{"id":"https://openalex.org/W2988680766","doi":"https://doi.org/10.1109/vts.2019.8758599","title":"Board-Level Functional Fault Identification using Streaming Data","display_name":"Board-Level Functional Fault Identification using Streaming Data","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2988680766","doi":"https://doi.org/10.1109/vts.2019.8758599","mag":"2988680766"},"language":"en","primary_location":{"id":"doi:10.1109/vts.2019.8758599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts.2019.8758599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 37th VLSI Test Symposium (VTS)","raw_type":"proceedings-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/A5038187283","display_name":"Mengyun Liu","orcid":"https://orcid.org/0000-0002-6476-3061"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mengyun Liu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018889229","display_name":"Fangming Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fangming Ye","raw_affiliation_strings":["Huawei R&D, Santa Clara, CA"],"affiliations":[{"raw_affiliation_string":"Huawei R&D, Santa Clara, CA","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353869","display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-4510-2436"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033880864","display_name":"Krishnendu Chakrabarty","orcid":"https://orcid.org/0000-0003-4475-6435"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krishnendu Chakrabarty","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014106133","display_name":"Xinli Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinli Gu","raw_affiliation_strings":["Huawei R&D, Santa Clara, CA"],"affiliations":[{"raw_affiliation_string":"Huawei R&D, Santa Clara, CA","institution_ids":["https://openalex.org/I4210146936"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5038187283"],"corresponding_institution_ids":["https://openalex.org/I170897317"],"apc_list":null,"apc_paid":null,"fwci":1.9602,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.89920607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"11","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9824000000953674,"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":0.7784593105316162},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.7482435703277588},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6359145045280457},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.6171016693115234},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5691032409667969},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.5327838659286499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5195848941802979},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.47514843940734863},{"id":"https://openalex.org/keywords/online-model","display_name":"Online model","score":0.45961540937423706},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4427129626274109},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.4389662742614746},{"id":"https://openalex.org/keywords/online-algorithm","display_name":"Online algorithm","score":0.41416722536087036},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4090340733528137},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.328768253326416},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.263760507106781},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2504647970199585},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.10513755679130554}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7784593105316162},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7482435703277588},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6359145045280457},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.6171016693115234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5691032409667969},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.5327838659286499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5195848941802979},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.47514843940734863},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.45961540937423706},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4427129626274109},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.4389662742614746},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.41416722536087036},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4090340733528137},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.328768253326416},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.263760507106781},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2504647970199585},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.10513755679130554},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vts.2019.8758599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts.2019.8758599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 37th VLSI Test Symposium (VTS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W767201593","https://openalex.org/W1525647652","https://openalex.org/W1544582518","https://openalex.org/W1680622244","https://openalex.org/W1990079212","https://openalex.org/W2000454347","https://openalex.org/W2002246747","https://openalex.org/W2004087388","https://openalex.org/W2006246460","https://openalex.org/W2009727399","https://openalex.org/W2068714596","https://openalex.org/W2103012681","https://openalex.org/W2114656739","https://openalex.org/W2115677675","https://openalex.org/W2119884533","https://openalex.org/W2135335717","https://openalex.org/W2140336868","https://openalex.org/W2143991132","https://openalex.org/W2149298154","https://openalex.org/W2160218441","https://openalex.org/W2168344315","https://openalex.org/W2177971469","https://openalex.org/W2295598076","https://openalex.org/W2524537451","https://openalex.org/W2806425357","https://openalex.org/W2847284300","https://openalex.org/W3003253354","https://openalex.org/W3009009611","https://openalex.org/W3102476541","https://openalex.org/W4235130247","https://openalex.org/W6675490775","https://openalex.org/W6680192438","https://openalex.org/W6681046083","https://openalex.org/W6683584131","https://openalex.org/W6752866118"],"related_works":["https://openalex.org/W4281572076","https://openalex.org/W2469699777","https://openalex.org/W2060628068","https://openalex.org/W2253527885","https://openalex.org/W2773951400","https://openalex.org/W3013371665","https://openalex.org/W4391093024","https://openalex.org/W3208495060","https://openalex.org/W2277307313","https://openalex.org/W2235038291"],"abstract_inverted_index":{"High":[0],"integration":[1],"densities":[2],"and":[3,28,45,137],"design":[4],"complexity":[5],"of":[6,37,59,80,114,134],"printed-circuit":[7],"boards":[8,115,125],"make":[9],"board-level":[10],"functional":[11,23],"fault":[12],"identification":[13],"extremely":[14],"difficult.":[15],"Machine":[16],"learning":[17,71,87,136],"provides":[18],"an":[19],"opportunity":[20],"to":[21,72,90,105,151],"identify":[22],"faults":[24],"with":[25,76,94,131],"high":[26],"accuracy":[27],"thereby":[29],"reduce":[30],"repair":[31],"cost.":[32],"However,":[33],"the":[34,57,107,132,138,142],"large":[35],"volume":[36],"manufacturing":[38],"data":[39,81,110],"comes":[40],"in":[41,50,126],"a":[42,51,65,77],"streaming":[43],"format":[44],"exhibits":[46],"time-dependent":[47],"concept":[48,91],"drift":[49,92],"production":[52,128],"environment.":[53],"These":[54,85],"drawbacks":[55],"limit":[56],"effectiveness":[58],"traditional":[60],"machine-learning":[61],"algorithms.":[62],"We":[63],"propose":[64],"diagnosis":[66,145],"workflow":[67],"that":[68,109],"utilizes":[69],"online":[70,86,135],"train":[73],"classifiers":[74],"incrementally":[75],"small":[78],"chunk":[79],"at":[82,118],"each":[83],"step.":[84],"algorithms":[88],"adapt":[89],"quickly":[93],"carefully":[95],"designed":[96],"update":[97],"rules.":[98],"A":[99],"hybrid":[100,140],"algorithm":[101],"is":[102],"also":[103],"proposed":[104,139],"handle":[106],"scenario":[108],"for":[111,144],"varying":[112],"numbers":[113],"are":[116],"collected":[117],"different":[119],"times.":[120],"Experimental":[121],"results":[122],"using":[123],"two":[124],"high-volume":[127],"show":[129],"that,":[130],"help":[133],"algorithm,":[141],"F1-score":[143],"can":[146],"be":[147],"improved":[148],"from":[149],"57.3%":[150],"78.9%.":[152]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}