{"id":"https://openalex.org/W4310881877","doi":"https://doi.org/10.1145/3563357.3567744","title":"Synthetic personal thermal comfort data generation","display_name":"Synthetic personal thermal comfort data generation","publication_year":2022,"publication_date":"2022-11-09","ids":{"openalex":"https://openalex.org/W4310881877","doi":"https://doi.org/10.1145/3563357.3567744"},"language":"en","primary_location":{"id":"doi:10.1145/3563357.3567744","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3563357.3567744","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3563357.3567744","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3563357.3567744","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056412412","display_name":"H. Das","orcid":"https://orcid.org/0000-0002-3335-2622"},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hari Prasanna Das","raw_affiliation_strings":["UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UC Berkeley","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013076652","display_name":"Costas J. Spanos","orcid":null},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Costas J. Spanos","raw_affiliation_strings":["UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UC Berkeley","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.041,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74113696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"280","last_page":"281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10990","display_name":"Infection Control and Ventilation","score":0.9724000096321106,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11954","display_name":"Energy Efficiency and Management","score":0.9599999785423279,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7051637768745422},{"id":"https://openalex.org/keywords/thermal-comfort","display_name":"Thermal comfort","score":0.603890061378479},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.559452474117279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5469751954078674},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5422398447990417},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5058460235595703},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4985682964324951},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.47038546204566956},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33224356174468994},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10287114977836609}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7051637768745422},{"id":"https://openalex.org/C133913538","wikidata":"https://www.wikidata.org/wiki/Q774514","display_name":"Thermal comfort","level":2,"score":0.603890061378479},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.559452474117279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5469751954078674},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5422398447990417},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5058460235595703},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4985682964324951},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.47038546204566956},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33224356174468994},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10287114977836609},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3563357.3567744","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3563357.3567744","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3563357.3567744","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3563357.3567744","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3563357.3567744","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3563357.3567744","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4310881877.pdf","grobid_xml":"https://content.openalex.org/works/W4310881877.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2962212997","https://openalex.org/W4288079310","https://openalex.org/W4380887541"],"related_works":["https://openalex.org/W4297537396","https://openalex.org/W2562892041","https://openalex.org/W1566949609","https://openalex.org/W2150081409","https://openalex.org/W2404565262","https://openalex.org/W3084415924","https://openalex.org/W3109499659","https://openalex.org/W4382315317","https://openalex.org/W2966641257","https://openalex.org/W4399530423"],"abstract_inverted_index":{"Personal":[0],"thermal":[1,9,37,50],"comfort":[2,10,38,51],"models":[3],"aim":[4],"to":[5,27,107,130],"predict":[6],"an":[7],"individual's":[8],"response,":[11],"instead":[12],"of":[13,17,46],"the":[14,43,72,82,112,120,131],"average":[15],"response":[16],"a":[18,33,47,101,125],"large":[19],"group.":[20],"Recently,":[21],"machine":[22,78],"learning":[23,60],"algorithms":[24,61],"have":[25],"proven":[26],"be":[28,139],"having":[29],"enormous":[30],"potential":[31],"as":[32,86,88,95],"candidate":[34],"for":[35,89,111,141],"personal":[36,49],"models.":[39],"But,":[40],"often":[41],"within":[42],"normal":[44],"settings":[45],"building,":[48],"data":[52,66,97,105,110,122,133],"obtained":[53],"via":[54],"experiments":[55],"is":[56,128],"heavily":[57],"class-imbalanced.":[58],"Machine":[59],"trained":[62],"on":[63],"such":[64,94],"class-imbalanced":[65,84],"perform":[67],"sub-optimally":[68],"when":[69],"deployed":[70],"in":[71],"real":[73,132],"world.":[74],"To":[75],"develop":[76],"robust":[77],"learning-based":[79],"applications":[80],"using":[81],"above":[83],"data,":[85],"well":[87],"other":[90,144],"possible":[91],"downstream":[92],"uses":[93],"privacy-preserving":[96],"sharing,":[98],"we":[99,117],"propose":[100],"state-of-the-art":[102],"conditional":[103],"synthetic":[104,109,121],"generator":[106],"generate":[108],"low-frequency":[113],"classes.":[114],"Via":[115],"experiments,":[116],"show":[118],"that":[119,127],"generated":[123],"has":[124],"distribution":[126],"close":[129],"distribution.":[134],"The":[135],"proposed":[136],"method":[137],"can":[138],"extended":[140],"use":[142,148],"by":[143],"smart":[145],"building":[146],"datasets/":[147],"cases.":[149]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}