{"id":"https://openalex.org/W4205843306","doi":"https://doi.org/10.1109/icsai53574.2021.9664213","title":"The Business Structure of a Metrology Institution Based on Linear Regression Analysis","display_name":"The Business Structure of a Metrology Institution Based on Linear Regression Analysis","publication_year":2021,"publication_date":"2021-11-13","ids":{"openalex":"https://openalex.org/W4205843306","doi":"https://doi.org/10.1109/icsai53574.2021.9664213"},"language":"en","primary_location":{"id":"doi:10.1109/icsai53574.2021.9664213","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai53574.2021.9664213","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th International Conference on Systems and Informatics (ICSAI)","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/A5025063341","display_name":"Dongshuo Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongshuo Zhao","raw_affiliation_strings":["National Institute of Metrology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing, China","institution_ids":["https://openalex.org/I4210162136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079115940","display_name":"Yudong Liu","orcid":"https://orcid.org/0000-0002-5153-3400"},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yudong Liu","raw_affiliation_strings":["National Institute of Metrology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing, China","institution_ids":["https://openalex.org/I4210162136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432832","display_name":"Xiaojing Zhang","orcid":"https://orcid.org/0000-0002-3952-4907"},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojing Zhang","raw_affiliation_strings":["National Institute of Metrology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing, China","institution_ids":["https://openalex.org/I4210162136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100430603","display_name":"Tianyi Liu","orcid":"https://orcid.org/0000-0002-3377-485X"},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyi Liu","raw_affiliation_strings":["National Institute of Metrology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing, China","institution_ids":["https://openalex.org/I4210162136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101147904","display_name":"Zhi Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Hu","raw_affiliation_strings":["National Institute of Metrology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing, China","institution_ids":["https://openalex.org/I4210162136"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013281511","display_name":"Yiran Zheng","orcid":"https://orcid.org/0000-0002-0159-1485"},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiran Zheng","raw_affiliation_strings":["National Institute of Metrology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing, China","institution_ids":["https://openalex.org/I4210162136"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5025063341"],"corresponding_institution_ids":["https://openalex.org/I4210162136"],"apc_list":null,"apc_paid":null,"fwci":0.2144,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61624063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quadrant","display_name":"Quadrant (abdomen)","score":0.5951465368270874},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5136029720306396},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5103856921195984},{"id":"https://openalex.org/keywords/metrology","display_name":"Metrology","score":0.5057954788208008},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.49005424976348877},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4717104136943817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4589338004589081},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38342124223709106},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2656953036785126},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16005820035934448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11114183068275452}],"concepts":[{"id":"https://openalex.org/C2780639617","wikidata":"https://www.wikidata.org/wiki/Q6516972","display_name":"Quadrant (abdomen)","level":2,"score":0.5951465368270874},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5136029720306396},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5103856921195984},{"id":"https://openalex.org/C195766429","wikidata":"https://www.wikidata.org/wiki/Q394","display_name":"Metrology","level":2,"score":0.5057954788208008},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.49005424976348877},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4717104136943817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4589338004589081},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38342124223709106},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2656953036785126},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16005820035934448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11114183068275452},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsai53574.2021.9664213","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai53574.2021.9664213","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th International Conference on Systems and Informatics (ICSAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1920170482","https://openalex.org/W2386302014","https://openalex.org/W2519706319","https://openalex.org/W3036595781","https://openalex.org/W3084833856","https://openalex.org/W4210557606","https://openalex.org/W6990259161"],"related_works":["https://openalex.org/W2610868774","https://openalex.org/W4399767649","https://openalex.org/W2092994918","https://openalex.org/W3216594821","https://openalex.org/W2390006526","https://openalex.org/W4363647291","https://openalex.org/W1915333409","https://openalex.org/W2393341384","https://openalex.org/W4377094298","https://openalex.org/W31220157"],"abstract_inverted_index":{"This":[0],"paper":[1],"is":[2,21,38,58],"based":[3,118],"on":[4,65,91,119],"the":[5,13,18,31,35,42,66,74,83,86,92,95,99,104,120,125],"business":[6,33,67,96,105,114],"data":[7,16,45,55,68,75],"of":[8,17,69,85,94,98,127],"a":[9],"metrology":[10],"institution.":[11],"First,":[12],"core":[14,43],"sample":[15,44],"measurement":[19,87,100],"institution":[20],"obtained":[22],"through":[23],"scattering":[24],"graph":[25],"analysis.":[26],"Then,":[27],"in":[28,107],"combination":[29],"with":[30,50],"actual":[32],"conditions,":[34],"four-quadrant":[36],"analysis":[37,56,64,76,126],"conducted":[39],"to":[40,60,80],"classify":[41],"into":[46],"four":[47],"quadrant":[48,71,109],"areas":[49],"their":[51],"characteristics.":[52],"Next,":[53],"SPSS":[54],"software":[57],"used":[59],"perform":[61],"linear":[62],"regression":[63],"each":[70,108],"area,":[72,110],"and":[73,88,124],"results":[77],"are":[78,116],"taken":[79],"further":[81],"study":[82],"impact":[84],"testing":[89],"fee":[90],"volume":[93],"units":[97],"agency.":[101],"Finally,":[102],"for":[103,113],"structure":[106],"some":[111],"suggestions":[112],"improvement":[115],"given":[117],"K-means":[121],"clustering":[122],"algorithm":[123],"customer":[128],"properties.":[129]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
