{"id":"https://openalex.org/W4393285830","doi":"https://doi.org/10.1109/jiot.2024.3382722","title":"A Traffic Flow Data Restoration Method Based on an Auxiliary Discrimination Mechanism-Oriented GAN Model","display_name":"A Traffic Flow Data Restoration Method Based on an Auxiliary Discrimination Mechanism-Oriented GAN Model","publication_year":2024,"publication_date":"2024-03-28","ids":{"openalex":"https://openalex.org/W4393285830","doi":"https://doi.org/10.1109/jiot.2024.3382722"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3382722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3382722","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-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/A5100428588","display_name":"Can Wang","orcid":"https://orcid.org/0000-0002-7361-0868"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Can Wang","raw_affiliation_strings":["School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-7361-0868","affiliations":[{"raw_affiliation_string":"School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","institution_ids":["https://openalex.org/I135310074","https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100727732","display_name":"Yan Zhao","orcid":"https://orcid.org/0000-0003-4577-7078"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yan Zhao","raw_affiliation_strings":["School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","institution_ids":["https://openalex.org/I135310074","https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103033142","display_name":"Linheng Li","orcid":"https://orcid.org/0000-0002-9244-739X"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Linheng Li","raw_affiliation_strings":["School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9244-739X","affiliations":[{"raw_affiliation_string":"School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","institution_ids":["https://openalex.org/I135310074","https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101699237","display_name":"Qiao Yang","orcid":"https://orcid.org/0000-0002-4098-3246"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao Yang","raw_affiliation_strings":["College of Civil and Transportation Engineering, Hohai University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Civil and Transportation Engineering, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033108732","display_name":"Xu Qu","orcid":"https://orcid.org/0000-0003-3256-8920"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Xu Qu","raw_affiliation_strings":["School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","institution_ids":["https://openalex.org/I135310074","https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060394098","display_name":"Bin Ran","orcid":"https://orcid.org/0000-0002-5464-0930"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Bin Ran","raw_affiliation_strings":["School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, the Institute on Internet of Mobility, Southeast University and University of Wisconsin–Madison, and the Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Nanjing, China","institution_ids":["https://openalex.org/I135310074","https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.137,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.85431094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":"12","first_page":"22742","last_page":"22753"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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":0.9818999767303467,"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":0.8109999895095825},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6223945617675781},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.6154451966285706},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5839646458625793},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.5409947037696838},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5380899310112},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5265491604804993},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4797464609146118},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4556063711643219},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.44584691524505615},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42479807138442993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36027562618255615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34716159105300903},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.27247369289398193},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.23701736330986023},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12082362174987793},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.12059754133224487},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11152723431587219}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8109999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6223945617675781},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.6154451966285706},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5839646458625793},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5409947037696838},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5380899310112},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5265491604804993},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4797464609146118},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4556063711643219},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.44584691524505615},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42479807138442993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36027562618255615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34716159105300903},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.27247369289398193},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.23701736330986023},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12082362174987793},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.12059754133224487},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11152723431587219},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3382722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3382722","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2055296752","display_name":null,"funder_award_id":"52202408","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1798398164","https://openalex.org/W1814521481","https://openalex.org/W2019005260","https://openalex.org/W2361510525","https://openalex.org/W2529827714","https://openalex.org/W2790496887","https://openalex.org/W2902048196","https://openalex.org/W2908547014","https://openalex.org/W2952267276","https://openalex.org/W3014706756","https://openalex.org/W3040311536","https://openalex.org/W3091320486","https://openalex.org/W3096295890","https://openalex.org/W4220721304","https://openalex.org/W4221034033","https://openalex.org/W4229069577","https://openalex.org/W4286587316","https://openalex.org/W4293235286","https://openalex.org/W4294690802","https://openalex.org/W4386826768","https://openalex.org/W4387957806","https://openalex.org/W6785482868"],"related_works":["https://openalex.org/W2149721642","https://openalex.org/W2587362999","https://openalex.org/W432084041","https://openalex.org/W2394010358","https://openalex.org/W2361078351","https://openalex.org/W2986732134","https://openalex.org/W4239349137","https://openalex.org/W1463884142","https://openalex.org/W2963251637","https://openalex.org/W239469043"],"abstract_inverted_index":{"High-quality":[0],"traffic":[1,10,19,29,119,158,196],"flow":[2,20,120,159],"data":[3,48,56,103,121,143,160,178,183,197],"is":[4],"foundational":[5],"to":[6,62],"the":[7,26,72,89,116,126,131,137,141,146,162],"study":[8],"of":[9,18,28,74,93,118,125,149],"issues":[11],"and":[12,40,70,77,98,128,130,140,191],"practical":[13],"engineering":[14],"applications.":[15],"The":[16,123,168],"development":[17],"detection":[21],"methods":[22,176],"has":[23],"greatly":[24],"facilitated":[25],"collection":[27],"data;":[30],"however,":[31],"anomalies":[32],"caused":[33],"by":[34],"factors":[35],"such":[36],"as":[37,57],"equipment,":[38],"networks,":[39],"environmental":[41],"conditions":[42],"present":[43],"a":[44],"common":[45],"challenge.":[46],"Traditional":[47],"restoration":[49,179],"methods,":[50],"which":[51],"require":[52],"extensive":[53],"complete":[54],"historical":[55],"prior":[58],"knowledge,":[59],"are":[60],"difficult":[61],"implement.":[63],"In":[64],"this":[65],"study,":[66],"we":[67,105],"first":[68],"analyze":[69],"categorize":[71],"causes":[73],"anomalous":[75],"data,":[76],"introduce":[78],"strategies":[79],"for":[80,115,194],"anomaly":[81],"identification":[82],"in":[83,102,177],"multi-source":[84],"freeway":[85,164,195],"data.":[86,151],"Based":[87],"on":[88],"unsupervised":[90],"learning":[91],"framework":[92],"Generative":[94,111],"Adversarial":[95,112],"Network":[96,113],"(GAN),":[97],"leveraging":[99],"their":[100],"advantages":[101],"generation,":[104],"propose":[106],"an":[107,189],"Auxiliary":[108],"Discrimination":[109],"Mechanism-based":[110],"(ADM-GAN)":[114],"task":[117],"restoration.":[122,198],"optimization":[124],"generator":[127],"discriminator":[129],"auxiliary":[132],"discrimination":[133],"matrix,":[134],"constructed":[135],"from":[136,161],"generator\u2019s":[138],"output":[139],"original":[142,150],"features,":[144],"enhances":[145],"model\u2019s":[147],"utilization":[148],"We":[152],"tested":[153],"our":[154],"model":[155],"using":[156],"ETC":[157],"G50":[163],"near":[165],"Suzhou,":[166],"China.":[167],"results":[169],"demonstrate":[170],"that":[171],"ADM-GAN":[172],"outperforms":[173],"other":[174],"state-of-the-art":[175],"tasks":[180],"across":[181],"various":[182],"missing":[184],"rates.":[185],"This":[186],"research":[187],"offers":[188],"efficient":[190],"reliable":[192],"method":[193]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}