{"id":"https://openalex.org/W4210930435","doi":"https://doi.org/10.1109/tase.2022.3146391","title":"A Generic Online Nonparametric Monitoring and Sampling Strategy for High-Dimensional Heterogeneous Processes","display_name":"A Generic Online Nonparametric Monitoring and Sampling Strategy for High-Dimensional Heterogeneous Processes","publication_year":2022,"publication_date":"2022-02-07","ids":{"openalex":"https://openalex.org/W4210930435","doi":"https://doi.org/10.1109/tase.2022.3146391"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2022.3146391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3146391","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Transactions on Automation Science and Engineering","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/A5020779806","display_name":"Honghan Ye","orcid":"https://orcid.org/0000-0001-5329-7344"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Honghan Ye","raw_affiliation_strings":["Department of Industrial and Systems Engineering, College of Engineering, University of Wisconsin–Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0000-0001-5329-7344","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, College of Engineering, University of Wisconsin–Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025012113","display_name":"Kaibo Liu","orcid":"https://orcid.org/0000-0003-2863-5748"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaibo Liu","raw_affiliation_strings":["Department of Industrial and Systems Engineering, College of Engineering, University of Wisconsin–Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0000-0003-2863-5748","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, College of Engineering, University of Wisconsin–Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":4.5197,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.95893809,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"19","issue":"3","first_page":"1503","last_page":"1516"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9908999800682068,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7382955551147461},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.7166337966918945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6637770533561707},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5790526866912842},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5516859889030457},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.5335951447486877},{"id":"https://openalex.org/keywords/cusum","display_name":"CUSUM","score":0.4741869866847992},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4417732059955597},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4267391562461853},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21870720386505127},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.17415624856948853},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14216545224189758}],"concepts":[{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7382955551147461},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.7166337966918945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6637770533561707},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5790526866912842},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5516859889030457},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.5335951447486877},{"id":"https://openalex.org/C178518018","wikidata":"https://www.wikidata.org/wiki/Q1024555","display_name":"CUSUM","level":2,"score":0.4741869866847992},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4417732059955597},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4267391562461853},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21870720386505127},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.17415624856948853},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14216545224189758},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2022.3146391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3146391","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G127860592","display_name":null,"funder_award_id":"W912HZ20C-0031","funder_id":"https://openalex.org/F4320338258","funder_display_name":"Engineer Research and Development Center"}],"funders":[{"id":"https://openalex.org/F4320307785","display_name":"3M","ror":"https://ror.org/00mgss748"},{"id":"https://openalex.org/F4320338258","display_name":"Engineer Research and Development Center","ror":"https://ror.org/027mhn368"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1969474438","https://openalex.org/W1971084072","https://openalex.org/W1973885534","https://openalex.org/W1975061413","https://openalex.org/W1988725147","https://openalex.org/W1992332533","https://openalex.org/W1999971199","https://openalex.org/W2006090484","https://openalex.org/W2019110314","https://openalex.org/W2045067839","https://openalex.org/W2056980115","https://openalex.org/W2062180331","https://openalex.org/W2068913238","https://openalex.org/W2070342587","https://openalex.org/W2074013991","https://openalex.org/W2091083310","https://openalex.org/W2095303958","https://openalex.org/W2121219412","https://openalex.org/W2128780546","https://openalex.org/W2131167729","https://openalex.org/W2137321113","https://openalex.org/W2145058161","https://openalex.org/W2166426063","https://openalex.org/W2292342773","https://openalex.org/W2319358815","https://openalex.org/W2327851143","https://openalex.org/W2607420770","https://openalex.org/W2765733960","https://openalex.org/W2790454619","https://openalex.org/W2791747180","https://openalex.org/W2816854051","https://openalex.org/W2894694938","https://openalex.org/W2895088082","https://openalex.org/W2898128856","https://openalex.org/W2898699838","https://openalex.org/W2914601930","https://openalex.org/W2972591958","https://openalex.org/W2990611428","https://openalex.org/W2996580393","https://openalex.org/W3008300502","https://openalex.org/W3032270254","https://openalex.org/W3034654297","https://openalex.org/W3089271697","https://openalex.org/W3105702803","https://openalex.org/W4234228486","https://openalex.org/W4242631541","https://openalex.org/W4249116379","https://openalex.org/W6606032028","https://openalex.org/W6639904974","https://openalex.org/W6676077707","https://openalex.org/W6696810316","https://openalex.org/W6738764001","https://openalex.org/W6783881714"],"related_works":["https://openalex.org/W2056974159","https://openalex.org/W2753583628","https://openalex.org/W2138199368","https://openalex.org/W1788036421","https://openalex.org/W4384561785","https://openalex.org/W1972553508","https://openalex.org/W2792838696","https://openalex.org/W2769609422","https://openalex.org/W2969593260","https://openalex.org/W2560320350"],"abstract_inverted_index":{"With":[0],"the":[1,58,117,140,153,172,176,215,219,222,231,240,263,269,304,324,359,368,374,389,397],"rapid":[2],"advancement":[3],"of":[4,134,151,155,165,221,234,250,283],"in-process":[5],"measurements":[6],"and":[7,41,75,88,191,206,217,242,258,299,318,362,382,404],"sensor":[8],"technology":[9],"driven":[10],"by":[11,230,238],"zero-defect":[12],"manufacturing":[13],"applications,":[14],"high-dimensional":[15,31,309],"heterogeneous":[16,98,173,310,408],"processes":[17,99],"that":[18,182,193,302,313,388],"continuously":[19],"collect":[20],"distinct":[21,315],"physical":[22,316],"characteristics":[23,317],"frequently":[24],"appear":[25],"in":[26,43,97,245,400],"modern":[27],"industries.":[28],"Such":[29],"large-volume":[30],"data":[32,38,53,63,136,174,185,198,276,285,311,337,343,349,370,409],"place":[33],"a":[34,83,123,147,162,207,296,383],"heavy":[35],"demand":[36],"on":[37,139,195,268,340,358],"collection,":[39],"transmission,":[40],"analysis":[42],"practice.":[44],"Thus,":[45],"practitioners":[46,305],"often":[47],"need":[48],"to":[49,55,91,114,130,170,213,225,287,306,331,346,351,364,372],"decide":[50],"which":[51,66,158,266,348],"informative":[52],"streams":[54,137,186,199,286,312,350,371],"observe":[56,352],"given":[57],"resource":[59,243,360],"constraints":[60,244],"at":[61,106,353],"each":[62,107,336,354],"acquisition":[64,108,355],"time,":[65],"poses":[67],"significant":[68],"challenges":[69],"for":[70,187,200,291,335],"multivariate":[71],"statistical":[72],"process":[73,236],"control":[74],"quality":[76],"improvement.":[77],"In":[78],"this":[79,293],"article,":[80],"we":[81,145],"propose":[82],"generic":[84],"online":[85,235],"nonparametric":[86,125],"monitoring":[87,149,171,237,298,376],"sampling":[89,119,300],"scheme":[90,150],"quickly":[92,160],"detect":[93,161],"mean":[94,167,189],"shifts":[95,190],"occurring":[96],"when":[100],"only":[101],"partial":[102],"observations":[103,282],"are":[104,210],"available":[105,289],"time.":[109],"Our":[110],"innovative":[111],"idea":[112],"is":[113,228,328],"seamlessly":[115],"integrate":[116],"Thompson":[118],"(TS)":[120],"algorithm":[121],"with":[122,407],"quantile-based":[124],"cumulative":[126],"sum":[127,154],"(CUSUM)":[128],"procedure":[129],"construct":[131],"local":[132],"statistics":[133],"all":[135,284],"based":[138,339,357],"partially":[141],"observed":[142],"data.":[143],"Furthermore,":[144],"develop":[146],"global":[148,375],"using":[152],"top-${r}$local":[156],"statistics,":[157],"can":[159],"wide":[163],"range":[164],"possible":[166,188],"shifts.":[168],"Tailored":[169],"streams,":[175],"proposed":[177,223,325,390],"method":[178,391],"balances":[179],"between":[180],"exploration":[181],"searches":[183],"unobserved":[184],"exploitation":[192],"focuses":[194],"highly":[196],"suspicious":[197,369],"quick":[201],"shift":[202],"detection.":[203],"Both":[204],"simulations":[205,381],"case":[208,384],"study":[209,385],"comprehensively":[211],"conducted":[212],"evaluate":[214],"performance":[216,395],"demonstrate":[218],"superiority":[220],"method.Note":[224],"Practitioners\u2014This":[226],"paper":[227,294],"motivated":[229],"critical":[232],"challenge":[233],"considering":[239],"cost-effectiveness":[241],"practice":[246],"(e.g.,":[247,272],"limited":[248,252,259],"number":[249],"sensors,":[251],"transmission":[253],"bandwidth":[254],"or":[255,278],"energy":[256],"constraint,":[257],"processing":[260],"time).":[261],"Unlike":[262],"existing":[264,398],"methodologies":[265],"rely":[267],"restrictive":[270],"assumptions":[271],"normally":[273],"distributed,":[274],"exchangeable":[275],"streams)":[277],"require":[279],"historical":[280,341],"full":[281],"be":[288],"offline":[290],"training,":[292],"proposes":[295],"novel":[297],"strategy":[301],"allows":[303],"cost-effectively":[307],"monitor":[308],"contain":[314],"follow":[319],"different":[320],"distributions.":[321],"To":[322],"implement":[323],"methodology,":[326],"it":[327],"necessary:":[329],"(i)":[330],"identify":[332],"sample":[333],"quantiles":[334],"stream":[338],"in-control":[342],"offline;":[344],"(ii)":[345],"determine":[347],"time":[356],"constraints;":[361],"(iii)":[363],"automatically":[365],"screen":[366],"out":[367],"form":[373],"statistic.":[377],"Experimental":[378],"results":[379],"through":[380],"have":[386],"shown":[387],"has":[392],"much":[393],"better":[394],"than":[396],"methods":[399],"reducing":[401],"detection":[402],"delay":[403],"effectively":[405],"dealing":[406],"streams.":[410]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}