{"id":"https://openalex.org/W4200507303","doi":"https://doi.org/10.1109/iros51168.2021.9636717","title":"Multi-Scale Aggregation with Self-Attention Network for Modeling Electrical Motor Dynamics","display_name":"Multi-Scale Aggregation with Self-Attention Network for Modeling Electrical Motor Dynamics","publication_year":2021,"publication_date":"2021-09-27","ids":{"openalex":"https://openalex.org/W4200507303","doi":"https://doi.org/10.1109/iros51168.2021.9636717"},"language":"en","primary_location":{"id":"doi:10.1109/iros51168.2021.9636717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636717","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5052378221","display_name":"Kuan\u2010Chih Huang","orcid":"https://orcid.org/0000-0001-7100-8091"},"institutions":[{"id":"https://openalex.org/I3020783763","display_name":"Asus (Taiwan)","ror":"https://ror.org/00bxkz165","country_code":"TW","type":"company","lineage":["https://openalex.org/I3020783763"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Kuan-Chih Huang","raw_affiliation_strings":["ASUS Intelligent Cloud Services, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"ASUS Intelligent Cloud Services, Taipei, Taiwan","institution_ids":["https://openalex.org/I3020783763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104036695","display_name":"Hao-Hsiang Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I3020783763","display_name":"Asus (Taiwan)","ror":"https://ror.org/00bxkz165","country_code":"TW","type":"company","lineage":["https://openalex.org/I3020783763"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hao-Hsiang Yang","raw_affiliation_strings":["ASUS Intelligent Cloud Services, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"ASUS Intelligent Cloud Services, Taipei, Taiwan","institution_ids":["https://openalex.org/I3020783763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100687514","display_name":"Wei\u2010Ting Chen","orcid":"https://orcid.org/0000-0003-4922-4518"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]},{"id":"https://openalex.org/I3020783763","display_name":"Asus (Taiwan)","ror":"https://ror.org/00bxkz165","country_code":"TW","type":"company","lineage":["https://openalex.org/I3020783763"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wei-Ting Chen","raw_affiliation_strings":["ASUS Intelligent Cloud Services, Taipei, Taiwan","Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"ASUS Intelligent Cloud Services, Taipei, Taiwan","institution_ids":["https://openalex.org/I3020783763"]},{"raw_affiliation_string":"Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052378221"],"corresponding_institution_ids":["https://openalex.org/I3020783763"],"apc_list":null,"apc_paid":null,"fwci":0.3807,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60835413,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7097","last_page":"7103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.991100013256073,"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/T10320","display_name":"Neural Networks and Applications","score":0.991100013256073,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9868999719619751,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7858424186706543},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5378218293190002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4551243484020233},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4292134940624237},{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.4286341667175293},{"id":"https://openalex.org/keywords/system-dynamics","display_name":"System dynamics","score":0.4267690181732178},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.41908320784568787},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.410601407289505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7858424186706543},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5378218293190002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4551243484020233},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4292134940624237},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.4286341667175293},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.4267690181732178},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.41908320784568787},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.410601407289505},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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/iros51168.2021.9636717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636717","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W122928789","https://openalex.org/W1924770834","https://openalex.org/W1983840444","https://openalex.org/W2018815490","https://openalex.org/W2034203008","https://openalex.org/W2064675550","https://openalex.org/W2097117768","https://openalex.org/W2103594049","https://openalex.org/W2119650165","https://openalex.org/W2138146286","https://openalex.org/W2140985802","https://openalex.org/W2161444287","https://openalex.org/W2194775991","https://openalex.org/W2565906511","https://openalex.org/W2888539709","https://openalex.org/W2890779068","https://openalex.org/W2922509574","https://openalex.org/W2948892662","https://openalex.org/W2955863859","https://openalex.org/W2963091558","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2963452667","https://openalex.org/W2963958130","https://openalex.org/W2982770724","https://openalex.org/W2997504144","https://openalex.org/W3007913393","https://openalex.org/W3014522660","https://openalex.org/W3015557838","https://openalex.org/W3090004407","https://openalex.org/W3103549414","https://openalex.org/W3176718939","https://openalex.org/W3178978045","https://openalex.org/W3198781161","https://openalex.org/W3205185163","https://openalex.org/W4206382157","https://openalex.org/W4288574863","https://openalex.org/W4385245566","https://openalex.org/W6604951952","https://openalex.org/W6640212811","https://openalex.org/W6725739302","https://openalex.org/W6739901393","https://openalex.org/W6743044124","https://openalex.org/W6743731764","https://openalex.org/W6751512325","https://openalex.org/W6757193177"],"related_works":["https://openalex.org/W4211139642","https://openalex.org/W2181721856","https://openalex.org/W2381418473","https://openalex.org/W2025879371","https://openalex.org/W2032986081","https://openalex.org/W1502305485","https://openalex.org/W326831310","https://openalex.org/W826886275","https://openalex.org/W4211080513","https://openalex.org/W2227085772"],"abstract_inverted_index":{"Modeling":[0],"induction":[1],"motor":[2,57,92,101,125,139,199],"dynamics":[3,17,41,66],"is":[4,172],"a":[5,49,80,145],"crucial":[6],"problem":[7],"in":[8,166],"the":[9,16,20,30,36,55,61,65,72,109,157,164,167,177],"industry.":[10],"The":[11],"previous":[12],"works":[13],"mainly":[14],"model":[15,22,96],"based":[18],"on":[19,195],"physical":[21],"assumption":[23],"and":[24,132,175,197],"state":[25],"equation.":[26],"However,":[27],"due":[28],"to":[29,63,88,137,150,183],"complex":[31],"internal":[32],"structure":[33],"of":[34,159,179],"motors,":[35],"traditional":[37],"methods":[38],"cannot":[39],"estimate":[40,64],"precisely.":[42],"To":[43,120,162],"address":[44],"this":[45,76],"issue,":[46],"we":[47,78,143],"adopt":[48],"deep":[50],"learning-based":[51],"approach":[52],"that":[53],"takes":[54],"time-series":[56],"data":[58],"measured":[59],"from":[60,100,181],"sensor":[62],"without":[67],"making":[68],"any":[69],"assumptions":[70],"about":[71],"motor\u2019s":[73],"interior.":[74],"In":[75],"paper,":[77],"propose":[79],"multi-scale":[81,98],"feature":[82,112],"aggregation":[83,113],"with":[84,90],"self-attention":[85,133],"network":[86,171],"(MASNet)":[87],"deal":[89],"modeling":[91,160],"dynamics.":[93,161],"First,":[94],"our":[95,170],"extracts":[97],"features":[99],"signals":[102,118],"by":[103,192],"various":[104],"convolutional":[105],"kernel":[106],"sizes.":[107],"Then,":[108],"proposed":[110],"adaptive":[111],"module":[114],"fuses":[115],"different":[116],"receptive":[117],"effectively.":[119],"further":[121],"refine":[122],"these":[123],"high-level":[124],"features,":[126],"two-stream":[127],"components,":[128],"containing":[129],"Bidirectional":[130],"LSTM":[131],"module,":[134],"are":[135],"applied":[136],"improve":[138],"contextual":[140],"information.":[141],"Moreover,":[142],"present":[144],"novel":[146],"temporal":[147],"relative":[148],"loss":[149],"enhance":[151],"consecutive":[152],"signal":[153],"consistency,":[154],"which":[155],"improves":[156],"performance":[158],"deploy":[163],"service":[165],"real-world":[168,198],"scenario,":[169],"very":[173],"lightweight":[174],"reduces":[176],"number":[178],"parameters":[180],"0.62M":[182],"0.09M":[184],"(around":[185],"85%":[186],"reduction)":[187],"but":[188],"outperforms":[189],"state-of-the-art":[190],"algorithms":[191],"extensive":[193],"experiments":[194],"simulation":[196],"datasets.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}