{"id":"https://openalex.org/W3047295971","doi":"https://doi.org/10.1109/access.2020.3014445","title":"Skeleton-Based Action Recognition Using Multi-Scale and Multi-Stream Improved Graph Convolutional Network","display_name":"Skeleton-Based Action Recognition Using Multi-Scale and Multi-Stream Improved Graph Convolutional Network","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3047295971","doi":"https://doi.org/10.1109/access.2020.3014445","mag":"3047295971"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3014445","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3014445","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09159664.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09159664.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100382421","display_name":"Wang Li","orcid":"https://orcid.org/0000-0002-9254-3082"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wang Li","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China","Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-9254-3082","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116294226","display_name":"Xu Liu","orcid":"https://orcid.org/0000-0002-6491-750X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Liu","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China","Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-6491-750X","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101775282","display_name":"Zheng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Liu","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China","Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-3630-9950","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022412408","display_name":"Feixiang Du","orcid":"https://orcid.org/0000-0002-2769-5418"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feixiang Du","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China","Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-2769-5418","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090084345","display_name":"Qiang Zou","orcid":"https://orcid.org/0000-0003-0668-1006"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Zou","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin, China","Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-0668-1006","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin International Joint Research Center for Internet of Things, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100382421"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.9616,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.88620256,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"144529","last_page":"144542"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9771000146865845,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8219211101531982},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7305538654327393},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7086591720581055},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6285617351531982},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6018426418304443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5941663384437561},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5760743618011475},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5477199554443359},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4989054203033447},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47873565554618835},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4702771008014679},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43928804993629456},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.17187994718551636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16222000122070312},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.13269773125648499}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8219211101531982},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7305538654327393},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7086591720581055},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6285617351531982},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6018426418304443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5941663384437561},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5760743618011475},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5477199554443359},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4989054203033447},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47873565554618835},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4702771008014679},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43928804993629456},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.17187994718551636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16222000122070312},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.13269773125648499},{"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/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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3014445","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3014445","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09159664.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d474799fe089443295f6ba76bde5560e","is_oa":true,"landing_page_url":"https://doaj.org/article/d474799fe089443295f6ba76bde5560e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 144529-144542 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3014445","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3014445","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09159664.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1662382123","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1950788856","https://openalex.org/W2048821851","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2099320314","https://openalex.org/W2101491865","https://openalex.org/W2156303437","https://openalex.org/W2172156083","https://openalex.org/W2183341477","https://openalex.org/W2313903725","https://openalex.org/W2412782625","https://openalex.org/W2510185399","https://openalex.org/W2565639579","https://openalex.org/W2593146028","https://openalex.org/W2602311553","https://openalex.org/W2603861860","https://openalex.org/W2604321021","https://openalex.org/W2607707631","https://openalex.org/W2716916105","https://openalex.org/W2736334449","https://openalex.org/W2751841288","https://openalex.org/W2752782242","https://openalex.org/W2799211965","https://openalex.org/W2884585870","https://openalex.org/W2892065377","https://openalex.org/W2914177721","https://openalex.org/W2944006115","https://openalex.org/W2948058585","https://openalex.org/W2950568498","https://openalex.org/W2955058313","https://openalex.org/W2963076818","https://openalex.org/W2963091558","https://openalex.org/W2963465695","https://openalex.org/W2964015378","https://openalex.org/W2964134613","https://openalex.org/W2964145825","https://openalex.org/W2964321699","https://openalex.org/W2964347220","https://openalex.org/W2964350391","https://openalex.org/W2996604547","https://openalex.org/W3092336341","https://openalex.org/W4385245566","https://openalex.org/W6637178625","https://openalex.org/W6638667902","https://openalex.org/W6640754710","https://openalex.org/W6674330103","https://openalex.org/W6682864246","https://openalex.org/W6694260854","https://openalex.org/W6704520437","https://openalex.org/W6713582119","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6730028046","https://openalex.org/W6736943367","https://openalex.org/W6739901393","https://openalex.org/W6743928348","https://openalex.org/W6747795875","https://openalex.org/W6754754690","https://openalex.org/W6771546625","https://openalex.org/W6784075110"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2964954556","https://openalex.org/W3034421924","https://openalex.org/W4386858688","https://openalex.org/W2982536526","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Graph":[0],"convolutional":[1,69],"networks":[2],"(GCNs)":[3],"have":[4],"achieved":[5],"outstanding":[6],"performances":[7],"on":[8,171],"skeleton-based":[9],"action":[10,117],"recognition.":[11],"However,":[12],"several":[13],"problems":[14],"remain":[15],"in":[16,103,116],"existing":[17],"GCN-based":[18],"methods,":[19],"and":[20,65,96,128,153,176,185],"the":[21,54,90,104,121,138],"spatial-temporal":[22,74,108,126],"features":[23,39,158],"are":[24,101,159],"not":[25],"discriminative":[26,37],"enough.":[27],"Temporal":[28],"convolution":[29,83],"with":[30,84],"one":[31],"fixed":[32],"kernel":[33],"cannot":[34],"obtain":[35,120],"more":[36],"temporal":[38,82,91],"for":[40,50],"different":[41],"actions.":[42],"Besides,":[43],"only":[44],"a":[45,62,143],"single-scale":[46],"feature":[47],"is":[48,113,188],"used":[49],"classification,":[51],"which":[52,166],"ignores":[53],"multilevel":[55,122],"information.":[56,123],"In":[57,72],"this":[58],"article,":[59],"we":[60,78,136],"propose":[61],"novel":[63,144],"multi-scale":[64,111,129],"multi-stream":[66],"improved":[67,81,94,125],"graph":[68],"network":[70],"(MM-IGCN).":[71],"each":[73],"block":[75,105],"of":[76,157],"MM-IGCN,":[77],"employ":[79],"an":[80,97],"multiple":[85],"parallel":[86],"kernels":[87],"to":[88,106,119,191],"enhance":[89],"features.":[92,109],"An":[93],"GCN":[95],"enhanced":[98],"attention":[99],"module":[100],"adopted":[102],"strengthen":[107],"A":[110],"structure":[112,130],"first":[114],"introduced":[115],"recognition":[118],"The":[124],"blocks":[127],"compose":[131,167],"our":[132,162,168,180,186],"single-stream":[133,163,181],"model.":[134],"Moreover,":[135],"adopt":[137],"bone":[139,154],"cosine":[140,155],"distance":[141],"as":[142],"input":[145],"feature.":[146],"Five":[147],"streams":[148],"(joint,":[149],"bone,":[150],"their":[151],"motions,":[152],"distance)":[156],"fed":[160],"into":[161],"model":[164,182],"respectively,":[165],"MM-IGCN.":[169],"Experiments":[170],"two":[172],"large":[173],"datasets,":[174],"NTU-RGB+D":[175],"NTU-RGB+D-120,":[177],"illustrate":[178],"that":[179],"achieves":[183],"state-of-the-art,":[184],"MM-IGCN":[187],"far":[189],"superior":[190],"other":[192],"models.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}