{"id":"https://openalex.org/W2774906721","doi":"https://doi.org/10.1109/ictc.2017.8191044","title":"Sensor faults detection and classification using SVM with diverse features","display_name":"Sensor faults detection and classification using SVM with diverse features","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2774906721","doi":"https://doi.org/10.1109/ictc.2017.8191044","mag":"2774906721"},"language":"en","primary_location":{"id":"doi:10.1109/ictc.2017.8191044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc.2017.8191044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Information and Communication Technology Convergence (ICTC)","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/A5048418386","display_name":"Sana Ullah Jan","orcid":"https://orcid.org/0000-0003-3950-4719"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sana Ullah Jan","raw_affiliation_strings":["School of Electrical and Computer Engineering University of Ulsan, Ulsan, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering University of Ulsan, Ulsan, South Korea","institution_ids":["https://openalex.org/I40542001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082206251","display_name":"Insoo Koo","orcid":"https://orcid.org/0000-0001-7476-8782"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"In Soo Koo","raw_affiliation_strings":["School of Electrical and Computer Engineering University of Ulsan, Ulsan, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering University of Ulsan, Ulsan, South Korea","institution_ids":["https://openalex.org/I40542001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048418386"],"corresponding_institution_ids":["https://openalex.org/I40542001"],"apc_list":null,"apc_paid":null,"fwci":0.4023,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.65033494,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"576","last_page":"578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9926999807357788,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8997201919555664},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7407848238945007},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6746933460235596},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.6389080882072449},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.579258382320404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5752338767051697},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.537054181098938},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5313929319381714},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.4817126393318176},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.45709553360939026},{"id":"https://openalex.org/keywords/matlab","display_name":"MATLAB","score":0.42250093817710876},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3764086663722992},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.2937486171722412},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17219674587249756},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09568527340888977}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8997201919555664},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7407848238945007},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6746933460235596},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.6389080882072449},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.579258382320404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5752338767051697},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.537054181098938},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5313929319381714},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.4817126393318176},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.45709553360939026},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.42250093817710876},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3764086663722992},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2937486171722412},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17219674587249756},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09568527340888977},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/ictc.2017.8191044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc.2017.8191044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository@napier.ac.uk:2937000","is_oa":false,"landing_page_url":"http://researchrepository.napier.ac.uk/Output/2937000","pdf_url":null,"source":{"id":"https://openalex.org/S4306402591","display_name":"Edinburgh Napier Research Repository (Edinburgh Napier University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I251738","host_organization_name":"Edinburgh Napier University","host_organization_lineage":["https://openalex.org/I251738"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Presentation / Conference Contribution"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2004039783","https://openalex.org/W2018066145","https://openalex.org/W2124776405","https://openalex.org/W2296077894","https://openalex.org/W2614556125"],"related_works":["https://openalex.org/W3095395190","https://openalex.org/W3123056048","https://openalex.org/W4389428786","https://openalex.org/W3100948281","https://openalex.org/W1603091392","https://openalex.org/W2408517584","https://openalex.org/W2096302783","https://openalex.org/W2095626363","https://openalex.org/W3118942106","https://openalex.org/W2165576085"],"abstract_inverted_index":{"Sensors":[0],"in":[1,50,102,117],"industrial":[2],"systems":[3],"fault":[4],"frequently":[5],"leading":[6],"to":[7,28,46,71,81],"serious":[8],"consequences":[9],"regarding":[10],"cost":[11],"and":[12,24,30,40,59,65,96,110],"safety.":[13],"The":[14,86,100],"authors":[15],"propose":[16],"support":[17],"vector":[18],"machine-based":[19],"classifier":[20],"with":[21],"diverse":[22],"time-":[23,109],"frequency-domain":[25,111],"feature":[26,112],"models":[27,113],"detect":[29],"classify":[31],"these":[32],"faults.":[33],"Three":[34],"different":[35],"kernels,":[36],"i.e.,":[37],"linear,":[38],"polynomial,":[39],"radial-basis":[41,62],"function,":[42],"are":[43,68],"employed":[44],"separately":[45],"examine":[47],"classifier's":[48],"performance":[49],"each":[51],"case.":[52],"Furthermore,":[53],"the":[54,73,83],"respective":[55],"kernel":[56,64],"scales,":[57],"\u03b4":[58],"p":[60],"of":[61,104,107],"function":[63],"polynomial":[66],"kernel,":[67],"varied":[69],"manually":[70],"obtain":[72],"optimal":[74],"values.":[75],"Leave-one-out":[76],"cross":[77],"validation":[78],"is":[79],"adopted":[80],"overcome":[82],"overfitting":[84],"problem.":[85],"dataset":[87],"was":[88],"acquired":[89],"from":[90],"a":[91],"temperature-to-voltage":[92],"converter":[93],"through":[94],"Matlab":[95],"Arduino":[97],"Uno":[98],"microcontroller.":[99],"efficiency":[101],"terms":[103],"percent":[105],"accuracy":[106],"proposed":[108],"can":[114],"be":[115],"seen":[116],"experimental":[118],"results.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}