{"id":"https://openalex.org/W4387421315","doi":"https://doi.org/10.1145/3594739.3610748","title":"User-Independent Motion and Location Analysis for Sussex-Huawei Locomotion Data","display_name":"User-Independent Motion and Location Analysis for Sussex-Huawei Locomotion Data","publication_year":2023,"publication_date":"2023-10-07","ids":{"openalex":"https://openalex.org/W4387421315","doi":"https://doi.org/10.1145/3594739.3610748"},"language":"en","primary_location":{"id":"doi:10.1145/3594739.3610748","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3594739.3610748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing","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/A5032860224","display_name":"Sungjin Hwang","orcid":"https://orcid.org/0000-0003-2685-5544"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sungjin Hwang","raw_affiliation_strings":["Hanyang University, Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"Hanyang University, Korea, Republic of","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065026213","display_name":"Youngwug Cho","orcid":"https://orcid.org/0000-0003-3279-8080"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngwug Cho","raw_affiliation_strings":["Hanyang University, Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"Hanyang University, Korea, Republic of","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041607424","display_name":"Kwanguk Kim","orcid":"https://orcid.org/0000-0002-4184-2058"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kwanguk Kim","raw_affiliation_strings":["Hanyang University, Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"Hanyang University, Korea, Republic of","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032860224"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":2.2022,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.87354278,"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":"517","last_page":"522"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9879999756813049,"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/T11106","display_name":"Data Management and Algorithms","score":0.9732999801635742,"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/computer-science","display_name":"Computer science","score":0.7433265447616577},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6731830835342407},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5931797027587891},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.4984626770019531},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4411185383796692},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.40000665187835693},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38725847005844116},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3639184236526489}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7433265447616577},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6731830835342407},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5931797027587891},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.4984626770019531},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4411185383796692},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.40000665187835693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38725847005844116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3639184236526489},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3594739.3610748","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3594739.3610748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G6030619266","display_name":null,"funder_award_id":"NRF-2018R1A5A7059549 & NRF-2021M3A9E4080780","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2020642377","https://openalex.org/W2023302299","https://openalex.org/W2068849277","https://openalex.org/W2108467170","https://openalex.org/W2136317921","https://openalex.org/W2771098373","https://openalex.org/W2787641251","https://openalex.org/W2883766876","https://openalex.org/W2896375043","https://openalex.org/W2907123474","https://openalex.org/W3200144996","https://openalex.org/W3203725677","https://openalex.org/W4318953586","https://openalex.org/W4387421349"],"related_works":["https://openalex.org/W2588198209","https://openalex.org/W1909006023","https://openalex.org/W4205824991","https://openalex.org/W3200723557","https://openalex.org/W4312713546","https://openalex.org/W2961085424","https://openalex.org/W2362195430","https://openalex.org/W2347494122","https://openalex.org/W2567983276","https://openalex.org/W2145520648"],"abstract_inverted_index":{"Transportation":[0],"mode":[1],"detection":[2,80],"(TMD)":[3],"is":[4],"a":[5,39],"context-aware":[6],"computing":[7],"technology":[8],"with":[9,95],"significant":[10],"potential":[11],"in":[12,106],"several":[13],"applications.":[14,112],"However,":[15],"the":[16,45,54,67,79,86,107],"development":[17],"of":[18,44,91,109],"TMD":[19,40,62,111],"technologies":[20],"for":[21],"real-world":[22],"scenarios":[23],"remains":[24],"challenging,":[25],"including":[26],"user-independent":[27,96],"evaluations":[28],"and":[29,51,57,70],"multimodal":[30],"analyses.":[31],"In":[32],"this":[33],"study,":[34],"our":[35,101],"team":[36],"(HYU-CSE)":[37],"suggested":[38,84],"model":[41,63],"as":[42],"part":[43],"Sussex-Huawei":[46],"Locomotion":[47],"(SHL)":[48],"recognition":[49],"challenge,":[50],"we":[52],"used":[53],"SHL":[55],"motion":[56],"location":[58],"data.":[59],"The":[60,82],"proposed":[61,87],"was":[64,75],"based":[65],"on":[66],"DenseNet":[68],"architecture,":[69],"post-processing":[71],"using":[72],"voting":[73],"schemes":[74],"applied":[76],"to":[77],"refine":[78],"performance.":[81],"results":[83],"that":[85,100],"method":[88],"achieved":[89],"94.13%":[90],"an":[92],"F1":[93],"score":[94],"analysis.":[97],"We":[98],"hope":[99],"study":[102],"will":[103],"ultimately":[104],"help":[105],"design":[108],"better":[110]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}