{"id":"https://openalex.org/W4321377044","doi":"https://doi.org/10.3390/s23042267","title":"Testing Thermostatic Bath End-Scale Stability for Calibration Performance with a Multiple-Sensor Ensemble Using ARIMA, Temporal Stochastics and a Quantum Walker Algorithm","display_name":"Testing Thermostatic Bath End-Scale Stability for Calibration Performance with a Multiple-Sensor Ensemble Using ARIMA, Temporal Stochastics and a Quantum Walker Algorithm","publication_year":2023,"publication_date":"2023-02-17","ids":{"openalex":"https://openalex.org/W4321377044","doi":"https://doi.org/10.3390/s23042267","pmid":"https://pubmed.ncbi.nlm.nih.gov/36850864"},"language":"en","primary_location":{"id":"doi:10.3390/s23042267","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23042267","pdf_url":"https://www.mdpi.com/1424-8220/23/4/2267/pdf?version=1676883538","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/4/2267/pdf?version=1676883538","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017581249","display_name":"George J. Besseris","orcid":"https://orcid.org/0000-0002-0183-3085"},"institutions":[{"id":"https://openalex.org/I4210094138","display_name":"University of West Attica","ror":"https://ror.org/00r2r5k05","country_code":"GR","type":"education","lineage":["https://openalex.org/I4210094138"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"George Besseris","raw_affiliation_strings":["Department of Mechanical Engineering, The University of West Attica, 12241 Egaleo, Attica, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, The University of West Attica, 12241 Egaleo, Attica, Greece","institution_ids":["https://openalex.org/I4210094138"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5017581249"],"corresponding_institution_ids":["https://openalex.org/I4210094138"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01241526,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":"4","first_page":"2267","last_page":"2267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9807999730110168,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9807999730110168,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9470000267028809,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5371001958847046},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.48468878865242004},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.48447489738464355},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.48388537764549255},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4732264280319214},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.46751099824905396},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.4465984106063843},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.41420865058898926},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.41275712847709656},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36680811643600464},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.28847044706344604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1485067903995514}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5371001958847046},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.48468878865242004},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.48447489738464355},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.48388537764549255},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4732264280319214},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.46751099824905396},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.4465984106063843},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.41420865058898926},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.41275712847709656},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36680811643600464},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.28847044706344604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1485067903995514},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23042267","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23042267","pdf_url":"https://www.mdpi.com/1424-8220/23/4/2267/pdf?version=1676883538","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:36850864","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36850864","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9963105","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9963105","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9963105/pdf/sensors-23-02267.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:dfaca3ad113b43648f64fb0a2d973f1b","is_oa":true,"landing_page_url":"https://doaj.org/article/dfaca3ad113b43648f64fb0a2d973f1b","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":"Sensors, Vol 23, Iss 4, p 2267 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/4/2267/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23042267","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23042267","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23042267","pdf_url":"https://www.mdpi.com/1424-8220/23/4/2267/pdf?version=1676883538","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4321377044.pdf"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W1507259579","https://openalex.org/W1588163064","https://openalex.org/W1971041576","https://openalex.org/W1975528636","https://openalex.org/W1975994995","https://openalex.org/W2004855787","https://openalex.org/W2020750044","https://openalex.org/W2023534516","https://openalex.org/W2025956887","https://openalex.org/W2036051023","https://openalex.org/W2045650933","https://openalex.org/W2065328651","https://openalex.org/W2077767282","https://openalex.org/W2079615115","https://openalex.org/W2084341220","https://openalex.org/W2093230975","https://openalex.org/W2112689396","https://openalex.org/W2142635246","https://openalex.org/W2150269682","https://openalex.org/W2160185408","https://openalex.org/W2168745915","https://openalex.org/W2512585223","https://openalex.org/W2616408024","https://openalex.org/W2617908299","https://openalex.org/W2788482751","https://openalex.org/W2799950705","https://openalex.org/W2898277215","https://openalex.org/W2922819464","https://openalex.org/W2922853138","https://openalex.org/W2923205743","https://openalex.org/W2925290238","https://openalex.org/W2962925676","https://openalex.org/W2968048819","https://openalex.org/W2985024764","https://openalex.org/W2993853848","https://openalex.org/W3101890301","https://openalex.org/W3120240921","https://openalex.org/W3141075380","https://openalex.org/W3158208127","https://openalex.org/W3168198506","https://openalex.org/W3171747893","https://openalex.org/W3173907290","https://openalex.org/W3183455096","https://openalex.org/W3184344653","https://openalex.org/W3191116886","https://openalex.org/W3196539257","https://openalex.org/W4200106487","https://openalex.org/W4200312742","https://openalex.org/W4210611514","https://openalex.org/W4210702638","https://openalex.org/W4211209398","https://openalex.org/W4224932083","https://openalex.org/W4225000460","https://openalex.org/W4229880569","https://openalex.org/W4232345992","https://openalex.org/W4247931724","https://openalex.org/W4251428492","https://openalex.org/W4289529061","https://openalex.org/W4292972088","https://openalex.org/W6642737583","https://openalex.org/W6644390931","https://openalex.org/W6661398024","https://openalex.org/W6675023293","https://openalex.org/W6810943224"],"related_works":["https://openalex.org/W3175321409","https://openalex.org/W4312561791","https://openalex.org/W2389894046","https://openalex.org/W2215717369","https://openalex.org/W2974356760","https://openalex.org/W4312309719","https://openalex.org/W4313123484","https://openalex.org/W2146461990","https://openalex.org/W4200142652","https://openalex.org/W1527014014"],"abstract_inverted_index":{"Thermostatic":[0],"bath":[1,59],"calibration":[2,219],"performance":[3],"is":[4,21,45],"usually":[5],"checked":[6],"for":[7,78,96,149,179,224],"uniformity":[8],"and":[9,72,81,83,99,151,200,212],"stability":[10,51],"to":[11,47,126,173,195],"serve":[12],"a":[13,57,113,163,170],"wide":[14],"range":[15],"of":[16,42,67,130,139,208,216],"industrial":[17],"applications.":[18],"Particularly":[19],"challenging":[20],"the":[22,25,30,73,128,131,135,140,146,156,181,196],"assessment":[23],"at":[24,52,62,175],"limiting":[26],"specification":[27],"ends":[28],"where":[29],"sensor":[31],"system":[32],"may":[33,188],"be":[34],"less":[35],"effective":[36],"in":[37,56,124,193,201],"achieving":[38],"consistency.":[39,226],"An":[40],"ensemble":[41],"eight":[43],"sensors":[44],"used":[46],"test":[48,127],"temperature":[49,68,141,217],"measurement":[50],"various":[53],"topological":[54],"locations":[55],"thermostatic":[58],"(antifreeze)":[60],"fluid":[61],"-20":[63],"\u00b0C.":[64],"Eight":[65],"streaks":[66],"data":[69,213],"were":[70,76,94],"collected,":[71],"resulting":[74],"time-series":[75,209],"processed":[77],"normality,":[79,211],"stationarity,":[80,210],"independence":[82,215],"identical":[84],"distribution":[85],"by":[86],"employing":[87],"regular":[88],"statistical":[89],"inference":[90],"methods.":[91],"Moreover,":[92],"they":[93],"evaluated":[95],"autoregressive":[97],"patterns":[98],"other":[100],"underlying":[101],"trends":[102],"using":[103,120],"classical":[104,197],"Auto-Regressive":[105],"Integrated":[106],"Moving":[107],"Average":[108],"(ARIMA)":[109],"modeling.":[110],"In":[111],"contrast,":[112],"continuous-time":[114],"quantum":[115,159,185],"walker":[116,160,186],"algorithm":[117,187],"was":[118,155,167],"implemented,":[119],"an":[121],"available":[122],"R-package,":[123],"order":[125],"behavior":[129],"fitted":[132],"coefficients":[133],"on":[134],"probabilistic":[136,165],"node":[137],"transitions":[138],"time":[142],"series":[143],"dataset.":[144],"Tracking":[145],"network":[147,164],"sequence":[148,214],"persistence":[150],"hierarchical":[152],"mode":[153],"strength":[154],"objective.":[157],"The":[158,184],"approach":[161],"favoring":[162],"framework":[166],"posited":[168],"as":[169],"faster":[171],"way":[172],"arrive":[174],"simultaneous":[176],"instability":[177],"quantifications":[178],"all":[180],"examined":[182],"time-series.":[183],"furnish":[189],"expedient":[190],"modal":[191],"information":[192],"comparison":[194],"ARIMA":[198],"modeling":[199],"conjunction":[202],"with":[203],"several":[204],"popular":[205],"stochastic":[206],"analyzers":[207],"end-of-scale":[218],"datasets,":[220],"which":[221],"are":[222],"investigated":[223],"temporal":[225]},"counts_by_year":[],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
