{"id":"https://openalex.org/W4385366635","doi":"https://doi.org/10.3390/e25081121","title":"Nested Binary Classifier as an Outlier Detection Method in Human Activity Recognition Systems","display_name":"Nested Binary Classifier as an Outlier Detection Method in Human Activity Recognition Systems","publication_year":2023,"publication_date":"2023-07-26","ids":{"openalex":"https://openalex.org/W4385366635","doi":"https://doi.org/10.3390/e25081121","pmid":"https://pubmed.ncbi.nlm.nih.gov/37628151"},"language":"en","primary_location":{"id":"doi:10.3390/e25081121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25081121","pdf_url":"https://www.mdpi.com/1099-4300/25/8/1121/pdf?version=1690422097","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/25/8/1121/pdf?version=1690422097","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003678012","display_name":"Agnieszka Duraj","orcid":"https://orcid.org/0000-0002-3047-6662"},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Agnieszka Duraj","raw_affiliation_strings":["Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland"],"raw_orcid":"https://orcid.org/0000-0002-3047-6662","affiliations":[{"raw_affiliation_string":"Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland","institution_ids":["https://openalex.org/I188884621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5092565076","display_name":"Daniel Duczymi\u0144ski","orcid":null},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Daniel Duczymi\u0144ski","raw_affiliation_strings":["Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Technology, Lodz University of Technology, al. Politechniki 8, 93-590 \u0141\u00f3d\u017a, Poland","institution_ids":["https://openalex.org/I188884621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5003678012"],"corresponding_institution_ids":["https://openalex.org/I188884621"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":0.5231,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71783734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"25","issue":"8","first_page":"1121","last_page":"1121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/support-vector-machine","display_name":"Support vector machine","score":0.7726010084152222},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7397164702415466},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7025651335716248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6942534446716309},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5924952626228333},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5923009514808655},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5679090023040771},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5575590133666992},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47437435388565063},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4724438786506653},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42670440673828125},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42519310116767883},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.4136267900466919},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20440903306007385}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7726010084152222},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7397164702415466},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7025651335716248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6942534446716309},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5924952626228333},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5923009514808655},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5679090023040771},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5575590133666992},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47437435388565063},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4724438786506653},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42670440673828125},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42519310116767883},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.4136267900466919},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20440903306007385},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e25081121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25081121","pdf_url":"https://www.mdpi.com/1099-4300/25/8/1121/pdf?version=1690422097","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:37628151","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37628151","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10453515","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10453515","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10453515/pdf/entropy-25-01121.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:393f35cc0718434cbba8f11c50518723","is_oa":true,"landing_page_url":"https://doaj.org/article/393f35cc0718434cbba8f11c50518723","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 25, Iss 8, p 1121 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/25/8/1121/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e25081121","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 25; Issue 8; Pages: 1121","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e25081121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25081121","pdf_url":"https://www.mdpi.com/1099-4300/25/8/1121/pdf?version=1690422097","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.75,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385366635.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W1876967670","https://openalex.org/W1979370046","https://openalex.org/W1982790367","https://openalex.org/W2049058890","https://openalex.org/W2061240327","https://openalex.org/W2068207234","https://openalex.org/W2084812512","https://openalex.org/W2090805767","https://openalex.org/W2090964461","https://openalex.org/W2097006579","https://openalex.org/W2108822529","https://openalex.org/W2125348401","https://openalex.org/W2125543909","https://openalex.org/W2536193977","https://openalex.org/W2914655456","https://openalex.org/W2948975938","https://openalex.org/W2977524124","https://openalex.org/W3013363567","https://openalex.org/W3025529660","https://openalex.org/W3110489115","https://openalex.org/W3135946144","https://openalex.org/W4210793690","https://openalex.org/W4282939410","https://openalex.org/W4293192716","https://openalex.org/W4381849947","https://openalex.org/W6667579353","https://openalex.org/W6839518874"],"related_works":["https://openalex.org/W1982477181","https://openalex.org/W4285488523","https://openalex.org/W4386259002","https://openalex.org/W2407837381","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W3011239835"],"abstract_inverted_index":{"The":[0,13,42,50,117],"present":[1],"article":[2],"is":[3,34,53],"devoted":[4],"to":[5,16,24,46,102],"outlier":[6,145],"detection":[7],"in":[8,31,93],"phases":[9],"of":[10,37,68,97,106,111,133,143],"human":[11],"movement.":[12],"aim":[14],"was":[15,44,86,121],"find":[17],"the":[18,69,104,107,131],"most":[19,70],"efficient":[20],"machine":[21,72],"learning":[22,73],"method":[23,52,85,132],"detect":[25],"abnormal":[26],"segments":[27],"inside":[28],"physical":[29],"activities":[30],"which":[32],"there":[33],"a":[35,47,57],"probability":[36],"origin":[38],"from":[39],"other":[40],"activities.":[41],"problem":[43],"reduced":[45],"classification":[48],"task.":[49],"new":[51],"proposed":[54],"based":[55],"on":[56,89],"nested":[58,118,134],"binary":[59,119,135],"classifier.":[60],"Test":[61],"experiments":[62],"were":[63],"then":[64],"conducted":[65],"using":[66],"several":[67],"popular":[71],"algorithms":[74],"(linear":[75],"regression,":[76],"support":[77],"vector":[78],"machine,":[79],"k-nearest":[80],"neighbor,":[81],"decision":[82],"trees).":[83],"Each":[84],"separately":[87],"tested":[88],"three":[90],"datasets":[91],"varying":[92],"characteristics":[94],"and":[95,114],"number":[96],"records.":[98],"We":[99],"set":[100],"out":[101],"evaluate":[103],"effectiveness":[105],"models,":[108],"basic":[109],"measures":[110],"classifier":[112,120],"evaluation,":[113],"confusion":[115],"matrices.":[116],"compared":[122],"with":[123],"deep":[124],"neural":[125],"networks.":[126],"Our":[127],"research":[128],"shows":[129],"that":[130],"classifiers":[136],"can":[137],"be":[138],"considered":[139],"an":[140],"effective":[141],"way":[142],"recognizing":[144],"patterns":[146],"for":[147],"HAR":[148],"systems.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
