{"id":"https://openalex.org/W4402157447","doi":"https://doi.org/10.1109/jiot.2024.3446551","title":"Multitask Correlation Constrained Topological Learning Toward Smart Prognostic and Health Management in IoT","display_name":"Multitask Correlation Constrained Topological Learning Toward Smart Prognostic and Health Management in IoT","publication_year":2024,"publication_date":"2024-08-20","ids":{"openalex":"https://openalex.org/W4402157447","doi":"https://doi.org/10.1109/jiot.2024.3446551"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3446551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3446551","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065139430","display_name":"Xuzhe Zheng","orcid":"https://orcid.org/0009-0001-5538-6890"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuzhe Zheng","raw_affiliation_strings":["School of Frontier Crossover Studies, Hunan University of Technology and Business, Changsha, China"],"raw_orcid":"https://orcid.org/0009-0001-5538-6890","affiliations":[{"raw_affiliation_string":"School of Frontier Crossover Studies, Hunan University of Technology and Business, Changsha, China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055675863","display_name":"Xiaokang Zhou","orcid":"https://orcid.org/0000-0003-3488-4679"},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiaokang Zhou","raw_affiliation_strings":["Faculty of Business Data Science, Kansai University, Osaka, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3488-4679","affiliations":[{"raw_affiliation_string":"Faculty of Business Data Science, Kansai University, Osaka, Japan","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073441538","display_name":"Wei Liang","orcid":"https://orcid.org/0000-0002-0689-256X"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liang","raw_affiliation_strings":["Xiangjiang Laboratory and the School of Computer Science, Hunan University of Technology and Business, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0689-256X","affiliations":[{"raw_affiliation_string":"Xiangjiang Laboratory and the School of Computer Science, Hunan University of Technology and Business, Changsha, China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091532881","display_name":"Kevin I\u2010Kai Wang","orcid":"https://orcid.org/0000-0001-8450-2558"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Kevin I-Kai Wang","raw_affiliation_strings":["Department of Electrical, Computer, and Software Engineering, The University of Auckland, Auckland, New Zealand"],"raw_orcid":"https://orcid.org/0000-0001-8450-2558","affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Software Engineering, The University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.8852,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.95610096,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"11","issue":"24","first_page":"39487","last_page":"39496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6672097444534302},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.6184872388839722},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5679415464401245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.339056134223938},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3304986357688904},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3274509012699127},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.15155988931655884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1486002504825592}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6672097444534302},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.6184872388839722},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5679415464401245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.339056134223938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3304986357688904},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3274509012699127},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.15155988931655884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1486002504825592},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3446551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3446551","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1864093853","display_name":"Research on Causality-Inspired Deep Learning Model for Anomaly Detection with Imbalanced Data","funder_award_id":"23K11064","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G2071613473","display_name":"\u591a\u57df\u5065\u5eb7\u5927\u6570\u636e\u9a71\u52a8\u7684\u91cd\u5927\u4f20\u67d3\u75c5\u75ab\u60c5\u65e9\u671f\u8bc6\u522b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"62072171","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4831919423","display_name":null,"funder_award_id":"23XJ01008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1544786743","https://openalex.org/W1832693441","https://openalex.org/W2008056655","https://openalex.org/W2016057312","https://openalex.org/W2049889029","https://openalex.org/W2096733369","https://openalex.org/W2123442489","https://openalex.org/W2158581396","https://openalex.org/W2332655816","https://openalex.org/W2530828645","https://openalex.org/W2792899709","https://openalex.org/W2794764013","https://openalex.org/W2798869704","https://openalex.org/W2891859208","https://openalex.org/W2965006690","https://openalex.org/W2977981067","https://openalex.org/W3006300626","https://openalex.org/W3015141382","https://openalex.org/W3020589325","https://openalex.org/W3101273072","https://openalex.org/W3153990350","https://openalex.org/W3155739706","https://openalex.org/W3204914169","https://openalex.org/W4200591402","https://openalex.org/W4206754003","https://openalex.org/W4206982817","https://openalex.org/W4210342630","https://openalex.org/W4226179997","https://openalex.org/W4287887252","https://openalex.org/W4308001098","https://openalex.org/W4362563552","https://openalex.org/W4367281523","https://openalex.org/W4383337188","https://openalex.org/W4387861048","https://openalex.org/W4391311259","https://openalex.org/W4396506525"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Due":[0],"to":[1,18,29,41,49,80,136,162,178],"the":[2,10,45,66,108,132,145,149,158,165,180,183,210,213,217],"high":[3],"dependence":[4],"of":[5,12,23,25,60,73,83,144,232],"social":[6],"development":[7],"on":[8,148,182,202],"electricity,":[9],"failure":[11],"energy":[13,34,233],"system":[14,52,234],"equipment":[15,62,235],"often":[16],"leads":[17],"inestimable":[19],"losses.":[20],"The":[21],"use":[22],"Internet":[24],"Things":[26],"(IoT)":[27],"technology":[28,40],"collect":[30],"real-time":[31,55],"data":[32,56,68,77],"from":[33],"devices":[35,46],"and":[36,64,70,101,123,141,187,198,216,224],"artificial":[37],"intelligence":[38],"(AI)":[39],"prognostic":[42,100],"faults":[43,63],"in":[44,104,153,236],"becomes":[47],"essential":[48],"achieve":[50],"power":[51],"security.":[53],"Although":[54],"contains":[57],"rich":[58],"descriptions":[59],"relevant":[61],"solutions,":[65],"complex":[67,154],"structure":[69],"severe":[71],"imbalance":[72],"condition":[74],"monitoring":[75],"(CM)":[76],"may":[78],"lead":[79],"poor":[81],"performance":[82],"AI":[84],"models.":[85],"In":[86,106],"this":[87],"study,":[88],"we":[89],"propose":[90],"a":[91,113,117,124,172,222],"multitask":[92,118],"correlation":[93],"constrained":[94],"topology":[95,119],"learning":[96,196],"model":[97,110,193],"for":[98,227],"smart":[99],"health":[102],"management":[103],"IoT.":[105],"particular,":[107],"proposed":[109],"mainly":[111],"includes":[112],"feature":[114],"extraction":[115],"module,":[116,122],"network":[120],"(MTTN)":[121],"class":[125],"balance":[126],"loss":[127,174],"(CBL)":[128],"algorithm":[129],"module.":[130],"First,":[131],"Bi-LSTM":[133],"is":[134,160,176],"employed":[135],"extract":[137],"word":[138],"collocation":[139],"features":[140,143,152],"numerical":[142],"data,":[146,205],"focusing":[147],"important":[150],"semantic":[151],"structured":[155],"data.":[156],"Second,":[157],"MTTN":[159],"constructed":[161],"efficiently":[163],"utilize":[164],"topological":[166],"dependency":[167],"between":[168],"multiple":[169],"tasks.":[170],"Finally,":[171],"CBL":[173],"function":[175],"applied":[177],"enhance":[179],"focus":[181],"minority":[184],"classes.":[185],"Experiment":[186],"evaluation":[188],"results":[189],"demonstrate":[190],"that":[191],"our":[192],"has":[194],"superior":[195],"efficiency":[197],"prediction":[199],"performance,":[200],"especially":[201],"extremely":[203],"imbalanced":[204],"which":[206],"can":[207],"correctly":[208],"predict":[209],"faulty":[211],"equipment,":[212],"fault":[214,218],"cause":[215],"severity":[219],"level,":[220],"providing":[221],"rapid":[223],"precise":[225],"reference":[226],"advance":[228],"repair":[229],"or":[230],"replacement":[231],"IoT":[237],"environments.":[238]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
