{"id":"https://openalex.org/W7225460478","doi":"https://doi.org/10.61784/jcsee3161","title":"TEMPORAL DEEP LEARNING FOR JOB COMPETENCY DEVIATION DETECTION IN COAL CHEMICAL VOCATIONAL TRAINING","display_name":"TEMPORAL DEEP LEARNING FOR JOB COMPETENCY DEVIATION DETECTION IN COAL CHEMICAL VOCATIONAL TRAINING","publication_year":2026,"publication_date":"2026-11-07","ids":{"openalex":"https://openalex.org/W7225460478","doi":"https://doi.org/10.61784/jcsee3161"},"language":"en","primary_location":{"id":"doi:10.61784/jcsee3161","doi":"https://doi.org/10.61784/jcsee3161","is_oa":true,"landing_page_url":"https://doi.org/10.61784/jcsee3161","pdf_url":"https://upubjournals.com/jcsee/article/download/2897/248","source":{"id":"https://openalex.org/S4389158072","display_name":"Journal of Computer Science and Electrical Engineering","issn_l":"2663-1938","issn":["2663-1938","2663-1946"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Science and Electrical Engineering","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://upubjournals.com/jcsee/article/download/2897/248","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5161172161","display_name":"Kai Fang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kai Fang","raw_affiliation_strings":["School of Energy and Power Engineering, Xinjiang Vocational University of Technology, Kashgar 844004, Xinjiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Energy and Power Engineering, Xinjiang Vocational University of Technology, Kashgar 844004, Xinjiang, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5161174319","display_name":"Siga A","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siga A","raw_affiliation_strings":["College of Intelligent Manufacturing, Xinjiang Vocational University of Technology, Kashgar 844004, Xinjiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligent Manufacturing, Xinjiang Vocational University of Technology, Kashgar 844004, Xinjiang, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5161172161"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"7","first_page":"43","last_page":"51"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14508","display_name":"Vocational Education and Training","score":0.75,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/T14508","display_name":"Vocational Education and Training","score":0.75,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.09960000216960907,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.05660000070929527,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/vocational-education","display_name":"vocational education","score":0.6150000095367432},{"id":"https://openalex.org/keywords/coal-chemical-industry","display_name":"coal chemical industry","score":0.921999990940094},{"id":"https://openalex.org/keywords/temporal-deep-learning","display_name":"temporal deep learning","score":0.7739999890327454},{"id":"https://openalex.org/keywords/bilstm-attention","display_name":"BiLSTM-Attention","score":0.9179999828338623},{"id":"https://openalex.org/keywords/fault-management","display_name":"fault management","score":0.996999979019165},{"id":"https://openalex.org/keywords/attention-analysis","display_name":"attention analysis","score":0.6209999918937683}],"concepts":[{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5407000184059143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5318999886512756},{"id":"https://openalex.org/C668760","wikidata":"https://www.wikidata.org/wiki/Q6869278","display_name":"Vocational education","level":2,"score":0.46799999475479126},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.4449999928474426},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43650001287460327},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3953999876976013},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.3808000087738037},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C518851703","wikidata":"https://www.wikidata.org/wiki/Q24489","display_name":"Coal","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3379000127315521},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.3328000009059906},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C2778583658","wikidata":"https://www.wikidata.org/wiki/Q849415","display_name":"On-the-job training","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C108615695","wikidata":"https://www.wikidata.org/wiki/Q12880211","display_name":"Coal mining","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.2581999897956848},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.61784/jcsee3161","doi":"https://doi.org/10.61784/jcsee3161","is_oa":true,"landing_page_url":"https://doi.org/10.61784/jcsee3161","pdf_url":"https://upubjournals.com/jcsee/article/download/2897/248","source":{"id":"https://openalex.org/S4389158072","display_name":"Journal of Computer Science and Electrical Engineering","issn_l":"2663-1938","issn":["2663-1938","2663-1946"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Science and Electrical Engineering","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.61784/jcsee3161","doi":"https://doi.org/10.61784/jcsee3161","is_oa":true,"landing_page_url":"https://doi.org/10.61784/jcsee3161","pdf_url":"https://upubjournals.com/jcsee/article/download/2897/248","source":{"id":"https://openalex.org/S4389158072","display_name":"Journal of Computer Science and Electrical Engineering","issn_l":"2663-1938","issn":["2663-1938","2663-1946"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Science and Electrical Engineering","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225460478.pdf","grobid_xml":"https://content.openalex.org/works/W7225460478.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7204861976","https://openalex.org/W7126155643","https://openalex.org/W4393195580","https://openalex.org/W4416589345","https://openalex.org/W4415112116","https://openalex.org/W7223174551","https://openalex.org/W3201528361","https://openalex.org/W7119197758","https://openalex.org/W3155206335","https://openalex.org/W7162561892"],"abstract_inverted_index":{"Conventional":[0],"assessment":[1],"in":[2,139,149,187],"coal":[3,188],"chemical":[4,189],"vocational":[5,190],"training":[6,23,42],"relies":[7],"heavily":[8],"on":[9],"final":[10],"scores":[11],"and":[12,60,62,72,93,120,128,142,152,164],"provides":[13],"limited":[14],"information":[15],"about":[16],"how":[17],"operational":[18],"competency":[19,46,95,98,171,185],"evolves":[20],"throughout":[21],"the":[22,104,176],"process.":[24],"To":[25],"address":[26],"this":[27,29],"limitation,":[28],"study":[30],"proposes":[31],"a":[32],"temporal":[33,80,180],"deep-learning":[34],"approach":[35],"for":[36,182],"detecting":[37],"job-competency":[38],"deviations":[39,99],"from":[40],"process-level":[41,179],"data.":[43],"A":[44,82],"multidimensional":[45],"framework":[47,174],"is":[48,85],"established":[49],"to":[50,88,170],"characterize":[51],"standardized":[52,140],"operation,":[53],"process":[54,74,162],"regulation,":[55],"abnormality":[56,150],"recognition,":[57],"fault":[58,153],"handling,":[59],"safety":[61],"emergency":[63],"response.":[64],"Time-stamped":[65],"operating":[66],"events,":[67],"action":[68],"intervals,":[69],"equipment":[70],"states,":[71,96],"key":[73],"variables":[75],"are":[76,100],"organized":[77],"into":[78],"multivariate":[79],"sequences.":[81],"BiLSTM-Attention":[83],"model":[84,113],"then":[86],"developed":[87],"extract":[89],"dynamic":[90],"behavioral":[91],"representations":[92],"estimate":[94],"while":[97],"quantified":[101],"by":[102],"comparing":[103],"predicted":[105],"states":[106],"with":[107],"job-oriented":[108],"reference":[109],"levels.":[110],"The":[111,173],"proposed":[112],"outperforms":[114],"Random":[115],"Forest,":[116],"XGBoost,":[117],"LSTM,":[118],"GRU,":[119],"Transformer":[121],"baselines,":[122],"achieving":[123],"an":[124,129],"R2":[125],"of":[126,131,178],"0.879":[127],"F1-score":[130],"0.876.":[132],"Dimension-specific":[133],"analysis":[134,156],"indicates":[135],"relatively":[136],"stable":[137],"performance":[138],"operation":[141],"safety-related":[143],"tasks,":[144],"whereas":[145],"larger":[146],"gaps":[147],"occur":[148],"recognition":[151],"handling.":[154],"Attention":[155],"further":[157],"identifies":[158],"alarm":[159],"occurrence,":[160],"critical":[161],"adjustment,":[163],"fault-handling":[165],"stages":[166],"as":[167],"important":[168],"contributors":[169],"estimation.":[172],"demonstrates":[175],"potential":[177],"data":[181],"fine-grained,":[183],"data-driven":[184],"diagnosis":[186],"training.":[191]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-11-08T00:00:00"}