiding walks on the cubic lattice or the contact matrices of real protein structures. Figure 6 Designability of selected structures for an increasing number of random sequences. energy where sequences with larger fitness are visited more often, in analogy with structures 2. Fitness evaluation We compute the folding free energy of the mutated sequence We simulate protein sequence evolution with structural constraints using a Monte Carlo work_c2lz4j5lkbafbijjezlchgwxom and likelihood methods, the construction of a tree search space graph, and the Keywords Phylogenetic, Python, Heuristic, Alignment, Maximum likelihood, Library, intended for heuristic search and analysis of the phylogenetic tree search space, as well as How to cite this article Safatli and Blouin (2015), Pylogeny: an open-source Python framework for phylogenetic tree reconstruction and large number of other classes and supports tree scoring using standard phylogenetic tree rearrangement, heuristic exploration, and landscape construction. landscape landscape Represents a phylogenetic tree search space, modelled as a graph. landscapeWriter landscapeWriter Allows one to write a landscape object to a file, including alignment and tree information. Exploring the space is done by performing rearrangements on trees as topology Performing a heuristic search of the combinatorial space comprised by a phylogenetic Pylogeny: an open-source Python framework for phylogenetic tree reconstruction and search space heuristics Pylogeny: an open-source Python framework for phylogenetic tree reconstruction and search space heuristics work_c3hqnyrzanhgtgzgi3odcggfey Fault injection simulators run a given testbench on the design under test (DUT), its driving logic cone, and perform an exhaustive fault injection campaign. that the FFs bounding the logic cone are injected single bit flips in all possible input Testing all possible configurations for a logic cone means 2nf injections, with nodes of this graph have indexed inputs and are associated to a logic function and a value, Having assumed that each FFs has one input, we can define the driving node for a given FF 2. TMR structure analysis: perform an exhaustive fault injection campaign on all valid To determine a useful set of valid configurations for a logic cone (here represented by a The algorithm takes each FF xi and determines the set of FFs that driving its logic In this work we presented an algorithm to verify TMR implementation for given netlists. work_c4pk4p3cpfa2di4meuzvtcvm5i Bag-of-view; Support Vector Machine; License Plate Vertical the morphological features for the license plate location when the image background and license plate area is in the is difficult to determine whether to license plate area. full use of the license plate in the image color information, When the license plate region color is very similar to And the color of the license plate image information is I. VISUAL WORD PACKAGE MODEL OF LICENSE PLATE features of license plate is similar, then interference region matrix of each pixel point and the pyramid image the size image contains a large number of Surf feature points.If the feature points to the visual word package generated A. The suspicious area extraction of license plate say, extracting surf feature points of images and mapping classifier to classify its license plate images .Locating the suspicious area of vehicle license plate in the image. work_caanmurdszbqbhldgzaf4tsziy Aspect extraction on user textual reviews using multi-channel convolutional neural the performance of the aspect extraction models (Poria, Cambria & Gelbukh, 2016; semantic feature for the aspect extraction, although word embeddings have shown general-purpose word embeddings in aspect extraction. For further improvement, the attention-based model has been used for aspect extraction embeddings method has been used to model aspect extraction using two different embedding features to improve the model performance. channels for better performance of the aspect extraction model. For the POS Tag embeddings, the main idea is to improve the aspect extraction process tag features improves the performance of NLP methods including aspect extraction. attention-based deep learning model for improving aspect extraction is worth exploring, Figure 4 F1 score of the MCNN-WV2-POS Variant of our model on different word embedding Aspect extraction on user textual reviews using multi-channel convolutional neural network Aspect extraction on user textual reviews using multi-channel convolutional neural network work_capyudeotzhcdosyorvr2om4ou mutual information-based nominal-data feature selection method is relatively In this paper, a nominal-data feature selection method based on relevance and the redundancy globally, the new feature selection method can evaluate Keywords Nominal data, Feature selection, Redundancy-removing, Mutual information How to cite this article Li and Gu (2015), A redundancy-removing feature selection algorithm for nominal data. In this paper, we also use MI, which addresses taking the MI as a matrix of relevance and redundancy among the features, to study the nominal-data feature selection methods. classification accuracy of the selected feature subset using different employed classifiers; From Table 3, for the decision tree classifier, the classification accuracy of the RedremovingMRLR algorithm on the different basic subsets is the best among the three compared Mutual information-based feature selection algorithm for nominal data, A redundancy-removing feature selection algorithm for nominal data A redundancy-removing feature selection algorithm for nominal data work_cbatoisvt5acjgjv5wrcdlslbe We present a probabilistic model of phonotactics, the set of well-formed phoneme sequences in a language. we take a fully generative approach, modeling a process where forms are built up out structured as an and-or graph, based on concepts of feature hierarchy from generative Second, our system can represent phonotactic generalizations not only at the level of fully specified segments, but also allows the storage and reuse of subsegments, inspired by the autosegments and class feature for vowels by structuring the generative process as below, so that the LATERAL or-node is only Our use of and-or graphs and lexical memoization to model inter-feature dependencies is inspired by work in phonology on distinctiveness this limitation, structure-building models of phonotactics have not generally included rich featural interactions. dependency graphs (Section 2.1), class node structure (Section 2.2), and tier-based conditioning (Section 2.4)— contributes to the ability of the model to work_cbelsegdzbdzpnylamotvq5aeq Previous work on automatic construction of taxonomies from text documents either ignored temporal information or used method can incrementally update the taxonomy by adding fresh relations from new data • We propose a time-aware method for taxonomy construction that extracts and utilizes temporal information to measure evidence weights Figure 1: Workflow of the proposed time-aware taxonomy construction method. There are three general steps to constructing a taxonomy: domain term extraction, taxonomic relation Using the timestamp contribution function, we incorporate temporal information into the three taxonomic relation identification methods described in there is new incoming data, we propose a novel incremental graph-based algorithm to update an existing taxonomy with a given set of taxonomic relations. the time-aware method also contributes to better performance as it helps identify new taxonomic relations effectively, while getting rid of obsolete and We apply the proposed time-aware method to construct and update the taxonomy for ''MH370'' incrementally every two days. work_cc75k3nhgzfdtkmohnfvvfarqy Tumor-induced osteomalacia in the head and neck region remains a challenging diagnosis Tumor-induced osteomalacia (TIO), also known as TIO of head and neck region previously reported in In recurrent or persistent cases, complete tumor literature for TIO cases involving head and neck region localizing the tumor to right head and neck region, other reported tumors in head and neck region causing phosphaturic mesenchymal tumour of the oral cavity: a case report. osteomalacia: case report and review of head and neck associated associated with oncogenic osteomalacia: case report. Osteomalacia caused by skull base tumors: report of 2 cases. tumor: a report of 6 patients treated at a single institution and Intracranial phosphaturic mesenchymal tumors: report of 2 Osteomalacia-inducing tumors of the brain: a case report, patients with tumor-induced osteomalacia. blood sampling for FGF-23 in tumor-induced osteomalacia. tumor and oncogenic osteomalacia: case report and review of CT in localization of tumor causing oncogenic osteomalacia. work_cduf62ok2nhobaot5ffimacjom Keywords Data integration, Data mapping, ShExML, YARRRML, Usability, SPARQL-Generate ShExML: improving the usability of heterogeneous data mapping languages for first-time users. designed to take one data source and transform it to an RDF output. With usability in mind we have designed the ShExML (García-González, FernándezÁlvarez & Gayo, 2018) language that allows transformation and integration of data from XML and JSON sources in a single RDF output. In this section we compare YARRRML, SPARQL-Generate and ShExML syntax by means ShExML, our proposed language, can be used to map XML and JSON documents to case, is different between SPARQL-Generate and the two other languages. https://github.com/herminiogg/shexml-paper-2019-data/tree/master/experiment-material https://github.com/herminiogg/shexml-paper-2019-data/tree/master/experiment-material https://github.com/herminiogg/shexml-paper-2019-data/tree/master/experiment-material Differences between ShExML and SPARQL-Generate for completeness percentage and easiness between YARRRML and SPARQL-Generate, this may be because SPARQLGenerate users did not use the whole language. Differences on subjective analysis between ShExML and YARRRML on general generic language for integrated rdf mappings of heterogeneous data. work_cjz5gcmhlzeylneb6avkrv5bui Branch and Bound Algorithm for Dependency Parsing For graph based projective dependency parsing, dynamic programming (DP) is popular for decoding It performs cubic time parsing for arc-factored models (Eisner, 1996; McDonald et al., 2005a) and biquadratic time for higher order models with richer There have been numerous studies on global inference algorithms for general higher order parsing. in sentence length for projective dependency parsing (Martins et al., 2009). For general high order models with non-local features, we propose to use Branch and Bound (B&B) algorithm to search the optimal parse tree. bound of the optimal parse tree score in the subspace: UBYi ≥ maxy∈Yi ϕ(x,y). a binary variable indicating whether factor c is selected in the parse tree. Algorithm 1 Branch and Bound based parsing method can be adapted to non-projective dependency parsing, as well as the k best MST algorithm parsing with non-local features. Non-projective dependency parsing using spanning tree algorithms. work_cjzncjfh4jgvffcb2oqjlenewi study attempts to use deep learning to predict SNARE proteins, which is one of the SNARE-CNN model which uses two-dimensional convolutional neural networks and position-specific scoring matrix profiles could identify SNARE proteins with achieved for identifying SNARE proteins and a basis for further research that can apply deep Keywords Position specific scoring matrix, SNARE protein function, Deep learning, Membrane molecular functions; (iii) valid benchmark dataset to train and test SNARE proteins with Figure 1 Flowchart for identifying SNARE proteins using two-dimensional convolutional neural networks. We then propose a method to predict SNARE proteins by using their PSSM profiles as the model might predict SNARE proteins accurately via the special features from those amino Performance for identifying SNARE proteins with 2D CNN Table 3 Performance results of identifying SNAREs with different filter layers. Figure 3 The validation accuracy on identifying SNARE proteins using different optimizers. layers, nadam optimizer, and dropout value of 0.1 to identify SNARE proteins with the work_co3aluz27vf67mmx2gwt73nree analyze the performance of Bayesian Neural Networks (BNN) in predicting the Bitcoin All frameworks attempt to predict the Bitcoin prices starting from five technical framework aims to predict the daily closing Bitcoin price at (t + n)th day, with n = 1, n = 10 predicts the daily closing price of Bitcoin at (t + n)th day1, as in the work by Patel et al. frameworks applying the k-fold cross-validation method to the train set just mentioned. work for the prediction of bitcoin price, describing the ML techniques used and their the daily closing bitcoin price series; The Framework''s Calibration and Performance machine learning-based classification and regression models for predicting Bitcoin price In this work we attempted of predicting the bitcoin price investigating the best Predictions of bitcoin prices through machine learning based frameworks Predictions of bitcoin prices through machine learning based frameworks Predictions of bitcoin prices through machine learning based frameworks work_cqzzh4tjajaz5jpicwx5hllhba P2P network system, this paper constructs a availability model the steady-state availability of repairable network There is no central node in the block chain network Block chain network nodes have availability of blockchain P2P network system is an composed of several network nodes and several repair chain, state transition probability in △t time is shown Steady-state availability is one of the reliability equations, and the steady-state availability of the calculate the steady-state availability, but to consider network nodes that can work normally is 4, that availability A of the network system is obtained. and Table 3 is for steady-state availability of each Table 4 is the steady-state availability of a different STEADY-STATE AVAILABILITY CALCULATION STEADY-STATE AVAILABILITY CALCULATION STEADY-STATE AVAILABILITY CALCULATION STEADY-STATE AVAILABILITY CALCULATION steady-state availability of the system is very high, of steady-state availability and instantaneous of steady-state availability and instantaneous The method of network reliability and availability work_cse4s3tt2famra6fdegfcy5mnu elimination method to solve virtual machine migration and placement of multi-objective optimization Keywords: Cloud computing, Virtual machine migration, Multi objective optimization, Ant solution in virtual machine migration, but the method is short of the ability of global optimization. load balance of each node, setting up the monitor signal in the virtual machine management program, increase the application rate of load, we propose an optimized virtual machine dynamic migration Figure.2 Dynamic migration of virtual machine placement framework optimization module The migration and placement of virtual machine has been the focus of research in cloud computing, it Multi Objective Optimization of Virtual Machine Migration Placement Based on Cloud Computing Multi Objective Optimization of Virtual Machine Migration Placement Based on Cloud Computing Multi Objective Optimization of Virtual Machine Migration Placement Based on Cloud Computing Multi Objective Optimization of Virtual Machine Migration Placement Based on Cloud Computing Multi Objective Optimization of Virtual Machine Migration Placement Based on Cloud Computing work_ctayywu6gfdgbowc6nbcvpyjoe Parsing entire discourses as very long strings: Capturing topic continuity in context of language acquisition, this independence assumption discards cues that are important to the learner, e.g., the fact that consecutive utterances are likely to share the same Figure 1: Unigram Social Cue PCFGs (Johnson et al., 2012) – shown is a parse tree of the input utterance "wheres In addition, our discourse model produces a performance improvement in a language acquisition task mappings and inferring sentence topics as a grammar induction task where input strings are utterances key feature of these grammars is that parameter inference corresponds both to learning word-topic relations and learning the salience of social cues in utterances in a single parse, our proposed grammatical formalism is a bigram Markov process that models transitions among utterance topics. can use the ability of the Earley algorithm to compute prefix probabilities (Stolcke, 1995) to rescale Turning to the discourse models, social information and topic continuity both independently boost work_cwuwqujlcjb2hduzqfbskahykq promote fluent translation output, but traditional n-gram language models are unable to log-linear parameters of an SMT system further increases translation quality when coupled with a syntactic language model. syntactic evaluation metric for optimizing the loglinear parameters of the SMT model. Section 2 describes our relational dependency language model; Figure 1: Translation output of baseline English→German string-to-tree SMT system with original dependency representation and conversion into constituency representation. Rather than directly comparing perplexity between different models, our focus lies on a perplexity comparison between a human reference translation and the 1-best SMT output of a baseline translaTranslation results for English→German with different language models added to our baseline are Table 3: Translation quality of English→German string-to-tree SMT system with different language models, with kIf we use BLEU+HWCMf as our tuning objective, the difference between the models increases. n-Gram and Dependency Language Models. Neural Language Models Improves Translation. work_cxe3a2zmnnge5ojw7lp3ztifam How to cite this article Newe (2016), Enriching scientific publications with interactive 3D PDF: an integrated toolbox for creating readyto-publish figures. model files and of the final PDF documents is still cumbersome. of both the 3D model files (which can be embedded into PDF documents) and the final, Creating 3D model files and PDF documents Although many tools and libraries are available that support the creation of 3D model files documentation including an example project, a wizard for creating tailored PDF modules R5 The software shall create 3D model files in U3D format. the creation of the final PDF documents with embedded 3D models. the MeVisLab menu: File → Run Project Wizard...→ PDF Module. complete workflow for generating 3D model files and 3D PDF documents for scholarly Document Format (PDF) files. scholarly 3D PDF (Portable Document Format) files. forembedding into 3D Portable Document Format (PDF) files for publication and work_cxgelzja2ve7blgq5bwv2zoshy UX practices and challenges in relation to other software quality characteristics or, reported in existing literature about usability or other software quality characteristics, Keywords Usability, Software quality, Quality requirements, User experience, Non-functional (2017), Integrating User eXperience practices into software development processes: implications of level, the actual experience of the end users as they interact with the software needs to be handling of general software quality characteristics, especially usability. related empirical studies on software quality characteristics, in particular, usability and UX. practitioners still focus more on functionality and usability issues in their UX work. practitioners.2 In addition, those studies that report software organizations often focus According to the practitioners, in many cases, the non-task-related needs of users that better UX work requires early involvement of UX practitioners in projects. practitioners face in their work with UX compared to other quality characteristics, including usability. power struggles between developers and designers as a challenge to UX and usability work work_cxyxl5vs6zd6xlanudcx46qoqy Joint Semantic Synthesis and Morphological Analysis of the Derived Word investigate different models of vector composition, showing that recurrent neural networks parts.2 In this work, we propose a novel joint probabilistic model of word formation that captures both • First, we show that jointly modeling continuous representations of the semantics of morphemes and words allows us to improve morphological analysis. • Second, we explore improved models of vector composition for synthesizing word meaning. second body of work, e.g., the unsupervised morphological segmenter MORFESSOR (Creutz and Lagus, 2007), does not deal with semantics and makes While most prior work on morphological segmentation has not explicitly modeled productivity,5 we model''s ability to segment words into their canonical morphemes as well as its ability to compositionally derive vectors for new words. Improved transition-based parsing by modeling characters instead of words with LSTMs. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 349–359, models for morpheme segmentation and morphology work_cziuyuoc3ffuznqfiluyvprwpq Deep Recurrent Models with Fast-Forward Connections for Neural Machine This is the first time that a single NMT model achieves state-of-the-art performance and outperforms the best conventional model by 0.7 BLEU points. After special handling of unknown words and model ensembling, we obtain the best score reported to date 2003; Durrani et al., 2014) which consist of multiple separately tuned components, NMT models encode the source sequence into continuous representation space and generate the target sequence in an the systems based on these models can achieve similar performance to conventional SMT systems (Luong et al., 2015; Jean et al., 2015). With our deep attention model, the BLEU score can be improved to layers of the two columns process the word representations of the source sequence in different directions. Next we list the effect of the novel F-F connections in our Deep-Att model of shallow topology in Table 5: BLEU score of Deep-Att with different model work_d2vjeeo4qjeyhn4ekhqacy6q3u in object-oriented languages, while the dynamic behaviour of neurons and synapses different kinds of neuron and synapse models to the constraints of temporal language aspects of temporal constrained objects followed by the essential modelling (Fritzson, 2004) is a constrained object language for modelling and simulation in the In this paper, we used temporal constrained objects to model the time-varying dynamics Temporal constrained objects allowed a direct implementation of the circuit model of a In modelling neurons and synapses with temporal constrained objects, the biophysical In temporal constrained object based implementation, synapses were also modelled circuitry with Purkinje neurons was modelled with temporal constrained objects (Fig. 8B) The temporal constrained object model of the microcircuit allowed computing the spiketrain responses of constituent neurons. The neuron and synapse models implemented using temporal constrained objects Temporal constrained objects for modelling neuronal dynamics Temporal constrained objects for modelling neuronal dynamics Temporal constrained objects for modelling neuronal dynamics work_d4brcbtmzzfcnhn3mfx5etocxu A Secure Voice Signature Based Lightweight space of operability of key in most of the cryptography based based voice signature based authentication scheme with a taint voice signature as the hash of the MFCC parameters of the extracting features of speech in voice recognition. voice signature of the user in the authentication phase. (DTW) based speech recognition system for feature new algorithm for extracting MFCC for speech Another work on voice recognition is speaker VOICE SIGNATURE BASED AUTHENTICATION The voice signature based authentication scheme windowing, MFCC generation, and voice signature Model of the remote voice based access control shows a speech signal after it has been framed. user''s voice signal through the mobile device in order to re-generate an access voice signature. compares the re-generated access voice signature with the voice based authentication scheme. PERFORMANCE EVALUATION OF VOICE SIGNATURE BASED signature from user''s voice signal. An efficient MFCC extraction method in speech recognition. work_d4oifelki5bajaka556kgxluoa focus on the short term profitability of BTC against the euro and the yen for an eightyear period using seven trading algorithms over trading periods of length 15 and 30 days. is no work to evaluate the short term profitability of BTC using algorithmic trading moving average based algorithms and consider buy and hold as a benchmark strategy. Reservation price algorithms result in 7.5% and 10% of average returns over 15 and 30 formal description for El-Yaniv reservation price algorithm for generating buy and sell between the short and long term moving averages in order to generate buy and sell signals. average trading period returns, the number of buy/sell signals generated and the impact of average based strategies (VLMA, FLMA) with BH, we found that for BTC, the returns of for the returns of BTC on various algorithms for 15 and 30 days trading periods. For 30 days trading period, the returns of moving average based strategies work_d6kjnyqzwjcgzjuphidi4rvpvu supervised optimization of dimensionality reduction and classification models. with deep learning architectures, and achieved accurate prediction results (top area Autoencoder, Biomedical informatics, Binary classification, Deep learning, Cervical cancer, Identifying patients with the highest risk of developing cervical cancer can problem of predicting the patient''s risk to develop cervical cancer through machine In this work, we propose a joint strategy to learn the low-dimensional space and the Generally, to tackle high-dimensional classification problems, machine learning this idea to model an individual patient''s risk of having cervical cancer. The machine learning models we proposed achieved high prediction results, As shown in the Results section, our deep learning algorithm can predict cervical cancer Learning Repository: https://archive.ics.uci.edu/ml/datasets/Cervical+cancer+%28Risk https://archive.ics.uci.edu/ml/datasets/Cervical+cancer+%28Risk+Factors%29 https://archive.ics.uci.edu/ml/datasets/Cervical+cancer+%28Risk+Factors%29 https://github.com/kelwinfc/cervical-cancer-screening/tree/master/risk-factors/data https://github.com/kelwinfc/cervical-cancer-screening/tree/master/risk-factors/data Supervised deep learning embeddings for the prediction of cervical cancer diagnosis Supervised deep learning embeddings for the prediction of cervical cancer diagnosis Supervised deep learning embeddings for the prediction of cervical cancer diagnosis work_dbgv2rgi25gz3jaoh7aktxtj3i compatible with existing networks (Internet using IPv4 of IPV9 can meet the needs of domain name address The IPV9 protocol uses 0-9 Arabic digital network TEXT REPRESENTATION OF THE IPV9 ADDRESS The representation of the 256-bit IPV9 address is IPv6 address, expressed in hexadecimal. represents an 8-bit IPv4 address, expressed in decimal. length is 16 bits, and the physical address of IPv4 will facilitates the compatibility of these IPv4 addresses in IPV9 address prefix, a representation similar to CIDR the IPV9 address, but the prefix length refers to the the IPV9 address prefix is converted to hexadecimal. However, the IPV9 address is still a decimal number. the law can use China''s IPV9 decimal network/digital unique domain name and address of China IPV9 can 4) China''s IPV9 start address is 2256 bit, and can IPv6 has a 128 bit address, but it can representation of the IPV9 address includes work_dcmrfgamtvhcxjgop5zumhpcha pointers and destructive update, higher order functions including closures and preand post-conditions concerning sharing for functions. Keywords Functional programming language, Algebraic data type, Destructive update, at a much lower level and consider aliasing of pointers and sharing of data structures. This requires analysis of pointer aliasing and data structure sharing, to destructive update of shared data structures but do not allow this impurity to be assignments and function calls, sharing analysis is used to check that all parameters which Ref t creates a closure of type t ->() containing that argument (and thus sharing the sharing analysis of the Pawns compiler allows a distinction between "abstract" variables, In our sharing analysis algorithm we use a function fc (fold component) which takes a v.c abstract domain contains "self-alias" pairs for each possible component of a variable which indirectly updated at that point only shares with variables of the same type or a more work_ddmboglpsndzdb7xkfgsgutgg4 Academic Collaboration via Resource Contributions: relevant resources, which scientists contribute into collaborations multiplex ego networks containing data on individual attributes (such as gender, scientific degree), collaboration ties (including alter–alter inventory of 25 types of academically relevant resources egos and Collaboration networks, Resources, Sociology of science, Ego 1. collect egocentric data on collaborative relations; 3. measure what resources (Item 2) collaborating parties (ego and alters) engage in their collaboration ties (Item 1). interviews conducted on a sample of Polish scientists, unique contribution in scientific collaboration studies, what resources were contributed by the collaborator. skills), and social resources (e.g. collaborators). Data about resources engaged by respondents data are provided in table resources having 1,761 Resources engaged in collaborations (variable code) types of resources in collaboration ties – certain Academic Collaboration via Resource Contributions: An Egocentric Dataset Academic Collaboration via Resource Contributions: An Egocentric Dataset Academic Collaboration via Resource Contributions: An Egocentric Dataset work_ddz5r4ceerf45fsxq46cai43tu We present a novel hierarchical distancedependent Bayesian model for event coreference resolution. widely used in supervised coreference models to guide the generative clustering processing for better event clustering both within and importantly, event coreference resolution is a necessary component in any reasonable, broadly applicable computational model of natural language understanding (Humphreys et al., 1997). the incorporation of feature-based, learnable distance functions as clustering priors, thus encouraging event mentions that are close in meaning to belong to the same cluster. learning of event coreference relations with unsupervised hierarchical modeling of event clustering Coreference resolution in general is a difficult natural language processing (NLP) task and typically requires sophisticated inferentially-based knowledgeintensive models (Kehler, 2002). Bejan and Harabagiu (2010; 2014) proposed several unsupervised generative models for event mention clustering based on the hierarchical Dirichlet Thus it is ideal to have a twolevel clustering model that can group event mentions within a document and further group them work_dh2iacdeezc77or4t64s2wnxoy at the experience of the importance of translation in the field of gender studies in the developing world Keywords: comparative feminism, translation, India, Arab Instigating social change: Translating feminism in the Arab world firstly that the translation of feminist texts in India and the Arab world involves the invention of new but translating in the Arab world and India is, to quote Spivak (1999) "often a political exercise of a Although both translators of feminist texts in India and the Arab world cannot avoid a form of this reinventive process the idea of starting off from an inferior position (that of woman, or that of translator) As women in both India and the Arab world continue to explore feminist texts and Those working in gender studies in India and the Arab world are viewed independent researchers in the Arab world engage with the study of gender and feminism, the usage work_dhfbsrtekzhwpbhp5vvyoh5mvq decomposition of the covariance function as the sum of periodic and aperiodic kernels. product to the implementation of the associated periodic kernels in a Gaussian process Keywords RKHS, Harmonic analysis, Circadian rhythm, Gene expression, Matérn kernels spaces (RKHS) and on the consequences for Gaussian process modelling. some expressions of kernels leading to RKHS of periodic functions can be found in the COSOPT, the periodic Gaussian process model and linear regression. • Gaussian process regression with a periodic kernel. Gaussian Process with periodic covariance function. The models fitted with COSOPT, linear regression and the periodic Gaussian process to consider a pseudo-periodic Gaussian process y = y1+yp with a kernel given by ''Decomposition in periodic and aperiodic sub-models'' for more details). Figure 4 Distribution of the periodicity ratio over all genes according to the Gaussian process models. COSOPT but not by the Gaussian process approach, whereas in (B) they are labelled as periodic only work_dhlxzkabinh5dbnupsc3ro2fke networks to map user interests in social media web site reddit and show how such a map could be used to navigate a social media world. analyze the network properties of the reddit social network and find that it has a scale-free, small-world, and modular community structure, much like other online social networks such as Facebook and Twitter. scale-free structure of most online social networks, these elementary navigation strategies result in users By viewing subreddits as nodes linked by users with common interests, we find that the reddit social user''s interests, thus establishing another standard real-world social network data set for researchers to These network statistics are plotted over a range of α cutoff values for the backbone reddit Next, we are interested in exploring whether the backbone reddit interest network is a scale-free the reddit interest network has a scale-free, small-world, and modular community structure, corroborating work_dje5ojarjrczblufj6vqhi46zi the address space, performance, network security and By using IPV9 routers, clients, protocol conversion routers and other devices to build a pure IPV9 network, controllable IPV9 future network root domain name data gram is processed using the IPV9 protocol. aimed at the original IPv4 protocol stack network layer Network Interface Layer Protocol according to the routing protocol of IPv4. according to the routing protocol of IPv4. host domain names to IPV9 addresses on a dual-stack The panel includes network connection indicator light, By building this dual protocol stack router, the IPV9 which is connected through the IPV9 private network. The router interface is configured as the IPV9 IPV9 private network transmission IPV9 private network transmission B. IPV9 Private Network Tunnel Transmission tunnel respectively, that is, the IPV9 address of router 1 and IPV9 address, and arrive at the destination router 2 to Network Working Group.Transmission of IPv6 Packets work_dkcqjp34xrbfzhxg3lxfqxjc3m the automatic learning of the features and relations between an essay and its score Keywords AES, Automated essay scoring, Essay grading, Handcrafted features, Automatic Automated language essay scoring systems: a literature review. Automated Essay Scoring (AES) systems usually utilize Natural Language Processing from text to start processing, then compares scores with human graded essays (Attali & automate essay scoring, but can be applied to any text classification task (Taylor, 2005). capable of learning features automatically to score essays. A neural network approach to automated essay scoring and learn them, and encode all the information required for essay evaluation and scoring neural network for automatic essay scoring Recurrent Neural Network architecture to score essays automatically. The AES systems do not assess the intrinsic qualities of an essay directly as human-raters Automated essay scoring with E-Rater R© V.2.0. deep convolution recurrent neural network for automatic essay scoring. A neural approach to automated essay scoring. work_dksywpuce5hyvazldbmanbc62i Both algorithms use statistical independence tests to infer the structure by successively constraining the set of structures consistent with the results of these Until very recently, algorithms for structure learning were based on maximum likelihood estimation, which has been proved to be NP-hard for Markov networks due to the We present two algorithms for MN structure learning from data: GSMN∗ (Grow-Shrink Markov Network learning algorithm) and GSIMN (Grow-Shrink Inference-based Markov and GSIMN algorithms presented apply to any case where an arbitrary faithful distribution can be assumed and a probabilistic conditional independence test for that distribution (Grow-Shrink Inference-based Markov Network learning algorithm), introduced in this section, uses the Triangle theorem in a similar fashion to extend GSMN∗ by inferring the value For each data set and each algorithm, we report the weighted number of conditional independence tests conducted to discover the network and the accuracy, as defined work_dlderla2pvcoffpl2iq6a6dw6i Research and Implementation of the Key Technology of UAV Aerial Image Transmission | Atlantis Press Proceedings of the 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018) Fan Yijun, Lai Yufeng This is an open access article distributed under the CC BY-NC license. This is an open access article distributed under the CC BY-NC license. TI Research and Implementation of the Key Technology of UAV Aerial Image Transmission TI Research and Implementation of the Key Technology of UAV Aerial Image Transmission BT 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018) BT 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018) Atlantis Press is a professional publisher of scientific, technical and medical (STM) proceedings, journals and books. The proceedings and journals on our platform are Open Access and generate millions of downloads every month. work_dmcovzu62jccrgxrk62safxfcu Keywords Smart factory, Machine learning, Honeypot, Botnets detection, IoT Classification of botnet attacks in IoT smart factory using honeypot with machine learning in developing a botnet detection model for IoT smart factories. Figure 3 Taxonomies for botnet detection and security layers of IoT smart factories. Applying machine learning in botnet detection for smart factories can become useful to � One study suggested to apply machine learning to detect botnet in the smart factory Table 2 A comparison of studies in botnet detection using honeypot and/or machine learning approaches for smart factories. IoT botnet attacks to smart factory reported in the previous work studying in network Figure 9 Process design of honeypot combined machine learning model to detect botnet attacks in Classification of botnet attacks in IoT smart factory using honeypot combined with machine learning Classification of botnet attacks in IoT smart factory using honeypot combined with machine learning work_dphsjhb7knae5pimptyktv4r2i investigate the phenomenon of fake online reviews in the tourism sector on social studies that addressed the following two main topics: (i) tourism (ii) fake reviews. Keywords Online reviews, Fake reviews, Consumer behavior, Algorithms, Tourism The importance of behavioral data to identify online fake reviews for behavior of hotel consumers, reviews on online travel sites and social networking sites most online platforms have their own false review detection algorithms (Cheng, Tseng overview of previous research on the state of art of online fake reviews in tourism social demonstrated in several studies, the currently available algorithms of false review detection Table 1 Previous studies on fake online reviews in the tourism industry. fake online reviews in the tourism industry. research on the impact of new approaches is necessary to detect fake online reviews for fake reviews in the tourism sector, further research that would perform in-depth analysis work_dpi57lzqsnbf3mz6huezcw3zoy Various resources have been developed for computational linguists working on ''Semantic Role Labeling'' (SRL), largely under the classical, categorical notion of role. And finally, (v) how do the resulting configurations of finegrained role properties compare to coarser annotated 1To be clear, Dowty himself does not make direct predictions about the distribution of proto-role properties within a corpus, except insofar as a corpus is representative of the lexicon. Proto-Agent properties predict the mapping of semantic arguments to subject and object. versions of Dowty''s proto-role properties about sentences of English. and annotating fine-grained role properties is valuable in both linguistic theory and in computational The results of this experiment, broadly, replicate Kako (2006b)''s earlier findings: human annotators on average indicate that, within the same sentence, the subject-position argument is more likely the proto-role hypothesis over a large corpus: finegrained role properties predict the mapping of semantic roles to argument position. work_dqn2txozcvhufgeljzjxcvc7mu Exercise and insulin resistance in PCOS: muscle Objective: Mechanisms of insulin resistance in polycystic ovary syndrome (PCOS) remain muscle in the overweight women with PCOS but were unresponsive to exercise training and hyperandrogenism in PCOS-specific insulin resistance in lean and overweight women. PCOS-specific insulin signalling defects were isolated to mTOR, while gene expression implicated TGFβ ligand regulating a fibrosis in the PCOS-obesity synergy in insulin muscle insulin signalling and gene expression of the ECM Covariate adjusted statistical difference reported as: *significant fold increase with insulin stimulation P < 0.05 (and clear effect at Covariate adjusted statistical difference reported as: *significant fold increase with insulin stimulation P < 0.05 (and clear effect at 99%CL), **significant fold increase with insulin stimulation P < 0.01 (and clear effect at 99%CL), asignificantly different between group training response The women with PCOS from the exercise training subgroup had improved, but not rescued mTOR signalling https://figshare.com/articles/Supplementary_Material_Molecular_Mechanisms_of_Insulin_Resistance_in_Skeletal_Muscle_of_Women_with_PCOS/6726761 https://figshare.com/articles/Supplementary_Material_Molecular_Mechanisms_of_Insulin_Resistance_in_Skeletal_Muscle_of_Women_with_PCOS/6726761 https://figshare.com/articles/Supplementary_Material_Molecular_Mechanisms_of_Insulin_Resistance_in_Skeletal_Muscle_of_Women_with_PCOS/6726761 work_dsbccp6hrncrfph5eqx5uhjmjm computes a similarity vector by comparing a template of a species call with time visualization, Recording annotation, Generic species algorithm, Web-based cloud-hosted system, (2017), Species-specific audio detection: a comparison of three template-based detection algorithms using random forests. (e.g., efficiency and accuracy) of three variants of a template-based detection algorithm and 547 recordings from Peru for comparing the three algorithm variants. Table 1 Species, class, location and count of recordings with validated data. In this article each species Ttemplate was created using five ROIs. In Fig. 5A a training set for the Eleutherodactylus coqui is presented and in Fig. 5B the need a set of validated recordings with the specific species vocalization present in some positives (number of times the algorithm states that the species is present while the expert Standard deviation of the number of times a recording is detected 7.78 the efficiency in terms of time execution of three variants of a template-based detection work_dud6jcho45havihrl4d6i4z6iu An Ensemble Learning Method for Text Classification Based on Heterogeneous obtain a diversity of base classifiers only through sample classification ensemble learning method based on multi-angle learning model has higher classification accuracy. learning method based on multi-angle perturbation classification results to integrate the classifiers. algorithms are ensemble learning based on homogenous heterogeneous classifiers can improve model classification accuracy of base classifiers and integrated models, and then integration model of the heterogeneous base classifier ENSEMBLE LEARNING MODEL BASED ON higher accuracy, more base classifiers with more diversity For each classification model, its algorithm parameters, an integrated learning model based on multi-angle B. The effect of feature selection algorithm and classifiers perturbation integrated model, only one of the classifiers can algorithm, feature dimension, classifier and its parameters integrated model based on multi-angle perturbation results show that the integrated learning model based on classification accuracy and rich base classifier diversity. work_dunvealesnba5i44lf4b6hxbni enhancement of the Mizar proof-checker which allow declaring properties of notions of The current implementation of the Mizar proof-assistant allows using properties for In this paper we propose an extension of both the Mizar language and the Mizar proofchecker which allows declaring properties of notions of arbitrary arity with respect to mathematical notions can be defined in Mizar articles. The Mizar Mathematical Library (MML) (Bancerek et al., 2018; Alama et al., 2011) was The current Version 5.63.1382 of the Mizar Mathematical Library contains 1385 articles Mathematical Library, and text-proper part, where new definitions, lemmas, theorems etc. When all formulae are accepted, the article can be submitted to the Mizar Mathematical article, and Transferer—transfers the knowledge into the Mizar Mathematical Library. Properties in Mizar are constructions which can be used to declare that predicates are applications working on the semantic level of the Mizar Mathematical Library (Urban, work_duq33giwkjd7djgxwuk3nmjagm Methods for Named Entity Recognition and Disambiguation (NERD) perform Motivation: Methods for Named Entity Recognition and Disambiguation, NERD for short, typically proceed in two stages: • At the NER stage, text spans of entity mentions are detected and tagged with coarsegrained types like person, organization, location, etc. not able to help NER, for example, by disambiguation "easy" mentions (e.g., of prominent entities probabilistic graphical model for the joint recognition and disambiguation of named-entity mentions • an inference method that maintains the uncertainty of both mention candidates (i.e., token spans) and entity candidates for competing entity candidates; 2) linguistic features about verbal phrases from dependency parse trees; 3) maintaining candidates for both mentions and entities entity, for a given mention token toki, based on the NER type and the NED label of a token toki generates binary features if toki appears in uppercase form and is NER-labeled as typej in the training corpus. work_dvt43m6lunfqncjpyuav4zbr6y optimization algorithm called grey wolf reconstruction algorithm (GWRA). GWRA: grey wolf based reconstruction algorithm for Here, we propose a new grey wolf based reconstruction algorithm (GWRA) for CS 1. Develop a novel reconstruction algorithm based on grey wolf optimizer (GWRA) that: Grey wolf reconstruction algorithm performs the following initialization in this phase: From Fig. 6, we can conclude that GWRA algorithm achieves the best reconstruction Figure 4 ANMSE in GWRA, CoSaMP, OMP, FBP, SP, BA and PSO algorithms over generated Figure 4 ANMSE in GWRA, CoSaMP, OMP, FBP, SP, BA and PSO algorithms over generated Figure 4 ANMSE in GWRA, CoSaMP, OMP, FBP, SP, BA and PSO algorithms over generated Figure 6 ANMSE in GWRA, CoSaMP, OMP, FBP, SP, BA and PSO algorithms for different GWRA: grey wolf based reconstruction algorithm for compressive sensing signals GWRA: grey wolf based reconstruction algorithm for compressive sensing signals work_dwgtwxbuv5frtgrviz2ypnjcqu Research on the Tunnel Geological Radar Image Flaw fast, nondestructive, continuous detection, real-time imaging, an improved method of void defect detection based on Faster RCNN (Regional Convolutional Neural Network) is proposed Keywords-Tunnel Geological; Radar Image; Flaw Detection; Geological radar detection method[1-2] is the survey images generated by radar equipment one by deep learning, using convolutional neural network R proposed the regional convolutional neural network Faster RCNN model is directly applied to the tunnel Faster RCNN model to expand original data sets, geological radar image detection. reflected in the radar image as positive and anti-peak Convolutional Neural Networks (CNN) can use output feature graph) is generated by convolution with image (because the RPN network and Fast RCNN Fast RCNN is a separate training detection network. Analysis of GPR image features of tunnel lining defects. object detection with region proposal networks[J]. Application of convolution neural network in image work_dz4hp2vbnvhntnb4aujexwenge strategies consist in identifying the key individuals, dividing the personal network in groups and classifying alters in concentric circles In this paper, we explore the contributions of visualizations when collecting personal network data, as data collection process and achieving the most accurate representation of respondents'' personal network This research is based on data from 95 foreigners residing in Seville for a study that aimed at understanding how the type of mobility could influence the composition and structure of personal networks (Cachia What the eye does not see: visualizations strategies for the data collection of personal network What the eye does not see: visualizations strategies for the data collection of personal network What the eye does not see: visualizations strategies for the data collection of personal network What the eye does not see: visualizations strategies for the data collection of personal network What the eye does not see: visualizations strategies for the data collection of personal network work_dzeata5onzf7rp26j2quaotjza sandboxing landscape covers a range of deployment options and policy enforcement techniques collectively capable of defending diverse sets of components while Keywords Sandboxing, Qualitative content analysis, Software protection, Access control, Sandboxes have been built to stop memory corruption exploits, ensure controland data-flow integrity, enforce information flow constraints, introduce diversity where security validation and (2) the neglect of sandbox and policy usability (''Strengthening Sandbox An encapsulation mechanism that is used to impose a security policy on user-level sandboxing and policy enforcement code, which closely We learned that evaluative questions were quite interesting while coding papers, thus frames concerning what claims were made about a sandbox and how those Sandboxes with fixed policies tend to prevent memory corruption or protect properties of application code (e.g., control Table 6 Claims made about sandboxes ( : Security, : Performance, and : Applicability) and their validation strategies ( : Proof, : Analytical Analysis, : Benchmarks, : Case Studies, and : Argumentation). work_dzfda62vxjemvos4a6kit6z3iu rhetorical entities of type Claims and Contributions from full-text scientific literature. available on our GitHub page at https://github.com/SemanticSoftwareLab. How to cite this article Sateli and Witte (2015), Semantic representation of scientific literature: bringing claims, contributions and Natural Language Processing (NLP), Linked Open Data (LOD)-based entity detection, mentions "linked open data," or even "LOD," since they are semantically related in the DBpedia ontology (DBpedia Ontology, http://wiki.dbpedia.org/services-resources/ontology). publications and their NLP analysis results into a knowledge base in RDF (Resource Description Framework, http://www.w3.org/RDF) format, based on a shared vocabulary, so web-based tool to help users annotate experiments in scientific papers with a set of General Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloud Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloud work_e2z3bbfbmvbzjjspphct63bhsa deep learning model based on a Fully Convolutional Network (FCN) architecture. The proposed model is trained in an end-to-end style and designed to predict visual A novel fully convolutional network for visual saliency prediction. (1) A new model of FCN architecture for visual saliency prediction that uses two types Subsequently, many models have been proposed to address visual saliency detection Since the superior success of transfer learning models for visual saliency prediction has Figure 1 explains the architecture of the proposed model for visual saliency prediction Figure 1 illustrates the proposed model architecture to predict visual one can see the proposed model has the ability to predict visual saliency in a given image. To evaluate the efficiency of the proposed model for predicting visual saliency, we is that the proposed model was specifically designed for saliency prediction, whereas A new deep CNN model has been proposed in this paper for predicting visual saliency work_e6jamuapavb4jnm3pcyykhj3ba (2017), DGPathinter: a novel model for identifying driver genes via knowledge-driven matrix factorization tumor samples, previous studies have reported that some driver genes are mutated at low interactome information (DGPathinter), to discover potential driver genes from mutation genes in the matrix G from information of somatic mutation data, pathways and interaction network, we can identify the potential driver genes by ranking their mutation Figure 2 Precision–recall curves of the prioritization results of the investigated methods for cancer specific known driver genes curated by DGPathinter to identify driver genes from mutation data with prior knowledge from Detection of driver pathways using mutated gene network in DGPathinter: a novel model for identifying driver genes via knowledge-driven matrix factorization with prior knowledge from interactome and pathways ... DGPathinter: a novel model for identifying driver genes via knowledge-driven matrix factorization with prior knowledge from interactome and pathways ... work_e6td4igoavconayt3iw5mwxlsi from WordNet senses to images, and a second game that performs Word Sense Disambiguation. Furthermore, because games may appeal to a different group of people than crowdsourcing, they provide a complementary channel for attracting new annotators. The first video game, Puzzle Racer, produces a mapping between images and quality to those of experts and at a cost reduction from gathering the same annotations via crowdsourcing; with the second game we show that video resources produced by the games: (1) an image library mapped to noun, verb, and adjective WordNet senses, consisting of 19,073 images across 443 In contrast, our Puzzle Racer game is purely visual and does not require players to read definitions, instead showing picture examples, increasing its video game-like quality. for enabling engaging NLP games: image representations of concepts, specifically WordNet senses. Experiment 1 measures differences in the quality of the three top-ranked images produced by Puzzle Racer and CrowdFlower for each sense. work_e7wzf6nye5ekvb5ddmyh7khavi Word meanings change over time and an automated procedure for extracting this information from text would be useful for historical exploratory studies, information retrieval change, which infers temporal word representations as a set of senses and their prevalence. Word meaning is modeled as a set of senses, which are tracked of terms from two time periods (Popescu and Strapparava, 2013; Cook and Stevenson, 2010), to training distributional similarity models on time slices (2014) manually identify 13 target words which undergo meaning change in a focus corpus with respect to a reference corpus (both news text). word, our model infers its senses for each time interval and their probability. Figure 4: Tracking meaning change for the words band, power, transport and bank over 20-year time intervals Figure 6: Precision results for the SCAN and SCAN-NOT models on the WordNet-based novel sense detection (Experiment 2). set of target words used for the task-based evaluation (in Section 8) and trained models on the DATE work_ea2y7a4x6zabxp5sgs3jl5skuy ABCNN: Attention-Based Convolutional Neural Network This work presents a general Attention Based Convolutional Neural The ABCNN can be applied to a wide variety of tasks that require modeling of sentence pairs. How to model a pair of sentences is a critical issue in many NLP tasks such as answer selection ABCNN, an attention-based convolutional neural ARC-I focuses on sentence representation learning while ARC-II focuses on matching features on phrase level. For the output feature map of the last convolution layer, we do column-wise averaging over all For the output feature map of non-final convolution layers, we do column-wise averaging over windows of w consecutive columns, denoted as w-ap; ABCNN-3, that each introduces an attention mechanism for modeling sentence pairs; see Figure 3. The ABCNN-1 (Figure 3(a)) employs an attention feature matrix A to influence conAs a result, the new input of convolution has two feature maps for each sentence (shown work_eabupqevvbdzbepciteahrkls4 Keywords Online social networks, Community evolution detection, Community ranking, community ranking algorithm for a modern online social network application. users are extracted using the Infomap community detection method (Rosvall & Bergstrom, the last and featured step, the evolution is studied in order to rank the communities and dynamic community containers which provide structured access to information. • a novel ranking framework for dynamic communities based on temporal and contextual Another dynamic community detection method used to extract trends was introduced of the complete network, and then applied a dynamic community detection algorithm on Every node in the resulting graphs represents a Twitter user who communicated tweets Table 2 Number of detected dynamic communities with and without the timeslot delay. B), Newman (C, D) and Louvain (E, F) community detection algorithms for the 2014 BBC''s Sherlock series (A, C, E) and the 2012 US elections (B, D, F). dynamic community detection in social networks. Community ranking in social network. work_eb3v35mzffhfldcyuvzyhi467q epidemiological risk factors and clinical outcomes among patients with papillary thyroid Results: The BRAF V600E mutation was present in 83.7% of patients (1715 of 2048). BRAF V600E mutation and extrathyroidal invasion, distant metastatic and disease mutation observed in PTC, BRAF V600E has received outcomes in patients with PTC, such as large tumor size, Table 1 Association of BRAF V600E with epidemiologic features of all PTC. In patients without BRAF V600E mutations, Table 3 Multivariate logistic regression analysis of BRAF V600E mutation of all PTC. In patients with BRAF V600E mutations, the disease BRAF mutation in papillary thyroid cancer and its value in meaning of BRAF V600E mutation in papillary thyroid carcinoma. value of BRAF mutation in thyroid cancer. 26 Xing M, Alzahrani AS, Carson KA, Shong YK, Kim TY, Viola D, BRAF V600E mutation and recurrence of papillary thyroid cancer. BRAF V600E mutation and mortality in patients with papillary work_eeqhqy25cjchrak5hfr6qg3kqi sys_1000 wp-p1m-38.ebi.ac.uk wp-p1m-38.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265372276 (wp-p1m-38.ebi.ac.uk) Time: 2021/04/06 17:58:22 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_efnphgi6gzaxhe7ef5nxddwh7u He, H, Lin, J & Lopez, A 2015, ''Gappy Pattern Matching on GPUs for On-Demand Extraction of Hierarchical Translation Grammars'', Transactions of the Association for Computational Linguistics, vol. https://www.research.ed.ac.uk/portal/en/publications/gappy-pattern-matching-on-gpus-for-ondemand-extraction-of-hierarchical-translation-grammars(f9f6c86d-3559-4697-9beb-0b85977ace12).html Gappy Pattern Matching on GPUs for On-Demand Extraction of Gappy Pattern Matching on GPUs for On-Demand Extraction of to new training data (Levenberg et al., 2010), making it useful for interactive translation (GonzálezRubio et al., 2012). Algorithm 1 Translation by pattern matching In this pass, we extract a translation for each match Our implementation of hierarchical grammar extraction on the GPU, as detailed in the previous section, We compared our GPU implementation for on-demand extraction of hierarchical grammars against the corresponding CPU implementation (Lopez, 2008a) found in pycdec (Chahuneau Table 3: GPU grammar extraction throughput (words/second) under different batch sizes, data conditions, to the GPU grammar extraction algorithm. words/second with GPU grammar extraction and to the 32-thread CPU baseline, our GPU extraction work_egt7fmczgjgbpjnjxzpgy5npoy Keywords Children activity recognition, Environmental sound, Machine learning, Deep artificial neural network, Environmental intelligence, Human activity recognition In works related to human activity recognition and classification, different data sources capture process when working on human activity recognition using environmental In the area of children activity recognition and classification common data sources For the generation of a human activity recognition and classification model, it is classification model using environmental sound data, working with a 34-feature set developed a children activity recognition and classification model using environmental artificial neural network in the generation of a children activity classification model � Deep artificial neural networks are efficient in generating children activity classification Human activity recognition from smart watch sensor data Deep artificial neural network based on environmental sound data for the generation of a children activity classification model Deep artificial neural network based on environmental sound data for the generation of a children activity classification model work_ehgjstdkgncm7pg3typfq6cpcu In this paper, we conduct an indepth adaptation of statistical machine translation to perform text simplification, taking Text simplification has applications for reducing input complexity for natural language processing (Siddharthan considerably less research on developing new paraphrasing models for text simplification — most previous work has used off-the-shelf statistical machine et al., 2015) to address problems in current simplification research — we amend human evaluation criteria, develop automatic metrics, and generate an Our focus on lexical simplification does not affect the generality of the presented work, since deletion or sentence splitting could be applied as preor tuning metrics and rich simplification-specific features into a syntactic machine translation model to Another challenge for text simplification is generating an ample set of rewrite rules that potentially simplify an input sentence. a universal metric that works for multiple text-totext generation tasks (including sentence simplification, compression and error correction), at the same work_ehr6hvkrsjbw7o6blqm2kzngf4 Keywords Malware analysis, Sequential models, Network security, Long-short-term memory, Deep learning based Sequential model for malware analysis using Our research is based on the analysis of API calls made by malware on the Windows We also construct malware detection models based on this dataset using the LSTM VirusTotal service, and LSTM algorithm used for our proposed malware classification API sequence dataset, which contains malware analysis information. In this study, the malware classification method was developed by using the LSTM In this study, the malware classification method was developed by using the LSTM Figure 4 LSTM classification model with Windows API calls. Single-layer LSTM models have been created that can classify 8 different types of malware. Two-layer LSTM models have been created that can classify 8 different types of malware. Table 8 shows the two layers LSTM model classification performance results.415 As expected, based on the experimental results, LSTM based malware classification model''s performance418 work_eiifbi6nnvfjdl2iphvrkxdkv4 (2016), Smart Brix—a continuous evolution framework for container application deployments. artifacts using Infrastructure as Code (IaC) (Nelson-Smith, 2013) techniques, such as Dockerfiles (https://docs.docker.com/engine/reference/builder/) for containerized applications. In this paper, we present Smart Brix, a framework for continuous evolution of container A recent study (http://www.banyanops.com/blog/analyzingdocker-hub/) shows that in the case of Docker, depending on the version of the images, The components in the Analyzer and Compensation Facet are managed as selfassembling omponents (http://techblog.netflix.com/2014/06/building-netflix-playbackwith-self.html), an approach we already successfully applied in previous work (Schleicher et implemented a Docker Analyzer component with a Base Image Processor and a Convention vulnerable images, we tested the implemented Container Processor strategy. process of compensation the Container Processor generates a new image with the upgraded compared to our approach, the authors do not provide a framework for analyzing container approach, the authors do not provide a framework for testing container-based deployments, work_ejjref45ynetbnipdfgfc5kmoe Figure 1: Sample 2D worlds and an instruction describing a goal location. instruction representation enables the model to sustain high performance when handling both local and Text instructions Prior work has investigated human usage of different types of referring expressions to describe spatial relations (Levinson, 2003; Generalization over both environment configurations and text instructions requires a model that the local structure and global spatial attributes inherent to natural language instructions. To that end, our model combines the textual instructions with the map in a spatially localized manner, as opposed to prior work which joins goal representations and environment observations via simpler Figure 5: Reward achieved by our model and the two baselines on the training environments during reinforcement learning on both local and global instructions. Table 2: Performance of models trained via reinforcement learning on a held-out set of environments and Figure 6: Value map predictions for two environments paired with two instructions each. work_en2rpj3s6rhivnhyoexbnb5mbq stakeholders to share dependability problems across software life cycle stages, which Keywords Assurance cases, GSN, DEOS process, Experience report, Service dependability How to cite this article Kuramitsu (2016), Continuously revised assurance cases with stakeholders'' cross-validation: a DEOS experience. assurance cases written in Goal-Structuring Notation (GSN) (Kelly & Weaver, 2004), a How assurance cases to be developed for improved software without regulators This section describes our ideas on how to use assurance cases in software-based IT systems Our aim in the use of assurance cases is to share dependability arguments among The Aspen project includes not only the development of assurance cases across different organizations but also Aspen''s software development and service operation with DEOS The developer started the argument with the claim ''''Aspen is dependable'''' and decomposed failures imply faulty arguments, the operator or the developer needs to revise the assurance Is the development of assurance cases useful in software? work_eopg7ki7vjcg7lxczmnt7oaeqq the attention-weighted sum of hidden states corresponding to nonlocal context (e.g., the hidden convolution filters derive a higher-level representation for word, denoted as wordnew, by integrating word with three pieces of context: leftcontext, We apply ATTCONV to three sentence modeling tasks with variable-size context: a largescale Yelp sentiment classification task (Lin et al., • ATTCONV shows its flexibility and effectiveness in sentence modeling with variablesize context. Figure 4: ATTCONV models sentence tx with context ty. Recall that ATTCONVaims to compute a representation for tx in a way that convolution filters encode not only local context, but also Attentive convolution then generates the higherlevel hidden state at position i: source of attention is hidden states in sentence tx, by function fmgran(Hy), feature map Hy of context ty acting as input; and (iii) attention beneficiary is learned by function fbene(Hx), Hx acting instance of generating source of attention by function fmgran(H), learning word representations words, our intra-context attentive convolution is work_eqip4jy63vbmti4clx5saaqwbi (Neuro-) physiological measures could capture a reader''s emotional state and use describe the theoretical foundation of the emotional and creative brain and review Keywords Creativity, Reading, Emotion, Neurophysiology, Brain–computer interfaces, Ebook, (2016), Toward physiological indices of emotional state driving future ebook interactivity. during the writing process to be able to compare the reader''s emotional state while reading signals that reflect the arousal and valence of emotions and that can potentially be measured The current case study focused on the writer and his emotional signals during the creative seem to show that creativity involves common cognitive and emotional brain networks also areas in the left hemisphere) except when writing emotional text, for which activity in Since there are no data available about neurophysiological correlates of emotional writing, to link specific neurophysiological indices to the emotional content of the writing. the task involved a multitude of emotional, creative and cognitive processes concealing work_etgjv3izcvcoxa7feakkgtd764 Sentence-processing in echo state networks: a qualitative analysis by finite analysis by finite state machine extraction'', Connection Science,, First published on: 22 March 2010 (iFirst) It has been shown that the ability of echo state networks (ESNs) to generalise in a sentence-processing machines (FSMs) from the data about the inputs, internal states, and outputs of recurrent neural networks that process symbol sequences. extracting finite state machines (FSMs) from network''s input symbols, recurrent-layer states, and probabilistic FSM given the network''s input, internal states, and outputs. To merge and split the state space, CrySSMEx creates a number of simple vector quantisers, arranged hierarchically in a graph (Figure 8 in Section 4.3 shows an example). network predicts the following input to be a noun, and indeed, all sentences of the language start After receiving the sentence''s second word (a verb), the FSM moves to State 2, where it predicts work_euxlou6l5nfy5prownqslmn7qq we propose a novel approach of concept based similarity estimation among court results suggest that the proposed approach of concept based similarity is effective in Finding similarity among legal documents, specifically among court judgments is one & Leskovec, 2016) for case citation data for finding similar legal documents. general agreement on the need for concept-based document retrieval in legal domain, and covering all legal concepts present in the document which results in single similarity value. In this proposed work, we present the legal document similarity In this paper, we propose a three-step approach for finding concept based similarity among court judgments: (i) Identification of main concepts/topics in the document, and we define base word concept set of the ''j''th sentence in the ''i''th (Vi,Ei) of a legal document Li, is constructed using the base concept words s.t. Vi =⋃ proposed approach of similarity estimation for extraction of relevant judgments from work_evnw3zjkvvd63mc2eu2m2ej6gm functionally equivalent versions of a service-based web shop—one with patterns Results: Both experiment groups were able to complete a similar number of tasks using service-based patterns, neither for the student experiment nor for the Keywords Design patterns, Evolvability, Modifiability, Controlled experiment, Metrics, On the impact of service-oriented patterns on software evolvability: a concept of (service-oriented) design patterns and discussing related work in the area. The research goal for our experiment was to analyze if selected service-based patterns have a Service-based patterns experience (1–10) Mean 1.86 2.85 that service-based patterns had a positive impact on participant effectiveness and efficiency. of 69 student participants, and nine metrics to all patterns and software developers. To analyze the impact of service-oriented design patterns on software evolvability, we On the impact of service-oriented patterns on software evolvability: a controlled experiment and metric-based analysis On the impact of service-oriented patterns on software evolvability: a controlled experiment and metric-based analysis work_evvbv2farjctznji56aki4kdpu Review of 3D Point Cloud Data Segmentation Methods of dividing the point cloud data set into several specific regions Despite widespread use, point cloud segmentation still faces many challenges because of uneven sampling popular algorithms and methodologies to segment point clouds. Keywords-Line Point Cloud; Segmentation; Classification We divide the 3D point cloud segmentation method The edge-based segmentation method is currently The edge-based segmentation method first segmentation; Wang et al.[6] proposed a fast point The region-based method classifies nearby points (a)original point cloud (b)segmented by Region Grow type of algorithm models the point cloud into a graph Machine learning treats point cloud segmentation as Segmentation methods based on edges and regions body contour extraction method based on LiDAR point cloud data [J]. 3D point cloud segmentation: A survey[C].2013 6th Based Multi-model Fitting for Point Cloud Segmentation. Optimized Lidar Point Cloud Scene Segmentation Method. recognition and model segmentation based on point cloud data [J]. work_ewm74zd5kzarrgihs43w6s6mxq Research and Application of SO2 Concentration Monitoring Algorithm in Flue Gas gas, this paper use cyclic iteration algorithm to measure the measurement of mixed gas with overlapping absorption, the SO2 Monitoring; Mixed Gas; Spectral Overlap Absorption; exist large errors for the gas concentration measurement of flue gas analyzer, to improve measurement accuracy, Wang Meng developed the portable gas analyzer based on the nondispersive ultraviolet absorption, and has improved resolution concentration from the absorption spectrum signal of the mixed calculate the gas absorbance and then get its concentration. of the gas absorb light is as follows: mixture if each kind of gas has a absorption of the light in between gas absorbance and concentration. wavelength by the measured gas absorption spectra, and then concentration, 2iA is a absorbance of gas to be measured. DOAS method for the mixture gas concentration with the concentration monitoring method of SO2 in flue gas. work_ezwbhq2nrvadncyjpwjlluuona trained an autoassociative network on a majority and a minority race of faces, and tested the model''s ability to process faces from the two races in different Using Caucasian faces as the majority race, the model There are data which suggest that the crossrace effect may indeed be a matter of differential exposure to faces of different races. any attempt to improve same-race face recognition by short-term training programs may be inadequate compared with years of extensive processing role of the eigenvectors as features for characterizing same-and other-race faces. Mean cosines between original and reconstructed images for the OLD and NEW majority and minority NEW majority and minority faces for the simulations. In both simulations, faces from the minority race Average inter-face similarity for the (a) Caucasian and (b) Japanese majority (95%) simulations, plotted simulations are more similar to one another than are faces in the majority race. work_f2qw6snsczggpc7yochevefzie resources information big data platform is of great significance framework of sports resources information big data platform, Keywords-Big Data; Sports Resources Information; Platform big data technology to build a sports resource information Sports resource information big data content is huge, called sports resources information big data platform. The business on sports resources information big data We shall build a sports resources information big data C. Construction of sports resources information big data social forces, the big data platform of sports resources 1) Framework of sports resources information big data data platform for sports resources information. establish the "sports resources information big data platform the core of big data platform of sports resource information Structure of Sports Resources Information Big Data Platform information big data platform and sports resources database, The Big Data Platform for Sports Resource Information The Big Data Platform for Sports Resource Information The Big Data Platform for Sports Resource Information work_f4yconvfenhincqamk2qowk37q Researchers use various skills in their works, such as writing, data analysis and skill ranking and propose a new model based on hypergraph theory to evaluate the on the PLOS ONE dataset and compare the rank of researchers'' skills with their papers'' Keywords Hypergraph model, Skill ranking, Researcher evaluation According to the above analysis, in order to rank researchers'' skill, field information to evaluate a researcher''s specific skill in a specific field by ranking methods. researchers, fields and skills, forming the vertex set of the heterogeneous network. The value of skill ranking of a researcher is calculated by the weight of the hyperedge in the rank the researchers according to the numbers of papers they published in field i, and for ranking of the researcher in a field at year i is calculated by all the papers he published until Based on the hyperedge weight, we can calculate the skill ranking of a researcher in a work_f4yz7eybbnfkfkp6xvojsv7npa The application of Thermal barrier coatings on the diesel engine piston head reduces the heat loss to the Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head Mechanical And Thermal Stresses Anylsis In Diesel Engine Poiston With And Without Different Thermal Coating Layer On Piston Head work_f5xxg7vqh5hp5elf56uvxcoqve Application of AGC Technology in Software Radio Abstract—The characteristics of software radio are flexibility, gain control(AGC) technology in software radio receiver and Keywords-Software Radio; Characteristics; AGC; Matlab At present, software radio technology is widely used in (AGC) algorithm in software radio. CHARACTERISTICS OF SOFTWARE RADIO Software radio adopts a standardized and structure torealize the concept of software radio. digital signal processors and various software components. The hardware platform of software radio should be a The hardware platform of software radio should be a So VME bus is often used in software radio. signal amplification can be realized. large signal is realized.Through the above algorithm,The Software radio receivers, Whether the for software radio system to be realized by DSP. [4] Application of Software Radio Technology in FM Transmitter Design [5] Application of Software Radio Technology in Ship Communication [6] Application and Development of Software Radio Technology [J]. work_fawdarttj5h2rku4pl5w34q76i Keywords: Browser war, Chrome, Market share, Software adoption, Benchmark, Feature selection. downloaded all the version of Chrome, Firefox, and Internet Explorer that were released over a period of five years, new approaches to testing and distribution of web browsers by releasing frequent beta versions to users in order to In the six years since its release Chrome has dethroned Internet Explorer, and Firefox''s market share has also were Chrome 1–12, Firefox 3–5, and Internet Explorer 8–9, i.e. all the browsers released up to May 2011. browsers versions used on the 64 bit system were Chrome 13–31, Firefox 6–26, and Internet Explorer 10–11. These results already show that Chrome tended to release new features ahead of the other browsers, with Firefox We tested the performance of the three dominant browsers, Chrome, Firefox, and Internet Explorer, and to a lesser We tested the technical performance of the three major browsers (Chrome, Firefox, and Internet Explorer) and work_fg4lfai5wrhatp2jhlns3wm4si Keywords: Battery welding condition checking, large current charge and discharge, microprocessor. inspecting a soldering point in a storage battery which can measure the inside resistance of the battery pad. are connected with soldered lead alloy straps, forming the anode and cathode elements shown in Figures 1 and 2. The purpose of this research is to develop a device for inspecting a soldering point in a storage battery, which can This soldering point testing machine''s signal processing procedures and mechanisms are shown as follows: When inspecting a storage battery, the test power signal (V1) is applied to the soldering points and the first and The testing machine can be installed in the auto-production line to inspect the soldering points of 12V-4AH battery. The resistance values of the soldering points are shown in Figure 13, which are 0.12, 0.07, 0.14, 0.08 and 0.13, work_fklnz2kdpjhwfjysurpx7koiti data (e.g., phrases like good but not excellent) to rank words by assigning them positions on a continuous scale. that extends the pairwise scores to a more complete joint ranking of words on a continuous scale, projection and cross-lingual MILPs. We evaluate our predicted intensity rankings using both pairwise classification accuracy and ranking correlation coefficients, achieving strong results, Table 2: Some examples from the Web-scale corpus of useful intensity-based phrases on adjective pairs. useful intensity-based phrase queries and their frequencies in the Web-scale corpus. of synonym differences to learn the extraction patterns, while we use only a raw Web-scale corpus. They collect lexicosemantic patterns via bootstrapping from seed adjective pairs to obtain pairwise intensities, albeit using the method for collecting the intensity scores for adjective pairs, using Web-scale n-grams (Brants and and the ranking patterns, we can compute the pairwise intensity scores using large-scale data in that work_fkn6grwf7be5hmmu5cqetl6dzm In our experiments on several different datasets and multiple types of context, the increased adaptation of the recurrent layer is always helpful, as measured by perplexity, the 6.3 Context-specificity of hotel class versus FactorCell rank and perplexity in generated reviews using the models learned on the TripAdvisor data. If statistical language models can be made to mimic this contextual adaptability, then they will be useful in a wider range of applications, including speech recognition, domains, contexts, and model and vocabulary sizes confirms that adapting the recurrent layer Chapter 6 deals with the use of language model adaptation for context-specific text adaptation method, model fine-tuning, does not require the use of a context embedding. For neural language model adaptation, context information is typically represented as an Low-rank RNN adaptation for context-aware language modeling. Low-rank RNN adaptation for context-aware language modeling. Low-rank RNN adaptation for context-aware language modeling. work_fljh2g733fa2fnxmkvwa4p3kby the topics per document into class-dependent deep learning models that extract (SDA) is then used to model the complex relationship among the topics per sentiment Keywords Topic modelling, Stacked denoising autoencoders, Text classification, Sentiment analysis Early work on sentiment analysis approached the problem from the traditional topic-based bag of words for text classification, topic modelling, and sentiment analysis tasks using a Topic modelling is used as a feature extraction method which provides a robust the sentiment of a given text, it is passed through the two topic models and the two SDAs to generate features used by two SDAs for the positive and negative sentiment. (7) between the input data (e.g. topic modelling features) and the reconstructed The topic modelling features of data from both polarities approach compared with the projected topic modelling features on a 2D space using (A) Word sentiment from positive and negative topic models for UMICH. work_fmhzphukuvglrmwo2uwkvy6oru Research of Network Closed-loop Control System Based Analysis delays how to influence closed-loop control system. Based on predictive control method of neural network, provides a new way of remote closed-loop control based on Keywords-Remote Control; Neural Network; Network Delay; parameters, increase the network delay value gradually network control Robust guaranteed cost state feedback under a random delay based on neural network theory. network delay closed-loop control system can be delay of the control network is time-varying and delay time to do the fixed step predictive control, neural network model of the controlled object to network model of the controlled object. Simulink Simulation of Network Closed-Loop Control System based on Predictive Neural Predictive Control Random Responses Curve based on Neural Network includes network delay controller design method, and network closed-loop control system, proposed by predictive control based on neural network to solve design of short delay network control systems[J]. work_fnpfl6ausndjxf26tx3wnlmpl4 et al., 2017), we propose a model that can encode a document while automatically inducing rich structural dependencies. we embed a differentiable non-projective parsing algorithm into a neural model and use attention mechanisms to incorporate the structural biases. Inspired by existing theories of discourse, representations of document structure have assumed several guises in the literature, such as trees in the style of Rhetorical Structure Theory (RST; Mann and Thompson, 1988), their model learns meaningful task-specific dependency structures, achieving competitive results in between tokens within a sentence, generating a context representation for each word with weak structural information. account while learning representations for both sentences and documents and an attention mechanism We then exploit the structure of T which we induce based on an attention mechanism detailed below to obtain more precise representations. a sentence-level bi-LSTM and applying the proposed structured attention mechanism, we obtain the presents three variants4 of our model, one with structured attention on the sentence level, another one work_fo2sjxybtvhovo3ljrsijpt4pi information diffusion, to understand: (i) whether positive conversations spread Keywords Computational social science, Social networks, Social media, Sentiment analysis, How to cite this article Ferrara and Yang (2015), Quantifying the effect of sentiment on information diffusion in social media. which sentiment drives information diffusion in online social media. Sentiment analysis was proven an effective tool to analyze social media streams, especially Figure 2 shows the effect of content sentiment on the information diffusion, as function of tweets polarity scores: Fig. 2A shows the average number of Figure 5 Evolution of positive and negative sentiment for different types of Twitter conversations. social media content plays with respect to the diffusion of such information. highlighted once again how central social media are in the timely diffusion of information, Quantifying the effect of sentiment on information diffusion in social media Quantifying the effect of sentiment on information diffusion in social media work_fpqzfbmakbhbnhu3lmp3xicgzi I discuss building blocks for creating marker-based AR applications that run as web Building blocks for commodity augmented reality-based molecular visualization and modeling in matured enough to enable web pages for AR-based molecular visualization and modeling IMMERSIVE MOLECULAR MODELING IN WEB BROWSERS handling data in neural networks, directly inside the molecular modeling web app to the web app in Fig. 2H allows visualization and manipulation of any molecule loaded in The web app shown in Fig. 4A allows exploration of the interaction space of two marker-based AR applications for molecular modeling in web browsers using regular Concurrent interactive visualization and handling of molecular structures is interactive exploration of 3D visualizations in immersive tangible augmented reality? https://github.com/labriata/prototype-web-apps-for-AR-molecular-modeling/ https://github.com/labriata/prototype-web-apps-for-AR-molecular-modeling/ Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers Part 1: overview of building blocks for immersive molecular modeling in web browsers work_fq3wovbfzjhkzhqcl3u7tfguii algorithm, which defines two kinds of vehicle detection errors Keywords-Vehicle Detection; Background Difference detection: optical flow method[1], frame difference Frame difference method detects moving objects vibe is proposed, and a moving target detection method The vibe background modeling algorithm was vibe algorithm, an adaptive background model of vibe image is input, the background model of the pixels in ADAPTIVE VIBE BACKGROUND MODEL In the vibe background model, threshold R error: the detection background area is mistakenly background modeling algorithm, which uses the vibe the traditional vibe background modeling algorithm for 3) Background modeling of three frame difference 3) Background modeling of three frame difference method and background modeling of vibe algorithm method and background modeling of vibe algorithm Improved ViBe algorithm of three frame difference method. frame difference algorithm based on vibe background difference method and adaptive vibe algorithm are background model for vehicle detection," 2017 IEEE 2nd Advanced work_fsexunhxlrhe3giv4462rvneza new approach for approximate structured inference for transition-based parsing that produces scores suitable for global scoring using local models. beam search has made transition-based parsing competitive in accuracy (Zhang and Clark, 2008; Huang how effective locally-trained neural network models are at predicting parser actions, while providing parsing approaches employed locally-trained multiclass models to choose a parser action based on the these models, classification is based on a set of features extracted from the current state of the parser, From state 2, the standard way of training local classifiers would be simply to associate features from state 2 to a shift action, of our transition-based parsers are the local classifiers that predict the next action given features derived from the current state. In contrast, Chen and Manning (2014) use 48 feature templates, including higher-order dependency information than has been shown to improve parsing accuracy significantly (Zhang and Nivre, 2011). work_fsfq3r3yrvhibdvquhm7vraa3i extraction of contour feature points is the key of Harris corner is used to extract the key feature points of Harris corner detection algorithm is a common contour feature points defined by us. Figure 1, this paper improves Harris corner detection derivatives of the point in the image respectively. as shown in Fig. 3 (a), and detected the points that Extraction of palmprint contour feature points Extraction of palmprint contour feature points Palmprint contour feature points Palmprint contour feature points palmprint image is to extract appropriate reference points from Palmprint and establish reference Palmprint location and feature space extraction After extracting the corner points, we set up the point, as shown in Fig.6 (a).The palmprint image is extracted and normalized as the Palmprint Feature made on the extraction of contour feature points in made on the extraction of contour feature points in palmprint images, and the Harris corner detection work_ftlenr77n5hvrfzc6qhzavunfe end-users want and what existing EUP systems support, and thus open the door for a analysis of challenges that end-users experience on the Web with solutions; (2) seven How to cite this article Lee and Bederson (2016), Give the people what they want: studying end-user needs for enhancing the web. end-user programming on the Web (WebEUP). end-user programming on the Web; (2) Proposing features of future EUP systems for that enable end-users to express their needs via demonstrations and examples of what the second study, we examine how users naturally express programming tasks, and explore STUDY 1: END-USER NEEDS ON THE WEB To better understand end-user needs on the Web, we conducted a semi-structured interview at least one programming language, and five participants had created web pages. For example, mashup tools enable users to integrate information from multiple pages end-users to express ideas more freely, future work needs to ask participants to both work_ftmr4sfzuveahklyxgbwfeyeh4 Keywords Virology, Data analysis, Genome annotation, Next-generation sequencing, Integration Reads containing viral integration sites are identified and sequenced in the WebLab and mapped to a reference genome. Together with genomic annotations from public database the analysis in Enhort is conducted to generated analysis of the given integration sites. be achieved in Enhort by setting the appropriate genome annotation as a covariate. MLV integration sites are compared to two different control sets: A random and an altered The upper diagram contains integration frequencies of MLV compared to random sites for a selection of annotations. MLV integration is no longer enriched but depleted in CpG islands when compared to the adapted background model. (A) Log fold changes of PB integration sites in relation to several annotations against a random and an adapted background model. We have shown that Enhort is capable of reproducing integration site analysis with less work_fy4lcnl2qrai3izcaywzso72bi Data Visualization Analysis of COVID-19 Epidemic matter, daily new confirmed cases started not distribution of number of confirmed cases by country? let''s see the confirmed cases for the top 30 countries, as Now let''s see mortality rate by country, as shown in mortality rate countries, as shown in Figure 7. The countries whose mortality rate is low are shown Let''s see number of confirmed cases on map. C. Daily NEW Confirmed Cases Trend Let''s see the DAILY new cases trend as shown in DAILY NEW Confirmed cases worldwide figure, the number of new cases are not so Countries with Confirmed Cases is shown as Figure 16 European Countries with Confirmed Cases, as of 2020-05-06 Confirmed cases by country in Europe, as of 2020-05-06 DAILY NEW Confirmed cases by country in Europe Confirmed cases by country in Asia, as of 2020-05-06 Unlike China or Korea, daily new confirmed cases work_fycwsprctvej7fdxxin7bffb7a and selective dependency relation based features are extracted. Keywords Feature extraction, Aspect based sentiment analysis, Machine learning, Natural language proposed a dependency rule-based methodology to resolve the issue of aspect extraction (2019) worked on ruled based methods for extracting product features. (2017a) presented a two-fold rule-based approach to extract aspects. Firmanto & Sarno (2019) proposed an aspect-based sentiment analysis method utilizing The rule-based features are extracted using dependency relations the performance of aspect category extraction is improved if rule-based features are aspect category and then applying the proposed method, features are extracted from Step 2: Extract lemma and rule based features from individual test sentence Review-aggregated aspect-based sentiment analysis with ontology features. A supervised scheme for aspect extraction in sentiment analysis using the hybrid feature set of word dependency relations and lemmas ... A supervised scheme for aspect extraction in sentiment analysis using the hybrid feature set of word dependency relations and lemmas ... work_fyoz3tp6bnhfbhpmqnis5i46c4 Application Research of Crawler and Data Analysis Based explores how to develop a crawler method based on the specific efficiently crawl the data of specific targets, analyze the dynamic pages, and complete the data cleaning, downloading, crawler method and data analysis method through practical basic data of each manufacturer''s preference for game This project will use the scrapy framework based on Python language to crawl steam website. crawler save the last crawled data in the form of CSV Executing the start request method selenium pop-up browser to crawl the dynamic page crawled data in the form of operation tables. The crawled data is presented in the form of Crawled data list paper explores the process of data crawling and basic data analysis of dynamic pages by combining the "Implementation of Crawler Based on Python Scrapy Data information crawler technology based on based data analysis and visualization platform [J]. work_fzksxbt7cfbrlliqou7wypqebm Application of K-means Algorithm in Geological Disaster Monitoring System K-means algorithm is that the k data objects are randomly selected from the sample set X as the initial clustering center, K-means algorithm initial center sensitivity and K value improved K-means algorithm for text clustering, which is A. The selection of data object in Cluster analysis algorithm can be used as the initial clustering center optimized initial clustering centers to the k-means algorithm the initial clustering centers selected by the algorithm are far initial clustering number of the data set distribution. means algorithm is used to cluster on the whole data set and clustering result of the traditional k-means algorithm is an data and random selection of initial clustering center, and Initialization Center Algorithm for K-Means Clustering[C]. [7] Application of Improved K-Means Clustering Algorithm in Transit [13] Efficient Data Clustering Algorithms: Improvements over Kmeans[J]. Efficient data clustering algorithm work_g4a2btckubh4rf5s7hbkwbzvpu and replicable software tests are frequently not available and that many packages Keywords Unit testing, Profiling, Optimization, Software engineering, R language, of the current state of R packages, general advice on software testing and optimization involves software is not as easy to access and evaluate for use of testing code as To analyze use of software testing techniques, we evaluated all CRAN packages on two Some packages use a testing framework, but do not list it as a dependency; for example, the software optimization tools and techniques, we evaluated all CRAN packages on history of commits, unit tests that time functionality, and package bug reports. frameworks available for assisting developers with the process of testing software. Available at https://CRAN.R-project.org/package=future.apply. Available at https://CRAN.R-project.org/package=doMC. Available at https://CRAN.R-project.org/package=doSNOW. Available at https://CRAN.R-project.org/package=doParallel. Available at https://CRAN.R-project.org/package=foreach. Available at https://cran.r-project.org/package=pccc. Available at https://CRAN.R-project.org/package=xlsx. Available at https://CRAN.R-project.org/package=parallelDist. Available at https://CRAN.R-project.org/package=tictoc. https://cran.r-project.org/package=pccc https://CRAN.R-project.org/package=unitizer https://CRAN.R-project.org/package=unitizer Available at https://cran.r-project.org/package=benchr. Available at https://CRAN.R-project.org/package=rbenchmark. Available at https://CRAN.R-project.org/package=sparklyr. Available at https://CRAN.R-project.org/package=feather. work_g5e4e5fjf5g2ve5fuetfkkz5wq The Design of QoS Guarantee Strategy Framework for Networked Control System for networked control, puts forward the multi-level QoS access algorithm components; On a class of networked control oriented QoS based semantic model of real-time system, service QoS management framework, finally through the for network-oriented control; Section 3 introduces QoS QoS semantic component application configuration diagram QoS framework core components, not only for the resource communication network and QoS strategies for resource the resource service according to the corresponding QoS component instance; (2) according to the service QoS need to choose for component instance QOS model satisfy component function configuration diagram CG and QOS of component specifications constructing service QOS diagram QoS simulation environment network structure QoS parameters, etc., makes the service components have the of QoS attribute of service component, the establishment and resource layer and network layer QoS strategy, finally designs the dynamic service components based on resource work_g5eo6uu34jandfw6go6vd7ezse Research on Method of Rapid Software Development Based on Component Design your system with custom components in Delphi. adopting the rapid software development method based on Keywords-Delphi; Custom Components; ERP; Efficiency; developed a way to customize the components to complete In a system development, design a custom component. function, the use of custom components to complete the custom components into different needs of the interface That by designing custom components: Add DElphi component is an object library, but also a class. TComponent, the base class for all Delphi components, A. The Basis for Custom Component Development In the development of custom components we need to C. Implementation of custom component development of custom components in Delphi contains the following steps:  Using the custom component technology, the  The use of custom components in the information development of custom components greatly reduce  This method of custom components in the work_gcjn4upkcbdybjfasoc2wb67b4 Motion Image Matching Based on UAV paper, the common algorithms of image fast matching are algorithm based on feature matching is proposed to obtain the obtained through the actual surface area image measurement technology, using the measurement type camera CCD image Image distortion correction -indirect method. method to realize image correction [3], As shown in figure 1. UAV IMAGE MATCHING In most cases, the UAV image mapping method adopts the image matching technology, which recognizes the algorithm adopts the matching based on local feature values result is used as control to match other feature points [7]. B. Image feature point extraction Using C++ to achieve SIFT image feature point extraction, The matching method is two dimensional feature point Brute method to eliminate error matching, SIFT was tested the matching test image is shown in figure 3. image feature points. two-dimensional feature point matching method, was work_gcwpgxioqfbr7bhenvqbhu2phy Existing work on domain adaptation for statistical machine translation has consistently assumed access to a small sample from the test Mismatch in phrase translation distributions between test data (target domain) and train data is estimated on out-of-domain training data to a target translation rule with source and target phrases having two similar distributions over the latent subdomains is likely safer to use. , K} encoding (arbitrary) K latent subdomains that generate each source and target phrase ẽ Table 3: Adaptation results when tuning on the in-domain development set. Table 4: Adaptation results when tuning on the mixed-domain development set. • Favouring the source-target coherence across subdomains (i.e., adding the feature D(ẽ, f̃)) provides a significant translation improvement of This paper aims at adapting machine translation systems to all domains at once by favoring phrases that Latent domain phrase-based models for adaptation. models for translation domain adaptation. domain adaptation for statistical machine translation. work_gcygeykq7ffsnenhntlew223ma we study an existing clustering/partitioning strategy to speed up the parallel execution Keywords Task-based, Graph, DAG, Clustering, Partitioning paper, is to investigate how to cluster the nodes of task graphs to increase the granularity of between the cluster of nodes should ensure to be executable as a graph of tasks, and keep explain why most existing algorithms do not solve the DAG of tasks clustering problem. time of the resulting graph in parallel considering a given number of threads and runtime The granularity problem of the DAG of tasks with a focus on the parallel execution has hardware without overhead, any clustering of tasks will reduce the degree of parallelism a cluster, the algorithm first picks one of the ready tasks, based on a heuristic that we in a cluster, the algorithm releases its dependencies and potentially adds new ready tasks Table 2 Speedup obtained by clustering the graphs on emulated executions for GDCA and GDCAv2. work_gdvuyjkrdbdftihkio6n2lmzhi https://www.research.ed.ac.uk/portal/en/publications/minimallysupervised-morphological-segmentation-using-adaptor-grammars(e5fc4878-09a7-4307-9b93-8934e8059e8b).html a small labelled data set to select which potential morph boundaries identified by the metagrammar should be returned in the final output. unsupervised training, while the model selection method yields the best average results over use the gold-segmented data to learn, for each language, which of the proposed splits from the original train semi-supervised AGs (using the data to accumulate rule statistics rather than for grammar selection). 1) scaling AGs to large data sets by using the posterior grammar to define an inductive model; 2) demonstrating how to train semi-supervised AG models, and Experiments with AGs for unsupervised word segmentation suggest that adding further latent structure The MC data sets contain gold standard morphological analyses (as well as segmentations) so we Figure 2: Effect of training data size on dev set SBF1 for AG Select (left) and semi-supervised SubMorphs grammar Unlike other morphological segmentation models, this method can adapt its grammar to languages work_gk6uak5jyfctxoj4richmjmlqm A Bayesian Model of Grounded Color Semantics We apply the approach to a large data set of color descriptions, where statistical evaluation documents which supports future efforts in grounded language understanding and generation by probabilistically mapping 829 English color descriptions to potentially context-sensitive regions in HSV color space. descriptions of colors in situated dialogue need models of meaning that capture this variability. to infer a corpus-based model of meaning that accounts for possible differences in word usage across allows for variability in meaning by positing uncertainty in classification boundaries that can get resolved when a speaker chooses to use a word on a model introduces a new layer of uncertainty that describes what category the speaker uses. A more general measure of model fit is the log likelihood of the color values and their labels jointly Using Vague Color Terms: A Model Using Vague Color Terms: A Model work_gocqmq4fknd2fjg2ixbgjj53nu data always overflow the working storage and sorting process is needed. Yaakobi & Bruck (2016) proposed an algorithm that sorts big data based on limited Let n be the total streaming numbers to be sorted and M ≪ n be the limited size of working constraint of the working storage in streaming data sort. Table 3 Sorting execution time of the proposed algorithm with respect to size of working storage. Since streaming data sort algorithm uses only one working storage of fixed Figure 7 Comparison of storage size change as the results of sorting a set of streaming data by the representing them in compact groups as implemented in streaming data sort algorithm. Correct and stable sorting for overflow streaming data with a limited storage size and a uniprocessor Correct and stable sorting for overflow streaming data with a limited storage size and a uniprocessor work_gti6s2kynvfxho6svyezzm33bm compared on four common centrality measures (degree, betweenness, closeness, and eigenvector) under a variety of network topographies. Figure 1: Scatterplot matrix comparing closeness centrality output for a large, two-mode network. Figure 2: Scatterplot matrix comparing output for closeness centrality in a small, one-mode network. sna package for R does not produce measures between disconnected components, resulting in correlation values listed as "NA". measurement of degree centrality was consistent among all programs in networks Figure 4: Scatterplot matrix comparing degree centrality output for a small, one-mode network containing loops. In networks with no loops or disconnected components, eigenvector centrality measures were inconsistent between Figure 6: Scatterplot matrix of eigenvector centrality output for a small, one-mode network with loops. from other programs in measuring betweenness in the small two-mode network of the differences between UCINET''s twomode measures and other programs'' approaches to two-mode networks, see Figure 3. work_gwruarfbz5a3lcgd3lqomenupi Research on Control Strategy of Matrix Converter Motor The effects of voltage vector and direct torque control are and researched the control strategy of matrix converter motor system combined with matrix converter control requirements of matrix converter voltage transfer ratio caused by the switch frequency, matrix converter motor Matrix converter control strategy has switch A. Matrix Converter Space Vector and Motor VVVF output voltage, matrix converter space vector current to control matrix converter by using hysteresis waveform of vector Control of Matrix Converter Motor control convert into the stator reference voltage, using converter output voltage space vector. converter motor direct torque control system generally control by using the matrix converter motor system of Simulated research to the matrix converter motor direct the matrix converter motor system control strategy the matrix converter motor system control strategy the matrix converter motor system control strategy combined matrix converter control method and motor work_gxjya3n3c5hhfc6rz2sbb333eq curating humanities nanopublications in the PeriodO period gazetteer. Keywords Nanopublication, Periodization, Scholarly communication, Time, Linked data, How to cite this article Golden and Shaw (2016), Nanopublication beyond the sciences: the PeriodO period gazetteer. definitions of time periods made by archaeologists and other historical scholars (http: Several European repositories of bioinformatic data have begun to publish their contents as nanopublications, including the Biosemantics Group (http://www.biosemantics. mapped these time periods to a consistent data model and published them as linked open PeriodO defines a "period definition" as a scholarly assertion about the name and The complete PeriodO representation in Turtle of Belarte''s collection of period definitions The relationships between a period definition and the start and end of its temporal extent are respectively mapped to the OWL-Time intervalStartedBy and as Linked Data requires a way to assign URLs to period collections and definitions. • Provenance of nanopublication: the history of the period definition within the work_h35ppmoemvbgdnrofwufellqvq We studied 22 opensource software projects developed using the Agile board of the JIRA repository. time required to fix issues and, in the majority of the analysed projects, it had a positive Keywords Social and human aspects, Politeness, Mining software repositories, Issue fixing time, To detect differences among the fixing time of polite, impolite and mixed issues, we used percentage of polite comments per month grouping issues per project. For studying the seasonality of the percentage of polite comments time series, we Groovy, JBoss) have a percentage of polite comments time series which presents seasonality, have affected validity of the results for RQ1 about lower issue fixing time for polite and politeness and attractiveness on 22 open-source software projects developed using the The more polite developers were, the less time it took to fix an issue. The more polite developers were, the less time it took to fix an issue. work_h3apwa2ag5bdjj7shw5i5z5iou Detection of Blink State Based on Fatigued Driving technology call Dlib open source library to detect 68 feature Kmeans clustering algorithm to collect the ratio The analysis quickly detect the fatigue characteristics of the human eye, has Keywords-Blinking Algorithm; Fatigue Detection; Digital Image Processing; Clustering Algorithm; Key Points Of Human blinking eyes, the degree of mouth opening, and the Dlib open source library to detect human eye features. A. Blink detection and threshold analysis methods formula and blink threshold analysis method. threshold analysis method uses the Kmeans clustering sample.This article uses the blink data set provided by The text person has 5 blink-eye aspect ratio data Public data set 3 times blinking eye aspect ratio effectively detect the fatigue state of blink, which is the fatigue detection algorithm in this paper needs to be method of fatigue driving based on face feature point analysis[J]. Multi-feature fusion fatigue detection method based on improved work_h3zthufefjdy5fufaftvouocdu prediction of products depends on the latent features of users in a rating matrix. of CF recommender systems by combining the latent factors, short-term preferences, Compared to other temporal approaches (e.g., the short-term based 2017a) addresses the drift issue not solved by previous short-term based approaches. • An LTO approach that learns the drift in the users'' interests through an improved prediction accuracy in the CF technique by learning accurate latent effects of the temporal It utilizes to find similar users or items and calculate predicted rating scores according The long temporal-based factorization approach (Al-Hadi et al., 2018b) learns The LTO approach addresses both long and short temporal preferences by using temporal-based factorization) are used to predict missing rating scores in the rating matrix temporal vectors in improving the prediction accuracy of the CF using the LTO approach. of the long temporal-based factorization approach (Al-Hadi et al., 2018b) is to solve the work_h4aasljqkvdjhgcpyi6kvxbpsy approach named CogNet that is an integrative gene selection tool that exploits CogNet provides a list of significant KEGG pathways that can classify the data with a Keywords Classification, Gene expression, Enrichment analysis, KEGG pathway, Rank, CogNet: classification of gene expression data based on ranked activesubnetwork-oriented KEGG pathway enrichment analysis. integrate the biological knowledge about the data in the process of gene selection and a list of significant genes and then performing pathway enrichment analysis of these active The most recent tool that integrates biological knowledge for grouping the genes was We have considered 13 gene expression data sets to test CogNet and for comparison with selection in gene expression data analysis. and feature selection from gene expression data. CogNet: classification of gene expression data based on ranked active-subnetwork-oriented KEGG pathway enrichment analysis CogNet: classification of gene expression data based on ranked active-subnetwork-oriented KEGG pathway enrichment analysis work_h7bzshd4nffpbkpjsz4lxtgzea networks and relational infrastructures are useful to research a process Social processes, Cooperation dilemmas, Multilevel networks, Multilevel relational infrastructures, Coopetitive learning, Institutional Figure 1: Superposed levels of collective agency: inter-individual network, inter-organizational This "long" term resilience of personal copublication ties, combined with strategies of investment in social discipline and relational infra structures, for navigating social processes on multilevel, socioorganizational networks. In the navigation of social processes, multilevel relational infrastructures can create collegial Embarked on social processes in dynamic and multilevel networks Embarked on social processes in dynamic and multilevel networks Embarked on social processes in dynamic and multilevel networks Embarked on social processes in dynamic and multilevel networks Embarked on social processes in dynamic and multilevel networks Embarked on social processes in dynamic and multilevel networks Embarked on social processes in dynamic and multilevel networks Embarked on social processes in dynamic and multilevel networks Social selection models for multilevel networks. work_ha75pkb77fcyza2iudmhhibak4 Learning Strictly Local Subsequential Functions called Input and Output Strictly Local (ISL ISL and OSL functions model mappings from underlying forms to surface forms, which are also the bedrock of constraintbased frameworks like Optimality Theory (Prince be modeled with ISL (and OSL) functions, we provide the strongest computational characterization of functions can model local phonological processes, Definition 2 (Input Strictly Local Function). A function f is Input Strictly Local (ISL) if there is a k Definition 3 (Output Strictly Local Function). function f is Output Strictly Local (OSL) if there is a function f is Output Strictly Local (OSL) if there is a 1998; Bennett, 2013; Payne, 2013), unbounded displacement/metathesis (Chandlee et al., 2012; Chandlee and Heinz, 2012), non-local partial reduplication (Riggle, 2003), and some tonal patterns (Jardine, 2013) cannot be modeled with ISL or OSL 5 Learning Input Strictly Local Functions Once the learner has constructed this onward representation of the data, it begins to merge states, work_hb5h33a6xnd2ngkrgel4i6p7i4 We merged the Apriori algorithm, Harmony Search, and classificationbased association rules (CBA) algorithm in order to build a rule-based classifier. are a number of famous association rule mining algorithms that are accessible to researchers classifier by utilizing association rule mining is one of the attractive domain for data and association rule mining algorithm based on their classification performance and In this paper, we present an association rule-based classification method to obtain Apriori is a standard and well-known basic algorithm in association rule mining that is used Apriori is the most beneficial association rule mining algorithm. The Classification Based on Association rules (CBA) algorithm is one of the first Time complexity of the Apriori algorithm and association rule mining is a critical result with traditional association rule classification algorithms. proposed method with the CPAR, CBA and C4.5 algorithms that are famous in rule-based shows the accuracy of applying four rule-based classification algorithm on a dataset. work_hc4up7ghr5dpre425mbxpgzlk4 using computational semantic models to decode brain activity patterns associated with Having both imageand text-based models of semantic representation, and neural activity patterns unclear whether either textor image-based semantic models can decode neural activity patterns associated with abstract words. text-based computational semantic models to decode an fMRI data set spanning a diverse set of analysis we split the fMRI data set into the most concrete and most abstract words based on behavioural The image-based model is built using a deep convolutional neural network approach, similar in nature to those recently used to study neural representations of visual stimuli (see Kriegeskorte (2015), although note this is the first application to study word we were able to compare how well English and Italian text-based semantic models can decode neural 2010; Darwish, 2013) we combined Italian and English text-based models in our decoding analyses in decode the more abstract nouns'' neural activity patterns with higher accuracy than the image-based work_hea3gijzhnc2rl4sxgyj6pvghm For example, content-based recommendation systems standardly represent user interest using frequent words from articles in a user''s history readable, well-written and topically interesting articles, giving an accuracy of 84% (Section 5). We collect a larger set of visual words from a corpus of tagged images from the ESP game (von Ahn We compute the precision of each topic as the proportion of these 200 words that match the MRC list Topic-based features: We also compute what proportion of the words we identify as visual matches We also compute a greedy cover set of topics for the visual words in the article. These features capture the mix of visual words from different topics. GOOD articles contain more visual words overall as a feature (SURP) and also this value normalized by total number of word tokens in the article We normalize each feature by the total words in the article. work_hebrzn33h5bmnl4jpzofb5owoe We develop parsing oracles for two transition-based dependency parsers, including the parser configurations to optimal transitions with respect to a gold tree. Goldberg and Nivre (2013) develop dynamic oracles for several transition-based parsers. if it has the form ([0], [],A), and in a final configuration arc set A always defines a dependency tree In the second step of the algorithm we use dynamic programming techniques to simulate all computations of the arc-standard parser starting in a configuration with stack σL and with a buffer consisting space defined by these computations includes the dependency trees for w that are reachable from the input configuration c and that have minimum loss. Algorithm 1 Computation of the loss function for the arc-standard parser T [i,j](h) stores the minimum loss among dependency trees rooted at h that can be obtained by running the parser on the first i elements of stack σL and work_hesivpqavbgo7bnwu55o7xw4hu used to develop a statistical model for predicting formality, which is evaluated under different feature settings and genres. A speaker''s level of formality can reveal information about their familiarity with a person, opinions of a topic, and goals Our results provide new evidence in support of theories of linguistic coordination, underlining the importance of formality (2011) provided a preliminary investigation of annotating formality on an ordinal scale and released a dataset of sentence-level Figure 1: Distribution of sentence-level formality scores by genre. Table 1: Examples of formal (positive) and informal (negative) sentences in different genres. of sentence-level formality annotations, which Figure 1 shows the distribution of mean formality scores for the sentences in each of our genres. The remaining features (e.g. length, POS tags, case, punctuation, formal/informal lexicons, and subjectivity/emotiveness) largely subsume the features a formality score to each post in our data using the Answers model in Section 4. Generation of formal and informal sentences. work_hfzgvsxijbervexbqhpcikatiq compatibility and reliable transmission between IPV9 network IPv9 protocol as one of the future network concepts, device router.IPV9 network management system is a It includes IPV9 future network root management of the decimal network root name server, The ping implementation of the decimal network IPV9 address of future network, the new address, domain name 1) IPv9 network management system A. Application 1—Pure IPV9 Network Architecture This application implements a pure IPV9 network IPv4 public network address between routers C and D transparent access between different IPv9 networks. The application implements the IPV9 network to The application implements the IPV9 network to The application implements the IPV9 network to The application implements the IPV9 network to access routers to establish network; (5) IPV9 core protocol to access Beijing node IPV9 network. network islands are connected using the IPV9 protocol IPV9 address text representation of decimal network address of the IPV9 domain name. work_hhljuimcpfdjrp7qy2oosk7bry SPRITE: Generalizing Topic Models with Structured Priors 2 Topic Modeling with Structured Priors are real-valued vectors of length equal to the vocabulary size V (for priors over word distributions) or length equal to the number of topics K By modeling the priors as combinations of components that are shared across all topics, we can learn interesting connections between SPRITE: Structured PRIor Topic modEls. To illustrate the role that components can play, Figure 2: Example graph structures describing possible relations between components (middle row) and topics or documents Edges correspond to non-zero values for α or β (the component coefficients defining priors over the document Table 1: Topic models with Dirichlet priors that are generalized by SPRITE. Each supertopic is associated with a Dirichlet prior over subtopic distributions, where subtopics are the low level topics that are associated with word parameters φ. work_hkzle3wyofchtcheq2mcsv3yiu small-scale nature of the deforestation signature left by uncontacted populations clearing villages and gardens has similarities to those made by contacted indigenous villages. A random forest algorithm with an optimally-tuned detection cutoff has a leaveone-out cross-validated sensitivity and specificity of over 98%. Keywords Random forest, Satellite imagery, South America, Indigenous societies remnant indigenous societies generally referred to as uncontacted or isolated populations Machine learning with remote sensing data to locate uncontacted indigenous villages in Amazonia. project along with high-resolution imagery for uncontacted villages is available at Map of 500 contacted indigenous villages in Brazil and 25 uncontacted uncontacted villages have (1) smaller cleared areas, (2) longer distances from lights, (3) top four distinguishing features in terms of variable importance in the random forest model are uncontacted villages have (A) smaller cleared areas, (B) farther distances to satellite-detected lights at night, (C) Random forest classifier for remote sensing classification. work_hmfm2qy66veqtbcqmo7nvj6ttu A Latent Variable Model Approach to PMI-based Word Embeddings Experimental support is provided for the generative model assumptions, the most important of which is that latent word vectors are found to be closely approximated by a low rank matrix: there exist word vectors in say 300 dimensions, analogies like "man:woman::king:??," queen happens to be the word whose vector vqueen is the most that the set of all word vectors (which are latent variables of the generative model) are spatially isotropic, out the hidden random variables and compute a simple closed form expression that approximately connects the model parameters to the observable joint vectors need to have varying lengths, to fit the empirical finding that word probabilities satisfy a power If the word vectors satisfy the Bayesian prior described in the model details, then Our model assumed the set of all word vectors theoretical explanation of RELATIONS=LINES assumes that the matrix of word vectors behaves like work_hn3zcuyx55c5hluvhowvnqdplm approach that learns a joint model of meaning and context for interpreting and executing Correct interpretation requires us to solve many subproblems, such as resolving all referring expressions to specific objects in the environment (including, "the corner" or "the third intersection"), disambiguating word sense based on context (e.g., "the To model complex instructional language, we introduce a new semantic modeling approach that can represent a number of key linguistic a start state s ∈ S and a natural language instruction x, we aim to generate a sequence of actions CCG parse builds a logical form for a complete sentence in our example navigation domain. state s, validation function V, lexicon λ and model parameters θ, and returns a set of lexical entries, as defined in Section 8. semantic parser that includes a joint model of meaning and context for executing natural language instructions. work_hn7ddwy34rcplg53wrpdqgqroy The Boston Special Youth Project (SYP) Affiliation dataset is a large, bipartite network representing interactions among 166 gang members from seven gangs for nearly three years. where an adult (typically a graduate student from one of the surrounding universities) was assigned to an area (local parks, housing projects) to establish and maintain contact with and attempt to change the behaviors of the gangs. ("contact cards") documenting the activities of study gang members. network data collected on the contact cards were never analyzed by SYP staff. These researchers electronically scanned and digitized the contact cards, and began the process of creating a network from From these cards, a bipartite network was created where 166 individuals (i.e. gang members) were connected to 33,653 events (i.e. contact cards). persons with names of known gang members from the roster of study participants. created where individuals (i.e. gang members) were connected to events (i.e. contact roster of gang members appear in the contact cards. work_ho2ac3l4ivbnbkr2yq3m3ik4re This study proposes CluSMOTE, which is a combination of a clusterbased undersampling method and Synthetic Minority Oversampling Technique. than other methods in the general protein antigen, though comparable with SEPPA 3 Keywords Cluster-based undersampling, SMOTE, Class imbalance, Hybrid sampling, Hierarchical DBSCAN, Vaccine design methods, including the structure and sequence-based approaches. discarded the negative class data that overlap the positive in a specific cluster based on the In this research, the cluster-based undersampling method is combined with SMOTE to Conformational B-cell epitope prediction method The number of clusters is less than the positive class data. A dataset used for conformational epitope prediction contains the class imbalance problem. An epitope is a small part of the exposed antigen that creates class imbalance problems in the prediction of learning-based conformational epitopes. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. A new performance measure for class imbalance learning. work_hqes4liwkjbipfnjiwg72ck2oe and protocols, Reproducibility, Semantic web, Research Object, FAIR data principles FAIR version of the PREDICT workflow, (c) new competency questions for previously on the coverage of manual steps, different workflow abstraction levels, and versioning on approach allows us to separate the workflow steps, enabling the reuse of instructions protocols to concrete and executable workflow steps, and the links between these levels. prov:generated to link a workflow activity (p-plan:Activity) to an output artefacts Figure 2 OpenPREDICT Workflow (version 0.1) with manual and computational steps. The workflow consists of four steps: data preparation, feature https://raw.githubusercontent.com/fair-workflows/openpredict/master/data/external/meshAnnotationsFromBioPorttalUsingOMIMDesc.txt https://raw.githubusercontent.com/fair-workflows/openpredict/master/data/external/meshAnnotationsFromBioPorttalUsingOMIMDesc.txt https://raw.githubusercontent.com/fair-workflows/openpredict/master/data/external/meshAnnotationsFromBioPorttalUsingOMIMDesc.txt using HCLS (https://www.w3.org/TR/hcls-dataset/) and FAIR data point specification SIO and PROV to model input data and workflows (I1). first version of OpenPREDICT workflow (opredict:Plan_Main_Protocol_v01). OpenPREDICT''s computational steps use datasets, as explained in ''FAIRified data Data and code are available at GitHub: https://github.com/fair-workflows/openpredict. A generic workflow for the data fairification process. work_hqsugbbgx5hlpnrplb7kpus5ai sys_1000 wp-p1m-38.ebi.ac.uk wp-p1m-38.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265368483 (wp-p1m-38.ebi.ac.uk) Time: 2021/04/06 17:58:18 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_hrkwn4taczellcyg24hufs5xk4 In this paper, we describe a joint model of coreference, entity linking, and semantic typing (named entity recognition) using a structured conditional random field. Variables in the model capture decisions about antecedence, semantic type, and entity semantic types and entity links across coreference The ai model coreference antecedents, the ti model semantic types, the ei model entity links, and the qi are latent Wikipedia queries. State-of-the-art approaches to coreference (Durrett and Klein, 2013) and entity linking Our NER model places a distribution over possible semantic types for each mention, which corresponds to a fixed span of the input text. Joint NER and entity linking factors (Section 3.2.1) tie semantic information from Wikipedia articles to semantic type predictions. Joint coreference and entity linking factors (Section 3.2.3) encourage relatedness between evaluate on gold mentions in this setting for comparability with prior work on entity linking; we lift Joint Coreference Resolution and Named-Entity Linking with Multi-Pass work_hs2hyu7fgngxhkf2o4s6gyqxxi Strategic and Genetic Networking: Relational Endowment in a Local Cultural Offer The local theatrical offer is the result of all the theatre companies which perform shows in the research adopts the network perspective to test hypotheses on companies'' relational behaviors and mechanisms of network formation in a local context in Italy. based on audience levels; companies tend to reciprocate hospitality relations and form clusters Keywords: cultural production; theatre; social network analysis; ERGM; arts In this study we observe the structural properties of the theatre offer in a local context in Italy, and we propose hypotheses about network formation mechanisms. the relational dimension of cultural production, which has been defined and empirically shown in different ways. the point at which research has arrived today in this field, we cannot count on a coherent and well defined perspective on relations and cultural production. Figure 1: Network of hospitality relations among professional theatre companies in Piedmont, 2011 work_hscp7elrtfakfkfv4zzrbyj23q from acoustic signals and then use information from the emotion recognition network Keywords Behavior quantification, Emotion, Affective computing, Neural networks, Couples behavior recognition from emotion-informed embeddings'') and study how this affects the speech capture, emotion recognition and behavior understanding as shown in Fig. 1 (Soken 2. Context-dependent behavior from emotion-informed embeddings: Instead of 3. Reduced context-dependent behavior from emotion-informed embeddings: Similar Context-dependent behavior recognition from emotion labels Context-dependent behavior recognition from emotion-embeddings Context-dependent behavior recognition from emotion-embeddings Reduced context-dependent behavior recognition from emotion-informed Binarized Emotion-Vector Behavior Primitives are generated by applying the SingleEmotion Classification Network (EC) systems on the couple therapy data: For each session, Table 3 Behavior binary classification accuracy in percentage for context-dependent behavior recognition model from emotion labels. Table 4 Behavior binary classification accuracy in percentage for context-dependent behavior recognition model from emotion-embeddings. 2. Can emotion-informed embeddings be employed in the prediction of behaviors? work_hwbci5wyvrc4vj6v6fg4taxjqm sys_1000 wp-p1m-38.ebi.ac.uk wp-p1m-38.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265360404 (wp-p1m-38.ebi.ac.uk) Time: 2021/04/06 17:58:08 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_hwz54ezyk5eq3arb5vhhhhhily multiple similarity criteria and a Neural Network classifier is proposed: starting from Keywords Record Linkage, Entity resolution, Neural networks, Feature extraction, Deduplication 4. Classification: the similarity vector obtained from each pair of records within the same a set of ensemble learning methods combining multiple base classifiers, including a Figure 2 Example of the similarity vector obtained comparing two records using four similarity functions (please see Table 2 for attribute mapping). The training data-set, in the format (feature,label) is generated based on the candidate • feature: is the similarity vector obtained comparing the records of the pair; Since non-matching record pairs are more than matching ones, the training data Figure 8 Results for multiple criteria similarity with threshold θ = 0.63, weighted. Figure 9 Results of the Levenshtein test with MLP classifier. then a classifier based on multiple criteria and Neural Networks has been proposed in Data matching: concepts and techniques for record linkage, entity work_hx46653twfhv5mfqggtxamgkbe Networking Services: A Case Study of a High School Classroom kind of media is examined, and when the online social network data Homophily, Social media, Multilayer networks, Exponential random our social networks researching offline or online alone. between offline and online social networks, studies Homophily in offline social networks Homophily in online social networks effect of gender homophily on a social network in the SNS social network layer, gender homophily First, in the SNS network, no gender homophily Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks Gender Homophily in Multilayer Media Social Networks work_hyou7qucmvhrbei6quydbibfdq Ethnic organizations, Collaboration networks, ERGM, Foci of activity, networks, which different ethnic organizations build Ukrainian and Russian organizations in Sweden from the Ukrainian and Russian ethnic organizations). organization, "ethnicity," and the conflict side. Ukrainian and Russian organizations active in Sweden. Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home Ukrainian and Russian organizations in Sweden and the conflict back home work_hzbgotiuhjazhgnm4aubvyb7pu known as ERGMs, are one of the popular statistical methods for analyzing the graphs ERGM is a generative statistical network model whose ultimate value between observed statistics and the ones generated by the ERGM model. ERGMs are one the main important network analysis methods investigated by analyzing the network of Romanian adolescents using ERGM modeling. This study offered an explanation of Exponential Random Graph Models aka ERGMs. We ERGMs in networked data in various field of engineering studies is a research path tools for the statistical modeling of network data. Exponential-family random graph models for valued networks. random graph (p*) models for social networks. in exponential random graph (p*) models for social networks. Exponential random graph models with big networks: The application of statistical network models in disease research. random graph modeling of whole-brain structural networks across lifespan. estimating exponential random graph models for large networks. Introduction to network modeling using exponential random graph work_hzrljsgczfffnf4dhbxxmv4zqi Discussion on Decimal Network Based on IPV9 decimal network digital domain name and IPV9 Keywords-Decimal Network; Digital Domain Names; gradually developed into a 256-bit address IPV9 Decimal network introduced the digital domain At present, digital domain name system and IPV9 applications based on THE IPV9 decimal network have IPV9 protocol family is a decimal network base protocol, including IPV9 header protocol, address IPV9 packet header format and field meaning are header of IPV9 protocol includes six types: segment IPV9 addresses, the rest of the header takes up only B. IPV9 Address Protocol The IPV9 address protocol specifies that the IPV9 ● IPV9 addressing model: Specifies that all types monocular addresses specified in the IPV9 The IPV9 transition protocol specifies the header IPV9 decimal network introduced the digital technology, and NAT-PT (Network address Transitional IPV9 decimal network supports two tunnel The decimal network is based on the digital domain work_i2qf3vbj7bampklw365wxgijja cognitive processes, yet software engineering research lacks theory on affects and theory of the impact of affects on development performance. concepts of events, affects, attractors, focus, goals, and performance. 1 For the purposes of this study, we consider affect as an underlying term for emotions and moods, in line with several other to understand the role of affects in software development processes and their impact on the understand how affect impact o software developers'' performance under a quantitative paper, we report an interpretive study of the impact of affects of developers on the software the results of our work, i.e., an explanatory theory of the impact of affects on programming the affects of software developers and their performance in terms of creativity and analytic Müller & Fritz (2015) performed a study with 17 participants, 6 of which were professional software developers and 11 were PhD students in computer science. work_i3wjbqxpmjecda7wa6hds75oyy A Research of Perforation Plan-decision Based on Grey Cluster Relation plan-decision based on Grey Cluster Relation is putted Keywords-Perforating Operation; Grey Cluster Relation; phase angle) act on the production ratio and casing strength perforation parameter optimization, and gives different perforation completion optimization schemes [3]. current subjective decision-making for perforation program productivity ratio[4], a Perforation Plan-decision Based on PERFORATION PLAN-DECISION BASED ON GREY drilling pollution degree and depth, perforation compaction Perforation Plan-decision based on Grey Cluster has made the model of perforation parameters and the oil well parameters of the perforation scheme, and the evaluation B. Perforation program base on Grey Cluster Relation penetration, perforation diameter and casing strength The normalization of attribute data based on the different attributes of perforation program are adjusted to: productivity ratio R1, perforation phase angle R2, shot density R3, casing In this paper, a Perforation plan-decision based on Grey Making to Optimization of perforated completion[D]. work_i4ok4yixpfbr5fdsfgea7qhnly Absorption Peak; Iterative Algorithm; Gas Concentration characteristic absorption of gases, leading to some gas good absorption of ultraviolet light by gas at the the iterative gas calculation algorithm. concentration of each gas is obtained one by one. concentration of each elemental gas is obtained again. initial concentration 1c of the elemental gas was absorbance and gas concentration.. gas and read the absorption photon number 2S of concentration of the second gas is calculated by ( A is absorbance), and the initial concentration of gas Mixed gas UV spectral absorption curve Zero gas is not absorbed in ultraviolet light of 190-290 NO2 and SO2 gas concentration iterative algorithm flow chart B. Calculating the Gas Concentrations of NO and calculates the actual concentration of the elemental gas spectrum is measured when the gas concentration is *Iterative calculation of gas concentration measure the concentration of flue gas and keep the work_i5qooiji7zh7lmzgdqg6bxvhf4 The frequency of topically similar talks in different concurrent sessions is, in fact, of preliminary schedules seeks to balance the topical similarity of talks within a session Keywords Topic modeling, Optimization, Conference scheduling Such large conferences often schedule oral presentations in concurrent sessions so conflicts, as might happen when talks of a similar topical nature are scheduled in concurrent We define the conference scheduling problem as the task of assigning talks to timeslots optimized conference schedules with multiple concurrent sessions in a fully automated talk and session placement in a Community-Informed Conference Scheduling approach Table 1 Parameters and variables used in the topic modeling, schedule creation, and optimization approaches. Figure 2 Mean discrimination ratio of the starting and final Ecology 2013 schedules for the four optimization approaches applied to each of the Random, Manual, Greedy, and ILP initial schedules. and optimization of conference schedules with concurrent sessions based on an objective work_i6l4k3m3zba3nlvdwx2wumw2fe parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. The parser''s graphs (also called ungrounded graphs) are mapped to all possible Freebase subgraphs (also called grounded graphs) by replacing edges and nodes with relations and types in Figure 2: Steps involved in converting a natural language sentence to a Freebase grounded graph. Our contributions include: a novel graph-based method to convert natural language sentences to grounded semantic parses which exploits the similarities in the topology of knowledge graphs and linguistic structure, together with the ability to train using a wide range represented by rectangles, relations between entities by edges, mediator nodes by circles, types by to construct ungrounded graphs topologically similar to Freebase, we define five types of nodes: We ground semantic graphs in Freebase by mapping two-stage procedure: first, a natural language sentence is converted to a domain-independent semantic parse and then grounded onto Freebase using a work_i6lb576gyjb35noib34kxoed2e Roth, M & Lapata, M 2015, ''Context-aware Frame-Semantic Role Labeling'', Transactions of the Association In this paper, we present a semantic role labeling system that takes into account sentence and discourse context. role labeled text, resources like FrameNet (Ruppenhofer et al., 2010) group semantic predicates into socalled frames, i.e., conceptual structures describing In Section 2, we present related work on semantic role labeling and the various features applied Early work in SRL dates back to Gildea and Jurafsky (2002), who were the first to model role assignment to verb arguments based on FrameNet. Their prior work where features based on discourse context are used to assign roles on the sentence level. Discourse-like features have been previously applied in models that deal with so-called implicit arguments, i.e., roles which are not locally realized Our goal is to learn a better model for FrameNetbased semantic role labeling using linguistically inspired features such as those described in the previous sections. work_ia5azdhzengttdfylnfe4qbu6a Decoding Anagrammed Texts Written in an Unknown Language and Script propose a method for deciphering substitution ciphers which is based on Viterbi decoding with mapping probabilities computed with the expectationmaximization (EM) algorithm. The method correctly deciphers 90% of symbols in a 400-letter ciphertext when a trigram character language model In this section, we propose and evaluate three methods for determining the source language of a document enciphered with a monoalphabetic substitution probability of the decipherment according to a bigram character language model derived from a sample document in a given language. We now directly evaluate the three methods described above by applying them to a set of ciphertexts from different languages. The decomposition pattern method makes many fewer errors, with the correct language ranked second in roughly half of those of the resulting decipherment with both characterlevel and word-level language models. Language Text Words Characters words, their distances to the VMS language according to the decomposition pattern method are 0.159, work_ic6cztnzvrhobibxk37oqugbma both prediction and moderation of information flow at multiple granularities: neural lattice language models. These models construct a lattice of possible paths through a sentence and marginalize across this lattice to calculate sequence probabilities or optimize parameters. This approach allows us to seamlessly incorporate linguistic intuitions – including polysemy and the existence of multiword lexical items – into our language model. are able to improve perplexity by 9.95% relative to a word-level baseline, and that a Chinese model that handles multi-character tokens is able to improve perplexity by 20.94% Figure 1: Lattice decomposition of a sentence and its corresponding lattice language model probability calculation Neural lattice language models define a lattice over possible paths through a sentence, and maximize the In this work, we do not explore models that include both chunk vocabularies and multiple embeddings. neural lattice language model implicitly marginalizes across latent segmentations. work_icxav2q5tjbe7kce734r5lp4wi absorption spectrum inversion gas concentrations, in the application of least square method of gas concentration complete the real-time display of gas concentration, and light-absorbing substance concentration; B is the absorption scattering, the absorbance and the concentration and absorption Two kinds of mixed gas Lambert-Beer absorbance light wavelength lambda, the mixed gas of photon number scattering of gas absorption interference can be ruled out characteristic absorption point, the gas absorbed photon number of photons absorbed minus every other gas absorption of the photon number, again to get the first gas concentration of an iteration, and so on to get other gas concentrations of an absorbance look-up table and the concentration of the gas as formula (7) to calculate the second gas absorbance, gas has obvious absorption peak, read the wavelength of Step 4: iterative inversion to calculate the first gas Step 6: calculation of gas concentration of the adjacent Mixed gas absorption spectrum work_idtsy3ntjzbwzcdkb2lm4zacoy A Comparative Study of Face Recognition Classification accuracy of different classification algorithms in This paper uses the face data published by algorithm, extracts the main features of the data, and linear discrimination LDA, nearest neighbor algorithm KNN, support vector machine SVM and the integrated Keywords-Classification Algorithm; Machine Learning; learning, face recognition technology is widely used in classification algorithms in face recognition. set in this paper uses the ORL face data set published (KNN), support vector machine (SVM), Naïve Bayes samples, the reduction rate is obtained after processing training samples in the data set, and there are c the distance between ax and bx in the sample set. b) For the test sample x, use the distance d) SVM is a novel small sample learning method samples, this paper predict the value. results more generalized, 80% of the data set is used as improved PCA+LDA face recognition algorithm [J]. work_ie6u4zqq7vhp3k4oezpc3koj2q Street View House Number Identification Based on Deep the network optimizes the input layer to accept three-channel number(SVHN) dataset, effectively improving the performance number, use the extracted features to train the SVM The samples in the data set are singleInternational Journal of Advanced Network, Monitoring and Controls Volume 04, No.03, 2019 optimizer has almost no improvement in the test set of the test set except the SGD optimizer is not accuracy of the test set of the other three networks even the highest test set accuracy, only the 7th epoch highest test set accuracy of the network using the other Comparing the training set accuracy rate of the test set in Figure 5, the curve with the weight view number, the better public data set is the SVHN extended set to the model training. Therefore, the different training sets in Figure 13 SVHN dataset to improve the classic LeNet-5 network work_ignbu6573rhffj4ahdsagcdn6m Segmentation for Efficient Supervised Language Annotation with an Explicit Cost-Utility Tradeoff In this paper, we study the problem of manually correcting automatic annotations of natural language in as efficient a manner as possible. method helps find the segmentation that optimizes supervision efficiency by defining user models to predict the cost and utility of supervising each segment and solving a constrained optimization problem balancing these language processing tasks: speech transcription and word segmentation. In this paper, we introduce a new strategy for natural language supervision tasks that attempts to optimize supervision efficiency by choosing an appropriate segmentation. The user model in this example might evaluate every segment according to two criteria L, a cost criterion (in terms of supervision time) and a utility criterion (in terms of number of removed errors), when Modeling cost requires solving a regression problem from features of a candidate segment to annotation cost, for example in terms of supervision time. work_igoeh44cmvczdc4di3oxmkl5wy algorithm is proposed to implement the mobile terminal cloud storage security. Keywords: Cloud Storage, HDFS, Dynamo, Dynamic Consistent Hashing Algorithm, AES, RSA, a result, a mobile cloud storage security technology solution is proposed in this paper, which enables of AES and RSA algorithms, a cloud storage security scheme for mobile is proposed in this paper. solution combines AES and RSA encryption algorithms to improve the shortcomings of the cloud 2) On the mobile side, the data that needs to be transmitted is encrypted with the AES key, and the The security design of the mobile cloud storage is implemented in a combination of the AES algorithm the AES key for each file is encrypted by using the RSA algorithm. In the cloud storage security technology solution designed in this paper, the 16-byte AES key is the In the mobile cloud storage security technology proposed in this article, the method of encrypting and mobile user data in the cloud storage system. work_ijabiykaibfnhbma2tyfindlu4 (2015), D4V: a peer-to-peer architecture for data dissemination in smartphone-based vehicular along the roads in urban and extra-urban environments, potentially encompassing multiple types of information ranging from traffic/road conditions to pollution data and others. peer may send a new join request to the bootstrap node, in order to obtain a list of recently The DGT allows peers to have accurate knowledge of geographically close neighbors GBs the closest known peers of the DGT overlay, within the Event Range, that are interested specific road density limit to model vehicles'' speeds in traffic jam conditions. shows that traffic information messages are highly distributed to active peers in the region Event Range as, ideally, the minimum distance of peers which did not receive the traffic maintain the DGT overlay and disseminate traffic information messages to other active D4V: a peer-to-peer architecture for data dissemination in smartphone-based vehicular applications D4V: a peer-to-peer architecture for data dissemination in smartphone-based vehicular applications work_iknuu3cd7re2rntzs6qpbod3ki Solutions for Governance and Suppression of Power Harmonic in Cities rolling and suppressing power harmonics in the public util Keywords-Power Harmonic; Governance and Suppression; Power harmonic in city utility grid is mainly produced in govern electric power harmonics.[11] The basic principle of and compensate or offset the electric power harmonic current, the field of future electric power harmonic governance and the governance of electric power harmonic. selection scheme for the power harmonic governance and Model Selection for Power Harmonic Governance and Suppression B. Specific Solution for Power Harmonic Governance and electric power harmonic. current waveform and harmonic analysis of the power supply before and after the power harmonic control and suppression standard GB/T14549-1993 Utility Grid Harmonic Power harmonics of low voltage power grid in oil field [J] .Electrical control technology in mine power supply and distribution system Research on harmonic suppression and reactive power work_im2qrukbnra2vdfxqduhays26i Keywords Programming performance, Coding challenge, Human factors, Personality, of a software engineer predict his or her performance in solving coding challenges. the performance in solving coding challenges, as well as between the personality trait of The way solutions to coding challenges are evaluated in interviews and programming a participant''s coding challenge performance score and the quantitative answers to the challenge performance score and items of the Scale of Positive and Negative Experience (SPANE) for operationalizing happiness (n=31, * p < .05, rs is Spearman''s rank correlation coefficient). personality traits and the coding challenge performance score (n=32, * p < .05). coding challenge performance score and the programming experience of a participant, second best coding challenge performance score of 2.66, while the participant with the best years of programming experience and the coding challenge performance, r(30)=0.420, Theory for predicting the performance in solving coding challenges negatively correlated with the performance in solving coding challenges. work_incs6r2ovzfh7ajrv56v5dou4i COVID-19 Health Communication Networks on Twitter: non-professional users responsible for major COVID-19 information COVID, Information diffusion, Health communication, Social network information sharing and network structures reflect of COVID-19 Twitter users by comparing the professional categorizations by their roles as sources, information for both retweet and mention networks (c) influential user identification in the retweet and mention networks. (c) influential user identification in the retweet and mention networks. number of influential users in a given network, top users, whereas the mention network had 758,313 ties the information flow is unidirectional: retweet network, In the mention network, the in-degree of the identified information sources was between 749 and 11,608 (N=100, Information disseminators, as in the retweet network, overall network structure and information flow. users in the retweet and mention networks may users in the retweet and mention networks may the mention network was not, users tended to retweet "Identifying influential users in Twitter networks work_inf7buxacnf4xdbpvz3cjaeqvm Keywords: Cloud computing, pricing schemes, resource allocation, revenue, utility 2.1 Cloud Users'' Choice with Different Pricing Schemes decisions, we first analyze which pricing scheme cloud users should choose. We will study how to set optimal prices in order to maximize the revenue of cloud providers while We will study how to set optimal prices in order to maximize the revenue of cloud providers while We will study how to set optimal prices in order to maximize the revenue of cloud providers while users'' decision choices, and then analyze cloud provider''s revenue problem. users'' net benefits vary with the price charged by cloud provider with θ and other parameters are utilities and net benefits vary with different types of cloud users and different number of VM instances, Figure.7 How cloud users'' net benefits vary with price of cloud resources p. users have more elastic demand for cloud services, cloud provider will get more revenue. work_inn62q2rznhknhfgujiaek3ctm A Collaborative Filtering Recommendation Algorithm with Improved Similarity Improved Pearson collaborative filtering (IP-CF) algorithm is algorithm''s similarity calculation, the prediction model is used Filtering; Similarity Calculation; Baseline Predictors Model proposed an itembased collaborative filtering recommendation algorithm that use the rating data to compute the similarity methods only consider the user-item behavioral data, and collaborative filtering recommendation algorithm based on neighborhood model, and uses the user portrait, item characteristics and user-item behavior data to compute characteristics and user-item behavior data to compute Collaborative filtering recommendation algorithm is to Collaborative filtering recommendation algorithm is to (3) According to the user sets prediction rating. This paper considers the user rating data from the overall recommends items that the users have rated highly but not recommends items that the users have rated highly but not recommendation algorithm on the rating data algorithm based on improved similarity computation is recommendation method based on a user''s item network[J]. work_ipnice3j5bdd5pqvvm65vhivse [PDF] Digital Scientific Notations as a Human-Computer Interface in Computer-Aided Research | Semantic Scholar Corpus ID: 47234108Digital Scientific Notations as a Human-Computer Interface in Computer-Aided Research title={Digital Scientific Notations as a Human-Computer Interface in Computer-Aided Research}, Figures and Topics from this paper Computer Simulations and Computational Models in Science User interfaces for computational science: A domain specific language for OOMMF embedded in Python Computational science: shifting the focus from tools to models. View 1 excerpt, references background View 1 excerpt, references background View 1 excerpt, references background View 1 excerpt, references background View 1 excerpt, references background View 1 excerpt, references background View 1 excerpt, references background Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI. By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License work_iqzi6a2wjbfc3g23fyfonvnujm Source Software (FOSS) for geospatial analysis in support of Maritime Spatial Planning Geoplatform (data.tools4msp.eu), an integrated web platform that supports MSP cumulative effects assessment (CEA) and marine use conflict (MUC) analysis. package can be used as stand-alone library or as collaborative webtool, providing userfriendly interfaces appropriate to decision-makers, regional authorities, academics and analysis, the Tools4MSP package as stand-alone library for advanced geospatial and (2018), Tools4MSP: an open source software package to support Maritime Spatial Planning. The inputs of the Tools4MSP CEA tool are: (i) the area of analysis; (ii) the grid (Kluyver et al., 2016; https://jupyter.org/), a web-based computational environment, which The Tools4MSP package is Python-based open source software available on github The Tools4MSP GeoNode plugin implements two sets of interfaces: the case study setup set up is released within the Tools4MSP software package (https://github.com/CNRISMAR/tools4msp/tree/master/data/demo_case_study) and is available for test and demo https://github.com/CNR-ISMAR/tools4msp/tree/master/data/demo_case_study https://github.com/CNR-ISMAR/tools4msp/tree/master/data/demo_case_study Tools4MSP geospatial tools to support maritime spatial planning. work_iuc5a5vyuvcflcj43d6khbokly Analysis and Compensation About Temperature Influence to Optical-Fiber Gyro optical-fiber gyro zero bias was studied, and a test method was temperature was a big influence to optical-fiber gyro zero bias, performance of optical-fiber gyro[1-4], the temperature system, so the compensation about optical-fiber gyro zero RESULTS ABOUT GYRO ZERO BIAS ABOUT DIFFERENT TEMPERATURE Gyro zero bias standard deviation compensate the effect of optical-fiber gyro zero bias. bias[5-6], the effect of temperature on the optical-fiber gyro OPTICAL-FIBER GYRO ZERO BIAS CHARACTERISTICS of the temperature character of zero bias of optical-fiber rate, 1 order compensation for temperature gradient. results, the gyro zero bias data was compensated for the The influence about temperature to gyro zero bias Relationship between temperature gradient and gyro zero bias temperature change rate on the gyro zero bias to a certain affect the zero bias of optical-fiber gyro. test of optical-fiber gyro was carried out, zero bias work_j2jsr5bribfrhcbqjphuvzoxqa ISO/IEC Future Network Standardization Expert, Network standardization project of the new future network international standard, it shows that international standard draft of 《 Future Network future network international version of the ISO/IEC the ISO/IEC future network as an example. the ISO/IEC future network as an example. promote the new future network technology program to V. NEW ARCHITECTURE FUTURE NETWORK a future network standardization project with an future network core technology areas. favor of the future of Internet international standards. the future research and development of network network technology standards. network security architecture based on the new design future network technology system. based on the new future network architecture has been international network standards in the future, which has international network standards in the future, which has architecture" represented by ISO/IEC future network architecture of the future network technology system. construction of a new architecture for future network work_j4jyyr4gnrbelgfykpcumrgui4 An HDP Model for Inducing Combinatory Categorial Grammars model for the induction of Combinatory Categorial Grammars from POS-tagged text. specification of a finite inventory of nonterminal categories and rewrite rules, but unless one adopts linguistic principles such as X-bar theory (Jackendoff, grammars, we use Combinatory Categorial Grammar (CCG, Steedman (1996; 2000)), a linguistically basic syntactic properties makes it very easy to create a language-specific lexicon for accurate unsupervised CCG parsing. combined in a bottom-up fashion (although generative probability models for CCG view them in a topdown manner, akin to CFG rules). Unlike dependency grammars, CCG requires an inventory of lexical categories. Note that this model generates only one CCG category but uniquely defines the two children of a parent node. Since our approach is based on a lexicalized formalism such as CCG, our system automatically induces lexicons that pair words (or, in our case, POStags) with language-specific categories that capture work_j4ovpuq7zvd4pl5l4gebrbzdny sys_1000 wp-p1m-39.ebi.ac.uk wp-p1m-39.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265358979 (wp-p1m-39.ebi.ac.uk) Time: 2021/04/06 17:58:06 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_j4ym2limgffn3isereirctplfi Simple Wikipedia has dominated simplification research in the past 5 years. reasons: 1) It is prone to automatic sentence alignment errors; 2) It contains a large proportion of inadequate simplifications; 3) It generalizes poorly to the sentence pairs in the PWKP corpus are not simplifications. Table 1: Example sentence pairs (NORM-SIMP) aligned between English Wikipedia and Simple English The breakdown in percentages is obtained through manual examination of 200 randomly sampled sentence pairs in the Parallel Wikipedia Simplification (PWKP) corpus. Siddharthan (2014)''s excellent survey of text simplification research states The Parallel Wikipedia Simplification (PWKP) corpus (Zhu et al., 2010) contains approximately Table 3: Example of sentences written at multiple levels of text complexity from the Newsela data set. Table 5: This table shows the vocabulary changes between different levels of simplification in the Newsela topics and degree of simplification between the Simple Wikipedia and the Newsela corpus. work_j6zirmtczrav3e56ilniy62vbi We explore the floating-point arithmetic implemented in the NVIDIA tensor cores, � Is the result of each floating-point operation in (2) normalized, or do tensor cores only available, in order to guarantee reproducibility and facilitate testing other matrix multiplyaccumulate units, such as the third generation tensor cores in the latest NVIDIA A100 Rounding modes in tensor core computations Tests for determining what rounding modes are used in the inner products and the final rounding Features of the accumulator Tests that explore the number of extra bits in the alignment step of floating-point addition inside 2. Can tensor cores take binary32 subnormal numbers as inputs for C in (2) without 2. Can tensor cores take binary32 subnormal numbers as inputs for C in (2) without 3. Can tensor cores compute subnormal numbers from normal numbers and return them? When tensor cores are used in binary16 mode, the result computed in the format of work_jfciwbeeifgkvl2k7eogkom2di work_jhgdjhqkh5dknobbgykk37oz4y model word confusions efficiently, without compromising on the semantic-syntactic Keywords Confusion2vec, Word2vec, Embeddings, Word representations, Confusion networks, (2003) proposed feedforward neural network based language models which jointly learned the distributed word (i) linguistic context (modeled by word2vec like word vector representations), and word vectors are shown to encode efficient syntactic-semantic language information. Traditional word vector representations such as word2vec only model the contextual the bag-of-word model in a semantic-syntactic analogy task. for acoustic confusions parallel to the analogy task and the word similarity task. The shortcomings of the indomain model compared to the Google Word2Vec on the Semantic&Syntactic analogy task baseline models perform well on the word similarity tasks as expected. observation is that modeling the word confusions boost the semantic and syntactic scores of case of ASR, the word-confusion subspace is associated with the acoustic similarity of acoustic-confusion through word vector representations, the confusion2vec can provide work_jhkfg5u4x5dotecqjonxyj7sbq Calculating the Optimal Step in Shift-Reduce Dependency Parsing: allows gold trees to be non-projective. If the gold tree is non-projective and the parsing strategy only allows projective trees, then there projective parsing algorithms, however (GómezRodrı́guez et al., 2014; Gómez-Rodrı́guez and its own right, and can be used to determine the optimal projectivization of a non-projective tree. Table 1: Shift-reduce dependency parsing. The three transitions of shift-reduce dependency parsing are given in Table 1. Figure 1: Dependency structure and corresponding parse tree that encodes a computation of a shift-reduce parser. Figure 1 presents a parse tree for the grammar parse tree, for stack of height 4 and remaining input of input, and the left-most and right-most dependency relations in the top-most two stack elements. To investigate the run-time behavior of the algorithms, we trained our shift-reduce dependency the optimal step for shift-reduce dependency parsing that is applicable on non-projective training work_jhs2l6kn55h5fbtcefmjli5asy A Study of Edge Computing Offloading Based on Security study a mobile edge computing model based on energy constraint, focus on an edge computing offload scheme based of user equipments during computing offload in the edge In mobile edge computing (MEC) systems, be achieved by offloading compute tasks to a wellresourced edge cloud. optimize the energy consumption of the execution task, designs a secure computational offloading method, the compute tasks of the user terminal to the cloud service, Performing computational offload tasks in MEC not offload in mobile edge computing, which has great Security-based mobile edge computing network architecture offloads the task to the edge server, =0 denotes during the detection of offloading computational tasks, In the security-based computing offload scenario, scheme than for an optimized energy-based offload Security-based computing offload Mobile-Edge Computing with Energy Harvesting Devices[J]. Offloading for Mobile-Edge Cloud Computing[J].IEEE/ACM Offload delay based on optimized energy consumption work_jlmpiucycfc6rdblexk6obfor4 reviews with publication year 2012 to generate three different networks: (1) The network based on disciplinary affiliations of Mendeley readers contains four groups: (i) (3) The country network focusses on global readership patterns: a group of 53 nations is identified readership network which is based on Mendeley readers per (sub-)discipline for a large (b) groups of readers in terms of their professional status (Professor, PhD student, postdoc, Table 1 Statistics of the full networks of disciplinary affiliations, countries, and status groups. 256 sub-discipline affiliations of Mendeley readers (group 1) with their connections in the Table 2 shows eigenvector centralities of the different status groups among networked Table 2 Eigenvector centralities and absolute number of reader counts (N) of different status groups Networks of reader and country status: an analysis of Mendeley reader statistics Networks of reader and country status: an analysis of Mendeley reader statistics Networks of reader and country status: an analysis of Mendeley reader statistics work_jmqylozdgrfyrjbdgrrfrh5pmm The building of large-scale Digital Elevation Models (DEMs) using various interpolation algorithms is one of the key issues in geographic information science. a specific scene to build large-scale DEMs. Subjects Distributed and Parallel Computing, Spatial and Geographic Information Systems Keywords Digital elevation model (DEM), Spatial interpolation, Radial basis function (RBF), interpolation algorithms are used to build DEMs, for example, the Shepard''s method Shepard''s method is to estimate expected values of the interpolation point by weighting and (2) comparing the interpolation accuracy and efficiency when data points are evenly of the presented eight GPU-accelerated interpolation algorithms with different data sets RBF, and Shepard''s interpolation method; when the data points are normal distribution, the density and distribution of the data points, the interpolation accuracy order from high to all the interpolation methods are larger than that for the uniformly distributed data points. accuracy when the data points are evenly distributed is higher than the interpolation work_jqo6bqehefaodeuuboo6oybjq4 Perception (LSP), a model for grounded language acquisition that learns to map natural language statements to their referents in to identify (1) the objects in its environment corresponding to "blue mug" and "table," and (2) the objects which participate in the spatial relation denoted mapping from natural language queries to sets of objects in a real-world environment. natural language query, LSP produces a semantic parse, logical knowledge base, grounding and denotation mug." Given these inputs, LSP produces (1) a logical knowledge base describing objects and relationships in the environment and (2) a semantic parse of The first contribution is LSP, which is more expressive than previous models, representing both one-argument categories and two-argument relations over sets of objects in the environment. is a weakly supervised training procedure that estimates LSP''s parameters without annotated semantic This paper introduces Logical Semantics with Perception (LSP), a model for mapping natural language statements to their referents in a physical environment. work_jr7irs7m6vg3lk2k6coje4kbgu ab initio plant miRNA identification methods over the last decade. only included studies on novel plant miRNA identification using machine learning. stringent plant-focused miRNA identification studies. Computational methods for the ab initio identification of novel microRNA in plants: a systematic review. full advantage of the available information in the sequencing data, such as novel miRNA The search strategy was used to identify plant miRNA prediction methods developed (novel miRNA identification in plants) AND (computational method) (QA6) Is the study focused only on plant miRNA identification? plant miRNA sequences for developing the prediction model or have they considered a considered all the plant datasets available in miRBase (a miRNA database) by (Kozomara & feature types for plant miRNA prediction. Whilst most studies utilized features extracted from data generated from various plant for identification of plant miRNA from RNA sequencing data. novel miRNA identification in plants using small RNA sequencing data. work_jttjd62ksvbjzkuni7ex4hohnm Application of wavelet analysis in the prediction of telemetry data Application of Wavelet Analysis in The Prediction of Based on the wavelet analysis, the prediction of forecasting model based on Mallat algorithm. Keywords-Wavelet Analysis; Fourier Transform; Periodic In this paper, the time series forecasting method is used The wavelet analysis method has the characteristics 1) Mallat algorithm based on wavelet decomposition THE RESEARCH OF TELEMETRY DATA TIME SERIES PREDICTION BASED ON MALLAT ALGORITHM point of the mutation, the wavelet function is usually Decomposition for telemetry data sequence telemetry data and the predicted value, it can be seen The comparison results between the predicted values and the TELEMETRY DATA FORECASTING MODEL TELEMETRY DATA FORECASTING MODEL This paper studies the telemetry data forecasting method based on wavelet analysis. analysis of the characteristics of the telemetry data, the the prediction algorithm based on wavelet analysis is forecasting model based on wavelet analysis[D].dalian:Computer work_jvoiujigvff45klae5xermbbae the FORCE11 Data Citation Implementation Group (DCIG) (https://www.force11.org/ A World Wide Web Consortium (http://www.w3.org) standard for machine-accessible [Repository Name] so that they will continue to resolve to a landing page providing metadata describing the data, including elements of stewardship, provenance, and availability. 7 Data Citation Implementation Group (DCIG, https://www.force11.org/ Registries of data repositories such as r3data (http://r3data.org) and publishers'' lists http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation 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http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation http://www.iassistdata.org/iq/evolution-data-citation-principles-implementation Achieving human and machine accessibility of cited data in scholarly publications work_jzdt3do5o5akfmhwn2s6ucbalu the proposed algorithm is achieved at different slow Doppler scenarios of the target Keywords LFMCW radar, SDLC–MTI, Doppler frequency, 2D-FFT, Signal processing Figure 5 LFMCW radar processor based on SDLC. LFMCW radar processor based on SDLC/SDLI Figure 7 General block diagram of LFMCW radar using the proposed processor. processor, proposed filter, MTI, SDLC/SDLI and CFAR detection. Figure 14 ROC of the proposed processor for middle Doppler target. Figure 13 ROC of the proposed processor for slow Doppler target. for both the proposed processor and traditional algorithm which based on SDLC/SDLI. Doppler frequencies; first one, is the off-pin target detection which traditional algorithm It is found that, the detection performance of the proposed processor is enhanced by Detection of targets with small apparent doppler frequencies in LFMCW radars. Enhancement of small doppler frequencies detection for LFMCW radar Enhancement of small doppler frequencies detection for LFMCW radar Enhancement of small doppler frequencies detection for LFMCW radar work_k2rbb6kaibeglln3pargxs36wy protein binding to a multiplexed sensor composed of a mixed layer of gold and silver binding events onto a mixed layer of gold and silver nanoparticles in a multiplexed Many plasmonic sensors can be modeled as a multilayer stack of homogeneous materials, (A) Panel to view material quantities such as index of refraction, n(λ), and nanoparticle extinction cross section, Currently shown is e(λ) for a layer of gold nanoparticles in water at a fill fraction of about 30% using Garcia''s mixing model. The optical properties of a gold nanoparticle, however, depend on the index Figure 4 Theoretical optical absorption and scattering properties of gold and silver nanoparticles. Surface plasmon resonance-based fiber optic sensors: principle, probe surface plasmon resonance sensor by controlling formation of gold nanoparticles and its on optical fiber using reflected localized surface plasmon resonance. Optical models for conjugates of gold and silver nanoparticles with surface plasmon resonance based fiber optic sensors. work_k4dphi7rgzgifgf4jv7luea7gu Research and Improvement of Apriori Algorithm Based on Hadoop parallel Apriori algorithms needs much more time in data IO Keywords-Apriori algorithm; Hadoop; Association rules Apriori algorithm, which is a classic association rule transaction database, and the support of this frequent set generate frequent 3-item set L3. 1) When the Apriori algorithm generates the candidate scan the transaction data set again and compare the candidate 2) Apriori algorithm need to rescan transaction datasets A. Reduce frequent item sets self-connection comparison merging processes, some frequent item sets of the data d) Scan transaction data set D minimum support count with the set of transaction items After association rules mine frequent item sets, it is experimental transaction data set. MEC-Apriori algorithm, and then the association rule is The transaction data set for this experiment is stored as a number of transaction item sets, apriori algorithm running on number of transaction item sets increases, the time work_k5irpuwxmrejppzgofqpx24ehe two groups of children, ages 5–18 years, performing verb generation in functional magnetic resonance imaging (fMRI) Across frequencies, we observed significant effective connectivity among proximal left frontal nodes. low frequency bands, information flux was rostrally directed within a focal, left frontal region, approximating Broca''s Key words: Broca''s area; causal network; children; functional magnetic resonance imaging; linearly constrained healthy young children have bilateral and diffuse language networks, which become increasingly left lateralized and focal with development (Brown et al., 2005; study is on integration of data from the two imaging modalities and the novel application of effective connectivity analyses for mapping a core functional network. identified brain regions showing significantly increased activation for verb generation, using a family-wise error correction of p < 0.01 and clustering threshold of k = 8 voxels. Group analyses of the fMRI data revealed consistent activation across individuals in bilateral frontal (including insular cortex) and posterior temporal regions, and the left work_k5zsbz3e7jfnxis6togjuxtjze Keywords Aspect phrase embeddings, Review rating prediction, Sentiment analysis, Social media, Cross-domain reviews, Yelp, Amazon, TripAdvisor, Word embeddings, Multinomial logistic Leveraging aspect phrase embeddings for cross-domain review rating prediction. different aspects that vary across domains, can be effectively leveraged for the review rating To the best of our knowledge, review rating prediction for non-popular domains has To enable our analysis of review rating prediction over different domains, we make use of review rating prediction, where the training and test data belong to the same domain. we show and analyse the results for cross-domain review rating prediction, where data from Tables 3 and 4 show results for in-domain review rating prediction, where the training Table 7 MAE Results for cross-domain review rating prediction with different percentages of the Table 8 RMSE Results for cross-domain review rating prediction with different percentages of the to propose a cross-domain review rating prediction system that would perform well for work_k6wfvskhsjdfzbbrhtoyfkwd7a Back to Basics for Monolingual Alignment: Exploiting Word Similarity and Contextual Evidence Back to Basics for Monolingual Alignment: Exploiting Word Similarity and aligning similar semantic units in a pair of sentences they found contextual evidence in the form of syntactic constraints useful in better aligning stop words. a central component of most aligners; various measures of word similarity have been utilized, including We apply the notion of dependency type equivalence to intra-category alignment of content words dependencies.) Given a word pair (si, tj) from the input sentences S and T , it collects contextual evidence and align all identical word sequence pairs in S and Note that in cwTextAlign we also align semantically similar content word pairs (si, tj) with no contextual similarities if no pairs (sk, tj) or (si, tl) exist word alignments are dependent on existing content similarity: a) aligned content word proportion, b) the work_kblwcbmnbbepdezi4zkqcjbydy This paper proposes a slow-moving management method for a system using of intermittent demand per unit time and lead time demand of items in service enterprise inventory We confirmed that the parameter of variability of the zeroinflated truncated normal statistical distribution used to model intermittent demand Keywords Demand during lead time, Inventory models, Zero-inflated truncated normal intermittent DPUT forecasting with non-zero values and the LTD by means of a zeroinflated truncated normal sum (ZITNOsum). 1: Generate a random sample of intermittent DPUTs of ZITNO statistical distribution To model the intermittent DPUT we used the statistical distributions in Table 1, and to Effect of variability and intermittent DPUT with ZITNO statistical distribution on total costs and Q and r decisions our proposed statistical distribution ZITNO DPUT model. Table 7 Parameters of the proposed statistical distribution to model DPUT and LTD and its competitors. Proposed statistical distribution inventory model performance. proposed statistical distributions for the DPUT/LTD modeling. work_kc3hrngeqbdsfc4atlsx5umlti How to cite this article Cánovas Izquierdo and Cabot (2016), Collaboro: a collaborative (meta) modeling tool. collaborative development of models defined with either General-Purpose Languages discuss at language element level (i.e., domain concepts and notation symbols) is required to model concrete systems, the collaborative aspects of language development are more definition of the abstract syntax of the previous DSML requires the collaborative creation We propose a collaborative approach to develop DSMLs following the process � providing a metric-based recommender that can help to develop high-quality DSMLs. Representing the elements of a DSML metamodeling language, on which we rely to represent the abstract syntax of DSMLs. Concrete syntax and concrete syntax definitions to existing abstract elements) on the Collaboro model only the abstract syntax of the language, there was no need for creating a notation model, Engaging end-users in the collaborative development of domain-specific modelling work_kcfnc6khsraxhcor4ocz3g7ixm embedding models based on matrix factorization, random-walks and deep learning machine learning problems on graphs, among which are node classification, link Keywords Graph embedding, Knowledge representation, Machine learning, Network science, Geometric deep learning, Graph neural networks, Node classification, Link prediction, high quality in relational machine learning tasks and constructing graph embeddings models (Lee et al., 2019) and graph neural networks (Wu et al., 2019b; Chen et al., 2018a; approaches to learn network embedding and introduce to a reader the core ideas of graph generalizing Node2vec (Grover & Leskovec, 2016) model to graph neural networks. Nowadays, many advanced deep neural network models are adapted to graph data. HSCA model, embedding homophily, network topological structure and node features dependency graph and learn node (word) embeddings using GCN. embedding models could really learn graph structure and its properties. embedding models for node classification, link prediction, node clustering and network Deep neural networks for learning graph representations. work_kewvexetpzdd5axo24uef7rq64 Imitation Learning of Agenda-based Semantic Parsers In this paper, we combine ideas from imitation learning and agendabased parsing to train a semantic parser that Figure 2: An example semantic parse, or derivation, for the beam search, where the number of parses (see Figure 2) for each chart cell (e.g., (SET,3:5)) is capped Specifically, we cast agenda-based semantic parsing as a Markov decision process, where that learns to choose good parsing actions, training from question-answer pairs only; Second, a lazy Figure 3: A semantic function (we show JOIN, LEX and INTERSECT) takes one or two child derivations and returns a set of controls the order in which derivations are constructed using an agenda Q, which contains a set of Most work on agenda-based parsing generally assumed that the scoring function s is Table 4: Accuracy, number of featurized derivations, and parsing time for both the training set and development set when work_kjydoa2mwfclpe5ldim7btjkni remission of CD, TSH, T3 and FT3 showed a significant increase, with a few cases above By 12 months, most CD patients'' thyroid functions returned to Thyroid hormones (including TSH, T3 and FT3) were negatively associated with remission of CD, TSH, T3 and FT3 increased significantly, even above the reference range, Before surgery, serum cortisol and thyroid hormones serum cortisol/thyroid functions in all the CD patients including thyroid hormones, serum cortisol levels, age, Table 3 Serum cortisol and thyroid functions of 102 CD patients before and 3 months after surgery. aComparison between hormones before and 3 months after surgery in remission group. Three months after surgery (n = 102)b Serum cortisol TSH −0.343d 0.000 aCorrelations between thyroid hormones and serum cortisol levels were analyzed in all the patients with CS (n = 112) before surgery. between thyroid hormones and serum cortisol levels were analyzed in all the patients with CD (n = 102) after surgery. work_knwdputcjze7viktx5uhxwuuke VESPA provides flexible software for simplifying these processes along with downstream selective pressure variation analyses. Keywords Selective pressure analysis, Protein molecular evolution, Large-scale comparative VESPA helps automation by preparing input data files and processing results but program For three of the five phases (data preparation, homology searching, and selective pressure analysis assessment) the functions invoked in both the basic and advanced options are identical. output files for each homologous gene family detailing the results of the codeML analysis. A tarball of the data and results of the VESPA analysis of 18 gene families (i.e., input sequences, alignments, trees, codeml output, VESPA summary at each phase) have been Table 3 Comparison of the results from 18 gene families from the Selectome database analysed in VESPA. positive selection following VESPA analysis using the alternative alignments, it should be VESPA could be used to perform a selective pressure analysis on protein-coding transcripts work_ko6amo5b3jdbdcrcns6rbo2zym sys_1000 wp-p1m-38.ebi.ac.uk wp-p1m-38.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. 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Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_kobewel4rjapzjr65c2suycham Organic Garbage Disposal Equipment Management System Based on WSN Keywords-Garbage Disposal; Equipment Management; basic information of staff and equipment, receiving data real-time simulation, task management and fault management of organic waste equipment, improving the The staff can manage the equipment and tasks and management of garbage disposal equipment. equipment management, thus improving operation and management efficiency of waste disposal equipment and  It will be able to manage user information, such as  The operator can carry out task management, add The operator can manage the basic information by the 2) User information management Manage user information, including add, delete, modify, Management equipment information, including adding, modifying, and deleting equipment information and other 2) Equipment management information 2) Equipment management information User can view the information of the device, add, User can check the fault information of the device and The organic garbage disposal equipment management disposal equipment information management. work_kq5iakcovbdnjclxf3ichyagwy BiLSTM is trained jointly with the parser objective, resulting in very effective feature extractors for parsing. The focus of this paper is on feature representation for dependency parsing, using recent techniques from the neural-networks ("deep learning") Graph-based parsers (McDonald, 2006) treat parsing as a search-based structured prediction problem in which the goal is learning a scoring function over dependency trees such that the correct tree by using the BiLSTM feature extractor in two parsing architectures, transition-based (Section 4) as The core features in a transition-based parser usually look at information such as the word-identity 3In all of these neural-network based approaches, the vector representations of words were initialized using pre-trained Beside using the BiLSTM-based feature functions, we make use of standard parsing techniques. Figure 2: Illustration of the neural model scheme of the graph-based parser when calculating the score of a given parse work_kqfkki6bovhuvk6e77bdp4fxei How to cite this article Bocher and Ertz (2018), A redesign of OGC Symbology Encoding standard for sharing cartography. map symbols is suitable to drive the definition of a standardized styling language that must At this level, SDI users discover pre-styled and ready to be visualized map layers, The OGC Web Map Service (WMS) standard (De la Beaujardiere, 2006) is currently the only Figure 3 Discovery of ready to be visualized map layers with OGC WMS standard. Figure 5 Authoring of user style to visualize map layers with OGC WMS/SLD and SE standards. Figure 7 Re-authoring of styles shared through catalogs with OGC WMS/SLD standards. Figure 8 Creation of a common map based on shared styles with OGC WMS/SLD, SE and OWS Wayland: Open Geospatial Consortium, Inc. Available at http://www.opengeospatial.org/standards/sld (accessed 27 September 2017). A redesign of OGC Symbology Encoding standard for sharing cartography A redesign of OGC Symbology Encoding standard for sharing cartography work_ksosgebmubgflck3znj5ybltdq Fast Aerial UAV Detection Based on Image Segmentation and HOG-FLD Feature method based on graph theory and HOG-FLD feature method based on image segmentation and HOG+SVM, the Keywords-Image Segmentation; Graph Theory; HOG; An image segmentation method based on graph theory and HOG-FLD feature fusion is proposed for UAV segmentation method based on graph theory and are extracted ability extracted by HOG-FLD feature fusion are rarely A. Segmentation Method Based on Graph Theory A. Segmentation Method Based on Graph Theory theory (Graph-Based Image Segmentation) and the region merging method are selected to segment the image in this The image segmentation method based on graph The image segmentation method based on graph merging degree of the image segmentation region, which is TARGET UAV DETECTION BASED ON HOG-FLD extract the feature of the regions to be detected, and the image segmentation with the region of interest based on image segmentation to detect UAV in terms of work_kt5jsmzxpfef3fivjs6s6tzd4m Computer Science researchers rely on peer-reviewed conferences to publish their work nonnative English speakers exhibit no differences in their experience of the peer-review Keywords Computer Systems, Author survey, Researcher Diversity, Peer Review within the same conference, we cannot design an experiment where papers are reviewed A survey of accepted authors in computer systems conferences. for publishing research results in systems is peer-reviewed conferences (Fortnow, 2009; includes data from 56 conferences, 2,439 papers, 8,193 authors, and 918 survey respondents. Table 1 Conferences in our dataset with their start date, double-blind policy, number of accepted papers, acceptance rate, and survey response rate by papers. Survey responses from different authors to the same paper were typically identical or Other authors opined that effective peer review provides feedback that improves the paper This paper presented a new survey of conference authors, exposing the experience of in systems research, and this paper looked at whether the peer-review process plays a role work_kv3srcrerrazfgb2arzc4pde5q are polyadenylate (polyA) tracks encoding for poly-lysine runs in protein Our data is based on the Ensembl genomic database of coding sequences and Keywords Ribosome stalling, Gene regulation, Eukaryotic genomes, mRNA stability, Translation (2016), PATACSDB—the database of polyA translational attenuators in coding sequences. such polyA track sequences may support programed translational frameshifts in such polyA track genes in Eukaryotes would be based on mRNA surveillance mechanisms, No genomic database reports polyA tracks in coding sequences, therefore we have designed PATACSDB (PolyA Translational Attenuators in Coding Sequences Highest percentage of polyA-carrying transcripts (first 5) Plasmodium berghei 68.259% on polyA tracks from human and yeast genomes, using the NCBI (Pruitt et al., 2014) carry polyA track and, as such, are subjects of translational attenuation. polyA segments are not the only sequence determinants of translation efficiency in coding PATACSDB---the database of polyA translational attenuators in coding sequences PATACSDB---the database of polyA translational attenuators in coding sequences work_kwuwhxyuhrdghduymgc3bhsk6q The monophyly of taxa is an important attribute of a phylogenetic tree. Keywords Phylogeny, Evolution, Monophyly, R package, Taxonomy, Rogue taxa, Tree conflict, How to cite this article Schwery and O''Meara (2016), MonoPhy: a simple R package to find and visualize monophyly issues. for assessing monophyly of taxa in a given phylogeny. from assessing monophyly for all groups and focal taxonomic levels in a tree at once, AssessMonophyly Runs the main analysis to assess monophyly of groups on a tree. GetIntruderTaxa Returns lists of taxa that cause monophyly issues for another taxon. GetIntruderTips Returns lists of tips that cause monophyly issues for a taxon. GetOutlierTaxa Returns lists of taxa that have monophyly issues due to outliers. GetOutlierTips Returns lists of tips that cause monophyly issues for their taxon by being CRAN: https://cran.r-project.org/package=MonoPhy/ Supplemental information for this article can be found online at http://dx.doi.org/10.7717/ https://cran.r-project.org/package=MonoPhy/ https://cran.r-project.org/package=MonoPhy/ http://dx.doi.org/10.7717/peerj-cs.56#supplemental-information http://dx.doi.org/10.7717/peerj-cs.56#supplemental-information work_kxfutgt6zfhobmwolnrtzr7dle requirements preclude the use of these models for training with longer sound samples. Keywords Sound synthesis, Machine learning, Reservoir computing, Conceptors, Dynamical Sample-level sound synthesis with recurrent neural networks and conceptors. Jaeger''s original work with ESNs included examples of models being trained to output questions through the application of conceptor models to a standard sound synthesis A new method of conceptor-based sound synthesis is demonstrated, named conceptular techniques that allow training and exploitation of the models for sounds synthesis. sound synthesis models to create new sonic variations of the original training material, Conceptular synthesis works by subdividing the audio training data into a set of subsequences, and learning an RNN and set of conceptors that can regenerate these subsequences, with the intention of resynthesising the audio sample by recombining the Figure 2 A comparison of the original kick drum sample and the output of the trained CCRNN model. work_kxuqkxr44vclndiw24jbsscsae techniques in Business Process Model and Notation (BPMN) model. that used operation research techniques and business process model and notation, Keywords BPMN, Business process model and notation, Operation Research, OR, Decision Approaches combining methods of Operational Research with Business Process Model and Notation (BPMN) process modelling and specific methods of Operational (BPMN) is the language that is used to model business process steps from start to end. focused on process modelling and BPMN and then on OR and its essential methods and (6), automation (3), bpmn (20), business process models (6), checking (6), cognitive analysis in business process models, � Tomaskova (2018): Modeling Business Processes for Decision-Making. In the article: Automated performance analysis of business processes Modeling business processes for decision-making. Approaches combining methods of Operational Research with Business Process Model and Notation: A systematic review Approaches combining methods of Operational Research with Business Process Model and Notation: A systematic review work_kybbk22puncxpbwlwra5tzagve Research on the Key Technology of Survey Measurement Image Based on UAV especially the emergence of high resolution image sensor, aerial Image Preprocessing; Image Matching; Feature Extraction At present, UAV surveying mainly relies on image aerial Correction of image distortion -Indirect method, the coordinates of the corresponding point on the original image x, y: coordinate of the image point which origin is the center of the image, x0, y0 : coordinates of the main point of Find the matching point in the top level image, the to match other feature points [6]. images and matching SIFT feature vectors. point will be a candidate for image at this scale. extract image feature points, uses the two-dimensional The matching test image is shown in figure 3. implement SIFT to extract the image feature points. two-dimension feature point matching method BruteForce Distinctive Image Features from Scale-Invariant Distinctive Image Features from Scale-Invariant work_kzvr63abvncexodi4czyqwcfwm interface (API) for injection molding machines (IMMs), which has the potential to be used with different IMMs to log and set the necessary process parameter values. Industrial Raspberry Pi (RevPi) was used to perform analog-todigital signal conversion and make sensors data accessible via the API prototype. Keywords Application programming interface (API), Data acquisition system, Injection molding, analysis of data from different manufacturing processes and injection molding is no Towards a general application programming interface (API) for injection molding machines. The frequencies for logging the IMM and mold data may differ depending on the the necessary parameters data is accessed on the IMM and logged from the additional sampling rates, the API was installed on the RevPi, where three different processes needed IMMs of other manufacturers; testing of the system with other injection molding machines; of the open API prototype for injection molding machines. as allow connection with RevPi for data acquisition from sensors installed in a mold. work_l3z5e7xzgfegbmvfa6eryggaaq sample sizes needed to observe the full range of DNA barcode haplotype variation that Keywords Algorithm, DNA barcoding, Extrapolation, Iterative method, Sampling sufficiency, DNA barcode haplotype sampling completeness, a technique suggested by Phillips, Gillis required sample sizes needed for adequate capture of within-species haplotype variation. the number of observed haplotypes (i.e., unique DNA sequences) (H*) for a given species. with N =5 sampled specimens (DNA sequences) possessing H*=5 unique haplotypes. Figure 3 Iterative extrapolation algorithm pseudocode for the computation of taxon sampling sufficiency employed within HACSim. A user must input N , H* and probs to run simulations. the H*=10 estimated haplotypes have been recovered for this species based on a sample size of N =180 the H*=10 estimated haplotypes have been recovered for this species based on a sample size of N =180 haplotypes for this species have been recovered based on a sample size of N =171 specimens. work_lajupfoawjd2vjpjstci2opryq A short presentation of concepts reflects in part the foundations of neostructural sociology (NSS) and its use of social and organisational network analyses, combined with other methodologies, to better understand the roles of structure and culture in individual and collective agency. Specific characteristics of institutional entrepreneurs who punch above their weight in institutionalization processes are introduced for that purpose, particularly the importance of multistatus oligarchs, status heterogeneity, high-status inconsistencies, collegial oligarchies, conflicts of interests and rhetorics of relative/false sacrifice. The second case focuses on a network study of a fieldconfiguring event (the so-called Venice Forum) lobbying for the emergence of a new European jurisdiction, the Unified Patent Court, and its attempt to create a common intellectual property regime for the continent. focus on network modelling of social processes helping actors in such settings manage the To illustrate this neo-structural approach, let me present two cases of institutionalization of new norms in businessrelated judicial institutions (Lazega, 2003), work_latiqsmi2fdrrd6ije6kneur64 Trajectory clustering and path modelling are two core tasks in intelligent transport restaurant process (DDCRP), a trajectory analysis system that simultaneously performs trajectory clustering and path modelling was proposed. Keywords Path modelling, Trajectory clustering, Anomaly detection, Chinese restaurant process, Novel trajectory clustering method based on distance dependent Chinese Most existing trajectory analysis methods can be categorized into similarity-based models When trajectories are clustered, some studies perform path modelling in a further used the weighted average of trajectories of each cluster to form the path model for that All these approaches, however, model the path after the trajectories are clustered. Also, the modelled path is not used to improve the trajectory clustering. trajectories and models the path taken by each cluster at the same time. This paper proposed an unsupervised approach for trajectory clustering and modelling. and usefulness of the proposed algorithm in trajectory clustering and modelling compared DPMM-based method for trajectory clustering, modeling, and retrieval. work_lbjz23isnfbh5bcl4jbmahp6r4 We investigated in two studies whether copeptin levels – the surrogate marker for AVP – are regulated by IL-1-mediated chronic inflammation in patients with inflammation is associated with increased circulating copeptin levels, antagonizing IL-1 does not significantly alter copeptin levels in patients with metabolic syndrome. HbA1c levels in patients with type 2 diabetes mellitus copeptin observed in patients with metabolic syndrome are To assess treatment effects on copeptin levels, we used were adjusted for baseline copeptin levels, treatment day, median copeptin levels for patients without diabetes were in baseline copeptin levels between the two treatment high copeptin levels with the metabolic syndrome. AVP/copeptin levels in patients with metabolic syndrome. copeptin levels in patients with metabolic syndrome. copeptin levels in patients with metabolic syndrome. Change in Copeptin levels from baseline according to treatment group abstract reporting study results on copeptin levels before Effect of IL-1 receptor antagonism on copeptin levels work_lbtgversgrfo3gnzobsayr36ti Objective: Investigate the prevalence of vitamin D deficiency in an equatorial population parathyroid hormone (PTH) serum levels measured by immunoassay method. Individuals were divided according to four age brackets: children, adolescents, adults model showed BMI, sex, living zone (urban or rural) and age as independent variables with vitamin D insufficiency (20–30 ng/mL), a difference between PTH levels in these two the most accurate predictive vitamin D level for subclinical hyperparathyroidism in ROC Conclusion: Our equatorial population showed low prevalence of vitamin D hypovitaminosis studies trying to evaluate vitamin D levels in equatorial age groups who had 25(OH)D serum levels measured at distribution of vitamin D levels according to each age with normal PTH levels) among patients with vitamin D Table 4 Prevalence of vitamin D deficiency in our population that subjects with vitamin D levels lower than 26 ng/mL levels of vitamin D intake when compared to other regions work_lbym4kns2nhrrcgrs5qrckanai The crosstalk between macrophages (MΦ) and adipocytes within white adipose tissue (WAT) influences obesity-associated insulin resistance and other associated metabolic increased in WAT during obesity, which is linked to decreased mitochondrial content and quantity and the quality of human adipose tissue macrophages (ATMΦ) and their impact on mitochondrial function of white adipocytes are discussed, including recent research White adipose tissue (WAT) is a metabolically active of ATMΦ factors that metabolically enhance adipocytes Obesity-associated impaired immune balance in white adipose tissue. MΦ increase in obese WAT, for example in human scWAT from 13 Obesity-associated impaired energy metabolism in white adipocytes. Activated macrophages control human adipocyte mitochondrial 42 van Harmelen V, Skurk T, Röhrig K, Lee YM, Halbleib M, AprathHusmann I & Hauner H. MΦ number increases in human white adipose tissue during obesity Mediators between ATMΦ and increased adipose energy metabolism work_lbzdpip75bexvoaes77ousbqay Research of Distributed Control System for Oilfield Oil Pump Keywords-Oil Pump; PLC; LAN; Distributed Control remote joint measurement and control of multi oil pump. local oil pump firstly can be controlled initially by pump remote measurement and control system as shown in Oil pump distributed measurement and control network topology control of the oil pump, and following the principle of topdown and gradual subdivision, we have designed the overall Oil pump control system hardware macro structure Oil pump remote control center computer DAValveCtl: Completing flow control of oil pump, on the on the other hand it controls the oil pump to be executed The oil pump IPC local session software subsystem is tasks in the oil pump operation, so subsystem design uses operation, for example, in the "oil pump data processing measurement and control system of oil delivery pump based RCC remote site oil pump process operation interface work_lc2vjdyopfgd5fx347xmqj6ore Estimation Algorithm for Low Frequency Seismic Motions Based on domain algorithm is presented to estimate the travel time difference of seismic waves with multi-path interferences The spectra of the seismograms are calculated through the fast algorithm, and the multipath parameters as well as the difference of travel time between a reference position and the seismographic stations are Keywords: Spectral analysis, low frequency seismograms, semblance function, frequency domain. array signal processing methods were proposed to maximize a semblance function using a grid search algorithm, then to data space, the multi-path parameters can be estimated, and the optimization for the extended semblance function yields the estimation of travel time difference between a reference position and tiltmeter stations. time difference can improve the location accuracy of epicenter from the seismograms spectra in the proposed algorithm. The extended semblance function based algorithm has been proposed to estimate the difference of travel time and work_lccqoj5iyjfcpd4preqa64baum 3D Target Recognition Based on Decision Layer Fusion proposes a target recognition method based on decision layer point cloud data and multi-view images. used in the decision layer to complete the fusion of features. became a classical convolutional neural network image use the method of manually extracting features to classify convolutional neural networks to classify and recognize point cloud images, of which the VoxNet network has the vector machines require manually extracting image features Convolutional neural networks use local connections, weight The input layer are images, there are 5 convolutional convolutional layers, and the number of feature maps is 32, this paper uses the method of decision layer fusion. The feature fusion of the decision layer is usually the VoxNet using point cloud feature, and AlexNet is used to method with the recognition accuracy of VoxNet and neural network frameworks to extract point cloud features Convolutional Neural Networks for 3D Shape Recognition. work_ld2ksivlgvd63cpdaez6tsr4ya public databases, such as related samples and features, we show that blind normalization recovery of confounding factors is formulated in the theoretical framework of compressed sensing and employs efficient optimization on manifolds. approach to the blind normalization of public high-throughput databases. Keywords Blind normalization, High-throughput data, Compressed sensing, Confounding Blind normalization of public high-throughput databases. In addition, high-throughput data based meta-analyses are best performed with high-throughput data with respect to sample information and the experimental protocol of compressed sensing it enables blind recovery of bias and subsequent normalization A database consisting of features, such as measurements of RNA, protein or metabolite and samples, such as different cell types under various stimuli, is observed. redundancies that commonly exists in high-throughput databases (see ''Blind recovery''). the case of blind recovery, high-specificity and low-sensitivity estimators can be used; as blind recovery of bias with increasing noise complexity (50×50). work_ld3htvi4tzfudjs3yulhvpnhwu one novel electrolytic capacitor-less converter and its control One proportional-Resonant control of a singlephase to three-phase converter without electrolytic capacitor converter without dc link electrolytic capacitor proposed in electrolytic capacitor-less converter that its dc link voltage is One novel electrolytic capacitor-less converter topology the phase-difference of output voltage and input power voltage conversation efficiency of the novel converter can When dc link voltage of the novel converter is six-pulse When dc link voltage of the novel converter is six-pulse Figure 4(a) is the dc link voltage of the novel converter. The dc link voltages of two converters with a motor load. demonstrates that the dc link voltage of the novel converter dc link voltage of the traditional converter is an voltage of the novel converter driving an induction motor is dc link voltage of the novel converter maintains six-pulse voltage at fifty frequency show that the novel converter has work_les4de22qzd4pkbxjnruyovkn4 interleaved subsets of data on GPUs and develop a massively parallel tree construction XGBoost is at its core a decision tree boosting algorithm. by scanning left to right through all feature values in a leaf in sorted order. XGBoost algorithm handles this by performing two scans over the input data, the second node, update the positions of training instances based on these new splits and then The first phase of the algorithm finds the best split for each leaf node at the current level. GPU algorithm is to perform a sum reduction over the entire feature before scanning. algorithm for a thread block processing a single feature at a given tree level is shown in The sorting implementation of the split finding algorithm operates on feature value data Given data sorted by node ID first and then feature values The performance and accuracy of the GPU tree construction algorithm for XGBoost is work_lhrdzyewqzbkrgorihi373miku MATLAB to analyze of the two phase chopping regulating all control type soft starter start performance Figure.1 The main circuit structure of two phase chopping regulating soft starter Based on the main circuit of two phase chopping regulating all control type soft starter shown in the Figure.2 The main circuit model of two phase chopping regulating soft starter The stator current simulation result of two phase chopping regulating all control type soft starter is Figure.3 The stator current simulation result of two phase chopping regulating soft starter Fig.4 is the speed and torque simulation results of two phase chopping regulating all control type soft The starting torque of two phase chopping regulating all control type soft starter is Fig.5 is the stator current local amplification figure of two phase chopping regulating all control type soft the two phase chopping regulating all control type soft starter. work_liz65ql5sngstk6qo3rdxliyw4 The Paraphrase Database (PPDB; Ganitkevitch et al., 2013) is an extensive semantic resource, consisting of a list of phrase pairs with We address these issues in this work by introducing ways to use PPDB to construct parametric paraphrase models. We find improved performance by training a recursive neural network (RNN; Socher et al., 2010) directly on phrase pairs from PPDB. We show that our resulting word and phrase representations are effective on a wide variety of tasks, PPDB phrase pairs and evaluates how well models We created two novel datasets: (1) AnnotatedPPDB, a subset of phrase pairs from PPDB which to establish a way to evaluate compositional paraphrase models on short phrases. For training, we extracted word pairs from the lexical XL section of PPDB. Table 8: Illustrative phrase pairs from Annotated-PPDB with gold similarity > 4. work_lkxmpxkzqfbxza6rdqwsawtzra Internet of Things Application in Satellite Communication mudslide disasters, the ground communication network is up satellite Internet of Things to realize real-time monitoring Satellite mobile communication refers to the use of Satellite communications generally use the L, S, Typical satellite mobile communication systems Mobile satellite communications are an effective orbit communication satellite can cover 42% of the operating rate of satellite communications is above advantages, satellite mobile communication also has C. Development Status of Satellite Communication phone with mobile satellite communication capabilities. Tiantong-1 satellite mobile communication system Tiantong-1 satellite mobile communication system Tiantong-1 satellite mobile communication system communication satellites developed and launched in low-Earth orbit to form an Internet satellite network, APPLICATION OF SATELLITE COMMUNICATION Therefore, the use of satellite mobile communication Trends of Satellite Mobile Communications[J]. Communication Satellite Technology[J]. Satellite Mobile Communications[J]. Satellite Mobile Communications[J]. Satellite Mobile Communications[J]. Application and Development of Satellite Mobile Application of Satellite Mobile Communication System. work_louh5h74dzaxlfocwpwaujtysu group of 22 mid-career military officers going through a one-year graduate program. collection included email communication collected from the Exchange server, as well as selfreported friendship, and time spent together, over a course of 20 weeks. data on the individual actors was collected from their military personnel files. The IkeNet data is from one year of a fiveyear strategic study of social networks among mid-career military officers admitted to a one-year graduate program run Social network data was collected on a In this particular year, 21 of 22 officers in the program consented to be participants in this project. Surveys were conducted on a weekly schedule, collecting network data on Response Rate 100% for email networks, collected at the central server Data Context Friendship formation among a group of mid-career military officers in Respondents Mid-career military officers in the Eisenhower Leadership Development Program of the US Army and Columbia University work_lowlmiflivaeblgbyxkxrbt3nq we introduce a data set and approach for systematically modeling this child-adult grammar provide a corpus of errorful child sentences annotated with adult-like rephrasings. model trained on our corpus that predicts a grammatical rephrasing given an errorful child sentence. The parameters of this noise model are estimated using our corpus of child and adult-form utterances, using EM to By automatically inferring adult-like forms of child sentences, our model can highlight and compare developmental trends of children over time using large We analyze the performance of our system on various child error categories, highlighting our model''s strengths (correcting be drops and morphological overgeneralizations) our data set.3 Resulting pairs of errorful child sentences and their adult-like corrections were split into After training our noise model, we apply the system to translate divergent child language to adultlike speech. the joint probability of the child sentence s and candidate translation ti, given by the generative model: work_lqd6yi6rlndzlkg35we4ycufqa In this study, we investigated the underlying brain networks in native speakers compared with proficient second language users while processing complex sentences. structures were processed by the same large-scale inferior frontal and middle temporal language networks of Furthermore, the second language users showed increased task-related connectivity from inferior frontal to inferior parietal regions of the brain, regions related to attention and cognitive complex sentence structures in a group of second language The processing of crossed dependencies in second language speakers is thus an interesting test bed to investigate Others propose that while the overall network for grammatical processing is very similar for the first and second language, there are activation differences. networks of native speakers and second language users and investigate, with activation and connectivity analyses of functional magnetic resonance imaging (fMRI) data, whether the second language user group for processing complex sentence work_lrdgtltc5rauvhtborqncq7uou Object schemas for grounding language in a responsive robot Keywords: object schema; language grounding; human-robot interaction; semantics schemas built from the processes provide object representations for planning and language use. object schemas assist the coordination of vision, touch, motor action, planning, and language use, in a tabletop object representations for language use and planning using the responsive behaviours, so a sensorimotor event In contrast, the reactive SMPA approach would use separate processes for collisionhandling and for building a model from sensory input to locate objects for verbal command processing. schemas and plan hierarchies out of interaction processes, information in the shared memory is coordinated planning system interacts with the belief context by using object schemas as targets for action and also as Likewise, a plan fragment process is bound to an object schema if actions and Interaction processes and the object schema model Interaction processes and the object schema model work_lt7hy66js5extgi7lfl3faat4a Event Time Extraction with a Decision Tree of Neural Classifiers In this paper we describe a new classifier for automatic event time extraction. document and can extract long-range relations between events and temporal expressions. possible TLINKs with the number of events and temporal expressions, resulting in more than 10,000 possible TLINKs for several documents in the TimeBank annotation for all pairs of events and/or temporal expressions in the same and in adjacent sentences. Day Events) happened at the document creation time. decides the relation between the event and the Document Creation Time (DCT). derive the final label given the information on the relevant temporal expressions, their relation to the event, Our previously presented baseline uses the extracted relations for Single Day Events and generates a set of tuples in which the event and the temporal expression (Input Text Features) for classifying the relation between those. Time Expressions, Events, and Temporal Relations. work_lxfkgxtl7za4dgjpbee5atxncy Stochastic computing (SC) is an alternative computing domain for ubiquitous deterministic computing whereby a single logic gate can perform the arithmetic operation Keywords Stochastic computing, Convolutional Neural Network, Deep learning, FPGA, IoT conventional binary in this specific use case, driving the rise of stochastic computing (SC). Stochastic computing in convolutional neural network implementation: a review. (2) How exactly is the CNN being computed/executed in the stochastic domain? computed stochastic streams can be converted back to the binary domain by using a simple activated convolution neuron block could perform as accurate as binary computing CNN Figure 19 Process flow in SC BNN, stochastic image generation methodology and the internal computing domain interchange. VLSI implementation of deep neural network using integral stochastic computing. A new stochastic computing methodology for efficient neural network implementation. Accurate and efficient stochastic computing hardware for convolutional neural networks. Neural Network (CNN) accelerators based on stochastic computing. work_lyz5e77pqfgn5owqleohcuxruq or maximum range and optimum energy level to select the best relay node to forward Keywords Opportunistic routing, Optimum energy, Threshold energy level, Relay node, Wireless routing using min-max range and optimum energy level for relay node selection in wireless sensor networks. packets to the destination node, the OR forwarder method selects a next-hop which is In this research work, a relay node selection method that uses maximum and minimum dead node, improved the network lifetime, and produced a higher receiving packet ratio select the forwarder node, it uses distance and energy level as in Eq. the single-path is congested, or the relay node has insufficient energy to forward packets In this method, the forwarder node is selected using energy-efficient metric. Thus, this research was carried out to propose a relay node selection method Opportunistic routing algorithm for relay node selection in wireless sensor networks. work_m2m35ilx25blzb7pdwwciv4riu applications assume that the data, obtained from the scans of the examined object, research has shown that also for an incomplete data set in the analyzed algorithm it is Keywords Computer tomography, Parallel algorithms, Incomplete set of data, Big Data, Implementation of the computer tomography parallel algorithms with the incomplete set of case of incomplete data set, whereas the algebraic algorithms can be successfully used convergence of such algorithms in case when the parallel computations are executed The algebraic algorithms, adapted to the problem with incomplete set of data, appeared Many authors have studied block and parallel algorithms Figure 6 Dependence of the reconstruction on λ parameter value for an equal number of threads. Convergence studies on iterative algorithms for image reconstruction. Implementation of the computer tomography parallel algorithms with the incomplete set of data Implementation of the computer tomography parallel algorithms with the incomplete set of data work_m3ktnhp6ojf3fkul4nelspot4a PM2.5 sensor and the wireless transmission module were Keywords-PM2.5 Sensor; Dust Monitoring; Temperature collect the PM2.5 in the scenic core area and transmit data in the data acquisition module, the key circuit, the alarm and the temperature data in a certain area through the dust MCU compares the collected data with the threshold, if the B. PM2.5dust sensor module concentration sensor module is the same with the single chip. CHARACTERISTICS OF DUST CONCENTRATION SENSOR structure of the dust concentration sensor is shown in Figure The structure of the dust concentration sensor The function and pin of the dust sensor is shown in Table signal from the single chip, the dust sensor controls the C. DS1820 temperature sensor module The data collection of the dust concentration is the key of When the power turns on, the dust monitoring sensor scenic area, and the sensor is opened to collect and transmit work_m4vkvi4ixvf4npuqtarxoap2m4 We propose a two step approach to selecting a dichotomization threshold. For example, in order to distinguish between positive and negative ties, since tie Here, we propose a two-step approach to dichotomizing. network data management software and dichotomize but our original question was about choosing a single dichotomization that would be used in all further choose the level of dichotomization that maximizes For each possible level of dichotomization, you measure betweenness centrality and predicted your valued data from your dichotomized we can use the emergent properties of the dichotomized networks themselves in order to identify the is to dichotomize the data set at every possible cutoff Now, to dichotomize valued data, we choose the threshold for dichotomization for social network Figure 8: DGG Women by Women dataset dichotomized at 4. Figure 8: DGG Women by Women dataset dichotomized at 4. #Dichotomize the network at all values data set and successive dichotomizations of it, we work_m5ynmpp4jnfqfaura642udcc4a Figure 2: An example of model propagation in a graph-structured LSTM. endorsement (Fang et al., 2016), is the task of interest in our work on tree-structured modeling of discussions. structure and timing are important in predicting popularity (Fang et al., 2016), the LSTM units include et al., 2016), our model makes use of the full discussion thread in predicting popularity. By introducing a forward-backward treestructured model, we provide a mechanism for leveraging early responses in predicting popularity, as with LSTMs; evaluation of the model on the popularity prediction task using Reddit discussions; and that characterizes a full threaded discussion, assuming a tree-structured response network and accounting for the relative order of the comments. The comment text features, denoted xct, are generated using a simple average bag-of-words representation learned during the training: bidirectional graph-LSTM model, language is helping identify overpredicted cases more than underpredicted ones. work_m77zzbb2kfbtxcgjfd5pecfqra Extracting instances of sentiment-oriented relations from user-generated web documents is sentiment-bearing expressions, and it can simultaneously recognize instances of both binary (polarity) and ternary (comparative) relations with regard to entity mentions of interest. Therefore, in this paper, we identify instances of both sentiment polarities and comparative relations for entities of interest simultaneously. Wiebe et al., 2005; Hu and Liu, 2004) in the following ways: i) both sentiment polarities and comparative relations are annotated; ii) all mentioned entities are disambiguated; and iii) no subjective expressions are annotated, unless they are part of entity expressions for training and can predict both sentiment polarities and comparative relations. mention-based relation instances expressed in a sentence. possible combinations of mention-based relation instances and their textual evidences (cf. edge correspond to an instance of mention-based relation and the associated textual evidence. sSoR and label the corresponding tuples with the relation types of the edges from an MRG. work_m7bikytkibezlorb42jgqtvbsi How to cite this article Darch and Borgman (2016), Ship space to database: emerging infrastructures for studies of the deep subseafloor Keywords Knowledge infrastructures, Scientific data, Microbiology, Long tail, Big science, Little support for researchers, and its data infrastructure, are designed to enable deep subseafloor infrastructure for the domain of deep subseafloor biosphere research and C-DEBI has Deep subseafloor biosphere research is a relatively new domain of study. As the deep subseafloor biosphere emerged as a domain of study, researchers adopted strategies was to build infrastructure specifically for deep subseafloor biosphere researchers, questions, IODP/IODP2 is an infrastructure that deep subseafloor biosphere research of IODP scientific activities to include deep subseafloor biosphere research required other circulation, and accessibility of data handled by the deep subseafloor biosphere researchers. of the single-domain and shared infrastructure, driven by the deep subseafloor biosphere Manage Research Data for the Deep Subseafloor Biosphere (Darch & Borgman, 2014). work_mety3a2v7zdilbbgj4lw5lxvte A model regarding the lifetime of individual source code lines or tokens can estimate lines or tokens change over the software''s lifetime. From the time that a line enters the code base of a project, for how long does it live, that is, that allow the tracking of the birth and death of individual source code lines and tokens To study source code evolution at the level of individual tokens as well as lines, Although lines of code are often used to measure software and its evolution, tracking project we could estimate the median lifespan of the line or token directly, by calculating the lines and the tokens that are part of the code base of a project at the last time we check. project, the lifetimes of lines that are changed by the same developer against those that Software function, source lines of code, and development effort work_meuao2faobcbtcmmnbk3wl5fju The individual electronic identification (EID) of cattle based on RFID technology (134.2 digital images of the animal would lead to the creation of a virtual archive of breeding Keywords Electronic identification, Digital Image, Bull morphology, Data sharing, Stakeholder, the RFID identification system for Charolaise breeding bulls with 3D imaging for virtual archive creation. The automatic RFIDbased identification of cattle will be part of the innovation process of animal recording, attributed to the morphology of the breeding bull has an impact on the economic value of the integration of RFID for animal identification with 3D images of the real bull for the Table 1 Scheme of the SWOT analysis carried out on the basis of intrinsic and extrinsic factors of the innovation of process for Charolaise bull morphological evaluation and appraisal of the genetic potential as a breeding bull through In the SWOT analysis of the evaluation process of Charolaise bull morphology, we work_mfo4kdtxkze3tmgueggfzpuxci We describe the Coefficient-Flow algorithm for calculating the bounding chain of an approach to ours using a combinatorial method to compute bounding chains of 1-cycles dimensional cycle, and we show that the proposed algorithm has a complexity which is linear method for calculating the minimum area bounding chain of a 1-cycle on a 2d mesh, that bounding chains of 1-cycles in 3-dimensional complexes, using a spanning tree of the dual In order to prove that the Coefficient-Flow algorithm solves problem (1), will use the form the corresponding bounding chain as computed by the Coefficient-Flow algorithm. the edges in blue form cycles, and the faces in red form the corresponding bounding chain as computed Table 1 Timing for computation of bounding chains using Coefficient-Flow, and using Eigen in its bounding chain using both Coefficient-Flow and by solving the sparse linear system as While the problem of finding a bounding chain for a given cycle in a simplicial complex work_mg56pigmxrfjtj5dkcxnsr4xhu Grounded Compositional Semantics for Finding and Describing Images with Sentences However, the sentence vectors of previous models cannot accurately represent visually grounded meaning. DT-RNNs outperform other recursive and recurrent neural networks, kernelized CCA and a bag-of-words baseline on the syntactic structure or word order than related models such as CT-RNNs or Recurrent Neural Networks Figure 1: The DT-RNN learns vector representations for sentences based on their dependency trees. use unsupervised large text corpora to learn semantic word representations. have used a compositional sentence vector representation and they require specific language generation techniques and sophisticated inference methods. In order for the DT-RNN to compute a vector representation for an ordered list of m words (a phrase or sentence), we map the single words to a vector space Figure 3: Example of a DT-RNN tree structure for computing a sentence representation in a bottom up fashion. work_mgv666kn3fcufdf2mxqysdu35m sys_1000 wp-p1m-39.ebi.ac.uk wp-p1m-39.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265365159 (wp-p1m-39.ebi.ac.uk) Time: 2021/04/06 17:58:14 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_mhhvvbsh2vawzcijtr33odztki While traditional methods for calling variants across whole genome sequence data rely free variant calling method based on information theoretic principles designed to detect We found that our variants are highly informative for supervised learning tasks with performance similar to standard reference based Our method uses the context surrounding a particular nucleotide to define variants. dataset using a known reference sequence revealed variants associated with boxB repeat Our variant calling method comprises two steps: modelling the probability that a base provides a mechanism to call variants in a sample given a set of contexts, and the latter interested in finding contexts which define variants that differ amongst samples and are not Figure 5 First two principal components derived from alignment-based SNP calls (A) and from variants detected by our method (B) applied to the Massachusetts S. map the variant and its context back to a given reference. work_miwaidddzvcp3gsopaxl4ly7ae aim of the present study is to compare the children''s BMI growth between offspring exposed to maternal gestational diabetes mellitus (GDM) and those not exposed and assess the associations between maternal GDM and their offspring''s overweight Moreover, maternal GDM was associated with a higher risk of childhood maternal GDM is an independent risk factor of childhood overweight and obesity and is women who develop gestational diabetes mellitus (GDM) obesity between offspring exposed to maternal GDM and Table 2 Comparison of children''s measurements according to maternal gestational diabetes status. BMI, body mass index; GDM, gestational diabetes mellitus. the risks of offspring''s obesity and diabetes: GDM affected of maternal glucose and gestational weight gain on child obesity over Gestational diabetes and the risk of offspring obesity. risk in children exposed to maternal gestational diabetes mellitus 16 Li W, Liu H, Qiao Y, Lv F, Zhang S, Wang L, Leng J, Qi L, work_mowcu4jdxvfyvmw4r3nsi27c2e and then learn rules describing the dissonance treatment of each category with GP. Keywords Counterpoint, Rule learning, Palestrina, Genetic programming, Clustering, Algorithmic composition, Dissonance detection, Computer music automatically clustered into different dissonance categories (passing notes, suspensions Note that this algorithm does not implement any knowledge of the dissonance categories To initiate rule learning, our algorithm compiles for each identified cluster (dissonance category) a set of three-note-long learning examples with a dissonance as middle note. be used in the learnt rules: the duration of the dissonant note (durationi), its predecessor For each cluster (dissonance category) at least one learnt rule constrains the treatment Machine learning of symbolic compositional rules with genetic programming: Dissonance Machine learning of symbolic compositional rules with genetic programming: Dissonance Machine learning of symbolic compositional rules with genetic programming: dissonance treatment in Palestrina Machine learning of symbolic compositional rules with genetic programming: dissonance treatment in Palestrina work_mpnezfgmz5g6diku4y7puutx2i of sea-sky line detection, this paper presents a method of seasky line detection based on the mathematical morphology. operator is used to obtain the sea-sky boundary of the image, algorithm can accurately and efficiently detect the sea-sky line Keywords-Sea-sky Line; Mathematical Morphology; Edge makes the sea-sky line detection error in this kind of image; conclusion, this paper adopts multi-dimensional, multipleshape structure elements to process sea-sky images. The sea-sky line detection algorithm in this paper is interference points, so that the sea-sky line detection is more remove the interference points, so that the sea-sky line Sea-sky-line detected after mathematical morphological processing The images are results of sea-sky lines detection in Fig.8.The sea-sky-line detected by the algorithm in this sea-sky lines detection after the Gauss filter processing, it is sea-sky lines detection after the Gauss filter processing, it is element, the interference points of the sea-sky lines can be work_ms5ojw7dunfmhanpja5c5cgjse GILE: A Generalized Input-Label Embedding for Text Classification generalizes over previous such models, addresses their limitations, and does not compromise performance on seen labels. (iii) they are outperformed on seen labels by classification baselines trained with cross-entropy loss non-linear input-label embedding with controllable capacity and a joint-space-dependent classification unit which is trained with cross-entropy (ii) We propose a novel joint input-label embedding with flexible parametrization which generalizes over the previous such models and Joint input-output embedding models can generalize from seen to unseen labels because the parameters of the label encoder are shared. on the generalized input-label embedding outperforms previous models with a typical output layer Table 3: Full-resource classification results on general (upper half) and specific (lower half) labels using monolingual and bilingual models with DENSE encoders on English as target (left) and the auxiliary language as target work_ms7apx6u4vd7vjvtuih7h6vqx4 Word Embeddings as Metric Recovery in Semantic Spaces as metric recovery of a semantic space unifies existing word embedding algorithms, ties a simple, principled, direct metric recovery algorithm that performs on par with the state-ofthe-art word embedding and manifold learning co-occurrences through semantic similarity assessments, and demonstrate that the observed cooccurrence counts indeed possess statistical properties that are consistent with an underlying Euclidean To this end, we unify existing word embedding algorithms as statistically consistent metric recovery study, unifying existing algorithms as consistent metric recovery methods based on cooccurrence counts from simple Markov random two sections, we establish this connection by framing word embedding algorithms that operate on cooccurrences as metric recovery methods. distances between words using the negative log cooccurrence counts (Section 3), while manifold learning approximates semantic distances using neighborhood graphs built from local comparisons of the 3. Use a word embedding method on this corpus to generate d-dimensional vector representations of the data. work_msh6qeabq5gh7dweztzxd5tdvi Keywords Top active author, Research collaboration, Topic trends active authors are working on, we can also get a sense of the general research topic trends in top active authors can not only show the general trends in doing research in the academic dataset is shown in Fig. 1, where we plot the annual number of active authors and papers Figure 1 Number of active authors and papers each year in the time window [1960,2009]. the collaboration pattern by top active authors, we also show the coauthors set size of the number of papers per author in each active window starting from different years. networks based on the existence of collaboration links between top active authors in Research collaboration and topic trends in Computer Science based on top active authors Research collaboration and topic trends in Computer Science based on top active authors Research collaboration and topic trends in Computer Science based on top active authors work_mtxmsl6sa5d5zbxq2cv3ih2k6m https://www.research.manchester.ac.uk/portal/en/publications/matrix-depot-an-extensible-test-matrix-collection-for-julia(7b87af3d-1828-415b-8b50-be918548ac52).html https://www.research.manchester.ac.uk/portal/en/publications/matrix-depot-an-extensible-test-matrix-collection-for-julia(7b87af3d-1828-415b-8b50-be918548ac52).html Keywords Julia, Software package, Test matrices, Matrix algorithm., Test problems How to cite this article Zhang and Higham (2016), Matrix Depot: an extensible test matrix collection for Julia. The purpose of this work is to provide a test matrix collection for Julia (Bezanson Users can add matrices from the University of Florida Sparse Matrix Collection Matrix Depot; and they can define new groups of matrices that give easy access to subsets parametrized test matrices and real-life sparse matrix data. For example, the following command will group test matrices frank, golub, All the matrices in Matrix Depot can be generated using the function call The macro @addgroup is used to add a new group of matrices to Matrix Depot and the Matrix Depot contains a group of regularization test problems derived from Hansen''s Matrices from the University of Florida Sparse Matrix Collection are stored in work_mu26domt6fcunj7gbzgeaw3ypi (NDN) supports name-based routing and in-network caching to retrieve content in content poisoning attack mitigation schemes more effective, secure, and robust. Keywords Content poisoning attacks, Named data networking, Maliciousconsumer interestpacket, � Detection and mitigation of the flooding attack of special interest packets generated to fill the cache with unwanted content in the NDN router by demanding the data packets When this packet reaches a particular router, it enables cached contents'' on-demand data packet as it is considered a malicious consumer upon hitting the threshold value. during the special interest packet flooding attack by a malicious consumer. Figure 7 Flooding attack with no threshold value and with two malicious consumers. Figure 7 Flooding attack with no threshold value and with two malicious consumers. Figure 7 Flooding attack with no threshold value and with two malicious consumers. Detection of malicious consumer interest packet with dynamic threshold values Detection of malicious consumer interest packet with dynamic threshold values work_mukxqnihnrepzo7h2b4dlvnabe Adaptively Truncating Gradient for Image Quality Abstract—Objective image quality assessment (IQA) the upper threshold, and we propose an IQA index images is presented by changes in intensity value or The gradient feature is sensitive to image the FSIM and GMSD, the image gradient magnitude is evaluate the image quality in the HVS perception space. an IQA index based on the adaptively truncating image content, and the adaptively truncating gradient is define the adaptively truncating gradient to measure the local quality of the distorted image is predicted by the The overall quality score of the distorted image is The TID2008 database consists of 25 reference images database contains 30 original images and 886 distorted COMPARISON SROCC FOR INDIVIDUAL DISTORTION OF TEN IQA METRICS ON TID2013 DATABASE. similarity index for image quality assessment," IEEE Trans. similarity index for full-reference image quality assessment," IEEE for image quality assessment," IEEE Signal Process. work_mxer45347banlgbuvlsc43gz5m map arithmetic word problem text to math expressions, by learning to select the relevant Consequently, there has been a growing interest in developing automated methods to solve math word problems (Kushman et al., 2014; Hosseini et al., 2014; We focus on arithmetic word problems, whose solution can be obtained by combining the numbers in the problem with basic operations (addition, subtraction, multiplication or division). For combining a pair of numbers or math subexpressions, our method first predicts the math concept that is needed for it (e.g., subset relationship, dimensional analysis, etc.), and then predicts a declarative rule under that concept to infer the mathematical operation. arithmetic word problems, as well as the declarative rules for each concept. of research automatic word problem solving, semantic parsing, and approaches incorporating background knowledge in learning. In this paper, we introduce a framework for incorporating declarative knowledge in word problem solving. work_mxyrjrwatzbxze2i7rhlholzum learning between two (source and target) classification tasks or aspects over the same domain. sentence-level aspect relevance to learn how to encode the examples (e.g., pathology reports) from the can be adjusted only based on the source class labels, and that it also reasonably applies to the target encodings, we must align the two sets of encoded examples.2 Learning this alignment is posinvariant representation, we introduce an adversarial domain classifier analogous to the recent successful use of adversarial training in computer vision (Ganin and Lempitsky, 2014). in our approach, 1) aspect-driven encoding, 2) classification of source labels, and 3) domain adversary, (aspect transfer) as well as on a more standard review dataset (domain adaptation). Domain Adaptation for Deep Learning Existing approaches commonly induce abstract representations without pulling apart different aspects in the methods first learn a task-independent representation, and then train a label predictor (e.g. SVM) work_n2ajueo2ozfp5hcybnms5ep22a We jointly model paraphrase relations between word and sentence model also captures lexically divergent paraphrases that differ from yet complement previous methods; combining our model with previous work significantly outperforms the stateof-the-art. Our approach to extract paraphrases from Twitter is general and can be combined with various topic detecting solutions. paraphrase identification, that specifically accommodates the very short context and divergent wording in Twitter data. 2 Joint Word-Sentence Paraphrase Model sentence-level annotations in our paraphrase corpus: In total, we constructed a Twitter Paraphrase Corpus of 18,762 sentence pairs and 19,946 unique sentences. Table 2: Performance of different paraphrase identification approaches on Twitter data. labels derived from 5 non-expert annotations on Mechanical Turk, which can be considered as an upperbound for automatic paraphrase recognition task We filter the sentences within each topic to select more probable paraphrases for annotation. paraphrase task requires additional sentence alignment modeling with no word alignment data. work_n3xwttbopngatcfdmiu7tbqtxu Keywords Active learning, Bandit, Rank aggregation, Benchmark, Multiclass classification propose to combine active learning suggestions with bandit and rank aggregation In active learning, we use the class probability estimates from a trained classifier to learning, where we select an object from a pool of unlabeled examples at each time step, estimate the true classifier performance using only the training set. Algorithm 2 Pool-based active learning with bandit theory. learning heuristics ℛ and the test set ℒS, some bandit algorithms also need to know n, the maximum active learning heuristics ℛ, and bandit algorithm b with two functions SELECT and UPDATE. for each i and select heuristic r� that has the highest sampled value of the mean reward: Figure 2 Active learning pipeline with rank aggregation methods. Input: unlabeled set U, labeled training set ℒT, classifier h, set of active learning suggestions R, ranking learning heuristics, five bandit algorithms, and three aggregation methods. work_n4o7bftya5ej7jassfu3b5i6zi sys_1000 wp-p1m-39.ebi.ac.uk wp-p1m-39.ebi.ac.uk exception exception Params is empty Params is empty Params is empty if (typeof jQuery === "undefined") document.write(''[script type="text/javascript" src="/corehtml/pmc/jig/1.14.8/js/jig.min.js"][/script]''.replace(/\[/g,String.fromCharCode(60)).replace(/\]/g,String.fromCharCode(62))); // // // window.name="mainwindow"; .pmc-wm {background:transparent repeat-y top left;background-image:url(/corehtml/pmc/pmcgifs/wm-nobrand.png);background-size: auto, contain} .print-view{display:block} Page not available Reason: The web page address (URL) that you used may be incorrect. Message ID: 265368419 (wp-p1m-39.ebi.ac.uk) Time: 2021/04/06 17:58:18 If you need further help, please send an email to PMC. Include the information from the box above in your message. Otherwise, click on one of the following links to continue using PMC: Search the complete PMC archive. Browse the contents of a specific journal in PMC. Find a specific article by its citation (journal, date, volume, first page, author or article title). http://europepmc.org/abstract/MED/ work_n4uw6vwblfdcpfokkebmfw6sxe Overcoming Language Variation in Sentiment Analysis with Social Attention novel attention-based neural network architecture, in which attention is divided among several basis models, depending on the author''s could in principle be applied to any language processing task where author network information is We apply SOCIAL ATTENTION to Twitter sentiment classification, gathering social network metadata for Twitter users in the SemEval Twitter sentiment analysis tasks (Nakov et al., 2013). social networks to train user embeddings. Convolutional neural network (CNN) has been described in § 4.2, and is the basis model of SOCIAL where we report results obtained from author embeddings trained on RETWEET+ network for SOCIAL ATTENTION. With the incorporation of author social network information, concatenation slightly improves Table 5: Top 5 more positive/negative words for the basis models in the SemEval training data. As shown in Table 5, Twitter users corresponding to basis models 1 and 4 often use some words work_n5p27oi6fzbm7nfia6k365h77e for initial registration, and the traditional ICP algorithm Fast Point Feature Histograms) are used to realize SACIA algorithm and ICP precise registration algorithm. data; the registration algorithm based on fast point Keywords-Point Cloud Registration; SAC-IA many times, and the point cloud registration algorithm whole 3D model, so point cloud registration has and accurate registration for two groups of point cloud descriptors in the initial registration algorithm and POINT CLOUD REGISTRATIONS The principle of point cloud registration algorithm the feature descriptors in the two sets of point cloud In the initial registration algorithm of point cloud, LCP, the registration accuracy of the point cloud can be SAC-IA algorithm registration based on 3Dsc, PFH cloud data is accurately registered by the ICP algorithm. error between the two point clouds of the registration descriptors and ICP precise registration algorithm is the initial registration, SAC-IA algorithm based on registration with a small number of point clouds and work_n64oj7fev5b33kne2prdmnt674 Keywords SPL, DSL, Domain engineering, Dashboards, Employability, Code generation paradigm to generate customized user interfaces for decision-making processes: a case study on university employability. line (generally following a feature model (Kang et al., 1990) allow stakeholders to build of generating customized dashboards can be seen as a specific case of graphical user models by developing a context-aware data visualization tool that can be adapted during That is why software product lines rely on feature models (Kang In this domain, the feature model will capture the dashboards'' visualization components, For the Observatory''s dashboards, three main configurable visual components (features) These high-level features of the dashboards'' product line are presented source code, providing a higher level language to specify the dashboards'' features, as well Finally, the customization levels of the dashboards'' visual design and data dashboards through software product line paradigms to analyse university employment and employability data. work_n6tm7logj5axzews3emhc2ok6i Keywords Parallel processing, GPU computing, Entropy estimator, NIST SP 800-90B, Random Table 1 Execution time of each single-threaded NIST program for the entropy estimation process the developer should run the NIST program k times when the RNG uses k noise sources. Table 5 Performance of proposed GPU-based parallel implementation of permutation testing depending on whether memory coalescing technique was used (the number of CUDA blocks = 16, the Figure 8 Operation times of CUDA threads in kernel Statistical test when applying each method Table 8 Execution time of kernel Statistical test according to parallel method (number of threads Figure 9 Execution time of the GPU-based parallel implementation of permutation testing according Table 9 Execution time of the GPU-based parallel permutation testing according to the value of the the noise source was determined as the IID by all 18 statistical tests in our GPU-based work_n76p34ulzzhl3bferrd3xk3pgu high precision knowledge base (KB), containing general (subject,predicate,object) statements about the world, in support of a downstream question-answering (QA) application. and a novel canonical schema learning algorithm (called CASI), that produces high precision knowledge targeted to a particular domain in our case, elementary science. able to extract (subject,predicate,object) tuples relevant to a domain with precision in excess of 80%. Second, we present a novel canonical schema induction method (called CASI) that identifies clusters of similar-meaning predicates, and maps them use an (independent) corpus of domain text to characterize the target science knowledge, and measure useful, these resources have been constructed to target only a small set of relations, providing only limited coverage for a domain of interest. this work we combine semantic high-quality features from WordNet, Moby thesaurus with weak distributional similarity features from AMIE to generate schema mapping rules. Table 3: Precision and coverage of tuple-expressible elementary science knowledge by existing resources vs. work_n7lby2rebfcctik64fikdfchni power consumption of the terminal, which use two sensors, one vehicle passes by, the spring switch wakes up the CPU and the Keywords-Vibration Detection; Zigbee; Micro-power low power consumption of ZigBee network and terminal uses CC2530 chip for ZigBee communication. short switching time and low power consumption. Initialize network coordinators shown in Figure 3. the network, the parent node (including the coordinator) D. Nodes join the network through Coordinator The node sends the association request command to to join the association request command, the node Mac the node sends the data request command to the nodes to join the ZigBee network. For a node, only if it has not joined the network can For a node, only if it has not joined the network can For a node, only if it has not joined the network can For a new node, it first scans the network it can find work_nbt6xi4mqjfi3ak2y5mzy6dndi constraint graph can break the structure learning task into independent subproblems How to cite this article Schreiber and and Noble (2017), Finding the optimal Bayesian network given a constraint graph. a super-structure, because constraint graphs are defined over sets of variables instead of be represented as a simple cycle in the constraint graph, such that the variables in node A constraint graph, all SCCs will be single nodes, and in fact each variable can be optimized from the constraint graph and the learned Bayesian network. graph contains six nodes, the opening and closing prices for each of the three markets. Constraint graphs allow learning of Bayesian network classifiers Bayesian network instead of a node in the constraint graph. cycles where we increase the number of variables in each node of the constraint graph and proposed for learning the structure of a Bayesian network given hidden variables (Elidan work_ndtqmncagrai7ec23g3kd4qk34 Angelidis, S & Lapata, M 2018, ''Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis'', learns to predict the sentiment of text segments, i.e. sentences or elementary discourse Instead of learning from individually labeled segments, our model only requires document-level supervision and learns to introspectively judge the sentiment of constituent segments. final sentiment prediction is produced using a softmax classifier and the model is trained via backpropagation using sentence-level sentiment labels. 2When applied to the YELP''13 and IMDB document classification datasets, the use of CNNs results in a relative performance decrease of < 2% compared Yang et al''s model (2016). Given a review, we predict the polarity of every segment, allowing for the extraction of sentiment-heavy opinions. classifier would learn to predict the document''s sentiment by directly conditioning on its segments'' feature representations or their aggregate: Figure 6 illustrates the distribution of polarity scores produced by the two models on the Yelp''13 dataset (sentence segmentation). work_nfb3nb2bjzgehk6wxpj525oqka measure stress in controlled experiments that is tailored to software engineering Keywords Stress, Software development, Biological markers, Methodology, Psychological assess, and understand stress responses of individuals and groups of developers, it is detecting stress, research in software engineering has focused on machine learning and due to the many medical, psychological, and biological ways to measure stress and on research on physical stress which the average software developer is not likely to experience We propose to assess stress, emotional state and cognitive load of participants, where the the personal stress levels and emotional state measured at the start and end of a task. the task under research and before the questionnaires assessing the personal stress level Table 2 Pre and post-experiment task values for ESR factors, control group, pilot, sample size = 11. A methodology for psycho-biological assessment of stress in software engineering A methodology for psycho-biological assessment of stress in software engineering work_nfiznlqmc5dubdw66g2y4lqila Keywords Ramp signal optimization, Correlation analysis, GRU neural network Coordinated ramp signal optimization framework based on time series In this article, we propose a coordinated ramp signal optimization framework based The traffic data of the congested road and ramps are predicted by the traffic flow prediction method and the time-series correlation measurement; In this article, we use the GRU neural network for traffic flow prediction. data pre-processing, traffic flow analysis and signal optimization scheme generation. is obtained by combining distance, ramp flow and traffic correlation. traffic flow time series data is continuous observed values collected by a loop detector This article uses neural network and time series methods to analyze dynamic traffic We model multi-ramp section in SUMO, and entering the traffic flow data during the Coordinated ramp signal optimization framework based on time series flux-correlation analysis Coordinated ramp signal optimization framework based on time series flux-correlation analysis work_nfqwywp3onayzkcizcm2w6ysqi Reliability study, SaaS quality, Software as a service Development of a valid and reliable software customization model for SaaS quality through iterative method: perspectives from academia. customization model for SaaS quality that was initially constructed in (Ali et al., customization practices of each type, and quality attributes of SaaS applications associated customization options, followed by the literature on quality models for SaaS applications. multi-tenant SaaS applications: desktop integration, user-interface customization, and Table 3 Multi-tenant SaaS customization practices of Personalization approach. Table 4 Multi-tenant SaaS customization practices of Configuration approach. Table 5 Multi-tenant SaaS customization practices of Composition approach. In its final version, the software customization model for SaaS quality consisted of 45 From the initial development of the software customization model for SaaS quality therefore, to develop a software customization model for SaaS quality to identify possible customization approaches, practices, and quality attributes in the SaaS Multi-Tenant work_ngj3u2h4ubaajm7sugmsj4gobi Exploring Neural Methods for Parsing Discourse Representation Structures https://research.rug.nl/en/publications/exploring-neural-methods-for-parsing-discourse-representation-structures(0abd0fff-f63b-44ff-bd7e-a7dc01acc782).html Semantic parsing is the task of mapping a natural language expression to an interpretable meaning representation. DRSs are recursive structures and thus form a challenge for sequence-tosequence models because they need to generate DRS parsers based on supervised machine learning emerged later (Bos, 2008b; Le and Zuidema, 4. Does adding silver data increase the performance of the neural parser? that can be (re-)trained on individual data sets, using the tokenized sentences of the published silver word-level neural parsers (10-fold CV experiment For factor (ii), we use our own best parser (without silver data) to parse the sentences in the PMB Table 8: Test set results of our best neural models Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, semantic parsing by character-based translation: Experiments with abstract meaning representations. work_ni24u3psuvbs5nb2fztgr6z4ba level-induced increased iron deposition in β-cells and the relationship between abnormal tissue isolated from db/db mice, cultured islets and Min6 cells in response to high glucose excessive iron on mitochondrial function eventually resulted in impaired insulin secretion. role of hepcidin in the glucotoxcity impaired pancreatic β cell function pathway. on blood glucose levels by decreasing iron intake or Low hepcidin expression induces iron overload in Hepcidin content was analyzed in isolated islets using an ELISA method with different concentration of glucose treatment for 48 h. control, Ad-hepcidin, Ru 360 and iron chelator groups control, Ad-hepcidin, Ru 360 and iron chelator groups Effects of iron restriction on blood glucose levels and Min6 cells were infected with Ad-hepcidin or treated with RU 360 or an iron chelator plus 33.3 mM glucose. hepcidin expression in Min6 cells with 33.3 mM glucose Low hepcidin expression induces iron overload in pancreatic β-cells work_nj6cpocaafedndn4c5yt5dstbu names and web pages that link to Wikipedia; (3) detailed development experiments, including analysis they learn entity representations based on similarity between link contexts and article text in Wikipedia. models derived from popularity metrics; alias models derived from Wikipedia redirects, disambiguation pages and inter-article links; textual context On the CoNLL development data, BOW context derived from Wikipedia article text achieves 50.6 p@1. We also build entity models from their mention contexts, i.e., the combined text surrounding all incoming links. Refer back to Table 2 for p@1 results for individual Web link components on the development data. Table 5 compares Wikipedia and Wikilinks coverage of entities from the CoNLL development set. The article, mention and web link models each attain their best performance with all component features (entity, name, BOW, and DBOW): 84.7, 81.1, Adding mention context features doesn''t improve the more conventional Wikipedia article model. replace Wikipedia derived data in entity linking. work_njhxoq7ltbf4pdaovqxbwx56nu The Reform and Innovation of Ideological and Political Teaching Under the Multimedia multimedia technology in teaching has greatly changed the technology to the ideological and political course in colleges multimedia technology to assist our teaching in ideological and Keywords-Multimedia Technology; Ideological and Political political class multimedia technology problems, the author Network multimedia technology assisted teaching map TEACHING OF IDEOLOGICAL AND POLITICAL COURSES students interest in learning for ideological and political Multimedia technology assisting the teaching process of D. Improving students'' memory of teaching content process of ideological and political teaching, how to make teachers never use multimedia technology in the normal multimedia technology is applied to the teaching material multimedia technology in university ideological and political ideological and political teaching in colleges and universities. The teachers of the ideological and political education multimedia technology to teach and reasonably allocate time Countermeasures of Multimedia Teaching in Ideological and Political work_njxbtq4pdzcqpdgnxubcg3qk54 Keywords Cognitive, Recognition, Emotions, Gaze-tracking The manuscript presents an extension of our work on the development of gaze trackingbased emotion recognition system (Viola & Jones, 2004; Raudonis et al., 2013). combination of EEG and gaze tracking over a display of database of emotional videos Gaze tracking-based emotion detection method must evaluate an individual motion of 3 finding the relationship between a gaze point and a displacement of the eye pupil The eye pupil is detected in a mapping image Mp. Each resulting point cloud in Mp is Figure 3 The eye iris and measurements to calculate a gaze point. four different emotional states: (A) neutral, (B) disgust, (C) shame and (D) sensory pleasure. Figure 7 Average pupil size of first six participants who were stimulated with four different emotional Using pupil size variation during visual emotional stimulation in measuring affective states of non communicative individuals. Eye gaze patterns in emotional pictures. work_nkcageyhhnffraxcotcfqod4q4 Rheological Properties of Pullulan and Aloe Vera The mixture of 13% pullulanaloe vera can be pumped with a minor effects on the properties of aloe vera. we investigate the rheological properties of pullulanaloe vera nanofibers, which will provide insight into prepare the nanofibers, first aloe vera leaves were first vera were prepared to study the rheological properties the first study to prepare pullulan-aloe vera nanofibers properties of aloe vera, pullulan is used as a carrier to pullulan and Aloe Vera, the complex modulus Elastic and viscous modulus of a mixture as a function of frequency at 19 oC. mixture of pullulan and aloe vera with respect to stress. The mixture of pullulan and Aloe vera is The mixture of pullulan and Aloe vera is behavior of the mixture of pullulan and aloe vera. It is concluded that the mixture of 13% pullulan-aloe [13] Coats B.C. Method of Processing Stabilized aloe Vera gel Obtained work_nkdki33fzvgtxnrotut7r4jdqe mostly rely on setting default values for kernel hyperparameters or using grid search, Our proposed approach for model selection relies on Gaussian Processes (GPs) (Rasmussen and allows us to easily propose new rich kernel extensions that rely on a large number of hyperparameters, which in turn can result in better • Since the model selection process is now finegrained, we can interpret the resulting hyperparameter values, depending on how the kernel is data (§4) and two real NLP regression tasks: Emotion Analysis (§5.1) and Translation Quality Estimation (§5.2). Table 1: Resulting fragment weighted counts for the kernel evaluation k(t,t), for different values of hyperparameters, where t is the tree in Figure 1. and SVM models we employ the SSTK as the kernel Our experiments with NLP data address two regression tasks: Emotion Analysis and Quality Estimation. Models We perform experiments using the following tree kernels: our models in this task use a pair of tree kernels. work_npdyuzu3pngqnlqxfq3y2p2gaa Image Inpainting Research Based on Deep Learning effectively improves the problems of poor image inpainting Keywords-Image Inpainting; Generation Adversarial inpainting the damaged area of the image[1-2]. and deep learning-based image repair methods. structure-based image repair technology and texture synthesis-based image inpainting technology. image inpainting algorithms based on structure and hotspot in the field of deep learning image inpainting, The foundation of image inpainting technology based which makes the image inpainting technology develop the path and use the given masked image to inpainting. generation path to encode; (2)The extracted two image network structure and use five-layer convolution. data processing is completed, the image inpainting task in the inpainting image, and M * N represents the area In this paper, the image inpainting network structure update the network parameters to inpainting the image, not only the similarity of the inpainting image structure, Image Inpainting via Generative Image Inpainting via Generative work_nptfrj23brdvvauxagfvg2dske Although all visualizations produce similar quality labels, simple visualizations such as word lists allow participants to quickly understand topics, while These sets of words or "topics" evince internal coherence and can help guide users to relevant To better understand these problems, we use labeling to evaluate topic model visualizations. topic, while a second set of users assessed the quality of those labels alongside automatically generated of topics, while more complex visualizations (network graph) take longer but reveal relationships between words. Automatic labels are generated from representative Wikipedia article titles using a technique similar to Lau et al. Additionally, the word list, word cloud, and network graph visualizations all lead to labels with similar "best" and "worst" votes for both the top and that the network graph helps users to better understand the topic words as a group and therefore label them using a hypernym. work_nq37vdnimjagpmgma7pomew6b4 collaborative filtering algorithm with the decision tree algorithm, create a collaborative filtering decision tree collaborative filtering decision tree algorithm on the Hadoop random analysis (sampling survey), the big data model big data model based on collaborative filtering. recommendation algorithm combines the decision tree data set processed by the decision tree, and vote. contact with users, Random Forest will not recommend time, AHP improved collaborative filtering algorithm recommendation algorithm cannot treat all user Step 2: The user''s rating data for the brand. need to calculate the user''s rating value for the brand. recommended to the user u based on the result of the random forest recommendation algorithm and the collaborative filtering recommendation algorithm, the random forest model can recommend brands that users filtering algorithm recommends brands that have not collaborative filtering algorithm can be calculated collaborative filtering algorithms and the result final collaborative filtering recommendation algorithm work_nu5xpentbrcxdlcdt3lmatbur4 This paper introduces the problem of predicting semantic relations expressed by prepositions and develops statistical learning models model the preposition relation and its arguments along with their semantic types, as a This paper addresses the problem of predicting semantic relations conveyed by prepositions in text. to model the predicate (i.e. the preposition relation) and its arguments (i.e. the governor and object). types to predict the preposition relation label. their types jointly and propose a learning algorithm that learns to predict all three using training data that annotates only relation labels. To aid better generalization and to reduce the label complexity, we follow this line of work to define a set of relation labels which abstract word senses across prepositions2. that our training data only annotates the relation labels and not the arguments and types. The first model aims at predicting only the relation labels and not the arguments and types. work_nux47c5vxngynfvamxfsjsk2bu Trunk fat and leg fat in relation to free impedance analyzer was used to measure total, trunk, arm and leg fat mass (FM) and The leg fat mass to trunk fat mass ratio (LTR) was calculated to Conclusions: In euthyroid postmenopausal women, trunk fat was positively correlated with level of FT3 within the reference range was related to adverse fat distribution. leg fat% were both negatively related to FT3 (standardized women, while increased leg fat accumulation was related men, none of the fat parameters were related to thyroid FPG, fasting plasma glucose; HbA1c, glycated hemoglobin A1c; HDL-c, high-density lipoprotein cholesterol; HOMA-IR, homeostasis model assessmentinsulin resistance; LDL-c, low-density lipoprotein cholesterol; LTR, leg fat mass to trunk fat mass ratio; SBP, systolic blood pressure; TC, total cholesterol; trunk fat ratio was negatively related to insulin resistance that trunk fat parameters were positively related to FT3 and that leg fat parameters were negatively related to work_nw3etn3etra45jwazg6txw2oly We address the task of joint training of transliteration models for multiple language pairs encoder-decoder model that maximizes parameter sharing across language pairs in order training multiple language pairs (referred to as multilingual transliteration henceforth). Multilingual transliteration can be seen as an instance of multi-task learning, where training each In this work, we explore multilingual transliteration involving orthographically similar languages. We propose that transliteration involving orthographically similar languages is a scenario where multilingual training can be very beneficial. output layer for target languages, but share the encoder, decoder and character embeddings across languages. The multilingual transliteration task involves learning transliteration models for l language pairs across all language pairs used to train the multilingual model is equivalent to the size of the bilingual target languages are covered, we use the trained multilingual model discussed in previous sections for the multilingual transliteration models can generalize well to language pairs not encountered during work_nx6kkwvy6bb4bkkqnpld6s7gty Hierarchical Image Object Search Based on Deep hierarchical deep reinforcement learning object Keywords-Object Detection; Deep Learning; continuously improve the object positioning speed is Traditional object detection algorithm Traditional object detection algorithm The traditional object search algorithm has the B. Object detection algorithm based on deep learning based on deep learning uses CPMC, Selective Search, C. Object detection algorithm based on deep learning technology in the field of object detection. HIERARCHICAL OBJECT SEARCH MODEL BASED Decision Process, and find an effective object detection process of learning to obtain high cumulative reward The reward function for the stop action According to the state, action and reward function, C. Hierarchical object search process CNN neural network model to extract feature values, search, or use the learned strategy to make action This paper propose an object detection model based model can effectively detect the object in the image. object detection with region proposal networks[C]//Advances in work_nyaahrjgj5h4hbe4yk5dmjq6d4 applying this approach to an existing citizen science dataset to classify images into Keywords Citizen science, Bayesian estimation, Data classification, Algorithms Using demographics toward efficient data classification in citizen science: in citizen science to accurately estimate reliability of each volunteer with only a few information toward enhancing data accuracy while safeguarding volunteers'' effort. and rank participants in citizen science projects based on their reputation, with the final accuracy by harnessing diversity of volunteers in citizen science. The data used in this study were collected within a citizen science project for obtaining volunteers considered to classify the i-th image, and of classification accuracy w, evaluated as In this study, we proposed a Bayesian approach to enhance data quality in citizen science Demographics toward Efficient Data Classification in Citizen Science: A Bayesian Using demographics toward efficient data classification in citizen science: a Bayesian approach Using demographics toward efficient data classification in citizen science: a Bayesian approach work_o3awhuaaxngcjmt2ayuw4avejy portion of the header are optional fields whose length is increases the IPv4 32 bit address length reduced to 16 processing on packet control and to limit IPV9 header and the destination address of IPV9 packet is specified. address field in the IPV9 header (or, if it is a multicast Option data length: 8-bit unsigned integer. length of the data field for this option, in 8-bit groups. of fill bits into the header option field. groups, the value of the option data length field should bit group of the data segment header. The routing header length is in 8-bit groups IPV9 source hosts use segment headers to send The destination option header length is in 8-bit Optional destination information in IPV9 packets is IPV9 to identify the data packets in the source node The 8-bit Category Type field in the IPV9 header have a value of 50 in its protocol field (if IPv4 header) work_o46l7yr5gjexfd6bydo6qftijy associated with bone parameters in patients Background: Biochemical control of GH/IGF-I excess in acromegaly (ACRO) is associated Aims: Identify differentially expressed miRNAs in the serum of patients with controlled ACRO vs controls and correlate miRNA levels with both biochemical and structural bone controlled ACRO patients and associated with bone structural parameters. ACRO patients show increased bone turnover and described in ACRO patients despite biochemical control the serum of patients with controlled ACRO as compared miRNAs are related to bone parameters in our patients, miRNAs and bone parameters in ACRO patients are Table 1 General, biochemical and bone characteristics of 27 patients with controlled acromegaly (ACRO) and 27 healthy score; vBMD, (volumetric bone mineral density) is expressed as mg/cm3. Table 2 miRNA expression levels in 27 controlled ACRO patients and 27 sex-, ageand BMI-matched controls. status of controlled ACRO patients and trabecular vBMD Differentially expressed microRNAs ACRO vs controls Differentially expressed microRNAs ACRO vs controls work_o5yf5ggv6nefzovxdmf5l4n2iu Thechoice ofthe modelhas itstradeoff: high-capacity models provide good estimations of the divergence, but, generally, proposed divergence family suggests using low-capacity models to compare distant Adversarial Optimization (AO), introduced in Generative Adversarial Networks (Goodfellow et al., 2014), became popular in many areas of machine learning and beyond with The proposed divergence family suggests using low-capacity models to compare models generally require fewer samples for training, AD allows an optimization algorithm same models as JSD with linear and logarithmic capacity functions, dashed lines represent some pseudodivergences from the families producing adaptive divergences. Require: XP, XQ — samples from distributions P and Q, B — base estimator training algorithm, N — maximal size of the ensemble, c :Z+→[0,1]— capacity function; ρ — Algorithm 3 Adaptive divergence estimation by a dropout-regularized neural network Algorithm 4 Adaptive divergence estimation by a regularized neural network regularization methods can be used to regulate model capacity in adaptive divergences. work_o6gmakdor5esthz2os3fr7tb4q case training with noise is a very effective app roach fo r sm oothing the estim ator. noise increase s the independence betw een diffe rent training sets, we can use optim al noise levels shou ld not be based on a single estim ator perform ance, b ut · F or a noise level « j estim ate an op tim al penalty term fo r weight decay l i : differen t m easurem ents, it is best to estim ate the diffe rent noise levels in each perfo rm ance of a ® ve-n et ensem ble trained with optim al weight decay. 40-n et ensem b le ave raging resu lts, with no weight decay and no noise are better Effe ct of training with diffe rent noise levels on ® ve-n et ensem b le networks com po nents: w eight decay, noise injection and ensem ble averag ing. work_o7rrr6k3uzbx5cpynca7plmmwy Keywords-Image Recognition; Deep Learning; Machine Learning; Convolutional Neural Networks DBN (Deep Belief Network), CNN (Convolutional CNN, compared to other network models, are better multi-cryptic neural networks have better feature the feature extraction function of convolutional neural development, from MP models, BP neural networks, to structure, and network training methods. the network structure (not just the CNN), and there are convolutional neural networks is not significant, percentage of the neural network convolutional layer. Zhang proposed a parallel network model based on convolutional neural networks for military target detection operators to extract the target image features neural network for deep feature extraction, which convolutional neural networks based on Faster RCNN of convolutional neural networks and will directly A Convolutional neural network A Convolutional neural network deep convolutional neural network [D]. convolutional neural network in pathological image classification of based on parallel convolutional neural network[J]. technology based on deep convolutional neural network [D]. work_oa2gtpcm7vdbji3sjl376w7e2u this problem, we created variants of the images by applying data augmentation methods. the collected malware samples are converted into binary file to 3-channel images This study uses five different deep CNN model for malware family detection. Keywords Convolutional neural networks, Cybersecurity, Image augmentation, Malware analysis based on creating a grayscale image from malware code and then using classification family classification model that exploits augmentation for malware variants and takes Herein, we demonstrate that the data augmentation-based 3-channel image classification from these studies because we used five different deep CNN models for malware family is applying data augmentation enhanced malware family classification model. samples according their family using malware images based CNN model. malware detection model with the best classification performance. malware environment using an image augmentation enhanced deep CNN model. Imbalanced malware images classification: a cnn based approach. Data augmentation based malware detection using convolutional neural networks Data augmentation based malware detection using convolutional neural networks work_oalnvw4najdf3bpfwxz2hqcpvu MathML / XML series: An introduction....MSOR Connections Nov 2005 Vol 5 No 4 The eXtensible Markup Language (XML) is changing the way the worldworks...The word processor used to write this piece is storing the text and Internet Explorer browser [1], uses the XML language XUL to describe its user XML is free to use, platform independent, non-proprietary ''non-standard technologies'' like Linux, Firefox, a screenreader or a nonEnglish language can access the data equally. access the data from any platform, and being able to use an XML resource into Using the XML implementation MathML, one arrives at a free, open, platform While MathML is obviously the XML format of most specific relevance for the MathML / XML series: An introduction Peter James Rowlett MathML or another XML format? store data as XML? • Does your statistical package use XML for data NASA XML Project [online], 2005. http://xml.nasa.gov/ [Accessed 13 October 2005]. work_oasf2ferpfgbnb5o62kmo4m3b4 Whole genome alignments and comparative analysis are key methods in the quest of us to develop our new tool AliTV, which provides interactive visualization of whole AliTV reads multiple whole genome alignments or automatically interactive co-linear visualization of multiple whole genome alignments with feature visualization) designed for interactive visualization of multiple whole genome alignments. genome alignments, rapidly explore the results, manipulate and customize the visualization library D3.js 3.5.17 (http://d3js.org/, 06.06.2016) provides a wide range of prebuilt functions for calculating and drawing the interactive figure. Table 1 Chloroplast genomes of the parasitic and non-parasitic plants used in the case study. Figure 1 Whole genome alignment of seven chloroplasts visualized by AliTV. adjacent genomes, it is apparent that the non-parasitic plants (e.g., Olea europaea and representation of whole genome alignments is the limited comparability of non-adjacent Therefore, AliTV provides a way for the user to re-order the genomes on the Analysis of 41 plant genomes supports work_oavbptqpunch5jy27k3m3zb5yi FUSI-CAD: Coronavirus (COVID-19) diagnosis based on the fusion of CNNs and and DL features extracted from multiple CNNs trained with COVID-19 CT images. � Stage (1)—Deep features fusion: This is performed by extracting and fusing the deep � Fusing features extracted from the deep layers of CNNs to diagnose COVID-19 patients, multiple individual CNNs models with three powerful handcrafted features based on The proposed CAD system consists of four steps, which are image enhancement, feature Deep and handcrafted features fusion stage (FUSI-CAD System) The FUSI-CAD system proposed the fusion of DL and HC features to examine the effect Table 5 A comparison between the classification scores obtained by the DL, HC feature fusion, and the FUSI-CAD system. FUSI-CAD system was based on the fusion of multiple DL features and handcrafted FUSI-CAD: Coronavirus (COVID-19) diagnosis based on the fusion of CNNs and handcrafted features FUSI-CAD: Coronavirus (COVID-19) diagnosis based on the fusion of CNNs and handcrafted features work_ocrpsnsynrh2nb7fy3scvt4ltu Approximation-Aware Dependency Parsing by Belief Propagation Recent improvements to dependency parsing accuracy have been driven by higher-order features. parsers depend on approximate inference and decoding procedures, which may prevent them from predicting the best parse. In contrast, we train the parser such that the approximate system performs well on the final evaluation function. We treat the entire parsing computation as a differentiable circuit, and backpropagate the evaluation function through our approximate inference and decoding methods to improve models, Stoyanov and Eisner (2012) call this approach ERMA, for "empirical risk minimization under approximations." For objectives besides empirical risk, Domke (2011) refers to it as "learning with approximation-aware learning method in the parsing setting, for which the graphical model involves to those probabilities.3 When our inference algorithm is approximate, we replace the exact marginal and Eisner (2008)—is exact for first-order dependency parsing. regularized objective function over the training sample of (sentence, parse) pairs {(x(d),y(d))}Dd=1. work_oevkxmdnrjfp5akoxbszu576km If the goal is to correct verb errors, the grammatical mistake in the original sentence has been addressed and we can move on. evaluation metrics computed over error-annotated We explore different methods for corpus annotation (with and without error codes, written by experts and non-experts) Fundamentally, this work reframes grammatical error correction as a fluency task. Table 2: An example sentence with expert and non-expert fluency edits. grammatical (following the NUCLE annotation instructions but without error coding), and two sets of Table 3: An example sentence with the original NUCLE correction and fluency and minimal edits written by experts Figure 2: Amount of changes made by different annotation sets compared to the original sentences. machine-translation metric BLEU because evaluating against our new non-coded annotations is similar Figure 3: Correlation of the human ranking with metric scores over different reference sets (Spearman''s ρ). Human evaluation of grammatical error correction systems. work_ofi4snsh4bfibk6cmnicyk37ai PHM contains two aspects, fault prognostics and health Failure prognostics refers to the prediction based on the and conceptual, that enables a shift from traditional sensorbased diagnostics to prognostics based on intelligent systems, fault detection, failure prediction, the remaining life prognostics Fault prognostics research includes the following PHM systems generally should be capable of fault detection, prognostic, health management, and component life tracking B. Fault prognostic model design of PHM fault detection, isolation and prognostic and state applied in the actual research, the fault prognostics Model-driven fault prognostic is a technique using either a dynamic model or process prognostics method. classified in Model-driven fault prognostics [26]. Model-based fault prognostics modeling of fault prognostic lags behind. The data-driven fault prognostic technology does not need data analysis and processing methods to prognosticate the knowledge-based fault prognostics technology have become a make the fault prognostic based on system characteristics more Prognostics and Health Management(PHM 2008), Denver, CO, work_ofmoubrcrjdlrgegtblcgq76ru through a LabVIEW program running on a new laptop designated and mounted to the mini jet turbine result, The Inlet Mass Flow Rate numeric indicator value is calculated, not measured. Keywords: LabVIEW, Engineering Equation solver (EES), Mini-turbine, Pressure Gas turbine engines include internal passages which serve to channel the cooling air from compressors addition, there are sensors on this engine to monitor thrust, RPM, and fuel flow rate. Figure 2 below shows the location of each temperature and pressure being measured on the engine. In order to calculate the Inlet Mass Flow Rate to the turbine engine, the static pressure is needed. Figure.9 Engine Testing Data Plot – Thrust vs RPM engine RPM and Thrust, Temperature, Inlet Mass Flow Rate, and Pressure. Figure.8 Engine Testing Data Plot – Inlet Mass Flow Rate vs RPM These tasks and subFigure.11 Engine Testing Data Plot – Pressure vs RPM Figure.10 Engine Testing Data Plot – Temperature vs RPM work_ofvzhtalhnfxfbyktffx6bud4a Interview with the Inventor of the Future Network IPV9 development of the Internet, the network information The emergence of a new generation of Internet IPV9 FUTURE NETWORK IPV9 insufficient length of the IPV6 address are as States is developing a new network (IPV10) with IPV9 is a protocol with an official version number completely build a pure IPV9 network, and then information can be used in IPV9 network content access to the Internet, China''s network can still address of the future network is basically 256 bits The future network IPV9 effective address FUTURE NETWORK PATENT future network IPV9 has formed a complete Future Network IPV9 has obtained 8 patents in Future Network China Standard Content projects of IPV9 address space, root domain name The IPV9 network has The IPV9 network has China''s digital currency network IPV9 is a new generation network architecture The future network will be developed in 15 years work_og2bcwliw5cifgbk5z4dlw35pm number of sub station meet the qualification, if not satisfied, Keywords-Wireless Return; Base Station Deployment; Kthe sub-station, and the cost of satellite equipment are 3) If it is the host station, the maximum number of and the host station, and the number of hops is less than overall cost of wireless return part of the station is a satellite; Secondly, the number of host stations should between host station, just meet the distance limit, so station to smaller path loss, when the host stand for host stations, and the maximum communication station, and there is only one path to the host limit for the total number of host stations, i.e., number of host stations in each subregion is obtained; The number of host stations is 222, the loss of the back transmission part of the sub-station is local optimal model based on k-means algorithm is adopted between the host stations and no loss is work_oh4axyozfnapfjex2hkzg6cdwu NEAT Drummer that interactively evolves a type of artificial neural network (ANN) called a Compositional Pattern Producing Network (CPPN), Keywords: compositional pattern producing networks; CPPNs; computergenerated music; interactive evolutionary computation; IEC; NeuroEvolution of Augmenting Topologies 1994; Katz and Longden, 1983; Oliver, 2006; Schuller, 1968; Weick, 1998). Finally, in NEAT Drummer, NEAT evolves a kind of ANN called a Compositional Pattern Producing Network (CPPN), which is designed to compactly The main idea in NEAT Drummer is that the temporal patterns of the instrumental parts of a song can be inherited by the drums by making the drums NEAT Drummer begins by generating an initial set of original drum tracks for To produce the initial patterns, a set of random initial CPPNs with a minimal initial topology (following the NEAT approach) and the chosen inputs That is, given a MIDI song, NEAT Drummer generates a drum pattern work_ojlv3fg34jcrnmyawv4ljovkci Kaplan, 2001; Marocco, Cangelosi and Nolfi, 2003; Quinn et al, 2003; for a review see Kirby, Robots located inside a target area produce signal B. (a) a signal A with an value of about 0.42 produced by robots located outside the target areas (5) robots located outside the target areas receiving signal E tend to modify their motor (5) robots located outside the target areas receiving signal E tend to modify their motor The fact that signals A and E produced by robots located outside target areas allow them to Indeed, robots located inside a target area switch their signalling behaviour from B to C when they detect the signal produced by another robot located in the same target area. The ability of robots located outside target areas to switch their signalling behaviour off condition in which robots outside target area were not allowed to switch their signalling behaviour from A to D. work_ok6ue4ib3fatlnuar26cvagtom Remote ECG System Data Encryption Scheme keys by means of a random number generator, establishes a multi-key model, and implements the encryption storage and software encryption cannot guarantee the security of the key A multi-key-per-machine encryption algorithm is used to encrypt patient data in the terminal device memory. encryption standard, the packet length is 64 bits, and the key is not suitable for encrypting real-time collected ECG data The 120 user data encryption keys (960 necessary to transfer the user data encryption key under any values, you can pre-calculate all device keys on the server encryption key sequence on the terminal device and the number of key-used-times on the terminal device. number K as a temporary communication key for modifying key length and encryption algorithm, the attacker tried on an existing various attack methods and fully protect patient data existing various attack methods and fully protect patient data work_okvvxviedrfdxmxumhunbaqdf4 Such results allow the development of an automated system for supporting both candidates and committees in the future ASN sessions and other scholars'' Keywords Predictive Models, Scientometrics, Research Evaluation, Data Processing, ASN, (https://www.scimagojr.com/) (for journals), the Performance Ranking of Scientific Papers examples of rankings that use bibliometric indicators to rate scientific performances. peer review and bibliometric indicators to allocate funding and evaluate the performance bibliometric indicators and the results of the Research Assessment Exercise (RAE) in indicators to predict the results of evaluation procedures performed through a peer review model based on previous publication volume and citation rate to predict authors'' relative Only a few works focused on the problem of using bibliometric indicators to predict indicators for predicting the results of peer judgments of researchers. Non-bibliometric indicators apply for the RFs for which MIUR assessed that citation be used to perform accurate predictions for the different RFs and scientific levels of the work_omyh7hfb2nd3flb4xlfcn3huhm Research on Noise Removal in Fiber Grating Sensing Signal fiber grating sensor, noise interference on signal transmission, order to solve the noise problem of fiber grating sensing signal, design a denoising method of fiber grating sensing signal based fiber Bragg grating sensing signals, and improve the quality of mechanism of fiber Bragg grating sensor signal denoising fiber Bragg grating sensor signal, in order to improve the quality of the fiber Bragg grating sensor signals, but as a grating sensor based on contour wavelet transform signal fiber Bragg grating sensor signals, won the high quality of the fiber Bragg grating sensing signal, so as to improve the threshold of the optical fiber grating sensor signal denoising, The signal of fiber grating sensor with noise The denoising results of fiber Bragg grating sensor in contour eliminate the noise in the fiber Bragg grating sensor signals outline of fiber grating sensing signal denoising method, work_opocgepdjnannc6k4c6c75p26e Review of Anomaly Detection Based on Log Analysis research status of anomaly detection based on log challenges faced by anomaly detection based on log Keywords-Log Analysis; Distributed; Big Data; With the increasing scale of log data and network With the increasing scale of log data and network for log data anomaly detection. of log analysis and anomaly detection, and then current The types and rules of log anomaly detection In data mining, anomaly detection identifies items, supervised anomaly detection method creates a model Anomaly detection behavior based on log With the rapid development of big data, log-based [10] used the log template to detect anomalies in 2018. anomaly detection in unstructured system logs, analysis Detect abnormal log files, and finally use a a log file anomaly detection method, which For anomaly detection based on log analysis, data through anomaly detection[J]. data through anomaly detection[J]. detection for big log data using a Hadoop ecosystem[J]. work_oqwzwsqahzdmxjlup3t334s4ei Inherent Disagreements in Human Textual Inferences to current work on learning common sense human inferences from hundreds of thousands of train models to make the inferences that a human multiple human raters to label pairs of sentences, should explicitly incentivize models to predict distributions over human judgments. not licensed in a specific context, instead advocating that annotation tasks should be ''''natural'''' for goal in NLP is to train models that reverseengineer the inferences a human would make humans use to draw inferences from natural language, but merely: Left to their own devices, To perform our analysis, we collect NLI judgments at 50× redundancy for sentence pairs drawn that, for many sentence pairs, human judgments Figure 4: Examples of sentence pairs with bi-modal human judgment distributions. the human labels, in one case because the model do not learn human-like models of uncertainty large annotated corpus for learning natural language inference. work_osxqmwo2yjakvpw3wcmliie4ri produce denotations for phrases such as "Republican front-runner from Texas" whose semantics cannot be represented using the Freebase schema. A training phase produces this probabilistic database using a corpus of entitylinked text and probabilistic matrix factorization with a novel ranking objective function. right: evaluating the logical form on the probabilistic database computes the marginal probability that each to map entity-linked texts to logical forms containing predicates derived from the words in the text. collect training data by analyzing entity-linked sentences in a large web corpus with the rule-based This process generates a collection of logical form queries with observed entity answers. From this simplified logical form, we generate two types of training data: (1) predicate instances, and (2) queries with known answers (see We generate two types of training data, predicate instances and queries with observed answers, by semantically parsing the sentence and work_ot7jvn6f25dqlag44iotnappoy outperform traditional count-based distributional models on word similarity and (2014) conducts a set of systematic experiments comparing word2vec embeddings to the more traditional distributional methods, such as pointwise To asses how each hyperparameter contributes to the algorithms'' performance, we conduct a comprehensive set of experiments and compare four different representation methods, while Golberg (2014c) show that SGNS is implicitly factorizing a word-context matrix whose cell''s values are shifted PMI. word and context vectors (e.g. SVD and SGNS). note that in the SVD-based factorization, the resulting word and context matrices have very different properties. Table 2: Performance of each method across different tasks in the "vanilla" scenario (all hyperparameters set to default): We begin by comparing the effect of various hyperparameter configurations, and observe that different settings have a substantial impact on performance (Section 5.1); at times, this improvement is greater than that of switching to a different representation method. work_ou6v3eqnl5bxnhbcixnjtwh65y partial least squares regression model that can generate realistic motion from a set of The described model has been validated for running motion, showing a highly (2016), A PCA-based bio-motion generator to synthesize new patterns of human running. to generate a database of running movements of a full human model. a bio-motion generator based on a statistical model capable of synthesizing new realistic running motion from a set of desired data: age, gender, height, body mass index (BMI) 3D shape models from anthropometric measurement data (age, height, weight, BMI, waist model capable of synthetizing new realistic running motion from a set of desired data: of regression model is suitable for the kind of data involved in the bio-motion generator This way, the motion information related to gender which is part of the PLS error matrix generator is based provides running motion models closely resembling the measurements work_ovcflywu7jf77iwsxybgfrw4tm Higher-order Lexical Semantic Models for Non-factoid Answer Reranking We introduce a higher-order formalism that allows all these lexical semantic models to the semantic similarity between question and answer using language models acquired from relevant texts (Yih et al., 2013; Jansen et al., 2014). model graphs, we observe that semantic association between two words (or structures) stored in representations, including alignment and language models, over both words and syntactic structures, can be adapted to the proposed our higher-order LS models on a community question answering (CQA) task (Wang of the alignment model in §4.2, where the representations of questions and answers are changed addition, we experimented with the opposite hybrid model: interpolating the NNLM vectors using alignment associate probabilities as weights, NNLM Corpus: We generated vector representations for words using the word2vec model number of most-similar neighbor vectors interpolated when constructing a higher-order model. higher-order NNLMs and alignment models are higher-order NNLMs and alignment models are work_ovwfhshipvdmtczjfk4mhb3qfm carcinoma group (nZ143), even after adjusting for different TSH levels. thyroid carcinoma patients (nZ50) received 1.57 mg/kg per day L-T4 (IQR 1.40, 1.69), compared apparent; some patients with fully suppressed TSH failed to raise FT3 above the median level. These findings imply that thyroid hormone conversion efficiency is an important modulator of the L-T4 dose with clinical categories and biochemical outcomes such as TSH, FT4 and FT3 levels. dose requirements of L-T4 including conditioning modulators, thyroid hormone conversion efficiency and analysis, 353 patients on thyroid hormone replacement carcinoma patients received significantly higher doses of carcinoma patients compared to autoimmune thyroiditis TSH (A) or FT3 (B) vs weight-adjusted L-T4 dose in three groups of patients groups were similar (PO0.1) in their age, BMI, weightadjusted L-T4 dose and TSH levels except for men being TSH in autoimmune thyroiditis or benign disease post At both comparable levels of TSH suppression or similar FT3 concentrations, athyreotic thyroid carcinoma patients were work_oxey5qpx5jcjpbuapq5ob57w2y Multi-function Monitoring and Alarm System for the Large Stadium combustible gas alarm, the infrared identification detection sensor and sends the data to the mobile phone or the control Keywords-Sensor; Wireless Transmission; Alarm;, MCU; communication module, the collected data was send to the minimum system based on STC89C52, sensor circuit temperature detection program[2]. of MCU, the GSM module, the display circuit, the buzzer composed of three parts: the smoke detection, the human From Figure 1, when the three sensors detect the smoke, the human body or the high temperature, the alarm Then the GSM module sends the alarm C. Example Sensor detection circuit with the single-wire interface, the temperature sensor, the The detection circuit of the smoke and combustible gas is If detects the human body sends the data to B. GSM module program design detect the smoke or combustible gas, the infrared detect the smoke or combustible gas, the infrared work_oxyhki32wvhqhkc7hia2kg2azu algorithm for securing big data: Hadoop the authors have evaluated the proposed ABHE algorithm by performing encryptiondecryption on different sizes of files and have compared the same with existing ones Keywords Big data, Data security, And encryption-decryption, HDFS, Hadoop, Cloud storage Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective. a data files) and later, encrypted DEKs with KP-ABE (public key cryptography primitive (International Data Encryption Algorithm) to encrypt the RSA based user key. encryption algorithm to secure the data at cloud storage. HDFS data encryption based on ARIA algorithm. and provides efficient encryption security and compression during storage of data. with reduction of encrypted file size by AES and OTP algorithms in HDFS. the proposed algorithm provides the security for data stored at HDFS and distributed Encryption is performed while writing the file on Hadoop so that the stored data can be Secure hadoop with encrypted HDFS. work_p2cpwlday5ajnd3ik2thxkavae ECG signals, three basic filters, the possibility to load other R-peak locations and Keywords R-peak detection, R-peak correction, User interface, Analysis software graphical user interface for the detection and correction of R-peaks. The detection of this complex is crucial for almost all ECG analysis algorithms. R-peak detection algorithm and provides the user with the possibility to correct possible We developed an R-peak detection algorithm that is based on an enveloping procedure. in Fig. 5, it can be divided in five segments: Data, Filter, Analysis Period, R-peak Detection their own preferred QRS detection algorithm, the software allows to load R-peak locations. signal in the analysis window, the R-peak locations and the RR-intervals. R-DECO is a MATLAB based GUI for detecting and correcting R-peaks in ECG signals. R-DECO: an open-source Matlab based graphical user interface for the detection and correction of R-peaks R-DECO: an open-source Matlab based graphical user interface for the detection and correction of R-peaks work_p2gfo6whijbf3nveq7bcobpptm Automated scoring of narrative essays is a challenging area, and one that has not been explored extensively in NLP research. We investigated the effectiveness of each feature for scoring narrative traits the first detailed annotation study on scoring narrative essays for different aspects of narrative quality. (2) We present an automated system for scoring narrative quality, with linguistic features specific to encoding aspects of good story-telling. for evaluating student writing, or whether encoding features that capture different narrative aspects The rubric provides the following criteria for an essay of score point 4 in terms of five aspects or sub-traits: "The organization of the narrative E-rater (Attali and Burstein, 2006), a state-of-theart commercial system for automatic essay scoring, uses a comprehensive suite of features covering many aspects of writing quality, such as grammar, language use, mechanics, fluency, style, organization, and development. Table 4: Performance (QWK) on predicting traits and Narrative and Total scores; Best feature combinations: work_p2xqvo6isfb75mbvnnkzerthaa patterns in Drosophila based on chromatin marks across three cell lines. to any similar biological dataset of chromatin features across various cell lines and experiments, Linear Regression, Gradient Boosting, Chromatin, DNA folding patterns, Machine for the prediction of chromatin folding in Drosophila using epigenetic features. Drosophila chromosome partitioning into TADs. Active chromatin marks are preferably characteristics of TADs result in assigning a continuous score to genomic bins along the TAD boundary prediction in Drosophila, where the histone modifications of extended chromatin features are most significant in predicting the TAD state. the RNN model, yt/2 represents the corresponding target value transitional gamma of the middle bin xt/2. First, we assessed whether the TAD state could be predicted from the set of chromatin Table 1 Evaluation of classical machine learning scores for all models, based on 5-features and 18TAD state prediction models are transferable between cell lines of model: genome-wide chromatin looping prediction. work_p3f4enbxxbetzcxwlxqv6hfqt4 We propose a new method for semantic parsing of ambiguous and ungrammatical input, of Kobe Bryant?" While answering these questions provides an excellent first step to natural language information access, in many cases the input is Figure 1 shows an example of using an SCFG to simultaneously generate a natural language string and data is out of the scope of the present work, if a corpus of real keyword inputs and question paraphrases joint semantic parsing and paraphrasing using trisynchronous grammars, or 3-SCFGs. In this framework, input γ1 corresponds to a keyword query K, During the process of model training, we first extract rules consisting of γ2 and γ3 using the algorithm in Section 2.2, then generate γ1 from γ2 by the proposed method using the Questions language model with NNLM reranking "Tri+LM." paraphrasing grammar and semantic parsing rules. model to do paraphrasing and semantic parsing synchronously. work_p4f7mjg22ravlpruv2gop7ixge recommends interesting news articles to the user based on their popularity as well as recommender systems that help users find the information they need, based on their recommends interesting news articles to the user using a micro-blogging service "Twitter." recommender systems recommend interesting news articles to the user solely based on the since they rank the news articles based on the user''s interests. Profile-based, or personalized, news recommender systems recommend articles to the recommend news articles to the user that are both relevant to their interests and popular Our basic approach is to recommend interesting news articles to the user based on a The second module ranks the news articles based on their similarity to a user''s profile. The news articles are ranked based on their similarity between the categories in the user''s two modules to produce a recommendation based on both the articles popularity to users work_pa2cgjgwrnepbdm4hnu6xpauc4 model builds on earlier models of unsupervised phone-like unit discovery from acoustic data (Lee and Glass, 2012), and unsupervised symbolic lexicon discovery using the on earlier work addressing the unsupervised discovery of phone-like units from acoustic data—in particular the Dirichlet Process Hidden Markov Model We provide preliminary evidence that simultaneously learning sound and lexical structure leads to synergistic interactions (Johnson, 2008b)—the various components of the model here are models which treat segmentation as a secondary consequence of discovering a compact lexicon which explains the distribution of phoneme sequences in the input (Cartwright and Brent, 1994; a fixed, two-level representation of linguistic structure, our use of adaptor grammars to model symbolic lexicon discovery means that we can easily and Phonological variability modeling In conversational speech, the phonetic realization of a word can In summary, our model integrates adaptor grammars with a noisy-channel model of phonetic variability and an acoustic model to discover hierarchical linguistic structures directly from acoustic signals. work_pd3ghpw4jneotm27sbfmo55ndi Keywords Information-providing, Direction giving, Belief about robots We first investigated what people would expect from an information robot, and developed an article search robot which enables visitors to request an item and let the with the names of locations and people in offices, and provide direction giving (Kopp et al., (2009), the robot provided direction-giving interaction ask/request in an information dialog with a robot. To investigate what people expect from information robots, we interviewed customers in The initial version of the robot imitated the interaction of human information staff. expectations the purpose of information staff we let the robot wait for a visitor to make Prediction 1: If the robot proactively explains its role as information staff, people will easily answer, people will more frequently make requests to the information robot. that what visitors expect for an information robot well overlapped with what human We developed a knowledge representation for information robot. work_pdhkjvfkbnb4ngi7bpbilobcq4 participated in the task developed a wide array of approaches that include discriminative classifiers, language models, statistical machine-translation systems, and rule-based modules. linguistic knowledge when developing error correction modules, e.g., to identify which type of verb NB model trained on Web1T and adapted to learner errors There are different ways to adapt a model that depend on the type of training data (learner or native) With adaptation, models trained on native data can use the author''s word (the source word) as a feature and thus Adaptation always helps on the CoNLL training data and the FCE data (except noun errors), but trained on learner data with word n-gram features and the source better approach is to train on learner data for agreement mistakes and on native data for form errors. the NTHU system also corrects all verb errors using a model trained on Web1T but handles all these work_pdqrtt6jizdy3jg4ft2bx3fkpa We present an experiment in which humans interact with a simulated robot swarm (B) A participant is attached to a virtual reality head set and interacts with a simulated swarm of (C) A participant interacts with a simulated swarm of 20 robots displayed on a computer they interacted with a robot swarm simulated in a virtual reality headset than when they study the psychology of humans interacting with a robot swarm are performed in a simulated robot swarm displayed in virtual reality than when they interact with a the participant supervises a simulated swarm of 20 robots displayed in a virtual reality performing a human-swarm interaction study with real robots, compared to simulated Investigating the effect of the reality gap on the human psychophysiological state in the context of human-swarm interaction Investigating the effect of the reality gap on the human psychophysiological state in the context of human-swarm interaction work_pe6afkaafrgthcfkm3jxai36zy Big data storage management is one of the most challenging issues for Hadoop cluster and resources a "Disparateness-Aware Scheduling algorithm" is proposed in the cluster environment. In this research work we represent K-centroids clustering in big data mechanism for Hadoop cluster. K-centroids Clustering algorithm in Big Data-Hadoop Cluster. scheduling length, speed up, energy consumption, and failure ratio with respect to the number of clusters. 4.4 Scheduling Delay Vs. Number Of Cluster Resource Fig. 7 The result of scheduling delay with respect to the number of cluster resources. Fig.7 shows the result of scheduling delay with respect to the number cluster resource for the existing The result of the scheduling delay with respect to the number cluster resource for the existing HPF and A Disparateness-Aware Scheduling using K-Centroids Clustering and PSO Techniques in Hadoop Cluster A Disparateness-Aware Scheduling using K-Centroids Clustering and PSO Techniques in Hadoop Cluster work_pee4lh5o6ncbrmy2pmtlywkela Keywords -IPV9; Interface; Socket; API which the transport layer connects is called a socket. (host address/port number) for the socket interface by socket interface handle, the length of my_addr is the parameter addrlen, which is called set interface name If the type of the socket interface is SOCK_DGRAM, connection to another socket interface. on the socket interfaces of types SOCK_STREAM and on the socket interfaces of types SOCK_STREAM and socket interface type of the connection socket interface similar to the parameter s, and then assigns a handle to that socket interface and returns. socket interfaces: FD_ZERO will empty a set; On success, return the socket interface handle contained in the socket interface set, returns 0 if no of whether the socket interface is connection-oriented. type of socket interface used to receive the message. socket interface is non-blocking, the return value is -1 socket interface options are setting, it must be specify work_phbri3nemnevfl2hhtmkl4bl3u endpoints where restrictions can be applied using the Role-Based Access Control Keywords Microservices, REST, RBAC, Access control, Authorization, Security, Access Control (RBAC) inconsistencies among microservices using static code analysis. popular methods of securing REST services where each user of the application is assigned microservice''s controller layer defines the REST endpoints that serve as request entry 2. Unknown access violations: if an API endpoint contains an authorization role that is not method, only the users that have the "ADMIN" role (defined in the realms) can access the different RBAC roles, we detect it as an entity access violation. Our system finds potential RBAC violations based on a user-defined role hierarchy @RequestMapping Class and Method Defines HTTP types and paths for REST endpoints method in CMS can be accessed with a "user" role which calls the getUserById endpoint This may not be true if users are defined in separate security realms; a role name in one work_pijwwvfoivdarkphykmuwwhuyi Keywords: Security, Privacy, Internet of Things, IoT, Middleware we look at each of the classic security challenges in three different aspects: device/hardware, network, WS-Security on Arduino, ESP8266 or Atmel systems (which are common targets for IoT device IoT devices may use much lower power, lower bandwidth networks than existing Internet systems. In [144] a theoretical model of traceability of IoT devices and particularly Radio Frequency Identification Device (RFID) systems is proposed in order to prevent unauthorised data being accessible. second approach to support the scale of IoT is user-directed security controls, otherwise known as consent. IoT devices are updated based on the secure identity and consent models used in OAuth2. The Hydra middleware does not offer any policy based access control for IoT data, and does not • Only two of the systems applied any concepts of context-based security or reputation to IoT devices. work_pikiwx2qgndj5avsy435cqccsm describe two supervised approaches for tagging causal constructions and their arguments. outperform naı̈ve baselines for both construction recognition and cause and effect head Table 1: Examples of causal language, reflecting the annotation scheme described in §2.1 (with connectives in bold, the fundamental units of language are CONSTRUCTIONS – pairings of meanings with arbitrarily complex linguistic forms. related approaches for tagging causal constructions The scheme defines causal language as any construction which presents one event, state, action, or The connective annotation includes all words whose lemmas appear in Causeway is a system that performs this causal language tagging task. the cause and effect arguments of a causal instance. During training, the system examines each causal language instance, generating a TRegex pattern that will match tree fragments our causal connectives, and both tasks require identifying argument spans for each trigger. Annotating causal language using corpus lexicography of constructions. work_pjnfr4gisnad5kktiybbac7hve Network methods have been applied to obesity to map connections used to create a network in which the nodes are community features Network science has made important contributions in obesity research along several dimensions. aware of no studies to date that focus on the structure of linkages between features of the environment, thought to be the main drivers of the obesity draw from network analysis tools to study these interrelations between features of the environment and We used a method analogous to Weighted Correlation Network Analysis (Zhang We generated a data array of covariates (32 obesity-related community features) that Obesity-related community features included in network analysis. Each node in the network represents one feature of the communities, and the and interactions among obesity-related environmental features among communities in Pennsylvania. communities, crime is weakly linked to the land usefoodphysical activity cluster; but in higher obesity variables of the obesity-related network in the network of community features. work_pldccdah4jaxfnfnhw7476klzi 1Department of Endocrinology and Internal Medicine and the Medical Research Laboratories, Clinical Institute, Aarhus University Hospital, treatment of hypogonadal patients decrease fat mass, increase lean body mass and improve Research design and methods: In a randomized, double-blind, placebo-controlled, BMImatched cross-over study, 13 males with KS (age: 34.8 years; BMI: 26.7 kg/m2) received treatment on insulin sensitivity, body composition, effect of treatment (placebo or testosterone) within the KS Total lean body mass increased during testosterone trial of testosterone and placebo in KS studying insulin Table 1 Age of participants, anthropometric data at baseline in males with Klinefelter syndrome and controls at baseline. In the lower part of the table anthropometric data at baseline and during treatment with either placebo or testosterone in Klinefelter syndrome is ambulatory blood pressure measurements (mmHg), and VO2max in males with Klinefelter syndrome during testosterone or Insulin sensitivity in males with Klinefelter syndrome and controls. work_pluda2lllfaddo2mpqs5n5hkoq When the MSOR Network was formed in 2000 I was a first year undergraduate student was an account of the implementation of MELEES in MSOR Connections in 2003 [1]. e-assessment in mathematics, to Cliff Beevers'' Maths-CAA Series which was published series which provided disability-related updates in response to new legislation. MSOR Network mini-projects scheme to investigate visual impairment and particularly initiated a new series of articles in MSOR Connections in 2005 MSOR Connections in 2010 about response system use Later in 2010 I started working for the MSOR Network on a impact of work that started in MSOR Connections. with the MSOR Network and its Connections. MSOR Connections, 11(3). MSOR Connections, 11(3). MSOR Connections, 11(3). MSOR Connections, 11(3). MSOR Connections, 11(3). MSOR Connections, 11(3). MSOR Connections, 11(3). Early career Connections with MSOR – Peter Rowlett Early career Connections with MSOR – Peter Rowlett seminar on teaching and learning in the Mathematics, work_pmgmlohszzcrxlzdesctv3cf3y Drug repositioning methods attempt to identify novel therapeutic indications for methods leverage side-effect data from clinical studies and drug labels, evidence describe a novel computational method that uses side-effect data mined from social sparse graphical models generated using side-effect data mined from social media Drug repositioning is the process of identifying novel therapeutic indications for marketed to perform large-scale mining of reported drug side-effects in near real-time from the In this study, we describe a drug repositioning methodology that uses side-effect data causality indicators, clinical trials, medical professional roles, side effect-triggers and drugs. x∈{0,1}, indicating whether each drug was reported to cause each side-effect in the Twitter Data-driven prediction of drug effects and drug side-effects and therapeutic indications. Systematic drug repositioning based on clinical side-effects. Computational drug repositioning based on side-effects mined from social media Computational drug repositioning based on side-effects mined from social media Computational drug repositioning based on side-effects mined from social media work_pomvj2ifwrbwjdcmiw5ube5dge Neural language embedding models can be effectively trained to map dictionary definitions (phrases) to (lexical) representations of the words defined by those definitions. On both tasks, neural language embedding models trained on definitions from a handful of freely-available lexical resources perform as well or better than The results highlight the effectiveness of both neural embedding architectures and definitionbased training for developing models that understand phrases and sentences. on only a handful of dictionaries identifies novel definitions and concept descriptions comparably or better than commercial systems, which rely on significant task-specific engineering and access to much input definition phrase sc defining word c to a location close to the the pre-trained embedding vc of To compile a bank of dictionary definitions for training the model, we started with all words in the target embedding space. As with the reverse dictionary experiments, candidates are extracted from models by inputting definitions and returning words corresponding to the work_pov3luuevzcuvon3rcd2obvd2e by Kraken, a very fast read-level classifier, along with information about the genomes (2017), Bracken: estimating species abundance in metagenomics data. KrakEN), estimates species abundances in metagenomics samples by probabilistically To compute species abundance, any genome-level (strain-level) reads are simply added We then apply our abundance estimator, Bracken, which uses the numbers of reads assigned Figure 2 Estimates of species abundance in the i100 metagenomics dataset computed by Kraken (blue) and Bracken (blue + orange). Figure 3 Estimates of species abundance computed by Kraken (blue) and Bracken (blue + orange) for the i100 metagenomics data. Precise numbers for the Kraken classification, true read counts, and Bracken estimates are contained in Table S2B. Precise numbers for the Kraken classification, true read counts, and Bracken estimates are contained in Table S2B. and the number of reads assigned to each species by Bracken after abundance reestimation. work_pp4msfxqizentabvmvas5sabne This paper describes an interactive audio-visual musical installation, namely Keywords Audio-visual interaction, Computer music, Webcam Artistic interactive musical installations, like Aether (Sanchez & Castro, 2014) and achieving new possibilities of musical performance and interaction (Jung et al., 2012; Chen, Interactive musical devices present both artistic and technological challenges (Garnett, How to cite this article Tavares (2015), An interactive audio-visual installation using ubiquitous hardware and web-based software Therefore, M uses a music generation model that responds to the This allows the audience to explore not only the interaction with M, but The movement detection process applied in M is very simple, as the web-based information from the note sequence generated by the musical models. This paper described M, a digital interactive audio-visual installation that requires An interactive audio-visual installation using ubiquitous hardware and web-based software deployment An interactive audio-visual installation using ubiquitous hardware and web-based software deployment work_psegqzocp5c6tdslpbvt6fmyre Keywords: Clustering analysis, improved K-means algorithm, geological disaster monitoring data the research object, which are served as a representative sample of the improved K-means clustering product based on mean and maximum distance to optimize the initial clustering center. first selects the set of data objects which are the farthest from the sample set to join the clustering center, a k-means algorithm to optimize the initial clustering center by using the minimum variance based on Improved K-means Algorithm Based on optimizing Initial Cluster Centers and Its Application Improved K-means Algorithm Based on optimizing Initial Cluster Centers and Its Application Improved K-means Algorithm Based on optimizing Initial Cluster Centers and Its Application value of the traditional k-means algorithm because the data objects in the optimized cluster are more variance, a k-means clustering algorithm is proposed to optimize the initial clustering center. [7] Application of Improved K-Means Clustering Algorithm in Transit Data Collection. work_ptbmdrtm2beztaoyct66zhkrme metrics and colour space transforms An object-oriented computational framework for the transformation of colour data In this way, new colour spaces can be implemented on the fly by transforming metric tensors and colour difference data can easily be transformed between the colour Keywords Colour metrics, Colour space, Transform, Object-oriented, Python conversion is particularly present for computations involving colour metric data, which, colour data and metrics including the automated computation of Jacobian matrices has How to cite this article Farup (2016), A computational framework for colour metrics and colour space transforms. Since the computation of generic colour space transforms and, in partiular the composition 2012), an object-oriented framework for transforming colour and metric data between the implementation of new colour spaces and metrics. classes for transforming new colour spaces from already existing ones. colour space tranforms are implemented as classes TransformXXX derived from Transform. metric developed in Reference (Farup, 2014) in any colour space. work_ptt4wjnlafbitn5ku5cpz22awy (2017), Gender differences and bias in open source: pull request acceptance of women versus men. Figure 1 GitHub user ''JustinAMiddleton'' makes a pull request; the repository owner ''akofink'' accepts it by merging it. GitHub data to evaluate whether pull requests from women are accepted less often. women tend to have their pull requests accepted at a higher rate than men! Why might women have a higher acceptance rate than men, given the gender bias Figure 4 Pull request acceptance rate by number of projects contributed to. pull requests that make changes to program code, women''s high acceptance rates might to have their pull requests accepted than women whose gender cannot be easily inferred, Figure 7 Acceptance rates for men and women for all data, outsiders, and open source projects using explain why women''s pull request acceptance rate drops when their gender is apparent. work_pu54zjotk5ed3ol4ajhrlzpfju This representation consists of distributional features, suffixes and word shapes of v and its local FLORS predicts unseen tags of known words better than prior work on DA for POS. FLORS uses representations computed from unlabeled text, representations of unknown words are For a word w occurring as token vi in a sentence, we build a feature vector for a local window Table 2: Tagging accuracy of four baselines and FLORS on the dev sets. (lines 1–4), basic FLORS setup (lines 5–6), effect of omitting one of the three feature types if the word to be tagged designed for tagging in-domain data and use feature In contrast to standard approaches to POS tagging, the FLORS basic representation does not contain vocabulary indices. Table 3: Tagging accuracy of four baselines and FLORS on the test sets. Table 7: Tagging accuracy of different word representations on the dev sets. work_pvs3jywvl5ajbjupklysfpwute our incremental TSG parser to generate partial parse The generative process starts with a fragment anchored in the first word of the sentence being generated. a way that the prefix of the yield of the partial structure is lengthened by one word (the lexical anchor of lex-first fragments into the partial derivation generated so far, and forward substitution (5), which is to efficiently compute all possible incremental derivations that an ITSG can generate given an input on the chart states in order to keep track of all possible ITSG derivations as new words are fed in. scanned, the parser reads the next word (''i) and introduces new states in state-sets i and i + 1 by applying specific operations on states present in the chart, As an example, consider the ITSG grammar consisting of the fragments in Figure 7 and the two derivations of the same parse tree in the same figure; work_pwcpe4ln3jeu7bcvge6twr4gru Traveling Route Generation Algorithm Based On LDA and Collaborative Filtering route recommendation and generation algorithm based on the results of topic city model based LDA and different The travel route recommendation algorithm based on playing time estimation module based on KDE, topic city through established travel city topic model based on LDA. LDA travel route recommendation algorithm based on KDE and classification Collaborative filtering travel route recommendation algorithm based on KDE and Classification Travel city topic model based on LDA travel city topic model based on LDA generates a feature INPUT AND OUTPUT OF TRAVEL CITY TOPIC MODEL BASED ON LDA INPUT AND OUTPUT OF TRAVEL CITY TOPIC MODEL BASED ON LDA The route correlation rate of collaborative filtering travel route recommendation algorithm based on KDE and classification travel route recommendation algorithm based on KDE and travel route recommendation algorithm based on KDE and work_pz3pacjpbrf6hm67aqomk5ag6e We here address this issue by assessing the genomewide performance of networks trained with sets exhibiting different ratios of positive be used to predict gene-start sites in a related species, when using training sets providing Keywords Transcription start sites, Promoters, Genome annotation, Deep learning, DNA motifs, A CNN (see Fig. 1) is trained in order to predict the presence of a GSS in a DNA sequence Training models for genome annotation of GSS model applied to human chromosome X still captures most of the GSS and gives a λ score (C) Lambda values computed for networks trained on each species non-X chromosome GSS (t) Lambda scores are computed from predictions done on GSS of (A) human, (B) mouse, (C) model trained on the chicken genome performs less well when applied on the mammalian use the X chromosomes of human and mouse GSS as a case study, and apply models work_q3s75ybxv5gppoolp5qemw6apq Deep Contextualized Self-training for Low Resource Dependency Parsing We present a novel self-training method, suitable for neural dependency parsing. lightly supervised and domain adaptation dependency parsing setups. adaptation case we consider 16 setups: 6 in different English domains and 10 in 5 other languages. embedding model is trained on sequence tagging Pre-training and Deep Contextualized Embedding Our DCST algorithm is related to recent 2008), adding inter-sentence consistency constraints at test time (Rush et al., 2012), selecting effective training domains (Plank and Van Noord, Their approach requires target domain labeled data for parser training and hence In the domain adaptation setups Base-FS is trained trained as a language model (DCST-LM). Table 1: Lightly supervised OntoNotes results with 500 training sentences. DCST with Syntactic Self-training DCSTENS, our model that integrates all three parser''s trees (or as a language model for DCST-LM) based on the integration of (a) contextualized embedding model(s) into a neural dependency parser, work_q656kozazbablahfqw63b62apa Signed Networks for the US Supreme Court Overturning network file with all Supreme Court decisions for the period 1789–2001 and their citations to earlier decisions Supreme Court, Overturning decisions, Signed networks, Citation Supreme Court Overturning Network Data" provides Section "Networks of Decisions Linked Only by Negative Citation Ties." The mobilization of inconsistency citation networks for studying Supreme Court decisions. at networks of Supreme Court decisions linked by Figure 1: Three inconsistent triples of hypothetical decisions each involving one overturning link. Figure 2 raises the issue of why the rates of overturning prior decisions have increased over time. Figure 2: Levels of overturning decisions within and between courts defined by Chief Justices. would be missed under the dyadic approach to considering the overturning of Supreme Court decisions. negative overturning links between Supreme Court decisions are placed in a more general network context. network of ties between Supreme Court decisions in work_q6u36m2psnc3rpytggbjzexftu internet capable device to run training algorithms and predictive models with no and (3) design research closures, software objects that archive ML models, algorithms, and training a large class of ML models using distributed stochastic gradient descent (SGD). Reproducibility: MLitB should foster reproducible science with research closures, universally readable objects containing ML model specifications, algorithms, and parameters, The usage of web browsers as compute nodes provides the capability of running sophisticated ML algorithms without the expense and technical difficulty of using custom grid or as clients join/leave the network, client computations are received by the server, users add to the master server they use Web Workers to perform different tasks. The data server is a bespoke application intended to work with our neural network use-case The most performant deep neural network models are trained with sophisticated scientific Other distributed ML algorithm research includes the parameter server model (Li work_q76lim7slzbszgspybrze23f3y robot swarm: Waffle automatically selects the hardware configuration of the individual implement the simultaneous design of hardware and control software for a robot swarm. simulated robots whose body and control software are designed simultaneously to perform also designed the control software for a robot swarm with fixed hardware configuration. implications of imposing economical constraints to the automatic design of a robot swarm methods for designing the control software of robot swarms (Francesca et al., 2014). hardware of the robot swarm, the design process must also respect the available monetary The performance of an automatically designed swarm depends on the number of robots is possible to concurrently design control software and hardware for a robot swarm using Automatic design of control software for robot swarms. novel approach to the automatic design of control software for robot swarms. Concurrent design of control software and configuration of hardware for robot swarms under economic constraints: supplementary work_qaeelizvxng5tkeu5rhhxdulxm Tai''an Finance Health Medical Information order to build Tai''an healthy big data ecological domain, business structure, core technology, network architecture, and health care big data service system construction, information system and public health medical data development of health care big data applications, and "Internet+ health care" services, and create new models medical and health platforms and other information residents with network and information health services Business architecture of health Tai''an big data ecological domain The health Tai''an big data ecological domain Technical architecture of health Tai''an big data ecological domain The standard architecture health Tai''an big data ecological domain The security architecture health Tai''an big data ecological domain Topology architecture of healthy Tai''an big data ecological domain network Topology diagram of health Tai''an big data ecological domain equipment. Tai''an City health big data ecological domain platform has been used in various medical and health national universal medical health information platform. big data in health care. work_qdsct3peezb6jgqd7q4pwkpcji combinations of simple, real-valued referential properties of predicates and their arguments. for example, EPISODIC, GENERIC, HABITUAL for statements and KIND, INDIVIDUAL for noun phrases. for predicting expressions of linguistic generalization that combine hand-engineered type and Most existing annotation frameworks aim to capture expressions of linguistic generalization using however, the annotations produced by this framework are mapped into a multi-class scheme containing only the high-level GENERIC-HABITUAL-EPISODIC In our framework, prototypical episodics, habituals, and generics correspond to sets of properties we simulate the bulk setting as closely as possible: (i) randomly sampling arguments and predicates for annotation from the same corpus we v. GENERIC) we conduct a study comparing annotations assigned under our multi-label framework of the normalized argument property annotations for that clause''s mainReferent and the normalized predicate property annotations for that particular-referring arguments and predicates, Figure 3: Distribution of normalized annotations in argument (left) and predicate (right) protocols. root of the annotated predicates and arguments, work_qe6lb6u4rfcq3faeborafelgze Keywords Protein sequences, Biological function, Animal venom, Automatic annotation, (2016), Machine learning can differentiate venom toxins from other proteins having non-toxic Moderate and Hard datasets); a sequence is classified as a toxin if the BLAST search ToxClassifier meta-classifier was calibrated by evaluating prediction score versus performance for each animal training set and for summary dataset constructed by combining Table 1 Prediction accuracy on positive and negative datasets, as well as range of measurements calculated for all test data, and described in detail in ''Methods.'' Annotation models used as classifier inputs either: the frequency of amino acids (TBSim) or combinations of two amino-acids (BIF); the presence of absence or ''Tox-Bits'' Table 2 Performance for selected annotation models and published toxin prediction tools. or BLAST (triBLAST) comparisons with the UniProtKB/SwissProt-ToxProt sequences supplemented with non-toxin sequences from the ''Moderate'' and ''Hard'' datasets lists comparison of classification performance for calibrated ToxClassifier to BLAST based annotation models and ClanTox toxin prediction server. work_qfsbk44dp5hapniij77q7pd4wi The Extraction of Comment Information and Sentiment Analysis in Chinese CRF, this paper will extract several pairs of theme words and Keywords-CRF; Extract Theme Words; Extract Sentiment information includes the theme words and sentiment words text sentiment analysis, the existing methods for extracting evaluation object as an sentiment word[2]. model to extract comment information. Based on the statistical method, this paper uses the CRF emotional dictionary to extract the comment information, as extracted sentiment words and exporting final results. Review Information Extraction Process Based on CRF Review Information Extraction Process Based on CRF 1) Building a sentiment word dictionary: This paper In a word, this paper uses the F1 value as an evaluation Theme words in data set / Total number of sentiment words The CRF model is trained after the data set is In this paper, the CRF statistical model is used to extract extraction feature of evaluation object based on CRFs," J. work_qg4vx3n3gjbmbihwvtuna3xnkm Research on Trust-Role Access Control Model in Cloud computing, a trust-role-based hybrid cloud computing access role-based and trust-based access control models. access control, that is, the user needs to verify the trust value The trust-based access control model has good As the number of user requests increases, both access control larger than the role-based access control method in terms of Keywords-Cloud Computing Access Control; Data Security; trust in the role-based access control method, and trust in the role-based access control method, and B. Role-Based Access Control Method In the role-based access control (RBAC) model, the Definition 1 Entity User: Access data in a cloud D. Trust-role-based access control algorithm BASED ON THE "TRUST-ROLE" ACCESS CONTROL proposes the access control model based on trust-role, control model based on "trust-role" and the access throughput than the role-based access control method. role access control based on trust degree in grid computing [J]. work_qht6crxtgndgtjcmaevau32wnm Monitoring System for Tailings Dam development of safety monitoring technology for tailings dam Once the tailings dam break, the loss caused by the is used to monitor the displacement of the dam, and the center of light is measured by the center of gravity, and the laser It is a new monitoring technology for dam displacement Keywords-Dam Displacement; Center of Gravity Method; to analyze the dam monitoring data in time, it resulted in a dam safety monitoring theory system was basically formed. (DL/T5178-2003), dam safety monitoring projects generally measure the displacement of the dam, and its structure is laser will form a spot on the receiver. When the dam displacement occurs, it will drive the lens to center of gravity method to deal with the spot, the image is used to accept the laser spot image. In this paper, the dam displacement monitoring system is [2] Tailings dam displacement monitoring system based on laser work_qivwkxnmazbqll5lutx7ibnvke extraction process, the classification of hand gestures, the applications that were recently proposed, the challenges that face researchers in the hand gesture recognition process, A systematic review on hand gesture recognition techniques, challenges and applications. Hand gesture recognition technique steps vary from simple to complex applications. The first method is using vision-based hand gesture recognition to extract images which hand gesture recognition and one data glove-based technique. based real time dynamic hand gesture recognition technique in Atharva & Apurv (2017), recognition was for 10 hand gestures, images were captured on two different backgrounds A real-time hand gesture recognition technique for presentation was proposed in Rishabh (2017) presented a real-time hand gesture recognition by using Kinect sensor, to control feature extraction process, the classification of hand gestures, the applications that were Sign language recognition using image based hand gesture based approach for hand gesture recognition using distinctive feature extraction. work_ql5liv4nfjah5lwcdnfg2r7ypm aware representations for semantic role labeling without recourse to an external parser. The backbone of our model is an LSTMbased semantic role labeler jointly trained with the arguments of semantic predicates in a sentence and label them with a set of predefined whose semantic role annotations have been produced on top of treebanked corpora, and as a result are closely tied to syntactic information. (2018) incorporate syntactic information in a multi-task neural network model that semantic role labeler jointly trained with a dependency information extractor with two auxiliary tasks: predicting the dependency label of serves as input (combined with word representations) to the semantic role labeler. • a word representation component that encapsulates predicate-specific dependency Figure 2: Model overview: Dependency information extractor (bottom) and a semantic role labeler (top). semantic role labeler and the dependency extractor. multi-task learning in order to make use of linguistic information for semantic role labeling as work_qldkrejomzbxjk65tmsufi3pum Design Heat Exchanger: Optimization and Efficiency The heat exchanger was tested at only three different Keywords-Heat Exchanger; Efficiency; Buildings; loss of fluid from the heat exchanger, this results in efficiency of the heat exchanger. efficiency of the heat exchanger. prototype heat exchanger is shown in Figure 1. Sectioned SolidWorks model of shell and tube heat exchanger with copper coil and finned inner wall. Initially the shell of the heat exchanger was going be assembled into a heat exchanger. The heat exchanger prototype shows the heat exchanger prototype. The electronic part of the heat exchanger Testing the heat exchanger Testing the heat exchanger Initially the heat exchanger was tested with fan efficiency of the heat exchanger at the specified air four designs the effectiveness of the heat exchanger at transfer surfaces in heat exchanger design", international journal of exchanger design", international journal of heat and mass transfer work_qn7irvgulrbyhoipdvk52f7jem international network, making the Internet a truly open has continued to assign IPv4 addresses to the United design architecture of the Internet and the tree network IPv4 network architecture (involving almost all the IPv6 network is too large, there are too many security Internet Protocol IPng" which was in transition to IPv6. for IETF to deal with Internet intellectual property China has more than 100 IPv6 intellectual property Network address and addressing mode of IPv6, data Internet, solidified the necessary route to the network present, IPv6 network in Colleges and Universities can Technically speaking, China''s public network has "two Chinas" on the Internet for a long time, of "two Chinas" that can cause network information became the national network information center. treatment as those of CNNIC (China Internet Network tolerate the emergence of "two Chinas" on the Internet fact that Taiwan can easily control China''s data work_qn7zm7yw3jaupivakvizv4usz4 This paper presents a real-time joint trajectory interpolation system for the purpose of frequency scaling the low cycle time of a robot controller, allowing a Python application implemented, demonstrating real-time feeding of a pre-calculated trajectory for cutting Keywords Interpolation, Robotics, Real-time, Python, Joint control, Trajectory Newer robot controllers are getting increasingly open towards real-time trajectory feeding. Real-time quintic Hermite interpolation for robot trajectory execution. enabling joint-level control in 100 Hz. Developing sensor-based, real-time robot control applications is challenging. paths in a distributed, real-time, sensor-based robot application implemented and deployed The seven-axis Panda robot from Franka Emika can be controlled in real-time through Several other robot controllers provide real-time interfaces for trajectory feeding at challenge for Python-based real-time trajectory feeding application. motion service, and thus control the robot arm in a moderate real-time frequency. • established a re-connectable real-time motion service via the Franka Control Interface Real-time robot trajectory generation with Sensor-based real-time control of industrial robots. work_qr5wenjkarbr7dbdgeia4qpux4 Design of University Resource Website and Security Measures in IPV6 of learning resource sharing platform in the pure IPv6 Keywords-IPV6; Address Binding; Decision Tree Internet users, making the urgent increase in IPv4 address maintain the use of ipv4 addresses, there are technologies develop the campus learning resource sharing platform based upload and download and browse learning resources, to verify the IPv6 address and user identity. users can browse the resources on this platform, but they authentication to determine the administrator''s IPv6 address and the registration of the IPv6 address is the same network B. A huge resource of IPv6 addresses makes it possible to IPv6 uses address prefixes to identify networks, C. IPv6 address and user information binding ensure each user has a unique IPv6 address. address and bind the user''s information to their IPv6 address. realization of ipv6 makes the site security, user and resource learning resource sharing platform and user and information work_qrknnrsfj5d3xinxeligze6g4i We compare and benchmark five nameto-gender inference services by applying them to the classification of a test data set assign a gender to 73% of authors with full first names by using data from the US Social Figure 1 Geographical region of origin of the personal names from our test data set as inferred by working instead with the 5,779 names in our data set which possess a defined gender label. API, and genderize.io to assign genders to all names in our test data set. Table 4 Benchmark 1a: performance metrics for all services with their default gender assignments on the entire data set. Table 6 Benchmark 1b, data source: Performance of all services with their default gender assignments in terms of the metrics errorCoded and Gender API is the best performing service on all data sets; of available gender inference tools, testing five services on a manually labeled data set work_qto5jhdf2nehzjcza67fh65wse We propose a routing scheme for data gathering and aggregation in wireless sensor networks. uses a generic data aggregation model which accommodates different correlation conditions. Keywords: Sensor networks, data aggregation, particle swarm optimisation, correlation coefficient, energy In this paper, we propose a routing scheme for data gathering and aggregation in wireless sensor networks. scheme utilises a heuristic algorithm to optimise data traffic and the transmission structure in terms of energy The particle swarm optimisation (PSO) algorithm stems from the simulation of a simplified society model, and it Given the set of source node S and the base station d in wireless sensor networks G(V, E), our objective is to find a advantage of data aggregation to reduce the transmission task, the SPT algorithm expends the most energy compared Fig.5(a) illustrates the average energy consumption of the four algorithms when the number of source node k=15. work_qtojh7qkjvfmjcxu45bmddfw3y labelset observed in the training data that minimizes a weighted sum of the distances in Experiments on benchmark multi-label data sets show that the proposed method on Nearest labelset using double distances for multi-label classification. The effectiveness of the proposed approach is evaluated with various multi-label data sets. A multi-label training data set is That is, NLDD predicts by choosing the labelset of the training instance that minimizes the Input: new instance x, binomial model g, probabilistic classifiers h(i), training data T of validation data set, T2.1 We next fit a binary classifier to each of the L labels separately In this section we compare different multi-label algorithms on nine data sets. We evaluated the proposed approach using nine commonly used multi-label data sets from Table 1 Multi-label data sets and their associated characteristics. true labelsets of the test instances were observed in the training data (subset A), NLDD work_qvfmvqialfhorlcowa3mhbljue this work, we propose a novel method for creating interactive, user-resembling avatars a point-cloud or a contiguous polygon surface, and avatar interactions with the virtual Keywords Virtual reality, Immersion, Oculus rift, Kinect, Avatar embodiment How to cite this article Macedo Silva and Moioli (2017), A method for creating interactive, user-resembling avatars. devices, on the other hand, allow for whole-body user interaction but limit the immersion explaining how both Oculus Rift and Kinect could be used to create virtual interactive interaction to obtain an improved immersion experience in virtual reality, this work graphic visualization and simulate interactions between the point cloud and the virtual Kinect sensor and displayed as a point cloud avatar that is able to interact with virtual 3D implementation for the avatar visualization, in this work, sends all kinect point data points are able to interact with the virtual objects in the simulated environment. Available at https://www.digitaltrends.com/virtual-reality/oculus-rift-vshtc-vive/ (accessed on 06 June 2017). work_qxcof3it6vhyxbcv4b7vyzzs4m one hand and the publication of software artifacts and data for making results reproducible Figure 3 Responses to the question "I want to reproduce the results of other researchers or groups from their original work (software tools or software tools and for being able to reproduce results of other researchers." So with the I am willing to pay for easily accessible software tools and for being able to reproduce results of other researchers. I want to publish software tools and methods from my research to allow others to reproduce my results. I want to reproduce the results of other researchers or groups from their original work (software tools or libraries) to I want to reproduce the results of other researchers or groups from their original work (software tools or libraries) to Making simulation results reproducible-Survey, guidelines, and examples based on Gradle and Docker Making simulation results reproducible-Survey, guidelines, and examples based on Gradle and Docker work_qxvnriwsrjgqnj45s4f47lnzca accuracy at 10 fps rate for sitting posture recognition. Keywords Posture detection, Computer vision, Deep learning, Artificial neural network, network approach for tracking human posture in home office environments, where solution to this problem is skeleton based posture recognition (Jiang et al., 2015) using (2019) exploit Deep CNNs based on the DenseNet model to learn directly an end-toend mapping between the input skeleton sequences and their action label for human Such position would cause other known skeleton-based posture prediction methods to fail, Table 1 Layers of the proposed neural network architecture for human posture recognition. Figure 3 Activity diagram of the proposed method for sitting posture state recognition. Our method allows to achieve the real time sitting posture recognition with the same or Human posture recognition based on Detection of sitting posture using hierarchical image composition and deep learning Detection of sitting posture using hierarchical image composition and deep learning work_qzjy63q6cbfzlfevurt7tyno7m Keywords Social networks, Named entity recognition, Evaluation, Digital humanities, extracting such networks, is to first identify characters in the novel through Named Entity Evaluating named entity recognition tools for extracting social networks from novels have social networks that have a structure that is very different from more recent 20 classic and 20 modern novels; (2) a comparison and an analysis of social network on 20 classic and 20 modern novels in the section ''Named Entity Recognition Experiments compared the performances of social network extraction on classic and modern such as the Ser and Lord in the above example in order to cluster the names of one persons mentioned in classic and modern novels for the construction of the social network Table A5 Social network measures for classic and modern novels. Evaluating named entity recognition tools for extracting social networks from novels Evaluating named entity recognition tools for extracting social networks from novels work_qzkjl64qufcnpbhh34cyn34ozu University Library Internet WeChat Public Account Applicated for Student Values Education | Atlantis Press Proceedings of the 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018) University Library; WeChat Public Account; Values Education With the popularization of intelligent mobile phones, mobile phones instant messaging application has achieved rapid development, at the same time, along with the SNS (Social Network Service) development, combined with mobile phones instant messaging and SNS has become an important means of the current Internet environment for people to communicate, in this trend, the university library is constantly looking for every kind of platform the expansion of information service. TI University Library Internet WeChat Public Account Applicated for Student Values Education TI University Library Internet WeChat Public Account Applicated for Student Values Education Atlantis Press is a professional publisher of scientific, technical and medical (STM) proceedings, journals and books. The proceedings and journals on our platform are Open Access and generate millions of downloads every month. work_r2n6utxtgzbuvo5emvxy7yq5um in router design to provide address authenticity proof to Keyword-IPV9; CPK-card; Real-Name Routing; Trusted generation router and future network protocol. address (Alfa) are identified for identity authentication. destination address is BetaID, and the connection CPK-card is used and the original address is 2) All routing routers verify the original address, signed data to the router AlfaID. 1) Pc3ID does not use CPK-card but sends data to address as the public key and verifies the correctness of IPV4/IPV6 protocol to route data to Pc4ID via AlfaID. the BetaID route and forward the data to PC4ID. 1) Pc1ID using the local address as the public key source address of the packet as the public key and insert a CPK-card defined as AlfaID on any router, the decryption, and this data is encrypted data, coded key data format" is adopted, the enterprise product coding C. Enterprise product IPV9 address format system, the IPV9 data format is: work_r3mmyvnufnawhgtys6o7f7z7lq the support threshold, called Top-k frequent itemsets mining (TKFIM). TKFIM: Top-K frequent itemset mining technique based on equivalence classes. of the transaction table for finding frequent itemsets that result in overhead on input and FIs. It refers to the user''s choice of frequent itemsets in the dataset. Top-most frequent itemset mining technique that processes the top N impressive results Top-k algorithms based on FP-growth use FP-tree for pattern mining. (2002) proposed TFP (Top-k frequent closed itemsets mining algorithm), which user-specified support threshold parameter can affect the performance of the FIs mining itemsets of highest support, and it mines the candidates of the current class-based on the In the area of Frequent Itemset Mining, the very first algorithm, i.e., Apriori, was proposed based Top-k FIs techniques make use of FP-tree for frequent mining patterns. Data was taken from the Frequent Itemset Mining Dataset Repository (http: Mining frequent itemsets without support threshold: with work_r3udk3pxondchj7ht2quqypene rule mining algorithm based on Hadoop load balancing. original database to generate frequent item sets, and use the minimum support is unchanged and the transaction data set is increased, the incremental association rule mining algorithm Hadoop-based incremental association rule mining algorithm Hadoop-based incremental association rule mining algorithm Frequent item Sets; Association Rules [5], the frequent item sets mining algorithm of association of FUP, Incremental Association Rule Mining Algorithm tropical fruit, yogurt, cream cheese , whole milk item set mining algorithm has been difficult to support the item set mining algorithm is to add the Hadoop distributed platform to the frequent item set mining algorithm, which incremental association rule mining algorithm under Hadoop Association Rule Mining Algorithm Based on Hadoop Load Association Rule Mining Algorithm Based on Hadoop Load into the global frequent item sets to get the association rules. number of association rules mined by the Apriori algorithm work_r5i77dk2kzawzo3ozx4fu4uiqi Junghöfer, 2011) are all open source tools for EEG and MEG data analysis. functionality for referencing the data, line noise removal and detecting bad channels. The core activity of CTAP is preprocessing EEG data by cleaning artefacts, i.e. detection CTAP can thus help to combine the existing methods for EEG signal processing. new analysis steps, working from the provided CTAP_template_function.m. Users can � Functions to detect artefactual data, in channels, epochs, segments or ICA components, aggregate results to the CTAP_reject_data.m function. to detection functions, CTAP_reject_data.m will call an EEGLAB function such as Figure 3 Raw EEG data centred around a synthetic blink (A) before preprocessing and (B) after output, to include functionality such as statistical testing of detected bad data, for the Computational testing for automated preprocessing: a Matlab toolbox to enable large scale electroencephalography data processing ... Computational testing for automated preprocessing: a Matlab toolbox to enable large scale electroencephalography data processing ... work_r5oszxygkzf63ju3e2l3nruudq Research on Information Service of Home Care in Internet Plus Era will be applied to the community home-based care services is a old-age service system should be home-based, community-based information service platform for home-based care services information platform, providing build information platform for home care services. information technology of home care service refers to the been built on the information platform for the old-age service. started the home-based care services information platform From the "Internet plus" home care services in the information platform to carry out home-based care services 1. Pension information platform has set up a public service center Although the "Internet plus" home-based care services in information in the community home-based care services is government''s pension service information network platform. of "Internet plus" community home-based care services of "Internet plus" community home-based care services of "Internet plus" community home-based care services invest in "Internet plus" home-based care services platform. work_r6leqo5ppjbtbo47mcs26brbx4 survey has been conducted on Spark-based clustering of Big Data. Big data clustering techniques based on Spark: a literature review. • A taxonomy of Spark-based clustering methods that may point researchers to new and Future Direction'', we present our discussion the clustering big data using Spark and The papers relevant to Spark-based clustering of Big Data were retrieved from the – papers in the area of Spark-based Big data clustering. In this work, the taxonomy of Spark-based Big Data clustering is developed to cover all the Table 1 Comparison of Spark-based Clustering methods in terms of the supported Big Data characteristic (volume, variety and velocity) and in area of Spark-based clustering of Big Data. Fuzzy based scalable clustering algorithms for handling big data using apache spark. of intelligent k-means based on spark for big data clustering. A novel k-means based clustering algorithm for big data. work_r6pcfgi7a5ejnbnkrndajtj3t4 experiments, to filter peptide intensities based on linear correlations between replicates, iTRAQ, Proteomics, Quantitative Chemical biology, Drug dose-response, Protein drug profiling (2017), DOSCHEDA: a web application for interactive chemoproteomics data analysis. and protein quantification, such as Proteome Discoverer (https://www.thermofisher.com/), (Down Stream Chemoproteomics Data Analysis), which includes: (i) an open-source code data-input routine which enables the user to import different file types (.txt, .xlsx, .csv), DOSCHEDA processes the data based on a series of pipelines developed and integrated When peptide intensities and two replicates are available, DOSCHEDA implements The user should initially run the exploratory data analysis in DOSCHEDA up to the DOSCHEDA generates a variety of different plots depending on the user''s data input, as DOSCHEDA Down Stream Chemoproteomics Data Analysis Supplemental information for this article can be found online at http://dx.doi.org/10.7717/ MSstats: an R package for statistical analysis of quantitative mass spectrometry-based http://dx.doi.org/10.7717/peerj-cs.129#supplemental-information http://dx.doi.org/10.7717/peerj-cs.129#supplemental-information work_raz6yc35h5exrkxeaaitdt322e Application of the Source Encryption Algorithm Model in a model of the information source data encryption algorithm, data security of power system. Keywords-Data Communication; Encryption Algorithm power Internet of things will be a key point of China''s source encryption algorithm model, hoping to provide As an important part of network security, data Key is the key of data encryption, which controls the encryption algorithms usually require two keys: public the partial key format of data information source, as 3) The source data is rearranged and encrypted The data format conversion of an encryption Determine the starting time of the data encryption obtain the key encryption variables of time, solar term 5) Data decryption process model of the data format according to the time variable and Data encryption model Internet of things, the security of data connection is above data encryption model, the source information real-time data communication in power system [J]. work_rd3cilvao5avtowjpe2c6looxq This paper introduces the Research Articles in Simplified HTML (or RASH), which is a Web-first format for writing HTML-based scholarly papers; it is accompanied paper also presents an evaluation that involved authors and reviewers of RASH articles (https://lists.w3.org/Archives/Public/public-lod/2014Nov/0003.html) and Semantic Web is a Web application that allows authors to create HTML-based scholarly articles directly HTML (https://github.com/scienceai/scholarly.vernacular.io), is a work by the science.ai (http://schema.org) annotations for describing specific structural roles of documents as group called ''''Scholarly HTML'''' (https://www.w3.org/community/scholarlyhtml/) which Authorea (https://www.authorea.com) is a Web service that allows users to write papers (DoCO) (http://purl.org/spar/doco) (Constantin et al., 2016) from two HTML documents The Research Articles in Simplified HTML (RASH) format is a markup language that https://rawgit.com/essepuntato/rash/master/documentation/index.html https://rawgit.com/essepuntato/rash/master/documentation/index.html https://rawgit.com/essepuntato/rash/master/documentation/index.html this document (in particular, in its RASH version (https://w3id.org/people/essepuntato/ papers/rash-peerj2016.html)) we mainly use CiTO (Peroni & Shotton, 2012) and other https://rawgit.com/essepuntato/rash/master/documentation/index.html#metadata https://rawgit.com/essepuntato/rash/master/documentation/index.html#metadata https://w3id.org/people/essepuntato/papers/rash-peerj2016.html https://w3id.org/people/essepuntato/papers/rash-peerj2016.html RASH documents into different LaTeX styles, such as ACM ICPS (http://www.acm. (https://github.com/essepuntato/rash/tree/master/tools/docx2rash) documents (that can work_rgrzanwrozbotp3dzhmj2rovzy Design and Research of New Network Address Coding address and the application layer in the design of IPv6 I. NEW NETWORK ADDRESS IPV9 IPV9 decimal network/digital domain name system address length to 2048 bits, reduces the network bit, and the destination address of IPV9 packet is IPV9 addresses specify 256-bit identifiers for the interface, not to the node.IPV9 unicast addresses The second method ：The 256-bit IPV9 address Since IPV9 has an address length of 256 bits, the representation of IPV9 address prefix, a addresses use decimal Numbers, but prefix length Ipv6 address of 16 bits, in hexadecimal. represents the original Ipv4 address of 8 bits, expressed the IPv4 host 16-bit address is used. IPV9 ADDRESS FORMAT PREFIX 2 IPV9 ADDRESS FORMAT PREFIX 2 IPV9 ADDRESS FORMAT PREFIX FOR THE ORIGINAL ALLOCATION TABLE 3 IPV9 Decimal Network Working Group 0000 0000 1 8388608——16777215 1/512 ipv4-compatible addresses, are prefixed by 0000 0000 work_rhds7awthngdzlh5allgvhl7bi environment provided by CATIA, though further developed using CAA, calling for information, Keywords: CATIA, TOOLMANAGER, Tool library, CAA such as TOOLMANAGER software which is a highly integrated tool information management CNC programming, staff use CATIA tool management functions and redefine their own tool Therefore, we studied the CATIA integration technology of tool library. digital manufacturing, CATIA software is further developed using Component Application Architecture (CAA), and dynamic integration of CATIA and TOOLMANAGER tool library is second development and using of CATIA component application architecture (CAA) to the 2. Integration of CATIA Tool Library Using a Macro dynamic tool library, it can realize integration of CATIA and TOOLMANAGER. Development process of the integrated tool library We studied a technology of integration research tool library of CATIA in Shaanxi scientific The methods of CATIA integrated tool database using of macro integrated of CATIA tool library. Program Based on CATIA, Aeronautical Manufacturing Technology, vol. work_riaql7nykvgypmnszeqnlhdrlu Word embeddings learned by neural language models (Bengio et al., 2003; Collobert and Weston, We propose a new method for compositional semantics that learns to compose word embeddings We learn transformations for composing phrase embeddings from the component words based on extracted features from a phrase, where we assume FCT has two sets of parameters: one is the feature weights (α,b), the other is word embeddings (language modeling) we train FCT so that phrase embeddings – as composed in Section 2 – predict contextual words, an extension of the skip-gram objective (Mikolov et al., 2013b) to phrases. where α,b,ew are parameters (the word embeddings ew become parameters when fine-tuning is enabled) of FCT model defined in Section 2. et al., 2013a) for learning task-specific word embeddings, first training FCT and the embeddings with the LM objective and then fine-tuning the word embeddings using labeled data for the target task. work_rm5frn4rmvawvklaxkaojqxb6a graphical model to cluster sentences describing similar events from parallel news streams. NEWSSPIKE-RE generates high quality training sentences and learns extractors that perform much better than rival approaches, more which can achieve high precision and recall, are limited by the cost of labeling training data and are unlikely to scale to the thousands of relations on the This paper develops a new unsupervised technique, NEWSSPIKE-RE, to both discover event relations and extract them with high precision. • We develop a method to discover a set of distinct, salient event relations from news streams. • We describe an algorithm to exploit parallel news streams to cluster sentences that belong to the same event relations. phase has two main steps: event-relation discovery and training-set generation. our event relation discovery algorithm, which processes time-stamped news articles to discern a set model, described in Section 5.2, to accurately assign sentences from NewsSpikes to each discovered event relation E. work_rmebpspynnarhfkf425gsjanaq Design and Analysis of Thermoplastic Metal Detector focused on a specific type of RC Car which is a Metal Detecting Through research there aren''t many metal detecting RC Cars Keywords-Metal Detector; Finite Element; Thermoplastic; The design and development of remotely operated solarpowered mobile metal detector robot is a rescue robot to metal detector robot has been designed and implemented. available metal detector for detecting CIEDs. Design. The objective of this research is to design a RC car that metal detector will be incorporated that will be useful on goal with an unlimited budget is to use this car to detect material to build the RC-car metal detector. THE MATERIAL AND THE COMPONENTS OF RC-CAR METAL DETECTOR Figure 3 shows Chassis Fixed at front Differential The metal detector detects deeper than expected. RC-car metal detector. "Remotely Operated Solar-powered Mobile Metal Detector Robot", detector in detection and localization of pediatric metallic foreign work_rn4umcfjb5acliccy3njrowvca Rotation center calibration based on line laser rotating platform a certain point, which is a rotation center, and the calibration of the rotation center is the main factor that At present, the calibration of the center of rotation is basic process of rotating scanning, rotating center, and the calibration methods of three rotating centers (ellipse Keywords-Line laser; rotary scanning; Rotation center; A more accurate rotation center calibration can ROTATION CENTER CALIBRATION During the rotational scanning, the measured object ROTATION CENTER CALIBRATION METHOD The center of rotation can also be obtained by In order to accurately calibrate the center of rotation, rotating platform or the circular calibration block is cloud is plane-fitted to fit the rotation center of the The n point cloud data obtained by the rotation scan rotating platform, a series of center points can be fitted COMPARISON BETWEEN ROTATION CENTER CALIBRATION METHODS laser rotation scanning. platform parameters during the rotating scanning work_rnvsfzs6ffgp7d7tryvjj7kggi trained to perform face recognition in order to additionally recognize age and Keywords Facial representations, Face clustering, Age and gender recognition, Convolutional Efficient facial representations for age, gender and identity recognition in organizing photo age and gender prediction by learning face representation using preliminarily training proposed network are fine-tuned for age and gender recognition on Adience (Eidinger, (age, gender, etc.) given a facial image using multi-task training. VGGFace2 face recognition problem and then fine-tuned for one task (age or gender accuracy of age/gender recognition when compared to the available models trained only on proposed model achieves 97.5% gender recognition accuracy and age prediction MAE age/gender recognition accuracy and the face clustering quality comparable to very Efficient facial representations for age, gender and identity recognition in organizing photo albums using multi-output ConvNet Efficient facial representations for age, gender and identity recognition in organizing photo albums using multi-output ConvNet work_rs2wtgz7yna75cnukbqjaf3pn4 Design of Electric Power Line Drawing Algorithm Based on the basic information of power lines, realizes the function of automatically drawing the power line Keywords-Power Lines; Automatic Drawing; The Database; supply enterprises need to draw and archive the power position of a pole or change the information of a power drawing software for power lines. multi-branch tree with transformer as root node (node Schematic diagram of power line multi-branch tree structure traversal process of a multi-fork tree, which provides The automatic drawing of power lines can be realized POWER LINE AUTOMATIC DRAWING FUNCTION power lines and all nodes in the tree can be processed the automatic drawing of power line graphics. traverse the nodes of the tree according to hierarchy. B. Power Line Traversal Algorithm traversal algorithm, so that the automatic drawing of traversal algorithm, so that the automatic drawing of when the information about a power line is changed. work_rujstqwje5gkdm2bqer4drugey bilingual parallel corpora in six Indian languages, and use them to train statistical machine translation systems. study by posting 25 sentences to MTurk for Spanish, Chinese, Hindi, Telugu, Urdu, and Haitian Creole. crowdsourcing to construct a 1.5 million word parallel corpus of dialect Arabic and English, training a statistical machine translation system that produced higher quality translations of dialect Arabic We created parallel corpora by translating the 100 most viewed Wikipedia pages in Bengali, Malyalam, Hindi, Tamil, Telugu, and Urdu into Figure 4: Translation quality for languages with at least 50 Turkers. For single word translations, we calculate the quality of translations on the level of individual assignments and aggregated over workers and languages. for the 51 foreign languages that Google Translate covered at the time of the study. Table 3 shows the differences in translation quality when computed using in-region versus out-ofregion Turkers, for the languages with the greatest work_rvkwzwr6mrdpfa3xaatodygocu This paper presents a fast CCD optical spectrum data acquisition method based on FPGA, FIFO and DSP. Introduces a linear CCD timing sequence control signal generation and high speed ADC interface with FIFO and DSP DSP, FPGA is used to generate variety CCD timing clock and asynchronized FIFO control signal. so by using this DSP chip, the CCD sampling optical spectrum data can be fast transmitted 3. Linear CCD Time Sequence Signal Generation and Optical Spectrum Data Aacquisition CCD and ADC time sequence control signal generation module is show in Figure 5. Fig 5 CCD and ADC time sequence control signal generation module diagram How do the CCD sampling data fast transmit to DSP internal SRAM is secondly key design point. Figure 6 give a whole CCD and FIFO control signal FPGA schematic, Lpm_counter1 is used only for simulation be utilized as synchronized FIFO read data clock signal R_clk; from the Fig6 schematic, ADC_StartCtr mode provides work_rxaui7o4kzczlmk53n3amxhe54 We present a new framework to induce an indomain phrase table from in-domain monolingual data that can be used to adapt a generaldomain statistical machine translation system We also conducted an error analysis that showed the induced phrase tables proposed useful translations, especially for words and phrases unseen data or highly comparable corpora, our method induces an in-domain phrase table from unaligned indomain monolingual data through a three-step pro• dealing with source and target phrases of arbitrary length collected from in-domain monolingual data, (2014) uses only phrases from the target side of their parallel data and their morphological variants ranked and pruned according to the forward lexical translation probabilities given by their in the general-domain parallel data, lexical translation probabilities may be useful to score candidate This section demonstrates the impact of the induced phrase tables in translating in-domain texts For each pair of domain and translation direction, sets of source and target phrases were extracted work_ryxojgna3vbkfek5l2onbkh3vu by: (1) defining a BioAssay Template (BAT) data model; (2) creating a software tool common assay template (CAT) to leverage the most value from the BAO terms. process corresponds to a specific property in the BAO that is used to link assays and the We describe a data model called the BioAssay Template (BAT), which consists of a small The semantic description of templates and annotations uses a small number of additional Figure 4 Data model for annotated assays, which is used to apply a template to a specific assay. machine-readable assay annotations, we avoided assignments where BAO terms were For example, annotating an assay for cell viability (PubChem ID 427) Figure 8 First example of PubChem Assay text ideally suited for annotation with the CAT. Figure 9 Second example of PubChem Assay text ideally suited for annotation with the CAT. The underlying semantic data model for the template and assay work_rzcndqwjcbdidbg5nsppqfii2q neural model into a rich feature-based wordlevel quality estimation system. the output of an automatic post-editing system as an extra feature, obtaining striking results on WMT16: a word-level F MULT1 score of 2014; Kim and Lee, 2016), and systems that combine linear and neural models (Kreutzer et al., 2015; Figure 1: Example from the WMT16 word-level QE training set. translation (MT), its manual post-edition (PE), and the conversion to word quality labels made with the TERCOM tool predict word-level quality labels (yielding APEQE, the datasets above, the word quality labels are obtained automatically by aligning the translated and baseline systems provided in WMT15/16, we include features that depend on the target word and Table 11: Performance of the several word-level QE systems on the WMT16 development and test datasets. Table 11: Performance of the several word-level QE systems on the WMT16 development and test datasets. the WMT16 Word-Level Translation Quality Estimation Shared Task. work_s24csddavbdw7gozzjdjmffafy Generating Training Data for Semantic Role Labeling based on Label resource-based supervision in relation extraction, we focus on complex linguistic annotations, more specifically FrameNet senses In this work, we present a novel approach to automatically generate training data for semantic role labeling only used WordNet (Cholakov et al., 2014), not considering other sense inventories such as FrameNet. Our distant supervision approach for automatic training data generation employs two types of knowledge sources: LLRs and linguistic knowledge formalized as rules to create data labeled with FrameNet for argument identification and labeling of the semantic roles, which depends on the disambiguation result. training data for SRL consists of two stages, first generating sense-labeled data, then extending these to corpora and evaluate them extrinsically using a classifier trained on the automatically labeled data on In this work, we are the first to apply distant supervision-based verb sense labeling to the FrameNet work_s2b4q3na4rdbllvwo3ogtt3lga The book "Conducting Personal Network Research" is a conceptual presents the strategies to estimate the size of personal networks. the structural properties of her personal network the structural study of personal networks. methodology with the study of personal networks. The three books on the study of personal networks visualization strategies of personal network data. Social Network Analysis for Ego-Nets (Crossley et al., to integrate personal network data with qualitative Conducting Personal Network Research (McCarty case of personal networks, such accuracy generally both for collecting personal network data and The book Conducting Personal Network Research The book Conducting Personal Network Research analysis of personal networks (Crossley et al., 2015; Structure in personal networks. Structure in personal networks. Conducting Personal Network Research: A Commentary: How to do personal network surveys: from name generators to statistical modeling Commentary: How to do personal network surveys: from name generators to statistical modeling for personal network analysis. work_s2x6fjbeyvbsvnhwqctlx4ajde Using drug, protein and disease interactions, we built an evidence-weighted Keywords Melanoma, Knowledge graphs, Drug repositioning, Uncertainty reasoning other biological entities, like drugs and diseases, interact with the systems biology drugs, 3,820 diseases, 69,279 proteins, and 899,198 interactions. We examined drug and gene connections that were three or less interaction steps from melanoma, and additionally filtered interactions with a joint probability greater or Figure 2 The interaction graph of predicted melanoma drugs with a probability of 0.93 or higher A number of the drugs we identified are in clinical trials for treatment of melanoma. drug and the disease, and "Joint p" is the joint probability that all of those interactions occur. The graphical web application enables users to initiate a search using drug, gene, and Finding melanoma drugs through a probabilistic knowledge graph Finding melanoma drugs through a probabilistic knowledge graph Finding melanoma drugs through a probabilistic knowledge graph work_s4duytxexra2nfgn56bylrtljy A Visual Data Collection Method: German Local Parties and Associations This research captures local networks of German political parties and welfare agencies in regards to poverty. The computer assisted drawn networks were collected in an interactive participative way together with the interviewed egonetworks. The first hypothesis states that heterophile networks imply more social capital, which referred to different measurements (size, density, homophily). capture the local network of political parties and welfare agencies regarding poverty, and to explore whether there are differences concerning homophily and brokerage between politicians and welfare result, it can be illustrated how a visual inquiry through digital networking maps enables a collection of quantitative data that at the structures of fighting poverty at a local level by analysing the networks between local politicians, welfare agencies collect data visually through network maps was to show how digital network maps facilitate collecting and analysing quantitative data. work_s6h3rwomgrfw3hvq5b7lfpywai Keywords: Simulation, Direct torque control, Space vector modulation. appropriate space voltage vector on the motorTorque, flux linkage for Bang-Bang control [4].However, Figure 2 depicts the relationship between the stator flux linkage and the space voltage vector in the motor 4. Direct Torque Control of Space Vector Modulation synchronous motor based on space vector modulation is shown in Fig.3, Where the reference flux calculation model element and the space voltage vector modulation element SVM replaces the flux that the conventional DTC can only be controlled by selecting six basic active space voltage vectors and voltage vector to by real-time sampling calculation can be more precise control of the stator flux linkage. The Research of Direct Torque Control Based on Space Vector Modulation The Research of Direct Torque Control Based on Space Vector Modulation The Research of Direct Torque Control Based on Space Vector Modulation The Research of Direct Torque Control Based on Space Vector Modulation work_s6nrg5wnavdkrjcrx45chwcn2a GRNsight is a web application and service for visualizing models of gene regulatory GRNsight is a web application and service for visualizing models of smallto mediumscale gene regulatory networks (GRNs). input file format is found on the GRNsight Documentation page: http://dondi.github.io/ et al., 2001; http://graphml.graphdrawing.org/) files and export network data in those the GRNsight user interface, Demo #4: Weighted GRN (21 genes, 31 edges; Schade et al., 2004 data), and displays weight parameters output by the demonstration file, Demo #3: Unweighted GRN (21 genes, 31 edges); (B) graph from (A) manually manipulated from within GRNsight; (C) the (D) GRNsight automatic layout of the demonstration file, Demo #4: Weighted GRN (21 genes, 31 edges; Schade et al., 2004 data); (E) graph from GRNsight: a web application and service for visualizing models of smallto medium-scale gene regulatory networks GRNsight: a web application and service for visualizing models of smallto medium-scale gene regulatory networks work_sa3hjtqiofa2vajqd4wuth7rmi Information and Infection Dynamics across Sub-networks dynamics of contact infection but the transfer of health-care beliefs and resulting health-care behaviors across that between sub-networks in (a) contact infection and (b) belief transfer. Measured in terms of time to total infection, degree of linkage between subnetworks plays a minor role. reinforcement, and measuring belief transfer in terms of time to community consensus, we show that degree of linkage between sub-networks plays a major role in social communication of beliefs. Castillo-Chavez 2005; Barrett, Bisset, Leidig, average time to total infection across a network, not hold in general that full linkage between subnetworks of type x will result in a single network of Average Time to Total Infection with Increasing Links between Sub-networks with a single link between total sub-networks Contrasting Dynamics of Infection in Single and Linked Sub-networks degree of sub-network linkage in belief or Time to Belief Consensus with Increasing Linkages between Sub-networks work_seu3plr3nfhaxfaujqqxfctmky Early attempts to automatically model physical systems searched for simple mathematical regularities in observed quantities. The Lagrangian is well-suited to be the output of an automated modelling algorithm. search over the possible Lagrangians, working to improve the score. Code for the score function, search algorithms and the datasets we use below can be Figure 2 Result of running the algorithm on simulated data from the five test systems. generating a model in this form the algorithm gives insight into the system directly from We have shown that the algorithm can find models which successfully predict the future Figure 4 Predictions for different initial conditions of the learned simple pendulum model (red tree-based expression search is able to converge on this model. We have shown that the algorithm generates models By capturing the idea of searching for least action models in an algorithm An algorithm for discovering Lagrangians automatically from data work_sez4tbvmsnazjc6uvf5fqvutky the text in a Burrows–Wheeler transform (BWT) and a compressed label sequence in The label sequence is taken in the order of the text (TL-index) or Results: These indexes allow efficient text–label queries to count and find labeled The TLBW-index has an overhead on simple label queries but is very efficient to index the text, a bit vector BA marking the positions in the text where the labels change, and a WT WA indexing a compressed label sequence (Fig. 2A). Figure 2 TLand TLBW-indexes store a text of length 21 with four unique labels. Given a labeled text (T, A), the TLBW-index is defined as (U, BD, WD) (Fig. 2B). TLBW-index, we look for the label of all the pattern''s letters. Table 2 Size, build and query times of three indexes indexing labeled texts, on three simulated files and on a genomic DNA sequence file with work_sgan6o56yzdw3a2lwkfmts7jma learn to perform implicit bridging between language pairs never seen explicitly during training, showing that transfer learning and zeroshot translation is possible for neural translation. model, taking advantage of multilingual data to improve NMT for all languages involved. combination during training (zero-shot translation) — a working example of transfer learning within neural translation models. improved with little additional data of the language pair in question (a fact that has been previously confirmed for a related approach which token at the beginning of the input sentence to indicate the target language the model should translate translation where the model learns to translate between pairs of languages for which no explicit parallel examples existed in the training data, and show again two single language pair models trained All of the multilingual and single language pair models have the same total number of parameters as the Table 1: Many to One: BLEU scores on for single language pair and multilingual models. work_shio3as3kbbcpkmwhnofspvq6q Keywords Personality prediction, Social media behavior, Deep learning, Feature learning How to cite this article Liu and Zhu (2016), Deep learning for constructing microblog behavior representation to identify social media attributes obtained by artificially means, LRFV could represent users'' linguistic behavior algorithm to investigate the correlation between users'' linguistic behavior on social media linguistic representation for personality prediction based on the deep learning algorithm. Lima & De Castro (2013) used a semisupervised method to predict personality based on the attributes of linguistic behaviors investigate the correlation between a user''s social network behavior and personality. characteristics, for each trait of personality, we build a linguistic behavior feature learning prediction model based on linguistic behavior feature vectors. is concluded that personality prediction based on the linguistic behavior in social network model also obtain better results based on the linguistic behavior feature vectors. users'' personality traits and their social network linguistic behaviors. work_si36pup6v5frdgnsep24cnugs4 samples of minority class that have identical distribution as real XSS attack scenarios. Data augmentation-based conditional Wasserstein generative adversarial network-gradient penalty for XSS attack detection system. (attack labels) to generate valid and indistinguishable samples of real XSS attack data. real training data arbitrarily; the process is performed only if the generated sample x̃ • The proposed method is evaluated with two real and large unbalance XSS attack datasets. generative model G for learning the distribution of data and, second, the discriminator D, generate synthetic samples of attack class (minority) with identical distribution to real XSS models using real training dataset to generate synthetic data. generate any sample found in the XSS attack training dataset. Table 3 Detection results using data augmented generated through different methods on the CICIDS2017 dataset. Table 4 Detection results using data augmented generated through different methods on the second dataset. work_skpo2nwcjjhrha4u7r42xpqgva In this article, we study a research paper recommender system focusing on serendipity. methods of candidate items (i.e. research papers) for computing profiles, as well as user Along with the three factors User Profile Source, Text Mining Method, and Ranking Most existing studies have evaluated research paper recommender systems by focusing In previous studies addressing content-based research paper recommender systems Another study proposed research paper recommendations based on a user''s Tweets, which 1. Candidate items of the recommender system (i.e. research papers) are processed by one build a user profile in the context of a research paper recommender system. of a user profile that have been covered by papers already selected for recommendation, each user''s Tweets and research papers by matching the text with the labels of the concepts User profile based paper recommendation system. Influence of tweets and diversification on serendipitous research paper recommender systems Influence of tweets and diversification on serendipitous research paper recommender systems work_snkm6xv4wzaolcpximorxj4j2m Although CCG parsers perform at state-of-the-art levels (Rimell et al., 2009; Nivre et al., 2010), fullsentence accuracy is just 25.6% on Wikipedia text, unlikely to be made available, recent work has explored using unlabelled data to improve parser lexicons (Thomforde and Steedman, 2011; Deoskar et similar techniques to CCG supertagging, hypothesising that words which are close in the embedding Recent work has explored using vector space embeddings for words as features in supervised models for a variety of tasks, such as POS-tagging, We introduce models for predicting CCG lexical categories based on vector-space embeddings. Dimensionality is the set of dimensions of the word embedding space that we experimented with, and Training Words refers to the size of the unlabelled corpus the other embeddings would perform better with different training data, dimensionality, or model architectures. Table 3: Comparison of different model architectures, using the Turian embeddings and a 5-word work_sobah75y3vbb7l3xrdslmpf2la remotely estimated water quality parameters are mostly approach to derive oxygen –related water quality parameter, Keywords-Remote Sensing; Algorithm Model; Coastal lake; A. Remote Sensing-based Water Quality Retrieval of water quality parameters using remote sensing presented water quality retrieval models with Observed DO data during four seasons in Lake Edku zones conditions defining water quality in coastal lakes of Spatial distribution of derived Temperature (ºC) within Lake Edku in spring, 2016 Spatial distribution of derived TSS (mg/L) within Lake Edku in spring, 2016 Spatial distribution of derived Chlorophyll-a (mg/m3) within Lake Edku in spring, 2016 water quality levels experienced in the lake is Retrieved DO concentrations in Lake Edku during winter season evaluation of remotely sensed data for water quality monitoring. sensing of lake water quality characteristics, including chlorophyll review on water quality parameters estimation using remote sensing Water quality assessment of Lake Edku using physicochemical and work_sps3smiruzambm2egtdi46wgpy and Nivre (2012) by giving a general characterization of dynamic oracles as oracles that are nondeterministic, in that they return sets of transitions, Using this framework, we derive novel dynamic oracles for the hybrid (Kuhlmann et al., 2011) and easy-first (Goldberg and Elhadad, 2010) transition systems, which dependency parsing, presenting the arc-eager, arcstandard, hybrid and easy-first transitions systems parse tree is given by Ac. The system has 3 transitions: RIGHTlb, LEFTlb, SHIFT, defined as follows: returns true if transition t is correct for configuration c and gold tree T . Traditionally, the oracles for the left-to-right systems are static: they return a single correct transition Finally, we use this method to derive concrete oracles for the arc-eager, hybrid and easy-first systems, A non-deterministic oracle is correct if and only if, for every projective dependency tree T , every configuration c from which work_spwpktmrkjellmefa22h7vbnp4 Transforming Dependency Structures to Logical Forms for Semantic Parsing based on the lambda calculus for deriving neoDavidsonian logical forms from dependency Semantic parsers map sentences onto logical forms DEPLAMBDA uses this system to generate robust logical forms, even when the dependency structure does not mirror predicate-argument relationships in constructions such as conjunctions, prepositional phrases, relative clauses, and wh-questions system is as follows: All natural language constituents have a lambda-calculus expression of type For example, (dobj acquired Pixar) receives the following expression after composition: Recall from Section 2 that every s-expression subtree receive a logical form of type η = Ind × Event → Bool. We next verify empirically that our proposed approach derives a useful logical compositional semantic representation from dependency syntax. In addition to the dependency-based semantic representation DEPLAMBDA (Section 3) and previous convert a graph built from dependency trees and semantic role structures to a first-order logical form, work_sqfox4ylnzcxfbetwox2eu5t2q TREETALK: Composition and Compression of Trees for Image Descriptions free text on web pages, to textual descriptions directly describing depicted image content (i.e. captions). Figure 1: Harvesting phrases (as tree fragments) for the target image based on (partial) visual match. useful bits of text (as tree fragments) from existing image descriptions using detected visual content and propose a tree compression algorithm that performs a light-weight parsing to search for the optimal set of tree branches to prune. Our work results in an improved image caption corpus with automatic generalization, which is publicly available.1 As illustrated in Figure 1, for a query image detection, we extract four types of phrases (as tree Figure 2 shows a simplified example of a composed sentence with its corresponding parse structure. scores (log probabilities) estimated from the 1M image caption corpus (Ordonez et al., 2011) parsed using the Stanford parser (Klein and Manning, 2003). work_srlmqknhfna7jkf6u2ea4wgme4 classification of cervical cells from Whole Slide Images (WSI) with optimum feature resizing, Convolution neural network, Sipakmed, Herlev, Metamorphic analysis, Deep learning propose a multi-class classification for single-cell and Whole Slide Images of cervical classification for whole slide images of the SIPaKMeD dataset, which helps in carrying Figure 3 Single cell Images from the Herlev Dataset, categorized into seven classes and shown as (A) superficial squamous epithelia, The VGG-19 model was trained on both the datasets to carry out binary and multi-class Table 1 The binary classification prediction scores for Herlev and SiPaKMeD Cervical Cancer Table 2 The multi-class prediction scores for the Herlev and SIPaKMeD Cervical Cancer datasets under evaluation criteria, that is, Accuracy, Cervical cancer detection in pap smear whole slide images using convNet with transfer learning and progressive resizing Cervical cancer detection in pap smear whole slide images using convNet with transfer learning and progressive resizing work_srqjbxaffzfbdcxe4yczy7eafi hybrid method for heartbeat classification via convolutional neural networks, Keywords Arrhythmia, Heartbeat classification, Focal loss, Convolutional neural network, A hybrid method for heartbeat classification via convolutional neural The article presents a hybrid method for heartbeat classification via CNN, multilayer 2001), our method achieves superior classification performance than existing heartbeat especially CNN-based, heartbeat classification methods have received a lot of attention. CNN and focal loss propose an ECG heartbeat classification method. (true negative) is the number of heartbeats that are not in the ith class and not classified Table 4 Performance comparison of our proposed method with existing works in SVEB and VEB classes. A hybrid method for heartbeat classification via CNN, MLP and focal loss is developed https://github.com/JackAndCole/Deep-Neural-Network-For-Heartbeat-Classification https://github.com/JackAndCole/Deep-Neural-Network-For-Heartbeat-Classification https://github.com/JackAndCole/Deep-Neural-Network-For-Heartbeat-Classification https://github.com/JackAndCole/Deep-Neural-Network-For-Heartbeat-Classification A hybrid method for heartbeat classification via convolutional neural networks, multilayer perceptrons and focal loss A hybrid method for heartbeat classification via convolutional neural networks, multilayer perceptrons and focal loss work_ssqv7d4xyjfizftlgawxtv4pvq A New Non-Singular Terminal Sliding Mode Control and Its Application to Chaos non-singular terminal sliding mode control to restrain the saturation function, the control method can solve the interconnected power system will be stable in a short time Function; Non-singularity; Sliding Mode Control; Fixed Time non-singular terminal sliding mode control to realize stability proposed a non-singular fixed-time terminal sliding mode singularity problem of the sliding mode controller, but the singularity problem of the sliding mode controller, but the By proposing a timing non-singular fast terminal control to overcome the singularity in terminal sliding mode control. systems, the fix time for the controlled system to reach the control method with fixed time stability has been applied in singularity problem in the terminal sliding mode control is Simulation of Load Frequency Control for Three Area Power System mode control design with application to power system chaos Y. Zuo, "Non-singular fixed-time terminal sliding mode control of work_su3ucr3qh5gv3isgkna5ie37mi A CEP Privacy Security Access Control Framework Based on Event Attribute the CEP privacy security access control object in depth, engine with the event attribute detecting tree as the operating result, CEP can perform security access control on the data CEP PRIVACY SECURITY ACCESS CONTROL OBJECT The user''s access right to the event attribute control operators of security access to event attribute (record privacy security access for the CEP input event flow should this, this article defines CEP privacy security access control Object The privacy security access control object in CEP CEP engine, Э is the set of the security access control CEP privacy security access control framework security access operation to the event attribute requiring definition of privacy security access operator of event Algorithm 1 Validity Verification Algorithm of CEP Privacy Security Access Control in Event Pattern (c) Event attribute security access operator efficiency test The event attribute access operator is completely read work_sylvnwgcdjbulhidyf7lrawwri how different types of empirical studies can be used for educational purposes in software empirical studies contribute to high-quality learning outcomes, to student motivation, (2017), Guidelines for using empirical studies in software engineering education. courses to (1) provide an environment in which students can experience real-life problems experimentation or case study research, and direct experience of the value provided by while it is common to carry out empirical studies in software engineering with students as lack of guidance for using empirical studies in software engineering education in cases (see ''An Overview of Empirical Study Types for Software Engineering Education'') for use The software engineering literature includes a number of empirical studies with students, an overview of (empirical) study types utilised in software engineering education. learning goals associated with empirical studies in software engineering teaching that we a software process modelling course, including an empirical study. Case study research in software engineering: guidelines and examples. work_sytjzbtv25fdlo34wpz4crxwue Results: Warmth and competence increased adherence intention and consultation doctor''s realism and potential for eeriness might affect a patient''s intention to adhere high-realism source was the doctor depicted by a real human actor and the low-realism message source''s warmth, competence, and realism influence the enjoyment of the virtual virtual or real, given that a doctor''s warmth and competence increase patient satisfaction designed to manipulate the doctor''s level of warmth, competence, and realism, respectively. Dr. Richards'' human realism and eeriness were measured using three source appearance test the main and interaction effects of Character, Outcome, and Depiction on Warmth, Warmth, Competence, Human Realism, Eeriness, and Enjoyment. Variables Warmth Eeriness Enjoyment Human Realism Depiction (Model 4a) and between both Eeriness and Warmth and Enjoyment and Human The doctor''s digital double: how warmth, competence, and animation promote adherence intention The doctor''s digital double: how warmth, competence, and animation promote adherence intention work_sznadejg4faflibuhqbxnvyuyy linking Wikidata and the Global Biotic Interactions database (GloBI). and GloBI were linked by comparing graphs of biodiversity identifiers external to each (2018), 20 GB in 10 minutes: a case for linking major biodiversity databases using an open sociotechnical infrastructure and a pragmatic, cross-institutional collaboration. Keywords Biodiversity, Collaboration, Identifiers, Wikidata, Graph, Linking Figure 2 Frequency of Wikidata taxa linked to biodiversity databases. Both Wikidata and GloBI have taxon graphs that map to identifiers from external databases OTT, Wikidata, and GloBI taxon graphs maintain links to GBIF, IF, NCBI and WoRMS All of the input data sets can be found at: https://doi.org/10.5281/zenodo.755513 (GloBI After 10 min of processing, GloBI was linked to Wikidata using pre-existing identifier The Wikidata, OTT, and GloBI taxon graphs overlap on the NCBI and (https://www.wikidata.org/wiki/Q140) has 25 links to external databases, not all of them Projects like OTT, Wikidata, and GloBI that keep identifier-based taxonomic graphs make work_t3ov6m4zkffijleqvdqdvl3z5u machines (VMs) in a large-scale data center consisting a few thousands physical Cloud data centers face highly dynamic workloads varying over time and We suggest an analytical model for cloud computing data centers when the with general distribution sojourn time, the mean power consumption is calculated. will be achieved with randomize assignment of incoming VMs onto PMs. Extensive simulation supports the validity of our analytical model. Keywords Optimization, Cloud computing, Placement, Energy consumption, Service level Microsoft, have huge data centers to provide on demand virtual machines (VMs) to their We calculate probability of SLAV as well as total power consumption in a cloud They obtained the distribution of response time for a cloud data center modeled as an Figure 3 depicts the SLAV probability in data center at steady state. Figure 3 SLAV probability in data center at steady state for various β (A) β = 69 (B) β = 73 (C) β = 80 work_t4zfmm6xmrhzlkr2cb7ksjcyvu Research on Multi Resonant LCL Harmonic Suppression Strategy multi-resonance LCL harmonic suppression strategy is active filter [1] [2] [3]; the micro-grid harmonic suppression multi-resonance control and LCL constant power control is Figure 1 is LCL multi-resonant constant power grid are the actual values of the grid voltage and current, d current loop control module, the reference values , current loop control module in Figure 1 solves the resonance B. Multi resonant LCL Grid connected Control current deviation, through the multi-resonant control get the multi-resonance constant power control, the simulation output after LCL multi-resonant constant power control is waveforms before the LCL multi-resonant constant power multi-resonant constant power control after the current LCL MULTI-RESONANT CONSTANT POWER GRID-CONNECTED LCL MULTI-RESONANT CONSTANT POWER CONTROL BEFORE LCL MULTI-RESONANT CONSTANT POWER CONTROL BEFORE LCL MULTI-RESONANT CONSTANT POWER CONTROL BEFORE power control filter before the voltage distortion rate of work_t5ywgdkj2zf2vla3p2ylgicvhe The contribution of this paper is to propose a split-andtransfer flow model for entropic centrality, where at every node, the flow can actually be transfer entropic centrality set-up for the ease of computation, and carry out three case transfer entropic centrality over a graph with suitable equivalent edge probabilities (which The transfer entropic centrality CH(v1) of v1 is computed using (1), for a uniform edge probabilities on graph edges and (3) prove that computing the split-and-transfer entropic centrality104 can be reduced to transfer entropic centrality over a graph with suitable equivalent edge probabilities105 Consider the network shown on Figure 1a and assume that the probability of an indivisible flow going114 Figure 1 The transfer entropic centrality CH (v1) of v1 is computed using (1), for a uniform edge distribution (the choice of an edge at a given vertex is chosen uniformly at random among choices of unvisited neighbors) in (A), and for a non-uniform distribution in (B). work_tbq5gksxpvdpph6wuaxrj725ju ABSTRACT: Aircraft design, manufacturing and CFD analysis as part of aerodynamic course, the students weight ratio and wing loading, use initial sizing and calculate the aerodynamic forces. aircraft based on the geometrical dimensions resulted from the calculations and use the model to build a The analysis of the aircraft resulted in a study that revolved around the lift and drag generation of this As to determine the lift and drag forces generated by this plane, a model was created in Keywords: computational fluid dynamics (CFD), design, aircraft, aerodynamic, wind tunnel to calculate the geometry of the wings, fuselage, airfoil, and tail section of the aircraft. The wind tunnel was used to measure lift and drag forces for various angles of attack that The wing area is also a vital component to the design of the aircraft, calculated by simply multiplying results for the designed aircraft''s aerodynamics. calculations, CFD simulation, and scale model wind tunnel test. work_tbt4lajyr5aenhlg2mr3q6h3wi Artificial intelligence and multi agent based distributed ledger system for better privacy and methodology for providing privacy and security combining the AI-based intelligent agents previous researchers regarding the security and privacy using the Multi agent bases based multi agent systems provide the communication between users and the EHR service The DLT based authentication agent receives the user name and and the DLT based authentication agent for accessing the EHR data. � The proposed system consists of two intelligent based connected agents such as the user � AI and blockchain based intelligent agents communicates between the users and the DLT based systems is used for user authentication and also for providing access to the Artificial intelligence and multi agent based distributed ledger system for better privacy and security of electronic healthcare records ... Artificial intelligence and multi agent based distributed ledger system for better privacy and security of electronic healthcare records ... work_tdfta4ovtfdmzgmjiwx5sfifvm of network recognition higher on the MNIST data set. Deep Capsule Network; Handwritten Digit Recognition Deep Capsule Network; Handwritten Digit Recognition training data than convolutional neural network, but the capsule network structure in the field of functional routing method between capsule layers based on EM 1) Encoder structure of deep capsule network Network structure of deep capsule Network structure of deep capsule connection layer of capsule network. improved deep capsule network as shown in the digital capsule layer, reconstructs a 28×28 image after STRUCTURE COMPARISON OF CAPSULE NETWORK AND DEEP the j prediction vector �̂�j|i of each low-level capsule I Test accuracy chart of deep capsule network under 30 epochs Test accuracy chart of deep capsule network under 30 epochs Comparison between the accuracy of capsule network and deep Comparison between the accuracy of capsule network and deep handwritten digital images with deep capsule network, shortcomings of capsule network, the convolution work_tdwmpi6kwvhcfluez2l5gq6ejm Creating a Conference Poster with High-Resolution Network Figures Creating a poster with high-resolution network images can be a challenging task. In this article, the process of exporting a network figure from a network analysis tool, importing it in a vector graphics tool, and preparing the poster for print is discussed. a tutorial-like description of the critical steps for creating a conference poster with highresolution network figures. a poster with a network figure, these mapping strategies cover only some of the necessary steps. poster with a high-resolution network figure are described below. Table 1: Workflow of creating a poster with a network figure. figure in your favorite SNA tool as a vector graphics file. Pre-Processing  SNA Tool  Vector Graphics Tool  Poster Printing • Prepare Network Data • Create Layout • Import Network Figure • Transfer Poster File PNG files can create decent network images, vector graphics files will always have work_tfvl7qzf7jgyhlqbehmj5muepi probabilistic programming languages, PyMC3 allows model specification directly in use custom statistical distributions, samplers and transformation functions, as required by Bayesian linear regression model with normal priors on the parameters. We can simulate some data from this model using NumPy''s random module, and then use from pymc3 import Model, Normal, HalfNormal Detailed notes about distributions, sampling methods and other PyMC3 functions are operators and functions to PyMC3 objects results in tremendous model expressivity. stochastic random variables or models with highly non-normal posterior distributions. from pymc3 import NUTS, sample Figure 2 Kernel density estimates and simulated trace for each variable in the linear regression model. points for variables at the model specification stage, it is possible to provide an initial value Figure 4 Posterior samples of degrees of freedom (nu) and scale (sigma) parameters of the stochastic volatility model. Figure 7 Posterior distributions and traces from disasters change point model. work_tkn7xe72drcwdmb4dnl5as5iii Keywords Data stream processing, Cloud computing, Resource elasticity, Resource optimization for data processing in near real-time, which requires the application of SPEs like System S SLA, the system needs to provide more computational resources for data processing. available resources, the SPE is required to lease a new host for the additional operator represents the time to process one data item and pass it on to the following operator type computational resources to instantiate a new instance for the required operator type, operators are needed for SLA-compliant data stream processing, the second possibility is the stepwise data arrival pattern; (C) shows the resource provisioning configuration using the BTU-based approach using a BTU of 60 min for the the stepwise data arrival pattern; (C) shows the resource provisioning configuration using the BTU-based approach using a BTU of 60 min for the Besides the SLA compliance, we also consider the operational cost for data processing. work_tkqxtanwfvbirnxysm5b7syhnq neural network model to learn the statistical law of air pollutant values to realize the prediction of air quality in experimental results show that the air quality prediction Keywords-AQI; Air quality Prediction; BP Neural establishing an air quality prediction model. prediction of the changing process of air pollutants in achieves air quality the accuracy of the prediction This paper uses air quality prediction network model to achieve air quality prediction, features, build an air quality prediction model, improve AIR QUALITY PREDICTION MODEL B. Design of air quality prediction model quality prediction based on BP neural network. of the domestic research results of air quality prediction, Then, an air quality prediction method model based on paper uses BP neural network to predict the air quality Urban air pollution numerical prediction model system and its air pollution forecasting method based on BP model [J]. neural network models for the prediction of NO 2 and PM 10 work_tlps2yqrsbhxto74qmc2lfcdme Large-scale Word Alignment Using Soft Dependency Cohesion large-scale word alignment experiments. dependency cohesion as a hard constraint (Lin and word alignment model to softly influence the a generative word alignment model with a generative word alignment model with a generative word alignment model with 3.1 The Sequence-based Alignment Model the sequence-based model, source words are 3.3 Dependency Cohesive Distortion Model be very useful in the HMM alignment model. To align sentence pairs with the model in Eq. alignment of the sequence-based model (HMM LARGE training set to evaluate whether our model for word alignment, we construct four sub-models dependency cohesion model: 8) Soft-Cohesion-Gibbs: the wd-hc-mc sub-model Hard-Cohesion systems improve word alignment alignment that uses dependency cohesion as a soft model improves word alignment quality as well as It is possible that our word alignment model can alignment models for statistical machine translation. hidden Markov model for word alignment using work_tlrea27h5faizhj4uusgiwtrvi Violence Cracking Technology of SSH Service brute force the SSH service to finally obtain the password. the server, network security follows the principle of SSH PASSWORD BRUTE FORCE APPLICATION file and brute force it to get the password of these At this time, you need to brute the SSH service through the ssh login module in Metasploit to 3) Use the ssh_login module in Metasploit to crack the ssh_login module, as shown in Figure 5. the ssh_login module, as shown in Figure 5. Ssh_login module parameters PASS_FILE: brute force password dictionary USE BRUTESPRAY TO VIOLENTLY CRACK SSH Kali Linux installs its user and password dictionary V. VIOLENT CRACKING OF SSH PASSWORDS 5) Password-free login using SSH root@ target_ip ~/.ssh/authorized_keys files on the servers that need to not bad to use Metasploit for ssh brute force cracking. cracked record into the ssh.log file; the patator can add work_tnmbm7issbbq7crsyarn5qtlve Finally, Top-N serendipitous collaborators are generated based on the cosine similarity between scholar vectors. Keywords Deepwalk, Collaborators recommendation, Serendipity, Vector representation A serendipity-biased Deepwalk for collaborators recommendation. a serendipitous collaborators recommendation strategy by improving DeepWalk (Perozzi, collaborators for recommendation based on the cosine similarity between author vectors. walk in DeepWalk for serendipitous collaborators recommendation. • Recommend serendipitous scientific collaborators: we perform Seren2vec to learn the on the subset of DBLP, and evaluate the recommendation results from both accuracybased and serendipity-based metrics. collaborator recommendation list is finally generated by computing the profile similarity for computing the relevance score of all collaborator nodes for their target scholars. serendipity of a collaborator for his/her target scholar to their edge weight. Seren2vec includes three main processes: integration of serendipity into DeepWalk, vector representation learning of each scholar, and collaborators recommendation collaborators recommendation, which are the serendipity-based metrics including algorithm to integrate serendipity into collaborators recommender system. work_tsqcfpvhajcedozkby6jtihnzu The Establishment and Implementation of Information Network Security Plan Abstract—This paper explains the idea of information security to prevent the main" network security and the overall plan to A. The Concept of Information Network Security and The Information network security is a security protection to network security is based on the physical layer and operation Information Network and the Establishment of the The development of information network technology has and improve the network security plan and disaster recovery NETWORK SECURITY PLAN and train technical groups with strong network security B. The Main Contents of the Network Security Plan The security of information network issystem vulnerability information network system, is an important active defense at all levels of information network system, attention to the collection of network security information, attention to the collection of network security information, information network, and constantly improves the of improving the network security. The implementation of network security plan has work_tss5noirkrebvmtjsidydmgfru Space-delimited words in Turkish and Hebrew text can be further segmented into meaningful units, but syntactic and semantic context is necessary to predict segmentation. A standard (dependency) parsing system decides segmentation, morphological analysis (including POS), and syntax one after the other in a pipeline In this paper, we present a graph-based dependency parser for lattice parsing that handles the increased complexity by applying dual decomposition. The parser operates on morphological lattices and predicts word segmentation, morphological analysis, and dependency syntax jointly. We introduce the segmentation problem in Turkish and Hebrew in Section 2 and present the lattice Depending on the selected morphological analysis for each word, syntax and semantics of the sentence change. As opposed to lattice parsing, baseline systems are trained on the gold standard segmentation (and thus gold morphological analyses) in Joint Morphological Analysis and Dependency Parsing of Turkish. Joint Evaluation of Morphological Segmentation and Syntactic Parsing. work_tw4wakfkzbfmvcyhbrwr7qmcc4 Keywords Information-centric network, Cache replacement policy, Context awareness examples of policies used in ICNs. The current literature presents a massive number of performance evaluations for cache Figure 4 Properties from content dimension extracted from the cache replacement schemes for ICNs. Full-size DOI: 10.7717/peerj-cs.418/fig-4 Figure 6 Properties from network dimension extracted from the cache replacement schemes for ICNs. Full-size DOI: 10.7717/peerj-cs.418/fig-6 Table 4 Content and Network-based cache replacement schemes. Table 5 Content, node, and Network-based cache replacement schemes. Table 6 Node and/or network-based cache replacement schemes. An in-network caching scheme based on energy efficiency for content-centric A cache content replacement scheme for information centric network. cache replacement policies for content-centric networks. On performance of cache policy in information-centric networking. between content popularity and network topology information for icn caching. Contextual dimensions for cache replacement schemes in information-centric networks: a systematic review Contextual dimensions for cache replacement schemes in information-centric networks: a systematic review work_tww7cprsyzdg5fsft2jhn6hweq server network to decentrally store and archive data in the form of nanopublications, researchers to publish, retrieve, verify, and recombine datasets of nanopublications in Keywords Data publishing, Nanopublications, Provenance, Linked Data, Semantic Web Basing the content of this network on nanopublications with trusty URIs has a number of Specifically, a nanopublication server of the current network has the following and the number of stored nanopublications, the server''s URI pattern and hash pattern, Pp, the number of stored nanopublications np, the journal identifier jp, the server''s URI To publish some new data, they have to be formatted as nanopublications. URI (or just their artifact code) from the nanopublication server network. also be published as a nanopublication, with a reference to the given index URI in the Figure 5 This screenshot of the nanopublication monitor interface (http://npmonitor.inn.ac ) showing the current server network. of the servers by requesting a random nanopublication and verifying the returned data. work_tyhqgdkjnzax3gvmp2ffowkomi Keywords Agent-based modeling, Standard model, Statistical analysis of simulation output, methods to help design the runs for simulation models and interpreting their output agent-based modeling framework, parallelization strategy, random number generator, In order to analyze the output of a simulation model from a statistical point-of-view, we for normally distributed samples, which is often not the case for simulation models Under the graphical methods umbrella, a histogram shows the approximate distribution of a data set, and is built by dividing the range of values into a sequence of parameter set 1, but as model size grows larger, the discrete nature of the data clearly stands arg maxCi. For smaller model sizes this FM follows a mostly normal distribution, but as studied from a statistical perspective for two parameter sets and several model sizes. Agent-based modeling and simulation: ABMS examples. Tutorial on agent-based modelling and simulation. work_u2itmvi23nfwjgk64b2kurj7xy Fully character-level neural machine translation without explicit Most existing machine translation systems operate at the level of words, relying on explicit segmentation to extract tokens. For one, they are unable to model rare, out-ofvocabulary words, making them limited in translating languages with rich morphology such as Czech, This demonstrates excellent parameter efficiency of character-level translation in a multilingual setting. empirically show that (1) we can train character-tocharacter NMT model without any explicit segmentation; and (2) we can share a single character-level instance, a character-level model may easily identify morphemes that are shared across different languages. Highway networks are shown to significantly improve the quality of a character-level language model when used and the translations from the subword-level baseline and our character-level model as bpe2char and char2char, respectively. bilingual character-level models can be trained in multilingual many-to-one translation task, where results show that the character-level model can assign work_u3ht4us6svdjlmykd4tpyl36vq Research on Robust Model for Web Service Selection Web services can solve this problem and become the most Web services can solve this problem and become the most paper first proposes a local optimal selection model based on The Web service selection method based on effectively select more robust services for users. robust QoS-aware, reliable Web service composition The application of robust optimization method to service selection model based on uncertain QoS is described in QoS-based Web service selection is gradually playing an service selection process based on QoS determination, it is service selection model for a single QoS attribute. method in the selection of Web services based on uncertain service selection method, considering the uncertainty of QoS, a single uncertain QoS service selection model based on the the service selection model based on uncertain QoS and The Web service composition based on uncertain QoS Service Composition Based on QoS.2013-06-08. work_u4ffrj3lbndn5l6msbd6yagame relates to the diversity of information accessed by individual users through an analysis of To study the diversity of information exposure we use a massive collection of Web clicks Figure 1 Diversity of information sources accessed through different online channels. (D) Social media traffic generated by a collection of users. clicking on a link from a search engine, email client, or social media site, and going to one To measure diversity of information exposure in the context of news, we created a separate targets in the click collection, yielding the news dataset used in our analysis. of diversity on number of clicks is different for each category of traffic. Figure 4 illustrates the top targets of traffic from search and social media on a diversity measurements based on anonymous traffic data do not distinguish between users, Figure 4 Top websites that are targets of 40% of clicks for search (A) and social media (B). work_u66sz3ktqbbzvan2wds5ow7shq texts, this paper constructs an intelligent reading model. algorithm, are filtered to build an intelligent reading model. Keywords-Natural language processing(NLP); Decision Tree; if a data is trained by three classifiers, the output result of Data acquisition Data processing Feature extraction Training classifier Building Model word segmentation, it is necessary to use the algorithm based new words into the custom dictionary, followed that process 3) Feature extraction：For the processed data in step (2), the TF-IDF algorithm is used to extract the feature value word-text matrix generated by step (3).so that three value, training classifier, establishing model and carrying out whose value is the number of words occurring in the training By using the TF-IDF algorithm, the text information is Decision tree algorithm mainly includes feature selection means that, if a data is trained by three model, the output decision tree Bagging Gauss Bayesian Combination algorithm reading model based on the combination of decision tree, work_ubkaeukuajb4nfg6rg52icqrbe research firstly presents a colored Petri net based formal model of CAROM. of resources in clouds by presenting a comprehensive formal analysis of CAROM. Keywords Cloud computing, Replication, Colored Petri net, Formal analysis Database as a Service (DaaS) is a self-service cloud computing model. primary goal is to develop a data scheduling model based on colored Petri net (CPN), As data types, the color sets are mapped to the places of the the place KEY while color set DATA, in the fourth row of Table 1, is mapped to the place Figure 8 shows the ReGenerate-Data module of the model. management of data centers for cloud computing. Petri Net based modeling and analysis for improved resource utilization in cloud computing Petri Net based modeling and analysis for improved resource utilization in cloud computing Petri Net based modeling and analysis for improved resource utilization in cloud computing work_ue4rck5t3fcszm254rhwc6ucoa richly annotated birdsong audio dataset, that is comprised of recordings containing bird vocalisations along with their active species tags plus the temporal annotations Keywords Audio dataset, Bird vocalisations, Ecosystems, Ecoacoustics, Rich annotations, annotations, labels that contain temporal information about the audio events. authors try to exploit audio tags in birdsong detection and bird species classification, ecological data with temporal annotations to train sound event detectors and classifiers is This means that many ecological datasets lack temporal annotations of bird vocalisations contains bird species tags and temporal annotations. Figshare (https://doi.org/10.6084/m9.figshare.6798548) (Morfi, Stowell & Pamuła, 2018). Dataset Name #recs #classes species tags annotations duration other info 10,000 different bird species (https://www.xeno-canto.org/). temporal annotations identifying the bird species and also classifying the vocalisation. http://dcase.community/challenge2018/task-bird-audio-detection Temporal annotations for each recording in the training set of the NIPS4B dataset were information about the recordings, their species specific tags and their temporal annotations. work_ufl2p734qbcd7nplzgj3g2poi4 Keywords Continuous integration, Mining software repositories, Replication, Pull-request based Studying the impact of CI on pull request delivery time in open source projects—a conceptual replication. time-to-delivery of merged Pull Requests (PRs) that are submitted to GitHub projects. factor impacting PR delivery time that is not directly captured in the original study is when as in the original study, and a control group of projects that have similar characteristics By applying non-parametric tests to the merge and delivery time of PRs, the authors CI, but 71.3% of the studied projects merge PRs faster before using CI. RQ1 of the original study investigated the impact of adopting CI on the delivery time original study built a multiple regression model based on 13 different variables (related In this work, we replicated an original study by Bernardo, da Costa & Kulesza (2018) that analysis of control group data has revealed that projects which never adopted CI do work_ufoenavatbfmfeqzhmlna4ywna of system structure in designing Verilog HDL source code artefacts for digital system designers and project managers, the paper proposes a DSM modelling method based on the characteristics of the digital system structural modelling with Verilog and the component dependencies relationship. Keywords: design structure matrix, modeling, Verilog HDL, digital design Verilog-HDL can be used to model and design a digital system in a form of software programming. How to manage the complexity of source code artefacts is an issue for digital designers. to use Dependency Structure Matrices (DSMs) for digital design using Verilog. The focus of the paper is how to model DSMs for Verilog HDL 3. DSM Modelling for Digital Designs Using Verilog for the module itself as a "macro" DSM element; for a block, a set of variables interacting with the DSM Modelling for Digital Design Using Verilog HDL DSM Modelling for Digital Design Using Verilog HDL work_uieqxqvitnd5rgfrhxmackzqre Networks of Canadian Business Elites: Historical Corporate of Directors in Canada, 1912, a public domain volume listing Canadian public companies in Canada. 1911 Census Division a company was located in has also been added so that the networks can be combined with other publicly available data from the period. file contains corporations as the nodes with directors as edges. second file has the individual directors as nodes and edges connecting them are corporate boards individuals both sat on. Corporate interlock network, Canadian business elites, business history. Finally, I have also linked the geographical location of companies to the 1911 Canadian Census data Latitude Location information Company, Person Longitude Location information Company, Person The graph file containing corporate executives and directors from the DoD has the firms as edges and the This file contains location data (longitude and latitude pairs) for both individuals and the firms work_ungu7a3275ferluuru6li22iky hierarchical message bus has defects such as strict component bus architecture requires too strict system components, and architecture new hierarchical message bus proposed in this Keywords-Hierarchical Message Bus; Middleware; Modem; traditional hierarchical message bus structure, this message bus for different types of components, and A. Traditional hierarchical message bus architecture A. Traditional hierarchical message bus architecture The Hierarchy Message Bus (HMB) architecture is Hierarchical message bus architecture diagram component through the message bus [5]. component through the message bus [5]. an atomic component and a local message bus. the component interface is a message-based passed between components through the message bus. passed between components through the message bus. the architecture based on the hierarchical message bus. B. New hierarchical message bus architecture of such components by adding an interface-message type of component and the message bus. non-standard components based on the message non-standard components based on the message work_upougi7rh5cjzkyqdpt77pgsya IPv4 is a widely deployed Internet protocol.  IPv6 uses smaller routing tables.  IPv6 has Better header formatting, it uses a new code to assign address for computer." IPV9 is a IPv4 defines the bit length of IP address is 32, that is, there are 232-1 addresses; While the length of IPv6 is there are 232-1 addresses; While the length of IPv6 is example, we assign the IPV9 address segment of segment of 86[21[5]/96 can realize the IPv9 address The address length of IPV9 is long enough to IPV9 address is backward compatible with digital domain system of IPV9 technology, which is of The IPV9 network expands the number of address IPV9/Future Network root domain name server The IPV9 root domain name server system is shown in The IPV9 network management system is a self-controllable IPV9/future network root domain 1) The application of 5G-future network/IPV9 IPv6 networks). work_urkrgneoazdutdue3pq3atzeaq describing actions in visual information extracted from videos. A natural next step is to integrate visual information from videos into a semantic model of event (2009) and contains pairs of naturallanguage action descriptions plus their associated video segments. • We report an experiment on similarity modeling of action descriptions based on the video They achieve better results when incorporating the visual information, providing an enriched model that pairs a single text with a picture. Their results outperform purely text-based models using visual information from pictures for the task of modeling noun similarities. MPII Composites comes with timed goldstandard annotation of low-level activities and participating objects (e.g. OPEN [HAND,DRAWER] or video corpus and its annotation (Sec. 3.1) we describe the collection of textual descriptions with The corpus contains 17,334 action descriptions (tokens), realizing 11,796 different sentences this paper (videos, low-level annotation, aligned textual descriptions, the ASim-Dataset and visual features) are publicly available. work_uu3zalov7vclddegvxyt2mvuka occurred on GitHub; (3) how curated resources are used by software developers; and curate resources on GitHub are similar to those that motivate them to participate in number of peers attract developers to engage in curation projects on GitHub. Benefits of curating on GitHub include learning opportunities, support for development work, and suggest that curation practices on GitHub mostly grow out of software developers'' internal better understanding of software developers'' motivation to curate resources and the nature communities, software developers'' motivation to engage in curation practices within Curation on GitHub appropriates the README.md file of a repository to create a list participation in curation practices on GitHub. The community of software developers on GitHub adopts a particular way to endorse Curated resources are useful for software developers to support their work, learn about a of the motivations that software developers appropriate GitHub for curation, and their work_uz5h6qoj2bhtlc5p3xsqkevrpq performance, we integrate the work-efficient strategy, and to address the loadimbalance problem, we introduce a warp-centric technique, which assigns many � We compare the traditional node-parallel method with the work-efficient version and In the edgeand node-parallel strategies, threads are assigned to all vertices or edges, To compute the BC on a weighted network, a parallel SSSP algorithm is applied in the both the node-parallel and work-efficient methods, resulting in four algorithms with work-efficient algorithm performs better than the node-parallel algorithm on all networks graphs, the warp-centric method results in even worse performance than the node-parallel node-parallel and work-efficient implementations combined with the warp-centric work-efficient method, algorithms with smaller WARP_SIZE values also perform better A GPU-based solution for fast calculation of the betweenness centrality in large weighted networks A GPU-based solution for fast calculation of the betweenness centrality in large weighted networks work_v2l3qcuonvdkxoeb5oplbydezm documents, induces constraints from this information and maps sentences to their dominant information structure categories through (2013a) recently applied the Generalized Expectation (GE) criterion (Mann and McCallum, 2007) to information structure analysis using This approach, however, requires human supervision in several forms including task specific constraint templates (see Section 2). for a GE model and a bias term for a graph clustering objective, such that the resulting models assign each of the input sentences to one information Information Structure Learning with Declarative Knowledge Recently, Reichart and Korhonen We therefore constructed two types of topic models: section-specific and article-level models, reasoning that some distinctions apply globally at the Table 6: ROUGE scores of zone (TopicGE, TopicGC, ExpertGE or gold standard) and Discussion section based summaries. Table 7: Topics and key features extracted by the article-level model (including modal, tense and voice marked in constraint-based modeling of the information structure analysis of scientific documents. work_v2ygecligzgubiokwwovbnqnqu Comparison Research on Future Network Between IPv4, Internet uses IPv4 protocol address scheme, the network address translation NAT technology to The length of IPv6 is 128 bits, or 2128 addresses. In the unicast address with more IPv6 applications, truly implement the 128-bit address space, the IPv16 for 64-bit effective address space; IPv26 for 128-bit designers of IPv6 decided that the 32-address space FUTURE NETWORK IPV9 IPV9 as the "future network" to distinguish the next and addressing" and "security" of the future network. IP address space for the future network architecture. IPv4 defines the bit length of IP address is 32, that is, there are 232-1 addresses; While the length of IPv6 is The address length of IPv9 is long enough to realize IPV9 addresses can be embedded with geo-location IPV9 address space and copyright ownership: IPv4 Host address(A) resource IPV9 technology and the whole network improvement of IPV9 Future Network, it will be work_v3azwvbzizhhznkwmikacudzji A Generative Model for Punctuation in Dependency Trees Also, our reconstruction of a sentence''s underlying punctuation lets us appropriately render the surface Across the 5 languages, our model predicts surface punctuation Treebank annotation guidelines for punctuation tend to adopt simple heuristics like "attach to the highest possible node that preserves projectivity" (Bies et al., more underlying punctuation tokens.3 The probability p✓(l, r | w) is given by a log-linear model punctuation model on a subset of the Universal Dependencies (UD) version 1.4 (Nivre et al., Recall that our model generates surface punctuation given an unpunctuated dependency tree. We evaluate the trained punctuation model by using it in the following three tasks. model supposes that the observed punctuated sentence x̄ would have arisen via the generative process (1). Surface punctuation marks are not directly attached to the syntax tree, but are generated from sequences of adjacent punctemes by a (stochastic) finite-state string work_v44vkh6bzramngvcrficy2no44 this model into a phrase-based decoder improves a strong Arabic-English baseline already including state-of-the-art early distortion cost (Moore and Quirk, 2007) and hierarchical phrase orientation models (Galley and Word order differences are among the most important factors determining the performance of statistical machine translation (SMT) on a given language includes a basic reordering model, called distortion cost, that exponentially penalizes longer jumps reordering models (Visweswariah et al., 2011) estimate, for each pair of input words i and j, the cost Long jumps are then suggested to the PSMT decoder by reducing the distortion cost for specific pairs of input words. Fig. 1 illustrates the scoring process: when a partial translation hypothesis H is expanded by covering a new source phrase f̃ , the model returns the Linguistically Motivated Reordering Modeling for Phrase-Based Statistical Machine Translation. A word reordering model for improved machine translation. reordering models for statistical machine translation. work_v5imgcaijzdjnkkiyoel5azmem millions of messages from eighty thousand counseling conversations conducted by hundreds of counselors over the course of one year. 1. Adaptability (Section 5): Measuring the distance between vector representations of the language used in conversations going well and going badly, we find that successful counselors In this work, we study anonymized counseling conversations from a not-for-profit organization providing free crisis intervention via SMS messages. Less successful counselors, positive conversations Less successful counselors, positive conversations Less successful counselors, negative conversations Less successful counselors, negative conversations between more and less successful counselors (blue circle/red square) than between positive and negative conversations (solid/dashed). However, we can study nearly identical beginnings of conversations where we can directly compare how more successful and less successful counselors react given nearly identical situations (the texter first sharing their reason for texting Figure 5: More successful counselors use less common/templated responses (after the texter first explains work_vaxtuleo6nfo7eq2dpcoadhgxa forward transform F r; cð Þ and sampled values of the continuous original function f ðr; uÞ specific sampled values of the continuous functions in both space and frequency domains, error between the sampled values of the continuous transform and the discretely calculated Figure 8 Error between the sampled values of the continuous transform and the discretely calculated Figure 8 Error between the sampled values of the continuous transform and the discretely calculated Figure 10 Error trend between the sampled values of the continuous transform and the discretely Figure 10 Error trend between the sampled values of the continuous transform and the discretely Figure 24 Error between the sampled values of the continuous forward transform and the discretely Discrete two dimensional Fourier transform in polar coordinates part II: numerical computation and approximation of the continuous transform ... Discrete two dimensional Fourier transform in polar coordinates part II: numerical computation and approximation of the continuous transform ... work_vbzp3iewy5h7rhfiok5o6i3du4 Experimental results show that the string-totree translation system using our Bayesian tree In recent years, tree-based translation models1 are tree-based translation models have shown optimal choice for training tree-based translation we propose an unsupervised tree structure for treebased translation models in this study. structures, tree nodes are labeled by combining the Bayesian model to infer the final tree structure tree structure in terms of the node labels derived from reasonable for tree-based translation than the parse Bayesian model to induce a U-tree for treebased translation. tree-based translation model with effective for tree-based translation models than SCFG. model to learn effective STSG translation rules and U-tree structures for tree-based translation models, string-to-tree translation model, which is based on for tree-based translation models. for tree-based translation models. for tree-based translation models. for tree-based translation models. for tree-based translation models. translation grammar for tree-based models. Tree-based translation without using Tree-based translation without using work_vcct7l7el5bixfvlltqxknqsyq achieve a rate of heat emitted by a fusion plasma that Soviet tokamak, fusion research became ''big science'' in fusion power plant, this energy will be used to generate energy density of fusion reactions in gas is very much alpha heating of magnetic confinement fusion. tokamak fusion test reactor (TFTR) at Princeton in the Device at Japan''s National Institute of Fusion Research, research into inertial fusion energy (IFE). The result was the ITER Fusion Energy Advanced Reactor) at the National Fusion Research Institute In the USA, the Tokamak Fusion Test Reactor field and highest plasma pressure of any fusion reactor, The world''s most powerful laser fusion facility, the fusion power and nuclear weapons research. The High Power Laser Energy Research Facility https://www.world-nuclear.org/information-library/current-and-future-generation/nuclear-fusion-power.aspx#Notes https://www.world-nuclear.org/information-library/current-and-future-generation/nuclear-fusion-power.aspx#Notes https://www.world-nuclear.org/information-library/current-and-future-generation/nuclear-fusion-power.aspx#Notes https://www.world-nuclear.org/information-library/current-and-future-generation/nuclear-fusion-power.aspx#Notes https://www.world-nuclear.org/information-library/current-and-future-generation/nuclear-fusion-power.aspx#Notes https://www.world-nuclear.org/information-library/current-and-future-generation/nuclear-fusion-power.aspx#Notes https://www.world-nuclear.org/information-library/current-and-future-generation/nuclear-fusion-power.aspx#Notes magnetic confinement field in a coil to trap the fusion second more powerful laser triggers the nuclear fusion nuclear fission or fusion) to create low-energy neutrons, work_vd6oruexsvf4fikunggshpi4vm user profiles and Linked Open Data (LOD) sources for representing competence topics. Researchers can then obtain personalized services through applications leveraging the semantic user profiles. constructing semantic user profiles in a linked open data format for automatic knowledge generic user and competence modeling with semantic web vocabularies. Figure 2 The RDF graph shown in this picture represents a semantic user profile that illustrates the relations between an author and the topics the workflow is a knowledge base populated with semantic user profiles, inter-linked with resources on the linked open data cloud. Table 3 Evaluation results for the generated user profiles in the first user study: this table shows the number of distinct competence topics extracted from the ten participants and the average precisions at 10, 25 and 50 cut-off ranks. to re-rank the results, based on the common topics in both the papers and a user''s profile: http://www.semanticsoftware.info/semantic-user-profiling-peerj-2016-supplements http://www.semanticsoftware.info/semantic-user-profiling-peerj-2016-supplements http://www.semanticsoftware.info/semantic-user-profiling-peerj-2016-supplements http://www.semanticsoftware.info/semantic-user-profiling-peerj-2016-supplements work_veftzkgr2rcptpywfzizjh2lli agent tutors which are frequently implemented within virtual learning environments. and material on a large scale via internet-based virtual learning environments for a Immersive virtual environments and embodied agents for e-learning impact the overall student experience when learning in IVEs. Specifically we report how impact learning retention, satisfaction and engagement, and student motivation to who learn without one because the presence of a virtual tutor influences motivation tutor, Non-virtual learning environment). Table 2 t-test results for the impact of tutor on motivation to learn. Mean scores for learner satisfaction and engagement in each virtual learning condition of learning condition within immersive virtual environments (no tutor, humanoid tutor, abstract Embodied Agent tutors impact learner satisfaction and engagement within IVEs by virtual learning environments for students. Informing the design of a virtual environment to support learning in Immersive virtual environments and embodied agents for e-learning applications Immersive virtual environments and embodied agents for e-learning applications work_vekcikqpvnfl5fcyouudnppwsm A Searchable Re-encryption Storage Method in Cloud Environment of the SReCSM is to generate a re-encryption key and Keywords-Cloud Storage; Re-encryption; Decrypt; storage is designed to store data in cloud and is widely used The reliability of the mobile cloud storage depends on SReCSM, Searchable Re-encryption Storage Method is proposed in [8] is Cloud-based Re-encryption Scheme First, for reencryotion, the data owner must obtain user''s public key generate a re-encryption key and decrypte while the method, SReCSM may increase the storage requirements generate a re-encryption key only when the keyword to the cloud server and the private key is shared to the data private key are contained in encrypted data. Algorithm 5: Re-encrypting Data Algorithm 5 introdeces the scheme of data re-encryption, Algorithm 5 introdeces the scheme of data re-encryption, The proposed scheme SReCSM Searchable Reencryption Storage Method was developed and verified relatively long time to encrypt files by using the CReS, work_vf3gpwvnzzet5j25nijp2jula4 are able to harvest fully disambiguated relation instances on a large scale, and integrate them automatically into a high-quality taxonomy of semantic relations. extract from our input corpus an initial set of semantic relations (Section 2); each relation is then scored (Navigli and Ponzetto, 2012), a wide-coverage multilingual semantic network obtained from the automatic integration of WordNet, Wikipedia and other both sets have a single hypernym covering all arguments, then R arguably captures a well-defined semantic relation and should be assigned high confidence. BabelNet provides a large heterogeneous set comprising definitions from WordNet, Wikipedia, Wiktionary, Wikidata and OmegaWiki. After the extraction process, our knowledge base comprises 255,881 distinct semantic relations, 94% of which also have disambiguated proportion of relations not appearing in existing resources (especially across the random samples) suggests that DEFIE is capable of discovering information not obtainable from available knowledge bases, unified word sense disambiguation and entity linking approach, extracts semantically richer patterns work_vft4ua43ojg5dj5wcu6e4d43ka dataset, also yielding state of the art validation and testing classification accuracies: How to cite this article Palatnik de Sousa (2018), Convolutional ensembles for Arabic Handwritten Character and Digit Recognition. on a dataset of 6,600 images of characters, obtaining a validation accuracy of 97.32%. namely, the selection and preparation of the datasets, the network architecture, the training The datasets chosen for training and parameter tuning were the MADbase and AHCD networks, each trained with two different strategies (with data augmentation and without). It was also observed that the final averaged test accuracy of 6-fold validation for MADbase validation and test accuracies for MADbase. The average test and validation accuracy values of ENS4 are very promising and improve The system was trained and tested on the two largest available datasets of Arabic digits and and one that ensures the test and validation sets have the same size for the MADbase dataset. work_vi7mhk6gg5gijkx2dieiskx6xu Research on House Price Prediction Based on MultiDimensional Data Fusion This paper proposes a house price prediction model finally, a fully connected neural network model is established After the neural network model has been established, the price Neural Network Model; House Price Prediction attributes that affect house prices are entered into the attributes that affect house prices are entered into the data fusion model, and the price of the commercial data fusion model, and the price of the commercial variables, such as housing prices in this paper, are a Data fusion[5] is a technology that fuses attribute neural network model to process the pixel matrix. 6 attributes that affect house prices: transaction date ; dependent variable: house price . model shown in (Figure 5 Network structure) is trained house price .After the neural network model has been house into this neural network model, and you can get work_vqm2sxewfjcnxp754zqhb4frdm https://www.research.ed.ac.uk/portal/en/publications/combined-distributional-and-logical-semantics(2aae1bb8-66ff-474c-be0d-3b829573bbbc).html We follow formal semantics in mapping language to logical representations, but differ in that the relational This approach is useful for a range of key applications including question answering and relation extraction Whilst distributional semantics has been effective in modelling the meanings of content words Our approach differs from standard formal semantics in that the non-logical symbols used in the logical form are cluster identifiers. verb syntactically as a function mapping two nounphrases to a sentence, and semantically as a binary relation between its two argument entities. compare semantic relations across different syntactic types—for example, both transitive verbs and argument-taking nouns can be seen as expressing binary semantic relations between entities. the cluster model learned in Section 6, using all possible corresponding typed predicates. • CCG-Distributional The logical form including the type model and clusters. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies Volume 1, HLT ''11, pages 610– work_vwxawihnvjb6xjwllmb2tut3m4 Research on Digital Holographic 3D Reconstruction Software the basic principle and the process of reconstruction, and the parallel operation of 3D reconstruction is realized by OpenMP. needs of digital three-dimensional reconstruction. Reconstruction; Parallel Computing; Software Design process the digital hologram to obtain the object information. reconstruction of digital holography. Digital holographic reconstruction software According to the need to reconstruct the hologram, Digital holographic 3d reconstruction process Digital holographic 3d reconstruction process reconstruction algorithm of the three dimensional digital Because the reconstruction process of digital holography Because the reconstruction process of digital holography reconstruction software of digital holography is developed software, a part of the hologram is reconstructed. reconstruction of off-axis digital holography based on reconstruction process of off-axis digital holography is given, and the 3D reconstruction software of digital holography is and the 3D reconstruction software of digital holography is reconstruction, and facilitates the process of digital work_vxcfrpl4rfdr7nmmpo4brledfm work implements User Specified energy model and DYMO (DYnamic Manet Ondemand) routing protocol. (PSM) is stationed on deducing the power utilization of the mobile device to point that lacks enable the user to assign the energy utilization of the nodes in various power modes Parameters to enable user-specified energy model in mobile node, relay node and an access point. Table 4 Power Saving Mode at mobile node. Parameters to enable Power Save Mode in the mobile node utilizing 802.11 Power Saving Mode, Energy model, Battery model and DYnamic Manet Algorithm for Power Saving Mode of a mobile station Case 2: Energy consumption of nodes using Power Saving Mode Case 2: Energy consumption of nodes using Power Saving Mode models and DYMO routing protocol for 802.11 standards including Power Save Mode on information about a station in Power Saving Mode. model, energy model, DYMO routing protocol and Power Saving Mode by using Qualnet work_w36sbsa2pjaoxdslwl2ehwtmba For each problem we provided data, a naı̈ve solution, and an evaluation program. Three of the four challenges also included unlabeled test data (except the decoding assignment, as We provided a web-based leaderboard that displayed standings on the test data in real time, identifying each submission by a pseudonymous handle known only to the team and instructors. The third challenge was evaluation: given a test corpus with reference translations and the output of several MT systems, students were challenged to produce a ranking of the systems that closely correlated We chose the English-to-German translation systems from the 2009 and 2011 shared task at the annual Workshop for Machine Translation (CallisonBurch et al., 2009; Callison-Burch et al., 2011), providing the first as development data and the second We conceived of the assignment as one in which students could apply machine learning or feature engineering to the task of reranking the systems, so we work_w42xlvpc3nagplvbetz6f74zyy model to encode or approximate structural information; nevertheless, it succeeded in recovering the majority of agreement cases even when four nouns of the language model trained without explicit grammatical supervision performed worse than chance on the We note that subject-verb number agreement is only one of a number of structuresensitive dependencies; other examples include negative polarity items (e.g., any) and reflexive pronouns model''s error rate was affected by nouns that intervened between the subject and the verb in the linear Figure 2: (a-d) Error rates of the LSTM number prediction model as a function of: (a) distance between the subject and the verb, in dependencies that have no intervening nouns; (b) presence and number of last summary, we conclude that while the LSTM is capable of learning syntax-sensitive agreement dependencies under various objectives, the language-modeling models predict a singular verb even though the number of the subject conservation refugees should be work_w6wqmfkatfctfhp4mwewy46yta Research on AORBCO Model and It''s Description Language components-belief, desire, ability, planning and behavior Keywords-AORBCO; Intelligent Mode; Agent; Selfconsciousness; Description Language intelligent model with agent as the core, simulates human''s ability, planning, and behavior control mechanisms, Defined by the agent; Oa represents the set of objects known by the plan of agent to realize the current wish; behavior_controller represents the agent''s behavior control mechanism; Definition 2: Acquaintance subject, acq-agent represents a acquaintance subject''s(acq-agent.i) acquaintance set; Oaa represents a set of objects known by acq-agent. Raa represents a set of relations perceived by acq-agent.i; subject at time t,R(ei, ej, t)∈Ra;ei, ej denotes agent or object, agent, Belief, Act, Desire, Plan, behavior_controller, Belief is description of the entity agent knows and its Belief is description of the entity agent knows and its represents the set of objects that the agent form a new AORBCO intelligent model with agent as the work_w73hiptz3bcxri5xhr47jx335e resources, development teams can apply defect prediction to identify fault-prone Method: We compute code metrics and apply association rule mining to create rules trained a classifier for methods with LFR using association rule mining. the metrics for each method, the data pre-processing, and the association rule mining Defect prediction models use code metrics (Menzies, comprises the computation of source-code metrics for each method, the data preprocessing before the mining, and the association rule mining. Like defect prediction models, IDP uses metrics to train a classifier for identifying LFR traditional defect prediction approaches are binary classifications, which classify a method precision than to predict all methods that do not contain any faults in the dataset. Table 5 RQ 1, RQ 2: Evaluation of within-project IDP to identify low-fault-risk (LFR) methods. An inverse view on defect prediction to identify methods with low fault risk An inverse view on defect prediction to identify methods with low fault risk work_w7xmeafrznavjlelreuofhde2i In this paper, we introduce a spanlevel pretraining approach that consistently outperforms BERT, with the largest gains on span Span-based masking forces the model to predict the output representations of the boundary tokens, x4 and x9 (in blue), to predict each token in the masked span. Together, our pre-training process yields models that outperform all BERT baselines on a tasks that do not explicitly involve span selection, and show that our approach even improves performance on TACRED (Zhang et al., In summary, SpanBERT pre-trains span representations by: (1) masking spans of full words including seven question answering tasks, coreference resolution, nine tasks in the GLUE benchmark (Wang et al., 2019), and relation extraction. answering and coreference resolution, will particularly benefit from our span-based pre-training. training with NSP with BERT''s choice of sequence lengths for a wide variety of tasks. for models pre-trained with span masking, and also work_waeoeckza5hvjfqri65tyffi54 We train the model using a large corpus of texts and their entity annotations extracted from Wikipedia. model on three important NLP tasks (i.e., sentence textual similarity, entity linking, and factoid question answering) involving both unsupervised and supervised settings. Methods capable of learning distributed representations of arbitrary-length texts (i.e., fixed-length continuous vectors that encode the semantics of texts), vector space enables us to easily compute the similarity between texts and entities, which can be beneficial for various KB-related tasks. Additionally, there have also been proposed methods that map words and entities into the same continuous vector space (Wang et al., 2014; Yamada model to three different NLP tasks, namely semantic textual similarity, entity linking, and In this section, we propose our approach of learning distributed representations of texts and entities In addition, because the length of a text t is arbitrary in our model, we test the following two settings: t as a paragraph, and t as a sentence3. work_we274m2onzbppkq6clxq7hg2pi [PDF] Probabilistic biomechanical finite element simulations: whole-model classical hypothesis testing based on upcrossing geometry | Semantic Scholar Corpus ID: 32214297Probabilistic biomechanical finite element simulations: whole-model classical hypothesis testing based on upcrossing geometry title={Probabilistic biomechanical finite element simulations: whole-model classical hypothesis testing based on upcrossing geometry}, journal={PeerJ Comput. Sci. Statistical analyses of biomechanical finite element (FE) simulations are frequently conducted on scalar metrics extracted from anatomically homologous regions, like maximum von Mises stresses from demarcated bone areas. Figures, Tables, and Topics from this paper View All 15 Figures & Tables Finite element method Sort by Most Influenced Papers Statistical methods in finite element analysis. View 3 excerpts, references background and methods View 1 excerpt, references methods View 1 excerpt, references methods View 1 excerpt, references methods By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License work_weg2bzj74zc7ho3i3aprp32l5e Past variational inference techniques for adaptor grammars assume a preprocessing step that We show our approach''s scalability and effectiveness by applying our inference framework in Section 5 on two tasks: unsupervised word segmentation and infinite-vocabulary topic modeling. Probabilistic context-free grammars (PCFG) define probability distributions over derivations of a Variational inference, however, is inherently parallel and easily amendable to online inference, but requires preprocessing to discover the adapted productions. The adaptor grammar inference methods use an approximate PCFG to equivalent to creating a "new table" in MCMC inference and provides truncation-free variational updates (Wang and Blei, 2012) by sampling a unseen Our approach is based on the stochastic variational inference for topic models (Hoffman et al., Algorithm 2 Online inference for adaptor grammars inference and topic models violate a fundamental assumption in online algorithms: new words are introduced as more data are streamed to the algorithm. work_wgi74n6oavhdxhlomowlxqjdhu Token and Type Constraints for Cross-Lingual Part-of-Speech Tagging where coupled token and type constraints provide a partial signal for training. Supervised part-of-speech (POS) taggers are available for more than twenty languages and achieve accuracies of around 95% on in-domain data (Petrov et POS taggers with type-level tag dictionary constraints Tag dictionaries, noisily projected via word-aligned bitext, have bridged the gap (CRF) model (Lafferty et al., 2001) that couples token and type constraints in order to guide learning type constraints and how we use these coupled constraints to train probabilistic tagging models. (2012).6 Since we use indirect supervision via projected tags or Wiktionary, the model Table 2: Tagging accuracies for models with token constraints and coupled token and type constraints. models that use only projected token constraints the token-level tag projections, so that the dictionary First, word types that occur with more token constraints during training are generally tagged more work_wiqq6vr24vbcjdnf4n4fbfulby method of classification for 3D organ images that is rotation and translation invariant. use a 20-layer deep convolutional neural network (DCNN) to perform the classification A 3D image classification method was proposed by Liu & Dellaert (1998) for the Liu & Kang (2017) introduced a lung nodule classification approach by using a multiview DCNN for CT images. segmented the lungs from the CT image using a pre-processing step and performed a In this paper, we consider the specific case of 3D organ image classification and propose invariant 3D organ image classification: volume reconstruction, segmentation, symmetry We also implemented the method used in the classification of 3D lung images introduced Table 2 Performance comparison with similar existing methods (with data augmentation by random transformation and axis swapping on Figure 8 Performance (confidence level of classification) of the proposed method with respect to some image feature extraction methods: bag of words (BoW) (Harris, 1954) and histogram of work_wlsykhomgjaxpjeqdsgd7bqasi based ELM (DCS-ELM) algorithm has been tested in steel fiber reinforced selfcompacting concrete data sets and public four different datasets, and a result of systems-based extreme learning machine (DCS-ELM) algorithm has been proposed using performances of DCS-ELM and other algorithms proposed on public data sets were The iterative map based DCS-ELM algorithm obtained values of The iterative map based DCS-ELM algorithm obtained values of The iterative map based DCS-ELM algorithm obtained values of The iterative map based DCS-ELM algorithm obtained values of The piecewise map based DCS-ELM algorithm obtained values of The piecewise map based DCS-ELM algorithm obtained values of The piecewise map based DCS-ELM algorithm obtained values of The piecewise map based DCS-ELM algorithm obtained values of DCS-ELM: a novel method for extreme learning machine for regression problems and a new approach for the SFRSCC DCS-ELM: a novel method for extreme learning machine for regression problems and a new approach for the SFRSCC work_wlzntvhrtjanfdcmp72fytknpe In this paper, a complex real-time exact acceleration method based on an Exact acceleration of complex real-time model checking • An exact acceleration method based on a parking cycle was proposed (Yin, Zhuang & method for complex real-time model checking based on an overlapping cycle, which is an The exact acceleration method for complex real-time models based on an overlapping cycle is proposed in ''Exact Acceleration of Complex Real-time System Model the timed automaton M with a parking cycle whose edge guard y controls the acceleration The appended cycle and parking cycle technologies in exact acceleration apply to a real-time method for the complex real-time model based on an overlapping cycle is an improved acceleration technology to complex real-time model checking to improve efficiency and real-time model checking differs from the exact acceleration of a single acceleratable cycle. Exact acceleration of real-time model checking. Exact acceleration of real-time model checking based work_wmp5caxjbrdcvfjdjjpiasghwa obtained by the algorithm, the workload indicators (scheduled distance, number Keywords Multi-objective optimization, Public bicycle system, Community discovery algorithm, The division of the public bicycle dispatching area involves operational research, scheduling area division scheme based on the improved K-means clustering algorithm. This part establishes the division model of public bicycle scheduling area, including of regional scheduling workloads, community discovery algorithms and multi-objective After the Fast Unfolding algorithm for the New York public bicycle rental site in this on multi-objective optimization solves the division model of the public bicycle scheduling Figure 8 Results of region partition based on multi-objective optimization algorithm in the New York Figure 11 Distance difference of bicycle scheduling area under three algorithms in the New York Figure 15 Results of region partition based on multi-objective optimization algorithm in the Chicago Figure 18 Distance difference of bicycle scheduling area under three algorithms in the Chicago work_wqab4ttubbdubhqub6dpdmptmq (CorEx), an alternative approach to topic modeling that does not assume an underlying generative model, and instead learns maximally domain knowledge can be flexibly incorporated within CorEx through anchor words, allowing topic separability and representation to 1Open source, documented code for the CorEx topic model may flexibly incorporate word-level domain knowledge within the CorEx topic model. can be naturally integrated into CorEx through "anchor words" and the information bottleneck. treat anchor words as fuzzy logic markers and embed them into the topic model in a semi-supervised anchor one word to multiple topics, allowing CorEx We compare CorEx to LDA in terms of topic coherence, document classification, and document clustering across three datasets. Figure 3: Comparison of anchored CorEx to other semisupervised topic models in terms of document clustering CorEx topic model with that label''s anchor words of the CorEx topic model to LDA, it does have some work_ws6l4gb3gvcpzpqceub7wmhoma Software TLB Management Method Based on Balanced TLB failure by software or hardware, it find the page method based on balanced binary search tree. TLB will help computer to process large virtual address. search tree based on virtual page number. TLB capacity of balanced binary search tree is large, quickly search the virtual page number and locate it to addressing is parallel TLB search and cache access. is also possible to perform TLB search and CPU cache no corresponding page number in the TLB. memory, call the corresponding page table entry search of the TLB according to the page table TLB has virtual page number, significant bit, root node index bit of left and right sub tree, balance When the TLB is full, some page table items need TLB is specifically used to cache page table entries the virtual address is found in the page table, it work_wsiwqbod3nbyvm3dffvduzocri a distinction between a project-specific cut-over and a release-specific rollout. scattered, project-specific deliverables useful for cut-over planning, this publication Keywords Release, Project-specific cut-over, Release-specific rollout, Go-live preparation, Go-live, Deployment, Application-specific cut-over, ITIL, IT Service Management, The project-specific cut-over, as defined in more detail below, requires detailed planning, SAP) recommend scattered project-specific deliverables useful for Cut-over Planning, Beside the project-specific cut-over and the release-specific rollout we are most likely to cut-over and a release-specific rollout is the go-live scenario. The Go-live Strategy of project A utilizes the Rollout Window of release 1 and 2, whereas In the same way as the project''s Go-live Strategy, the release-specific rollout uses a Go-live During the project-planning phase an initial dialogue with Rollout Management is A collective participation by projects in a release-specific rollout causes a need to manage incidents two weeks after rollout and the number of participating projects per release. work_wt6msc2u5rfk7duy5hzvqoldtu Research and Development of Millimeter Wave The military application of millimeter wave communication attenuation rate of millimeter waves propagating in bps / Hz in the 28 GHz millimeter-wave band, and its realization of millimeter wave communication Usually the millimeter wave band refers to 30 GHz Millimeter wave communication refers to communication in which millimeter waves are used millimeter wave communication is a typical Current millimeter wave communication systems millimeter wave communication is obtained. A. Millimeter wave ground communication millimeter wave band and the high end of the short-range millimeter-wave communication devices in B. Millimeter wave satellite communication the development of millimeter-wave systems. GHz millimeter band, and the communication In short, millimeter-wave communication is very Millimeter wave communication technology is a secret communication in the millimeter wave band, and Development and Application of Millimeter Wave Development and Application of Millimeter Wave algorithm in 60GHz millimeter wave communication. Development of China''s millimeter wave technology. work_wysobjngavdtdivi2qo2jkd6fi From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions construct a denotation graph, i.e. a subsumption hierarchy over constituents and their denotations, based on a large corpus of 30K images and 150K descriptive captions. everyday activities (each paired with multiple captions; Section 3) to construct a large scale visual denotation graph which associates image descriptions that constructs the denotation graph uses purely syntactic and lexical rules to produce simpler captions variety of descriptions associated with the same image is what allows us to induce denotational similarities between expressions that are not trivially related similarities (cos, Lin, Bal, Clk, Σ, Π) on our image captions ("cap"), the BNC and Gigaword. To allow a direct comparison between distributional and denotational similarities, we first define P(w) (and P(w,w′)) over individual captions the vectors obtained from the image-caption training data) and denotational similarity features to this work_x5mcpywaavaodktsewwistrpgy In the text, A method of image watermarking based on DCT (Discrete Cosine Transform) experimental results, the quality of the watermarked image is almost no decline relative to the original. This paper focuses on a theme on DCT-based image digital watermark design and implementation. Improve a digital image watermarking algorithm which is based on DCT transform and Arnold The experimental results show that it is hiding the information of gray image, and make an and the gray level digital watermark value directly embedded into the DCT transform domain vector image from I, and the extraction process is the inverse of the embedded watermarking algorithm. Figure.6 Experimental results for gray image compression factor of 70 A DCT Domain Image Watermarking Method Based on Matlab A DCT Domain Image Watermarking Method Based on Matlab A DCT Domain Image Watermarking Method Based on Matlab A DCT Domain Image Watermarking Method Based on Matlab work_x6dykc6hezhvlnovvg2d6vmdxe social balancing can be triggered by network topology and by the ratio of opinion event simulation on diverse social network topologies, we validate our opinion Keywords Social networks, Opinion diffusion, Phase transition, Discrete event simulation, (2016), Tolerance-based interaction: a new model targeting opinion formation and diffusion in such as network size, topology, and opinion source ratio (i.e., stubborn agents In real-world social networks there are agents which do not hold any opinion, and they Figure 11 Simulation results for the tolerance-based opinion interaction on a small-world network with 10,000 nodes, of which are 32 green dynamics of opinion formation is influenced by topology, network size and stubborn agent Modeling opinion dynamics in social networks. Tolerance-based interaction: a new model targeting opinion formation and diffusion in social networks Tolerance-based interaction: a new model targeting opinion formation and diffusion in social networks work_xaqa5nndx5b53m2indgg7t4zxm system that include mention extraction, candidate generation, entity type prediction, entity Chang, 2012) performs surprisingly well, and 2) incorporating a fine-grained set of entity types raises • We compare VINCULUM to 2 state-of-the-art systems on an extensive evaluation of 9 data sets. including mention extraction, candidate generation, entity type prediction, entity coreference, and Group Data Set # of Mentions Entity Types KB # of NILs Eval. Entity types: The AIDA data sets include named entities in four NER classes, In TAC KBP data sets, both Person (PERT ) and Organization entities Table 2: A sample of papers on entity linking with the data sets used in each paper (ordered chronologically). In the TAC KBP, in addition to determining if a mention has no entity in the KB to link, For each identified mention m, candidate entities Cm = {cj} are generated for linking. work_xihaospkm5g7xoaeabghvmripi Comparison of the performance of skip lists and splay trees in classification of internet packets. The main aim of the paper is to compare the performance of the skip list and splay tree data With both skip lists and splay trees, packet classification is as following. fields in the packet, a skip list or a splay tree is created and searched simultaneously to find Figure 3B evaluates both the skip list and splay tree for 32k packets. The difference in packet classification time between skip list and splay rules in which the splay tree accesses memory 1496966 times more than the skip list. different numbers of rules, the skip list has less memory access than does the splay tree. reduction in the number of memory accesses and packet classification time in skip lists. of rules, packet classification time and memory access increase less in a skip list than in a work_xkh7hjnskrfjrgg22exaud7tam approach for hiding secret text message in color images is presented, combining Steganography in color images with random order of pixel selection and encrypted Method The method is based on spread spectrum image steganography with RSA message encryption. using random order of pixel selection and embedding encrypted text message. � choosing random pixels (in chaotic order) from an image, using the constructed pseudorandom generator for embedding information The key-space includes the variety of possible values of the used variables in random bit The color images are tested by embedding secret messages where px,y and sx,y are the corresponding pixel values from the plain and stego images, steganography when a secret message is hidden in the tested color images. Steganography in color images with random order of pixel selection and encrypted text message embedding Steganography in color images with random order of pixel selection and encrypted text message embedding Steganography in color images with random pixel selection work_xp5ehtk7w5gx5cv7hwqaqf7rvm We finally investigate the problem of quantitative reasoning over multiple quantities mentioned across 8.1 An example arithmetic word problem and its solution, along with the type of domain knowledge required to generate each operation of the solution . Even in such a simple quantitative reasoning problem, there are several challenges involving multiple interactions among the numbers in the text. Reasoning over multiple quantities often require correct hierarchical composition of numbers with mathematical operations, as in the case of the following math word problem: strategies allow reducing a math word problem with any number of quantities, into simple quantitative particular, our approach achieves state of the art performance on two publicly available arithmetic problem datasets and can support natural generalizations for quantitative reasoning over multiple quantities We introduce the concept of unit dependency graph (UDG) for math word problems, to represent the relationships among the units of different numbers, and the question being asked. work_xpucujovsfdthnzk2l2u4345oa Keywords Pyomo, Python, Algebraic Modeling Languages, Mathematical programming, How to cite this article Triantafyllidis and Papageorgiou (2018), An integrated platform for intuitive mathematical programming modeling using LaTeX. Figure 1 The levels of abstraction in modeling; from natural language to extracting the optimal solution via computational resources. proposed platform exports the generated optimization model in Pyomo whereas the ability as an input language to perform mathematical programming modeling, and currently • Data files: The input of the data set which follows the abstract definition of the model Pyomo, the modeling component of the Python programming language. effectively translate the user model input from LaTeX, we need an array of programming optimization models in the platform with a given example and the successful parsing to mathematical expression at each line of the .tex input model file into the corresponding We presented a platform for rapid model generation using LaTeX as the input language for work_xst34jwrn5fhhlikkhua7vjw6e Keywords Physical-layer security, Secrecy outage probability, Transmit-receive diversity, On the secrecy performance of transmit-receive diversity and spatial multiplexing systems. More recently, in Maichalernnukul (2018), the average secrecy capacity of transmitreceive diversity systems in the fading MIMO wiretap channel and its upper bound were probability of a transmit-receive diversity system in the fading MIMO wiretap channel. Figure 1 Secrecy outage probability of transmit-receive diversity system (Pout,TR) as a function of γ̄r. This figure shows the theoretical and simulated secrecy outage curves for the transmit-receive diversity theoretical secrecy outage probability of the transmit-receive diversity system (computed Figure 3 Comparison of exact and asymptotic secrecy outage probability of transmit-receive diversity Figure 4 Secrecy outage probability of spatial multiplexing systems with ZF equalization (Pout,ZF) and theoretical secrecy outage curves for the ZF equalization-based and MMSE equalization-based spatial multiplexing systems with different numbers of antennas and average SNRs at the eavesdropper (Me and γ̄e), work_xvbrtnwmqbe55drlyo3jmsshuq detection capability to GLS-coding by ensuring that the compressed file (initial value aim is to incorporate error detection into GLS-coding by using Cantor set while not this, we incorporate error detection into GLS-coding using a Cantor set in ''Incorporating Error Detection into GLS-Coding Using a Cantor Set'' and show simulation results of the 2.1 Effect of single-bit error on GLS-decoding: Sensitive dependence on initial value of93 In GLS-coding, the compressed file is the initial value of the symbolic sequence (the In GLS-coding, the compressed file is the initial value of the symbolic sequence (the message M) on99 value (compressed file) will result in a wrongly decoded message (symbolic sequence), which will be very104 In GLS-coding, every real number on the interval [0,1) represents an initial value (compressed file). whether the initial value received belongs to the Cantor set or not is used for error detection at the decoder.193 work_xwij57ezufevpgkcs2vwd6r76u Linear Algebraic Structure of Word Senses, with Applications to Polysemy Classical vector space models (see the survey by Turney and Pantel (2010)) use simple linear algebra of embeddings, with the internal information extracted only via inner product, is felt to fail in capturing word senses (Griffiths et al., 2007; Reisinger paper strongly suggest that word embeddings computed using modern techniques such as GloVe and To do so we rely on the generative model of Section 2.1 according to which unit vector in the embedding space corresponds to a micro-topic or discourse. Table 2: Fitting the GloVe word vectors with average discourse vectors using a linear transformation. We tested three standard word embedding methods: GloVe, the skipgram variant of word2vec, and SN (Arora et al., linear algebraic structure of word senses within existing embeddings, it is desirable to verify that this work_y2ft2jwmyrby7fpj24hznq275e A Polynomial-Time Dynamic Programming Algorithm for Phrase-Based Decoding of phrase-based translation models in the general case is known to be NPcomplete, by a reduction from the traveling for phrase-based decoding with a fixed distortion limit. novel representation that gives a new perspective on decoding of phrase-based models. the general case decoding of phrase-based translation models is NP-complete. 1An earlier version of this paper states the complexity of decoding with a distortion limit as O(I32d) where d is the distortion limit and I is the number of words in the sentence; however (2010) make use of bit string coverage vectors, giving an exponential number of possible states; in contrast to our approach, the translations are not formed This section first defines the bandwidth-limited traveling salesman problem, then describes a polynomial time dynamic programming algorithm for the We now describe the dynamic programming algorithm for phrase-based decoding with a fixed distortion limit. work_y2wdmmp76vgxzolncbcl4sfin4 all power levels, as compared to activation or load-proportional blinking policies. Keywords Green data center, Intermittent power, Blink, Green cache, Memcached, policy, which keeps nodes active in proportion to the popularity of the data they store, policy only varies the number of active servers at each power level (Chase et al., 2001; Our Blink prototype uses a cluster of low-power server nodes. a proportional policy ranks servers and uses a proxy to monitor object popularity and of a number of low-power servers, since a single large cache is not energy-proportional, GreenCache uses a low-power always-on proxy and staggered load-proportional blinking cache server to set the start time and active period every blink interval. Both cache server and power client run together on each blinking node. Figure 18 As S3 transition overhead increases, the hit rate from the load-proportional policy decreases relative to the activation policy with key migration for a Zipf distribution at a moderate power work_y35s5ut7lrfohfo57zc6wejzyu this approach is that it works with both relational similarity (analogy) and compositional similarity between word pairs (SAT analogies and SemEval 2012 Task 2) and measuring compositional similarity between nounmodifier phrases and unigrams (multiplechoice paraphrase questions). two words is calculated by comparing the two corresponding context vectors (Lund et al., 1995; Landauer and Dumais, 1997; Turney and Pantel, 2010). On a set of eighty multiple-choice synonym questions from the test of English as a foreign language (TOEFL), a distributional approach phrase or sentence is computed from the representations of the individual words (Mitchell and Lapata, 2010; Baroni and Zamparelli, 2010). The dual-space model has been applied to measuring compositional similarity (paraphrase recognition) and relational similarity (analogy recognition). To measure the relational similarity between two word pairs, we train SuperSim The general feature space for learning relations and compositions is presented in Section 3. This section presents experiments with learning relational similarity using SuperSim. The training work_y4fwwb63b5a77gm3wpynicxd4q Probabilistic Verb Selection for Data-to-Text Generation In this paper, we address the problem of verb selection for data-to-text NLG through a principled model for verb selection based on large-scale realworld news corpora, and demonstrate its advantages similar to ours is a corpus based method for verb selection developed by Smiley et al. Given a new percentage change, their method randomly selects a verb verb selection for data-to-text NLG (see Section 1) verbs w, and P(x|w) is the likelihood, i.e., the probability of seeing the percentage change x given that percentage change x is to compute the posterior probability distribution P(w|x) over all the possible verbs Given a new percentage change x, in order to calculate its probability of being generated from a verb that we are aware of to this specific task of verb selection in the context of data-to-text NLG is the method work_y6i7l3737zhnxb6nkrgyvnvbou enhance the running time of the ANN pruning algorithms we implemented. set of features that remained in the pruned ANN with those obtained by different stateof-the-art feature selection (FS) methods. Keywords Artificial neural networks, Pruning, Parallelization, Feature selection, Classification Gan, Chen & Huang, 2016; Gardnera & Dorlinga, 1998; Hatzigeorgiou, 2002; HernándezSerna & Jiménez-Segura, 2014; Jayne, Iliadis & Mladenov, 2016; Kalkatawi et al., 2013; tool, which implements several parallelized variants of ANN pruning algorithms. We measured the performance of the implemented ANN pruning algorithms, on 15 OBS variants, the accuracy resulting from ANN pruning and the effects on input features effects of the different ANN pruning algorithms on the network, we evaluated the training Figure 3 Effects of different pruning algorithms on ANN performance on the training data. and pruned ANNs by the different algorithms on our datasets. Table 4 Selection of the input features through the ANN pruning and the effect on performance. work_y6y774uctjetvarldheqeoenfy cars and their willingness to be exposed to auditory feedback in automated driving. Keywords Driverless car, Crowdsourcing, Survey, Questionnaire, Fully automated driving, Highly automated driving, Auditory interface, Auditory feedback, Warning How to cite this article Bazilinskyy and De Winter (2015), Auditory interfaces in automated driving: an international survey. automated driving systems not only control the longitudinal motion of a vehicle, but also people who will be driving highly and fully automated cars will suffer from a reduction to a male voice in automated driving systems was also tested. Respondents were asked to imagine fully automated driving as follows: "Imagine a fully respondents who indicated a preference for a particular takeover request during highly automated driving a preference for a male and a female voice for a takeover request during highly automated driving Auditory interfaces in automated driving: an international survey Auditory interfaces in automated driving: an international survey work_yb2mzleh2rdpbgrztb2m5gw7fy employed to improve state of the art binarization algorithm, and achieve automatically character size estimation, line extraction, stroke width estimation, and feature We then utilize this information to improve state-of-the-art binarization, line segmentation, and characterizing feature behavior in a document collection. For a given property of the connected components in a document, the evolution maps document analysis algorithms, such as binarization and line extraction, provide poor Figure 1 A document image, and the distribution of connected components along their width property (x-axis), for each possible gray scale threshold (y-axis). represents the width CEM for a text document image, where ''hot'' colors represent high threshold, and the corresponding components in the document for two ranges of width Figure 5 A document image with its components according to the width evolution map. Figure 11 (A) A document and (B) its stroke width evolution map. line segmentation in degraded documents, stroke width estimation, and analysis of work_ydnazyhnonfvhfabfx2jkhm3pi Keywords Evolutionary feature selection, Bagged decision trees, Extreme learning machines, market, previous studies have highlighted that in addition to firm features such as the based on Bagged Decision Trees (BDTs) and Extreme Learning Machines (ELMs), are other Machine Learning methods that have been previously applied (Jiménez & Herrero, Klein & Roth 1990 477 firms in Canada (multinomial logit model) The authors analyze the impact of experience and psychic distance 2009 8 French manufacturing firms (qualitative study) The authors critically review the concept of psychic distance and authors posit that the individual perceptions of psychic distance are shaped by the country The present work aims at obtaining the most relevant features from enterprise-country Best individuals obtained by BDT and ELM share the following features: "Vicarious Table 4 Number of features in the best individuals for the different classifiers. Journal of International Business Studies 41(8):1259–1274 DOI 10.1057/jibs.2010.41. Journal of International Business Studies 41(8):1259–1274 DOI 10.1057/jibs.2010.41. work_ydypvtvejbby3ieiuc7quu6yge A Study on the Sinter Brazing Joint of Powder Metal Components The research focuses on the development of a new joint method, the sinter brazing of powder metal Various kinds of powder metallurgy composition were tested in the sinter brazing joint, Powder metallurgy is a processing method where green parts are compacted using dies and get sintered. Sintering offers equivalent strength as a cast iron and superior design flexibility and produces Near-NetShaped (NNS) parts at lower costs and it reduces the need for the machining process. is an established joining process for Powder Metal components, and it is often used in the production of processed through sinter brazing to heat treatment with air quench and to compare different brazing pastes during the sinter-brazing process by Burgess Norton. But to challenge the capabilities of sinter brazing materials and its components, another test Koiso, "Application of Sinter-Brazing," Metal Powder Report, work_yezbgqcljrdqjbrvjauzx4sxby distinct output formats, a DOCX file for submission to a journal, and a LATEX/PDF Keywords Open science, Markdown, Latex, Publishing, Typesetting, Document formats How to cite this article Krewinkel and Winkler (2017), Formatting Open Science: agilely creating multiple document formats for academic manuscripts with Pandoc Scholar. Currently, arXiv (https://arxiv.org/) publishes e-prints related to physics, mathematics, Examples such as the Journal of Statistical Software (JSS, https://www.jstatsoft.org/) and Figure 2 Estimated publishing cost for a ''hybrid'' journal (conventional with Open Access option). Figure 3 Workfow for the generation of multiple document formats with Pandoc. authoring of academic documents and their conversion into multiple output formats. illustrates the generation of various formatted documents from a manuscript in Pandoc (http://www.geany.org/), plugins provide additional functionality for markdown editing; Scientific manuscripts have to be submitted in a format defined by the journal or publisher. The document settings and styles of the resulting file pandoc-manuscript.docx can be https://github.com/robert-winkler/scientific-articles-markdown/ https://github.com/robert-winkler/scientific-articles-markdown/ work_ygvsy3rrzbfqfd2zbo4b2ehohq Towards computational reproducibility: researcher perspectives on the use and sharing of software Research software, which includes both the source code and executables used as part of disciplines, we found that researchers create, use, and share software in a wide variety of Research software is a important consideration when addressing concerns related to reproducibility (Hong27 services related to research software and computational reproducibility might look like. the characteristics or research software, its uses, and elucidating the related practices and perceptions of122 In order to understand researcher practices and perceptions related to software and computational repro-126 2. Characteristics of research software: Included questions related to how the participants use software146 our survey for terms like "source code", "executable", and "open source software" that participants could156 We asked participants about the generation and use of source code and executables (i.e. Do you write185 shown in Figure 2 more participants indicated that they use open source software (94.9%, N = 214) than197 work_ygxu3etm6zehvdovnjdt3htauu In neural machine translation (NMT), generation of a target word depends on both source Table 1: Source and target contexts are highly correlated to translation adequacy and fluency, respectively. 5src and 5tgt denote halving the contributions from the source and target contexts when generating the translation, respectively. contribution from the source context, the result further loses its adequacy by missing the partial translation "in the first two months of this year". each decoding step, NMT treats the source and target contexts equally, and thus ignores the different control the contributions of source and target contexts on the generation of target words (decoding) previous decoding state ti−1 and the previously generated word yi−1 constitute the target context.3 whether source and target contexts correlate to translation adequacy and fluency. each source word is translated.4 The decoding state implicitly models the notion of "coverage" by recurrently reading the time-dependent work_yhebvymmmrhipnq36s66tjy2u4 Keywords: Virtual Classroom, Collaborative Mechanism, Petri Net, Process Control Figure.1 The states graph of teacher and student in virtual network classroom According to the changed states of teacher and student in figure 1, their collaborative relationships are The collaborative mechanism among the virtual network classroom can be described into a Petri net, as Figure.2 Petri net model of the collaborative mechanism among the virtual network classroom of the waiting speech students, Simultaneously the right to speak resources flows from the P6 place to the to listening state, simultaneously the right to speak resources flow from the P6 place to the P5 place, which Research of Virtual Network Classroom Collaborative Mechanism Based on Petri Net Research of Virtual Network Classroom Collaborative Mechanism Based on Petri Net Research of Virtual Network Classroom Collaborative Mechanism Based on Petri Net Research of Virtual Network Classroom Collaborative Mechanism Based on Petri Net work_yiggwirfrrdmxotzboejxtmxuy Dynamic Language Models for Streaming Text Language models are typically assumed to be static—the word-given-context Our model also exploits observable context variables to capture temporal variation that is otherwise provide useful auxiliary information that might indicate the similarity of language models across different timesteps. Language modeling for streaming datasets in the context of machine together temporal dynamics, conditioning on nonlinguistic context, and scalable online learning suitable for streaming data and extensible to include to learn language models for streaming datasets. The intuition behind the model is that the probability of a word appearing at day t depends on the background log-frequencies, the deviation coefficients of the word at previous timesteps β1:t−1, and the similarity of current conditions of the world (based on online learning of dynamic topic models. one," and "base exp" are unigram language models. one," and "base exp" are bigram language models. dataset with bigram base models, the five stocks with work_yjeaxa5xifgpzgw7buftmhsgta How to cite this article Dow (2016), Decomposed multi-objective bin-packing for virtual machine consolidation. resources (Virtual machines) onto the minimum number of host servers. virtual machine packing stem from previous analyses and solutions to general purpose and suitable for small-to-medium business-sized virtual machine data centers on the Stated in terms of the classical Bin Packing problem, virtual machine consolidation is multiple large resource consumption VMs are less likely to fit onto a single bin (host), computing hosts for IaaS virtual machines, offers VM sizes in small, medium, large, host capacities and virtual machine consumption requirements of memory, CPU, disk type to be equivalent for the purposes of virtual machine bin packing. the size of equivalence sets combinations are known a priori because virtual machines are SMALL-VM set that could be satisfied by concrete virtual machines that are considered the SMALL sized VMs. As an example of performance of our two-phased approach to solution generation for work_yk2gyqjyvfawrgxcooxtlutl2u We assumed that increasing the image size using interpolation methods would result of interpolation methods in medical images, we used a Gender01 data set, which is a using an interpolation method with data augmentation by inversion and rotation, we Training the CNN by increasing the image size using the interpolation Effects of data count and image scaling on Deep Learning training. input image data size using the interpolation method. method, the average classification accuracy was improved for all models trained with image Bilinear image interpolation method was 0.675 for 100 training data and an image size of Figure 8 Comparison of the classification accuracy between training models of data augmentation using rotation and inversion and image augmentation using Bilinear. that image interpolation is an effective method to improve accuracy compared with the In this paper, we investigated the effect of using interpolated image sizes for training data work_ylcltxmpvvdbdmljbf3fmued3q model for unsupervised morphological analysis that integrates orthographic and semantic views of words. We model word formation in terms of morphological chains, from log-linear models with morpheme and wordlevel features to predict possible parents, including their modifications, for each word. In contrast, earlier approaches that capture semantic similarity in morphological variants operate solely at the word level (Schone and Jurafsky, 2000; Baroni et al., 2002). We evaluate our model on datasets in three languages: Arabic, English and Turkish. Currently, top performing unsupervised morphological analyzers are based on the orthographic properties of sub-word units (Creutz and Lagus, 2005; words (observations) and their segmentations (hidden), using morphemes and their contexts (character n-grams) for the features. We use morphological chains to model words in the where C(w) ⊂Z refers to the set of possible candidates (parents and their types) for the word w ∈W. model for unsupervised morphological segmentation that seamlessly integrates orthographic and semantic properties of words. work_ymogj4wlmff5xp3rhpie6woylq Visualising higher-dimensional spacetime and space-scale objects as projections In this paper, we look at how such higher-dimensional spacetime and space-scale objects can be visualised as projections from R4 to R3. the changes in a 3D object''s shape across time (Arroyo Ohori, Ledoux & Stoter, 2017) or (2017), Visualising higher-dimensional space-time and space-scale objects as projections to interactively, namely how to project higher-dimensional objects down to fewer dimensions. Higher-dimensional modelling of space, time and scale real-world 0D–3D entities are modelled as higher-dimensional objects embedded in higherdimensional space. Figure 2 The geometry of a 4D perspective projection along the x axis for a point p. exists during [−0.67,0.67], resulting in (B) a 4D model shown here in a ''long axis'' projection. the projected model with all its faces, edges and vertices. Higher-dimensional modelling of geographic information. topological data structures for the representation of objects in a higher-dimensional work_yo4hhuxsifh47lsegdobem34hi Earthquake Damage Predicting System of Songyuan Based on GIS creates a spatial database by field data and Baidu maps. simulate the earthquake by using the seismic intensity at different earthquake levels on the urban buildings in Keywords-Earthquake Damage Prediction; Songyuan; Baidu Earthquake predicting system of urban lifeline based on GIS, Prediction of Earthquake Disaster in Urban Area. Urban Earthquake Damage Prediction Virtual Simulation different directions for urban earthquake damage prediction, the vulnerability of building structures to earthquake disaster loss of the city under different intensity earthquake damage. intensity table to the building''s damage level is divided into seismic intensity, Dj means the damage level of the house, it buildings under different intensities of damage degree of earthquake damage prediction for lifeline engineering, and earthquake damage prediction in Songyuan. remote sensing image in urban rapid earthquake damage prediction earthquake damage prediction [J]. on prediction model of earthquake damage of urban bridge based on work_yprpgiiievbp5bhrll36375u3e sensor with the white cover has low hysteresis and high kind of the force sensor, because the feedback of the slip Only different is the slip sensor focuses on the force a force sensor, which bases different theories. R Neuman designed a kind of force sensor by changing the sensor had high sensitivity, low hysteresis, and good contact sensor using optical theory, which based on detecting light, the optical sensor will cost high consumption simple and low consumption slip sensor. Figure 3 shows the slip sensor. optical sensor which is under the cover. light from the cover, the participant puts a white thin paper First step, the participant put a white paper on the cover the output voltage and force using white cover. the output voltage and force using gray cover. simple way to build a slip sensor. that white cover of the sensor has high repeatability, low work_yrmvuqtjgjbyxdvawwajt7csp4 Modeling Missing Data in Distant Supervision for Information Extraction Distant supervision algorithms learn information extraction models given only large readily available databases and text collections. mentions a pair of entities (e1 and e2) that participate in a relation, r, is likely to express the proposition r(e1,e2), so we can treat it as a positive training model obtains a 27% increase in area under the precision recall curve on the sentence-level relation extraction task. entity pair, whereas we jointly model relation extraction and missing data in the text and KB. The model also makes the converse assumption: if Freebase contains the relation BIRTHLOCATION(Barack Obama, Honolulu), then we must extract it from at least one sentence. To learn the parameters of the sentence-level relation mention classifier, θ, we maximize the likelihood of the facts observed in Freebase conditioned missing data model corresponds to choosing the values of αMIT and αMID dynamically based on the entities and relations involved. work_yrxg3hcbpjelzfodvpcbszljxy Abstract—Since the United States developed the IPv4 protocol security considerations, IPv4''s address space is running out of in the address space, performance, network security routers and other devices to build a pure IPV9 network, controllable IPV9 future network root domain name This application implements a pure IPV9 network This scenario is applicable to IPv4 networks in IPv4 public network address between routers C and D major feature is the use of existing IPv4 networks scenario 1 is that the IPv4 public network address achieve IPV9 network connectivity in different The IPv4 network through 9over4 connection topology tunnel test The IPv4 network through 9over4 connection topology tunnel test The application implements the IPV9 network The application implements the IPV9 network access between different IPV9 networks. feature is the use of existing IPv4 networks between router accesses the IPv4 network at the same time, the The IPV9 network has established a digital domain work_yvqupgxxtvfxzpqganvqyp7f3m Design of the Hotel Monitoring System for the Image and Video Collection the image acquisition process and the embedded BOA server, designed an intelligent video image acquisition system. embedded Web server, which complete the image acquisition, Keywords-Video Sensor; Linux; USB Camera; V4L2; Web includes the image and video collection, the display module, The image acquisition module collects the image data Web server communicates the client PC browser between the The image data was collected by the USB camera; Based on the Linux operation system, the image acquisition program, the Web server BOA and the V4L2 driver (struct video_device) Build a standard video device driver C. Video image acquisition programs video image acquisition is shown in Figure 5. After the video image file collection is well done, the program, realizes the video data transmission. the system, and completes the image video acquisition and Unconstrained Video Collection", IEEE Transactions on Image work_yxwqykdd4bd63dezjbqsgfvk3y The Research and Implementation of 3D Scene Simulation of Camouflage camouflage scene simulation method based on MFC and Vega engine Vega Prime API renders the model and creates a virtual scene of camouflage can be generated by using visual Keywords-Camouflage; Terrain Modeling; Visual the Vega prime-based(VP) visual simulation technology to 3D visual simulation method[2-6] and real DEM data, environment, establish the Vega Prime visual simulation The camouflage 3D scene simulation system includes and the simulation scene refers to the virtual camouflage model of a simulation scene in Terra Vista to construct the data of the ground surface around the simulation scene, the around the simulation scene, Yu''s[7] camouflage design simulation model mainly including three steps: data loading, 6.camouflage pattern mapping to the surface of 3D model, model data, generates digital camouflage pattern, and implements the camouflage to terrain and object model in shows that, the camouflage simulation scene designed in this work_yxyq6ahmcjafbdnyyrzgzesjse continuum-level hypothesis testing, but very few offer power computing capabilities, How to cite this article Pataky (2017), Power1D: a Python toolbox for numerical power estimates in experiments involving onedimensional continua. The test statistic continuum is depicted along with uncorrected, random field theory (RFT)-corrected and power analysis that permits arbitrary signal and noise modeling. • Continuum-level omnibus power does not necessarily pertain to the modeled signal. model1 = power1d.DataSample( baseline , signal1 , noise , J=J ) model1 = power1d.DataSample( baseline , signal1 , noise , J=J ) underly power computations, and in particular the nature of the signal and noise models. power1d can be achieved using a null signal and two different noise models as follows: The noncentral RFT method models signal as a constant continuum shift (Hayasaka et al., yet exist in any other package: arbitrary continuum-level signal and noise modeling and computational power analysis via continuum-level signal and noise modeling. work_z3zhgzbn6bfgrf7trxjp34j5da Design of Pellet Recycle Scraper System in Sand-Blasting Chamber system and mechanical recycling system of pellet, we designed a trapezoidal scraper recycle system of pellet which powered by the cylinder and controlled by PLC to realize the pellet trapezoidal scraper pellet recycling system efficiency is much Keywords-Pellet; Cylinder; PLC; Scraper; Trapezoid to design a recycle system for pellet of low cost, resistance to Scraper-typed pellet recycle system [6] designed by this design is mainly composed of 2 rod, 3 scraper, 5 cylinder, 6 trench, 4 is air rod and 7 is pellet material. air rod is retracted, the scraper will move the pellet material stretched out, the scraper will flip without pushing pellet, so installing pneumatic valve on the cylinder, air rod speed can Scraper pellet recycle system Once the scraper-typed pellet recycle is started, the mechanical screw conveyor pellet recycling efficiencies are scraper pellet recycle system efficiency is much higher. work_z4osyr4lbfg65mntn73iqciy6a Therefore, the NMT decoders cannot clearly identify the contexts in which one word sense should modeling of word senses can be helpful to NMT • Weakly supervised word sense disambiguation (WSD) approaches integrated into NMT, • Three sense selection mechanisms for integrating WSD into NMT, respectively based occurrence of such nouns or verbs in the training data, we use word2vec to build word vectors all ambiguous words before clustering their occurrences, and do not adapt to what is actually observed in the data; as a result, the senses are often To model word senses for NMT, we concatenate the embedding of each token with a vector our sense-aware NMT models on large data sets Table 5: BLEU scores of our sense-aware NMT systems over five language pairs: ATTini is the best one among Word sense disambiguation improves statistical machine translation. Improving word sense disambiguation in neural machine translation work_z6a2e7o6xneifhhzpx4u5zutgi The technique is interesting because it provides a natural algorithmic process for symmetry breaking generating complex n-dimensional structures frequency of the set of 2-dimensional Turing machines to classify the algorithmic results from the Coding theorem method to approximate the Kolmogorov complexity of Figure 2 The top 36 objects in D(4,2)2D preceded by their Km,2D values, sorted by higher to lower frequency and therefore from smaller to larger Kolmogorov complexity after application of the Coding lossless compression method as approximation techniques to Kolmogorov complexity. length (files with more complex (random) strings are expected to be less compressible Figure 7 Top: Distribution of complexity values for different string lengths (l). and smallest to largest compression lengths using the Deflate algorithm as a method to approximate Kolmogorov complexity (Zenil, 2010). Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility Two-dimensional Kolmogorov complexity and an empirical validation of the Coding theorem method by compressibility work_z6dwctmg7zd2tjpjeloj4o25mm networks are UNet, Segmentation Network (Seg Net), High-Resolution Network Keywords Convolutional neural networks, Computed tomography, COVID-19, Segmentation, High-Resolution Network (HR Net), Segmentation Network (Seg Net), UNet, VGG-UNet segment infectious lung tissues of COVID-19 cases from tomographic images. Existing models works by linking high to low resolution convolutions subnetwork in series, segmentation of each pixel of the image by the model. the True Positive Rate, measures the quality of segmentation of one class and Specificity, or models like HR Net and UNet offer better performance than Inception ResNetV2 and the worst model to use for the Segmentation of COVID-19 based on our study. In this article, we analyzed four models for segmenting COVID-19 from Lung CT Images. Performance analysis of lightweight CNN models to segment infectious lung tissues of COVID-19 cases from tomographic images Performance analysis of lightweight CNN models to segment infectious lung tissues of COVID-19 cases from tomographic images work_zaoccjidqrghfmkriplbpj6m3a Performance, workload, and usability in a multiscreen, multi-device, information-rich environment computing environment factor included one with a desktop computer with a single monitor (control, condition A); one with a desktop with dual monitors, as well as a single tablet 29 condition A); one with a desktop with dual monitors, as well as a single tablet computer 205 condition while completing a flow process chart to document a different pit crew member''s tasks 259 Hypothesis 3: Participants will rate the usability of the work area computing set-up in conditions 323 computing environment in condition B (dual monitors and one iPad); 3 participants expressed a A single desktop monitor with two tablet computers (condition C) did not A single desktop monitor with two tablet computers (condition C) did not 386 pit stop scenario as an example of an information-rich task, where the use of multiple screens work_zbpzx43flfaifddpftczprcome network and use its embedding for further generalizing author attributes. graph feature engineering and network embedding methods were combined for co-authorship network embeddings and manually engineered features for HSE researchers. future links based on network topology without any additional information on authors. embeddings for author research interests and node proximity and evaluated different Table 3 Comparing machine learning models based on the Neighbor Weighted-L2 link embedding applied to future links prediction on the Table 5 Comparing machine learning models based on the Neighbor Weighted-L2 link embedding for link prediction problem on the HSE dataset. Table 6 Comparing machine learning models based on the Neighbor Weighted-L2 link embedding for link prediction problem on the Scopus Dual network embedding for representing research interests in the link prediction problem on co-authorship networks Dual network embedding for representing research interests in the link prediction problem on co-authorship networks work_zecvwmdvwvacdcb7oko24oq6fy Modeling Word Forms Using Latent Underlying Morphs and Phonology involves loopy belief propagation in a natural directed graphical model whose variables are unknown strings and whose conditional distributions are encoded as finitestate machines with trainable weights. In fact, generative linguists traditionally posit that each morpheme of a language has a single representation Figure 1: Our model as a Bayesian network, in which surface forms arise from applying phonology to a concatenation of SR at layer 3 is generated using the phonology model Sθ (a probabilistic finite-state transducer). morph M(a) ∈M as an IID sample from a probability distribution Mφ(m).3 This model describes Figure 2: Illustration of a contextual edit process as it pronounces the English word wetter by transducing the underlying /wEt#@r/ (after erasing #) to the surface [wER@r]. We are given a training set of surface word forms word types of a language, we sample a training set work_zeh74wbijvb65adjkkafyhybvu (2017), SymPy: symbolic computing in Python. (2017), SymPy: symbolic computing in Python. the operator overloading functionality of Python, SymPy follows the embedded domain Section S1 discusses the Gruntz algorithm, which SymPy uses to calculate symbolic limits. The following statement imports all SymPy functions into the global Python namespace.2 Expressions are created from symbols using Python''s mathematical syntax. Matrices (sympy.matrices) Tools for creating matrices of symbols and expressions. Simplification (sympy.simplify) Functions for manipulating and simplifying expressions. Solvers (sympy.solvers) Functions for symbolically solving equations, systems of SymPy matrices support common symbolic linear algebra manipulations, including For example, the symbolic SymPy summation expression Sum(f(x), SymPy includes several submodules that allow users to solve domain specific physics In SymPy every symbolic expression is an instance of the class Basic,12 the superclass of Many SymPy functions perform various evaluations down the expression tree. SymPy expressions are immutable trees of Python objects. work_zg4qriee75dphc3uvx6own7gka applied machine learning to fight COVID-19 pandemic from a different perspective. Many studies adopted machine learning to fight the COVID-19 pandemic from a COVID-19 datasets that can guide researchers access different data for studies on (2020) applied transfer learning with CNN to detect COVID-19 from X-ray images applied a deep learning algorithm on a chest CT scan of a patient with COVID-19 to result and non-image clinical information to predict COVID-19 infection in a patient. learning approach to predict COVID-19 potential infections based on reported cases in (2020) developed a machine learning COVID-19 predictive model and deployed Table 3 The summary of the COVID-19 diagnostic tools based on machine learning algorithms. deep learning application to COVID-19 medical imaging analysis, and listed and described Early survey with bibliometric analysis on machine learning approaches in controlling COVID-19 outbreaks Early survey with bibliometric analysis on machine learning approaches in controlling COVID-19 outbreaks work_zg62yupdxbb5tb2624egapptde Lin was a towering figure in social network analysis, one of the pioneers of the field, and a major contributor to a wide range of topics in the discipline. terms." Lin''s research on social networks brought practices across disciplines, Lin consciously modeled his editorial approach at Social Networks after circle of social networks, Lin and Sue''s genuine interest in me, my family and my work never waned. Lin Freeman was always at Sunbelt Social Network conferences – and always visible – he invariably stood in a central spot outside the meeting rooms Lin''s work was a key to the mid-1970s transformation of social network analysis from a vague movement to a coherent program. social network analysis, SNA gave Lin a community Lin and his many contributions to my life, the nature of the social networks field, the social network field had nothing to do with Lin! in studying social networks than Lin Freeman. work_zgex2teysbcjjhnn7t4oyvqu5q Demand Forecast of Weapon Equipment Spare Parts Based on Improved Gray-Markov Model Keywords-Grey Theory; Markov Model; Spare Parts prediction of spare parts demand is an important means predict the random demand for repair spare parts. the method based on the time series prediction model network-based spare parts demand prediction method the prediction accuracy of the demand for spare parts improved gray Markov model, in order to effectively effective spare parts demand forecasting model will gray mean model is used to predict the future demand several states, establish a Markov model, and predict gray prediction result residual model. the predicted result of the gray model with the actual process prediction, so the gray modeling part and The the gray model and make predictions; then divide the relative error of the gray prediction results State, Using the improved gray-Markov model to predict Through the prediction of the gray model, you can gray-Markov prediction method. work_zhl5dw75nfhy7oputsllvjjcqq Evaluating the Stability of Embedding-based Word Similarities NLP research in word embeddings has so far focused on a downstream-centered use case, where direct human analysis of nearest neighbors to embedding vectors, and the training corpus is not simply an Other studies use cosine similarities between embeddings to measure the variation Table 3: The three settings that manipulate the document order and presence in each corpus. of documents could be an important factor for algorithms that use online training such as SGNS. a document-based embedding method that uses matrix factorization, LSA (Deerwester et al., 1990; Landauer and Dumais, 1997). To train our PPMI word embeddings, we use This indicates that the presence of specific documents in the corpus can significantly affect the cosine similarities between embedding vectors. across runs of the BOOTSTRAP setting for the full corpus of AskScience, the whole document length, and the GloVe in cosine similarities between word embeddings vectors. work_zjh4gwjbrfbs3m2w5jy3as4kdu persona2vec, a graph embedding framework that efficiently learns multiple Keywords Graph embedding, Overlapping community, Social context, Social network analysis, persona2vec creates a persona graph, where some nodes are split into multiple personas. algorithm, node C in the original graph belongs to two non-overlapping clusters {A,B} node A only belongs to one ego cluster {B,C}, so it does not split into multiple personas. Any graph clustering algorithm can be employed for splitting a node into personas. common embedding methods could not be directly applied to the splitted graph. In the persona graph, we set the weights of the unweighted original edges as 1 and embedding where each persona node has its own vector representation. fine-tune the embedding vectors with the information from the persona graph (see Fig. 1). Our method for generating persona node embeddings. Persona2vec: a flexible multi-role representations learning framework for graphs Persona2vec: a flexible multi-role representations learning framework for graphs work_zl6536xffjcdbhnnz257hqkpwu Mobile Phone Assessment in Egocentric Networks: A Pilot Study on Gay Men and Mobile Phone Assessment in Egocentric Networks: A Pilot Study on Gay Men and Mobile phone-based data collection encompasses the richness of social network research. behaviors were reported through a mobile phone-based daily assessment that was administered through Keywords: Gay men, HIV risk behaviors, mobile phone log, ecological momentary assessment, ohmage Mobile phone-based data collection was supported by ohmage and the following centers at Figure 1: Recruitment and enrollment of egos (gay men) and alters and initiation of mobile phone-based data collection. Mobile Phone Assessment in Egocentric Networks Mobile Phone Assessment in Egocentric Networks Mobile Phone Assessment in Egocentric Networks Mobile Phone Assessment in Egocentric Networks Mobile Phone Assessment in Egocentric Networks Mobile Phone Assessment in Egocentric Networks Mobile Phone Assessment in Egocentric Networks Mobile Phone Assessment in Egocentric Networks work_zmfcmcryxjg5rb3adtopcdqnza Task-based programming models have demonstrated their efficiency in the development of scientific applications on modern high-performance platforms. parallelism when it is uncertain if some tasks will modify data, and we formalize a new methodology to enable speculative execution in a graph of tasks. Increasing the degree of parallelism using speculative execution in task-based runtime systems. objectives are to get a generic pattern/method to use speculation in task-based RS''s and to • Introduce SPETABARU, a new task-based RS capable of speculation. Here, task B may or may not write data, but to ensure a correct execution, we must use the data, then the speculation has failed no matter the result of the other uncertain tasks. writes data, then we will have to compute task i+1 and speculate over it with duplicate of 26 // Insert t as a speculative task using data duplicates, 26 // Insert t as a speculative task using data duplicates, work_zmw4nyamdvhgbjpenjnarukk7m The FORCE11 Software Citation Working Group was created in April 2015 with the overlaps and differences; create a list of use cases related to software citation, recorded Software Citation Principles document was discussed in a day-long workshop and then modified based on discussions of the FORCE11 Software Citation Working Group We documented and analyzed a set of use cases related to software citation in FORCE11 Software Citation Working Group (https://docs.google.com/document/d/ Wilson (2013) suggests that software authors include a CITATION file that documents cite software, and journals such as F1000Research (http://f1000research.com/for-authors/ research product, provenance data will include some of the cited software. https://www.force11.org/group/software-citation-working-group https://www.force11.org/group/software-citation-working-group section Use Cases, originally found in FORCE11 Software Citation Working Group. use cases, including explaining in more detail how the software citation principles � Format for citing software in source code, documentation, or citation metadata file � Format for citing software in source code or citation metadata file Available at https://www.force11.org/group/jointdeclaration-data-citation-principles-final. work_zmzfnu5br5grbipquovhai5d7a learning called Generative Adversarial Networks (GANs) are employed. Keywords Deep Learning, Counterfeit Money, Generative Adversarial Networks DeepMoney: counterfeit money detection using generative adversarial networks. genuine ones, state-of-the-art models of machine learning called Generative Adversarial used class descriptions for real and fake images of the currency for security threads in the fingerprint records which can be used for detecting counterfeit currency note. To differentiate between genuine and counterfeit notes, the researchers used a threedimensional imaging security feature according to the FF-OCT system. Kang & Lee (2016) Fake banknote detection Multispectral imaging sensors Feature extraction and classification require high computation Mirza & Nanda (2012a) Currency verification Image processing: edge detection generative and discriminative models for the recognition of real and counterfeit currency generative model G was used to input the counterfeit notes to classify with discriminative Generative Adversarial Networks cope with real and fake data. Image processing based detection of counterfeit work_znxqek43rrc75ooytxtbi73bom (2014) also developed the image-based in situ visualization method and implemented place the visualization cameras all over the simulation region, that is, not only around simulation space and apply in situ visualization with them. (B) Each camera records the time development of the simulation viewed from its position with 4p steradian and the omnidirectional images are specifies the position, direction, and time (or frame) to extract images from the data collection. multiple points of view, omnidirectional rendering, and in situ visualization. (B) Example of the six images obtained by the in situ visualization in a test simulation. visualization cameras into a Hall MHD turbulence simulation code (Miura & Hori, the true value of 4D Street View for the interactive analysis of the in situ visualization. 4D street view: a video-based visualization method 4D street view: a video-based visualization method 4D street view: a video-based visualization method work_zo6mjxbmffhftidtrj7nfurd3q Hazard Grading Model of Terrorist Attack Based on First, the data related to the hazard in the Global Terrorism each type of terrorist attack is calculated. are divided into 1-5 levels of hazard grading models in order of Keywords-Terrorist Attacks; Hazard; Hierarchical Model; analysis of data related to terrorist attacks will help terrorism events is obtained with a hazard rating of 5. In this paper, the hazard grading model of terrorism Terrorism Hazard Classification Model Data Table has frequency to the attack type indicator value. frequency to the weapon type indicator value. Calculate the cluster center to which each type of event 4) Calculating the entropy value of the j-th indicator, average value of the hazard score of each type of event for the hazard grading of terrorist attacks; after preprocessing the data used, through principal component scores of the five types of attacks, a graded to fivelevel classification model was obtained. work_zpb5q6j2qjbcjhw5xefjwjkgse neighbour interpolation and cross-validation error-distance fields provide reliable Discrete natural neighbour interpolation with uncertainty using cross-validation errordistance fields. neighbour interpolation is the cross-validation error field (Willmott & Matsuura, 2006). that when estimated for all cells produces a cross-validation error-distance field (Fig. 3B). The discrete natural neighbour interpolation and cross-validation error-distance field (Pérez, Granger & Hunter, 2011) using the NumPy (Van der Walt, Colbert & Varoquaux, each data cell ri calculated through cross-validation, and then an estimated rate of absolute error field r̂ is To summarise the performance of both natural neighbour interpolation and the crossvalidation error-distance field, the MAE (Eq. cross-validation error-distance field (Fig. 6B) reduced as the number of data points n and (B) the resulting natural neighbour interpolation ẑ from the sampling points, and (C) value error e(ẑ) = Figure 6 Performance of natural neighbour interpolation and cross-validation error-distance fields data points, therefore as interpolations move further beyond the convex hull the error-field work_zsdcnoxlmvf4rm6xntj2tme3ye Keywords Microscope, Do-It-Yourself, Open source, Raspberry Pi, Twitter, Flickr Once the DIY microscope was constructed, we developed user interfaces by exploiting Simple message syntax was developed in order to allow other user to adjust microscope an approach to control a local DIY Microscope by exploiting the API of the popular video again adjust microscope focus, capture single images or initiate time-lapse recordings. For example, the Twitter user can capture single images, control sample To locally control the microscope, we designed a Python script that will create a user Flickr account is required for storage of images acquired by the DIY Microscope. drawn on the image and returned to the requesting user in a Twitter message (Fig. 3B). removed from the RPi. In Fig. 3, a single image is requested by the user @pellinglab and an Figure 3 Twitter acquisition of a single image from the DIY Microscope. work_zsyuh5xaxnhyxbfjgxkd3jpzla Keywords Image fusion, Guided filter, Saliency, Infrared, Nightvision, Thermal imagery, of algorithms are the multi-scale image fusion schemes, which decompose the source In this paper we propose a multi-scale image fusion scheme, where iterative guided As mentioned before, most multi-scale transform-based image fusion methods introduce the saliency maps corresponding to the individual source images; guided filtering is applied weighted recombination phase of multi-scale image fusion schemes (Bavirisetti & Dhuli, source images together with the result of the proposed fusion scheme (F) for each of the 12 scenes used in this study. guided filtering of the binary weight maps with their corresponding base layers as guidance images. scene 12) source images together with the result of the proposed fusion scheme (F) for We propose a multi-scale image fusion scheme based on guided filtering. We propose a multi-scale image fusion scheme based on guided filtering. fusion with the use of multi-scale edge-preserving decomposition and guided image work_ztklkdhf5fexjdonz6dgaysziq Keywords MPI extension library, Deep copy, Serialization, Marshalling, Dynamic data structures, Deep copy requires recursively traversing pointer members in a data structure, library only handles the use case of fully buffered deep copy in the context of MPI_Send Listing 2 User example–hand coded deep copy using a dangling pointer from the sending process Listing 4 User example–hand coded buffered deep copy using a dangling pointer from the sending initiating deep copy as send/receive, broadcast, or file-IO operation; a transport API a deep copy as a send, receive, broadcast, or file access operation on a templated pointer 11 void MEL::Deep::Send(T *&ptr, const int len, ...) 17 void MEL::Deep::Recv(T *&ptr, int const &len, ...) 28 void MEL::Deep::Bcast(T *&ptr, int const &len, ...) The deep copy function declares to our algorithm how data dependencies of a type need Listing 15 MEL implementation–Message::packSharedPtr. 1 // Transport a deep shared pointer to len objects work_ztwbqgudijgzxlxrphrkhfclui the use of dynamic detection safeguards that prevent code injection attacks while the Keywords Application security, Code injection attacks, Countermeasures, Static analysis, untrusted input verbatim into an output program is vulnerable to code injection attacks''''. bugs that could lead to a code injection attack without actually executing the program. an SQL injection attack, developers can use specific features provided by the language they (2011) have proposed a model checking approach to detect binary code injection defects can be easily adapted to detect vulnerabilities that may lead to code injection attacks. 2010) was first introduced into Firefox to detect various types of attacks, including crosssite scripting https://developer.mozilla.org/en/Introducing_Content_Security_Policy. Table 1 Static Analysis: Comparison summary of tools designed to detect vulnerabilities that can lead to a code injection attack. Table 2 Dynamic Detection: Comparison summary of mechanisms developed to counter code injection attacks. major categories: static analysis mechanisms that detect code injection vulnerabilities, and work_zukr6fkh3zbxdcgipfzstjjrqu proposes and evaluates a logic level fault-tolerant method based on parity for designing combinational circuits. Keywords: Soft Error, Transient Fault, Fault-Tolerance, Combinational Circuits, Full Adder. implement for logic blocks [8,9].However, combinational circuits are very importance for fault-tolerant design. fault sensitivity in combinational and sequential circuits ;in section 3 we proposed a new faulttolerance technique in elements, and combinational logic are the most sensitive parts and could be affected by soft errors and transient faults. These masking effects have been found to result in a significantly lower rate of soft errors in combinational logic errors in combinational logic circuits and suggest a logic level fault-tolerant design method. In this paper we presented a new approach to design fault-tolerant combinational circuits. TMR method is a conventional technique to design fault-tolerant circuits. In this paper, we proposed a new approach to design fault-tolerant combinational circuits. the soft error rate of combinational logic," presented at the DSN. work_zwxfdtyt5jcbtelumlduow5tpu Discriminative Lexical Semantic Segmentation with Gaps: Running the MWE Gamut MWEs containing gaps, thereby enabling efficient sequence tagging algorithms for featurerich discriminative models. linguistically-driven evaluation of MWE identification with truly heterogeneous expression It is difficult to establish any comprehensive taxonomy of multiword idioms, let alone develop linguistic criteria and corpus resources that cut across type, and that facilitates free text annotation without requiring a prespecified MWE lexicon (§2). (2014) we have applied this scheme to fully annotate a 55,000-word corpus of English web reviews To build and evaluate a multiword expression analyzer, we use the MWE-annotated corpus of Schneider et al. the first dataset of social media text with MWE annotations beyond named entities. A multiword lexical expression may contain gaps, The language of derivations licensed by the grammars in §3 allows for a tag-based encoding of MWE With the above representations we model MWE identification as sequence tagging, one of the paradigms