{"id":"https://openalex.org/W4389041230","doi":"https://doi.org/10.1109/csit61576.2023.10324235","title":"Trap Detection in Brownian Particle Trajectories Using Machine Learning Clustering Methods","display_name":"Trap Detection in Brownian Particle Trajectories Using Machine Learning Clustering Methods","publication_year":2023,"publication_date":"2023-10-19","ids":{"openalex":"https://openalex.org/W4389041230","doi":"https://doi.org/10.1109/csit61576.2023.10324235"},"language":"en","primary_location":{"id":"doi:10.1109/csit61576.2023.10324235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csit61576.2023.10324235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 18th International Conference on Computer Science and Information Technologies (CSIT)","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/A5082804247","display_name":"Lyudmyla Kirichenko","orcid":"https://orcid.org/0000-0002-2780-7993"},"institutions":[{"id":"https://openalex.org/I107158390","display_name":"Kharkiv National University of Radio Electronics","ror":"https://ror.org/01ctj1b90","country_code":"UA","type":"education","lineage":["https://openalex.org/I107158390"]}],"countries":["UA"],"is_corresponding":true,"raw_author_name":"Lyudmyla Kirichenko","raw_affiliation_strings":["Kharkiv National University of Radioelectronics,Applied Mathematics Department,Kharkiv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Kharkiv National University of Radioelectronics,Applied Mathematics Department,Kharkiv,Ukraine","institution_ids":["https://openalex.org/I107158390"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061239218","display_name":"Daryna Khatsko","orcid":null},"institutions":[{"id":"https://openalex.org/I107158390","display_name":"Kharkiv National University of Radio Electronics","ror":"https://ror.org/01ctj1b90","country_code":"UA","type":"education","lineage":["https://openalex.org/I107158390"]}],"countries":["UA"],"is_corresponding":false,"raw_author_name":"Daryna Khatsko","raw_affiliation_strings":["Kharkiv National University of Radioelectronics,Applied Mathematics Department,Kharkiv,Ukraine"],"affiliations":[{"raw_affiliation_string":"Kharkiv National University of Radioelectronics,Applied Mathematics Department,Kharkiv,Ukraine","institution_ids":["https://openalex.org/I107158390"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013612820","display_name":"Oksana Pichugina","orcid":"https://orcid.org/0000-0002-7099-8967"},"institutions":[{"id":"https://openalex.org/I23686167","display_name":"National Aerospace University \u2013 Kharkiv Aviation Institute","ror":"https://ror.org/048j5n646","country_code":"UA","type":"education","lineage":["https://openalex.org/I23686167"]}],"countries":["UA"],"is_corresponding":false,"raw_author_name":"Oksana Pichugina","raw_affiliation_strings":["National Aerospace University,“Kharkiv Aviation Institute “,Kharkiv,Ukraine"],"affiliations":[{"raw_affiliation_string":"National Aerospace University,“Kharkiv Aviation Institute “,Kharkiv,Ukraine","institution_ids":["https://openalex.org/I23686167"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082804247"],"corresponding_institution_ids":["https://openalex.org/I107158390"],"apc_list":null,"apc_paid":null,"fwci":0.4066,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59560618,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.8342831134796143},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.743525505065918},{"id":"https://openalex.org/keywords/brownian-motion","display_name":"Brownian motion","score":0.6265341639518738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5301369428634644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49925851821899414},{"id":"https://openalex.org/keywords/trap","display_name":"Trap (plumbing)","score":0.49463197588920593},{"id":"https://openalex.org/keywords/particle","display_name":"Particle (ecology)","score":0.4518316984176636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38062024116516113},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.33447927236557007},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.23508232831954956},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2318728268146515},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.18808531761169434},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.18354174494743347},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15742254257202148}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8342831134796143},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.743525505065918},{"id":"https://openalex.org/C112401455","wikidata":"https://www.wikidata.org/wiki/Q178036","display_name":"Brownian motion","level":2,"score":0.6265341639518738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5301369428634644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49925851821899414},{"id":"https://openalex.org/C121099081","wikidata":"https://www.wikidata.org/wiki/Q665580","display_name":"Trap (plumbing)","level":2,"score":0.49463197588920593},{"id":"https://openalex.org/C2778517922","wikidata":"https://www.wikidata.org/wiki/Q7140482","display_name":"Particle (ecology)","level":2,"score":0.4518316984176636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38062024116516113},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.33447927236557007},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23508232831954956},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2318728268146515},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.18808531761169434},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.18354174494743347},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15742254257202148},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/csit61576.2023.10324235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csit61576.2023.10324235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 18th International Conference on Computer Science and Information Technologies (CSIT)","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":26,"referenced_works":["https://openalex.org/W139306811","https://openalex.org/W151377110","https://openalex.org/W1894414046","https://openalex.org/W1973713182","https://openalex.org/W2009693444","https://openalex.org/W2128281473","https://openalex.org/W2133231029","https://openalex.org/W2312387783","https://openalex.org/W2346473394","https://openalex.org/W2511729348","https://openalex.org/W2610815847","https://openalex.org/W2619824656","https://openalex.org/W2725992404","https://openalex.org/W2767758023","https://openalex.org/W2789625356","https://openalex.org/W2992734792","https://openalex.org/W3103050776","https://openalex.org/W3105176712","https://openalex.org/W3106308358","https://openalex.org/W3144750446","https://openalex.org/W3195558912","https://openalex.org/W3217746002","https://openalex.org/W4246905246","https://openalex.org/W4292752971","https://openalex.org/W4304814296","https://openalex.org/W4382776170"],"related_works":["https://openalex.org/W3163639875","https://openalex.org/W3176449234","https://openalex.org/W2767235736","https://openalex.org/W2353158678","https://openalex.org/W4225278791","https://openalex.org/W2045002201","https://openalex.org/W2971352445","https://openalex.org/W4322502698","https://openalex.org/W2604015980","https://openalex.org/W2042747968"],"abstract_inverted_index":{"The":[0,19,54,99],"article":[1],"is":[2,25],"focused":[3],"on":[4,104],"the":[5,22,80,84],"detection":[6],"of":[7,21,56,66,93,101],"traps":[8],"that":[9,83],"capture":[10],"a":[11,28],"Brownian":[12,23,29],"particle":[13,24],"using":[14,27],"machine":[15],"learning":[16],"clustering":[17,47,105],"methods.":[18],"trajectory":[20],"simulated":[26],"motion":[30],"model":[31,102],"with":[32],"drift,":[33],"encompassing":[34],"both":[35],"free":[36],"diffusion":[37],"and":[38,50],"trap-bound":[39],"motion.":[40],"For":[41],"temporal":[42],"data":[43],"clustering,":[44],"two":[45],"density-based":[46],"methods,":[48],"DBSCAN":[49,85],"HDBSCAN,":[51,88],"are":[52],"employed.":[53],"versatility":[55],"these":[57],"methods":[58],"allows":[59],"for":[60,74],"cluster":[61],"identification":[62],"without":[63],"prior":[64],"knowledge":[65],"their":[67],"quantity":[68],"or":[69],"shape,":[70],"making":[71],"them":[72],"suitable":[73],"trap":[75],"detection.":[76],"Through":[77],"extensive":[78],"experimentation,":[79],"study":[81],"reveals":[82],"method":[86],"outperforms":[87],"achieving":[89],"an":[90],"average":[91],"accuracy":[92,106],"94.0%":[94],"compared":[95],"to":[96],"HDBSCAN\u2019s":[97],"85.7%.":[98],"effect":[100],"parameters":[103],"was":[107],"also":[108],"investigated.":[109]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}