{"id":"https://openalex.org/W3093796538","doi":"https://doi.org/10.1145/3408062","title":"Modular Neural Networks for Low-Power Image Classification on Embedded Devices","display_name":"Modular Neural Networks for Low-Power Image Classification on Embedded Devices","publication_year":2020,"publication_date":"2020-10-15","ids":{"openalex":"https://openalex.org/W3093796538","doi":"https://doi.org/10.1145/3408062","mag":"3093796538"},"language":"en","primary_location":{"id":"doi:10.1145/3408062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3408062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3408062","source":{"id":"https://openalex.org/S105046310","display_name":"ACM Transactions on Design Automation of Electronic Systems","issn_l":"1084-4309","issn":["1084-4309","1557-7309"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Design Automation of Electronic Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3408062","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091813504","display_name":"Abhinav Goel","orcid":"https://orcid.org/0000-0003-1827-1389"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhinav Goel","raw_affiliation_strings":["Purdue University"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013697286","display_name":"Sara Aghajanzadeh","orcid":"https://orcid.org/0000-0002-7879-351X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sara Aghajanzadeh","raw_affiliation_strings":["Purdue University"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019938504","display_name":"Caleb Tung","orcid":"https://orcid.org/0000-0003-0513-0528"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Caleb Tung","raw_affiliation_strings":["Purdue University"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060246506","display_name":"Shuo-Han Chen","orcid":"https://orcid.org/0000-0002-1619-4335"},"institutions":[{"id":"https://openalex.org/I118292597","display_name":"National Taipei University of Technology","ror":"https://ror.org/00cn92c09","country_code":"TW","type":"education","lineage":["https://openalex.org/I118292597"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shuo-Han Chen","raw_affiliation_strings":["National Taipei University of Technology, Taiwan, Republic of China"],"affiliations":[{"raw_affiliation_string":"National Taipei University of Technology, Taiwan, Republic of China","institution_ids":["https://openalex.org/I118292597"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074177185","display_name":"George K. Thiruvathukal","orcid":"https://orcid.org/0000-0002-0452-5571"},"institutions":[{"id":"https://openalex.org/I1925986","display_name":"Loyola University Chicago","ror":"https://ror.org/04b6x2g63","country_code":"US","type":"education","lineage":["https://openalex.org/I1925986"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George K. Thiruvathukal","raw_affiliation_strings":["Loyola University Chicago, Chicago, IL"],"affiliations":[{"raw_affiliation_string":"Loyola University Chicago, Chicago, IL","institution_ids":["https://openalex.org/I1925986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016258301","display_name":"Yung-Hsiang Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yung-Hsiang Lu","raw_affiliation_strings":["Purdue University"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5091813504"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":1.6684,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.86695293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"26","issue":"1","first_page":"1","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12676","display_name":"Machine Learning and ELM","score":0.9945999979972839,"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/computer-science","display_name":"Computer science","score":0.8812370300292969},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6246699094772339},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5540291666984558},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5455985069274902},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5099633932113647},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48729097843170166},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.48431339859962463},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4756562113761902},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4635692238807678},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.4319629967212677},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4162895083427429},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.37960273027420044},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.37399551272392273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3553680181503296},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.353037565946579},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33041656017303467},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14657160639762878},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1323067545890808}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8812370300292969},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6246699094772339},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5540291666984558},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5455985069274902},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5099633932113647},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48729097843170166},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.48431339859962463},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4756562113761902},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4635692238807678},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.4319629967212677},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4162895083427429},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.37960273027420044},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.37399551272392273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3553680181503296},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.353037565946579},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33041656017303467},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14657160639762878},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1323067545890808},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3408062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3408062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3408062","source":{"id":"https://openalex.org/S105046310","display_name":"ACM Transactions on Design Automation of Electronic Systems","issn_l":"1084-4309","issn":["1084-4309","1557-7309"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Design Automation of Electronic Systems","raw_type":"journal-article"},{"id":"pmh:oai:ecommons.luc.edu:cs_facpubs-1254","is_oa":true,"landing_page_url":"https://ecommons.luc.edu/cs_facpubs/254","pdf_url":"https://ecommons.luc.edu/cs_facpubs/254","source":{"id":"https://openalex.org/S4306402030","display_name":"Loyola eCommons (Loyola University of Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1925986","host_organization_name":"Loyola University Chicago","host_organization_lineage":["https://openalex.org/I1925986"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science: Faculty Publications and Other Works","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3408062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3408062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3408062","source":{"id":"https://openalex.org/S105046310","display_name":"ACM Transactions on Design Automation of Electronic Systems","issn_l":"1084-4309","issn":["1084-4309","1557-7309"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Design Automation of Electronic Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9100000262260437}],"awards":[{"id":"https://openalex.org/G2349040998","display_name":"CCRI: Planning: Collaborative Research: Planning to Develop a Low-Power Computer Vision Platform to Enhance Research in Computing Systems","funder_award_id":"1925713","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5778516689","display_name":"Summit of Software Infrastructure for Managing and Processing Big Multimedia Data at the Internet Scale","funder_award_id":"1747694","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7117148915","display_name":null,"funder_award_id":"OAC-1747694","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7214084939","display_name":null,"funder_award_id":"153510","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338284","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3093796538.pdf","grobid_xml":"https://content.openalex.org/works/W3093796538.grobid-xml"},"referenced_works_count":91,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1491383947","https://openalex.org/W1576445103","https://openalex.org/W1686810756","https://openalex.org/W1817561967","https://openalex.org/W1821462560","https://openalex.org/W1851597118","https://openalex.org/W1919191429","https://openalex.org/W1951304353","https://openalex.org/W1953590900","https://openalex.org/W1964794811","https://openalex.org/W1969840923","https://openalex.org/W1972482772","https://openalex.org/W1996901117","https://openalex.org/W2034076462","https://openalex.org/W2040376026","https://openalex.org/W2044195942","https://openalex.org/W2073723945","https://openalex.org/W2081580037","https://openalex.org/W2100935296","https://openalex.org/W2108598243","https://openalex.org/W2112993448","https://openalex.org/W2116339064","https://openalex.org/W2119144962","https://openalex.org/W2122111042","https://openalex.org/W2122856209","https://openalex.org/W2135508918","https://openalex.org/W2145607950","https://openalex.org/W2149706766","https://openalex.org/W2157065343","https://openalex.org/W2158535772","https://openalex.org/W2163605009","https://openalex.org/W2167215970","https://openalex.org/W2194775991","https://openalex.org/W2220384803","https://openalex.org/W2279098554","https://openalex.org/W2293824885","https://openalex.org/W2300242332","https://openalex.org/W2335728318","https://openalex.org/W2419597278","https://openalex.org/W2436453945","https://openalex.org/W2508837377","https://openalex.org/W2515385951","https://openalex.org/W2516141709","https://openalex.org/W2528206015","https://openalex.org/W2529958663","https://openalex.org/W2624507639","https://openalex.org/W2625457103","https://openalex.org/W2742044854","https://openalex.org/W2766839578","https://openalex.org/W2781821509","https://openalex.org/W2782001222","https://openalex.org/W2795444169","https://openalex.org/W2804177786","https://openalex.org/W2810361442","https://openalex.org/W2893813411","https://openalex.org/W2896900236","https://openalex.org/W2897117324","https://openalex.org/W2900075744","https://openalex.org/W2901969984","https://openalex.org/W2906374897","https://openalex.org/W2912430214","https://openalex.org/W2936781293","https://openalex.org/W2937108468","https://openalex.org/W2951433694","https://openalex.org/W2962858109","https://openalex.org/W2963163009","https://openalex.org/W2963261650","https://openalex.org/W2963446712","https://openalex.org/W2963759595","https://openalex.org/W2963903397","https://openalex.org/W2963993763","https://openalex.org/W2964137095","https://openalex.org/W2964299589","https://openalex.org/W2967826572","https://openalex.org/W2974859516","https://openalex.org/W2979439447","https://openalex.org/W3021770667","https://openalex.org/W3028425232","https://openalex.org/W3093859587","https://openalex.org/W3101516857","https://openalex.org/W3103722964","https://openalex.org/W3103818906","https://openalex.org/W3118608800","https://openalex.org/W4211007335","https://openalex.org/W4248480789","https://openalex.org/W4287777422","https://openalex.org/W6631190155","https://openalex.org/W6679349572","https://openalex.org/W6724998850","https://openalex.org/W6733793881"],"related_works":["https://openalex.org/W2378076731","https://openalex.org/W4286888643","https://openalex.org/W3210795196","https://openalex.org/W2088988140","https://openalex.org/W2803103875","https://openalex.org/W2103019253","https://openalex.org/W2951529875","https://openalex.org/W2752178021","https://openalex.org/W2783781479","https://openalex.org/W2019053833"],"abstract_inverted_index":{"Embedded":[0],"devices":[1],"are":[2,50,144],"generally":[3],"small,":[4],"battery-powered":[5],"computers":[6],"with":[7,146,211],"limited":[8],"hardware":[9],"resources.":[10],"It":[11],"is":[12,116,137,157],"difficult":[13],"to":[14,96,125,153,180,186,192,198,207],"run":[15],"deep":[16],"neural":[17],"networks":[18],"(DNNs)":[19],"on":[20,105,216],"these":[21],"devices,":[22],"because":[23],"DNNs":[24,92],"perform":[25],"millions":[26],"of":[27,33,43,68,79,102,114,176,203],"operations":[28,204],"and":[29,48,62,165,200,224],"consume":[30],"significant":[31],"amounts":[32],"energy.":[34,166],"Prior":[35],"research":[36],"has":[37],"shown":[38],"that":[39],"a":[40,44,106,112,119,147],"considerable":[41],"number":[42,202],"DNN\u2019s":[45],"memory":[46,163,182],"accesses":[47],"computation":[49,151],"redundant":[51,161],"when":[52,209],"performing":[53],"tasks":[54],"like":[55],"image":[56,171],"classification.":[57],"To":[58],"reduce":[59,64,181],"this":[60,87],"redundancy":[61],"thereby":[63],"the":[65,72,85,128,132,174,201],"energy":[66,194],"consumption":[67,195],"DNNs,":[69],"we":[70,143],"introduce":[71],"Modular":[73],"Neural":[74],"Network":[75],"Tree":[76],"architecture.":[77],"Instead":[78],"using":[80,169],"one":[81],"large":[82],"DNN":[83,213],"for":[84],"classifier,":[86],"architecture":[88],"uses":[89],"multiple":[90,140],"smaller":[91],"(called":[93],"modules":[94,141],")":[95],"progressively":[97],"classify":[98],"images":[99],"into":[100],"groups":[101,156],"categories":[103,115,130],"based":[104],"novel":[107],"visual":[108],"similarity":[109],"metric.":[110],"Once":[111],"group":[113],"selected":[117,133],"by":[118,184,190,196,205],"module,":[120],"another":[121],"module":[122],"then":[123],"continues":[124],"distinguish":[126,154],"among":[127],"similar":[129],"within":[131],"group.":[134],"This":[135],"process":[136],"repeated":[138],"over":[139],"until":[142],"left":[145],"single":[148],"category.":[149],"The":[150],"needed":[152],"dissimilar":[155],"avoided,":[158],"thus":[159],"reducing":[160],"operations,":[162],"accesses,":[164],"Experimental":[167],"results":[168],"several":[170],"datasets":[172],"reveal":[173],"effectiveness":[175],"our":[177],"proposed":[178],"solution":[179],"requirements":[183],"50%":[185],"99%,":[187],"inference":[188],"time":[189],"55%":[191],"95%,":[193],"52%":[197],"94%,":[199],"15%":[206],"99%":[208],"compared":[210],"existing":[212],"architectures,":[214],"running":[215],"two":[217],"different":[218],"embedded":[219],"systems:":[220],"Raspberry":[221,225],"Pi":[222,226],"3":[223],"Zero.":[227]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
