{"id":"https://openalex.org/W4403447414","doi":"https://doi.org/10.1109/etfa61755.2024.10710988","title":"Democratized Learning Enabling Multi-Level Digital Twin Model Integration","display_name":"Democratized Learning Enabling Multi-Level Digital Twin Model Integration","publication_year":2024,"publication_date":"2024-09-10","ids":{"openalex":"https://openalex.org/W4403447414","doi":"https://doi.org/10.1109/etfa61755.2024.10710988"},"language":"en","primary_location":{"id":"doi:10.1109/etfa61755.2024.10710988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa61755.2024.10710988","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)","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/A5057143279","display_name":"Benedetta Picano","orcid":"https://orcid.org/0000-0003-4970-1361"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Benedetta Picano","raw_affiliation_strings":["Univ. of Florence,Dept. of Information Eng.,Florence,Italy"],"affiliations":[{"raw_affiliation_string":"Univ. of Florence,Dept. of Information Eng.,Florence,Italy","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098316668","display_name":"Marco Becattini","orcid":null},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marco Becattini","raw_affiliation_strings":["Univ. of Florence,Dept. of Information Eng.,Florence,Italy"],"affiliations":[{"raw_affiliation_string":"Univ. of Florence,Dept. of Information Eng.,Florence,Italy","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023394171","display_name":"Laura Carnevali","orcid":"https://orcid.org/0000-0002-5896-4860"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Laura Carnevali","raw_affiliation_strings":["Univ. of Florence,Dept. of Information Eng.,Florence,Italy"],"affiliations":[{"raw_affiliation_string":"Univ. of Florence,Dept. of Information Eng.,Florence,Italy","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037029993","display_name":"Enrico Vicario","orcid":"https://orcid.org/0000-0002-4983-4386"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Enrico Vicario","raw_affiliation_strings":["Univ. of Florence,Dept. of Information Eng.,Florence,Italy"],"affiliations":[{"raw_affiliation_string":"Univ. of Florence,Dept. of Information Eng.,Florence,Italy","institution_ids":["https://openalex.org/I45084792"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057143279"],"corresponding_institution_ids":["https://openalex.org/I45084792"],"apc_list":null,"apc_paid":null,"fwci":0.3507,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65249029,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10763","display_name":"Digital Transformation in Industry","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10763","display_name":"Digital Transformation in Industry","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6947507858276367},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.38160455226898193},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.36497604846954346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6947507858276367},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.38160455226898193},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.36497604846954346}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/etfa61755.2024.10710988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa61755.2024.10710988","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)","raw_type":"proceedings-article"},{"id":"pmh:oai:flore.unifi.it:2158/1400238","is_oa":false,"landing_page_url":"https://hdl.handle.net/2158/1400238","pdf_url":null,"source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2518003110","https://openalex.org/W2604829132","https://openalex.org/W2783918566","https://openalex.org/W2910597635","https://openalex.org/W2989253922","https://openalex.org/W3049282540","https://openalex.org/W3058760796","https://openalex.org/W3110257784","https://openalex.org/W3123361801","https://openalex.org/W3126709645","https://openalex.org/W3129932124","https://openalex.org/W3137862937","https://openalex.org/W3160877984","https://openalex.org/W3170397984","https://openalex.org/W3172890132","https://openalex.org/W3183945916","https://openalex.org/W3188569078","https://openalex.org/W3195590230","https://openalex.org/W4205740992","https://openalex.org/W4283713103","https://openalex.org/W4285171351","https://openalex.org/W4293183138","https://openalex.org/W4385484188","https://openalex.org/W4390711494","https://openalex.org/W4393201813","https://openalex.org/W6759238902"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032"],"abstract_inverted_index":{"Effective":[0],"exploitation":[1],"of":[2,36,59,67,74,89,95,125,158,168],"Machine":[3],"Learning":[4],"solutions":[5],"in":[6,50,103],"the":[7,41,51,72,75,114,126,130,136,141,156,159],"Digital":[8,55,63],"Twin":[9,56,64],"(DT)":[10],"paradigm":[11],"may":[12],"largely":[13],"benefit":[14],"from":[15],"Federated":[16],"Analytics":[17],"(FA)":[18],"approaches,":[19],"to":[20,80,153],"mitigate":[21],"data":[22,90],"scarcity,":[23],"by":[24,92],"merging":[25],"distributed":[26,96],"data,":[27],"and":[28,34,62,98,120,129,144,171],"heterogeneity":[29],"while":[30],"limiting":[31],"communication":[32],"overhead":[33],"exchange":[35],"sensitive":[37],"raw":[38],"data.":[39],"In":[40],"DT":[42],"paradigm,":[43],"federated":[44],"schemes":[45],"find":[46],"a":[47,60,82,93,104],"native":[48],"collocation":[49],"conceptual":[52],"association":[53],"between":[54,118],"Prototype":[57],"(DTP)":[58],"class":[61],"Instance":[65],"(DTI)":[66],"individual":[68],"products.":[69],"We":[70],"propose":[71],"application":[73,102],"democratized":[76],"learning":[77],"(Dem-AI)":[78],"scheme":[79,112],"provide":[81],"scalable":[83],"solution":[84],"for":[85],"multi-level":[86],"hierarchical":[87],"integration":[88,111],"owned":[91],"multiplicity":[94],"DTs,":[97],"we":[99],"showcase":[100],"its":[101],"failure":[105,146,161],"prediction":[106,162],"scenario.":[107],"The":[108],"proposed":[109],"model":[110,128,137,169],"preserves":[113],"inherent":[115],"cohesive":[116],"relationships":[117],"generalization":[119],"specialization":[121,170],"(or":[122],"personalization)":[123],"capabilities":[124],"DTP":[127],"DTI":[131],"model,":[132],"respectively.":[133],"Based":[134],"on":[135],"acquired,":[138],"DTs":[139],"monitor":[140],"system":[142],"behavior":[143],"forecast":[145],"occurrences.":[147],"Experimental":[148],"analysis":[149],"has":[150],"been":[151],"conducted":[152],"thoroughly":[154],"investigate":[155],"performance":[157],"Dem-AI":[160],"framework":[163],"designed,":[164],"considering":[165],"different":[166],"levels":[167],"public":[172],"dataset.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
