{"id":"https://openalex.org/W2385952371","doi":"https://doi.org/10.1109/icics.2015.7459896","title":"Human activity classification in people centric sensing exploiting sparseness measurement","display_name":"Human activity classification in people centric sensing exploiting sparseness measurement","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2385952371","doi":"https://doi.org/10.1109/icics.2015.7459896","mag":"2385952371"},"language":"en","primary_location":{"id":"doi:10.1109/icics.2015.7459896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icics.2015.7459896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 10th International Conference on Information, Communications and Signal Processing (ICICS)","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/A5036022527","display_name":"Lei Liao","orcid":"https://orcid.org/0000-0003-1325-2410"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Lei Liao","raw_affiliation_strings":["A * STAR, Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"A * STAR, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103271426","display_name":"Fei Xue","orcid":"https://orcid.org/0000-0003-1135-4894"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Fei Xue","raw_affiliation_strings":["A * STAR, Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"A * STAR, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100618343","display_name":"Miao Lin","orcid":"https://orcid.org/0000-0002-5198-1780"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Miao Lin","raw_affiliation_strings":["A * STAR, Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"A * STAR, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418684","display_name":"Xiaoli Li","orcid":"https://orcid.org/0000-0002-0762-6562"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xiao-Li Li","raw_affiliation_strings":["A * STAR, Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"A * STAR, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079470760","display_name":"Shonali Krishnaswamy","orcid":"https://orcid.org/0009-0001-4601-3830"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shonali Priyadarsini Krishnaswamy","raw_affiliation_strings":["A * STAR, Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"A * STAR, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036022527"],"corresponding_institution_ids":["https://openalex.org/I115228651","https://openalex.org/I3005327000"],"apc_list":null,"apc_paid":null,"fwci":0.2872,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.60984142,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9995999932289124,"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":0.9995999932289124,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9983000159263611,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.8241182565689087},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7517515420913696},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7054529786109924},{"id":"https://openalex.org/keywords/phone","display_name":"Phone","score":0.6014977693557739},{"id":"https://openalex.org/keywords/mobile-phone","display_name":"Mobile phone","score":0.5937790274620056},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.551313042640686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.539779543876648},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5318329930305481},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5284661650657654},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45986318588256836},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4587453007698059},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4471203088760376},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.42607882618904114},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.41914474964141846},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4176664352416992},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.41469305753707886},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.411737859249115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3980734646320343},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12329712510108948},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08932629227638245}],"concepts":[{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.8241182565689087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7517515420913696},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7054529786109924},{"id":"https://openalex.org/C2778707766","wikidata":"https://www.wikidata.org/wiki/Q202064","display_name":"Phone","level":2,"score":0.6014977693557739},{"id":"https://openalex.org/C2777421447","wikidata":"https://www.wikidata.org/wiki/Q17517","display_name":"Mobile phone","level":2,"score":0.5937790274620056},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.551313042640686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.539779543876648},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5318329930305481},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5284661650657654},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45986318588256836},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4587453007698059},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4471203088760376},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.42607882618904114},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.41914474964141846},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4176664352416992},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.41469305753707886},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.411737859249115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3980734646320343},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12329712510108948},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08932629227638245},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icics.2015.7459896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icics.2015.7459896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 10th International Conference on Information, Communications and Signal Processing (ICICS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.6200000047683716}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323500","display_name":"Nemzeti Fejleszt\u00e9si Miniszt\u00e9rium","ror":"https://ror.org/01hygy214"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1570448133","https://openalex.org/W1982790367","https://openalex.org/W2017634428","https://openalex.org/W2041454412","https://openalex.org/W2048231652","https://openalex.org/W2064327970","https://openalex.org/W2074206703","https://openalex.org/W2098197972","https://openalex.org/W2106595237","https://openalex.org/W2110526334","https://openalex.org/W2117788706","https://openalex.org/W2148048965","https://openalex.org/W2149216032","https://openalex.org/W2160996690","https://openalex.org/W2168538666","https://openalex.org/W2184944785","https://openalex.org/W2185705172","https://openalex.org/W2214916291","https://openalex.org/W2544426316","https://openalex.org/W2997833137","https://openalex.org/W4233825451","https://openalex.org/W4285719527","https://openalex.org/W6610017368","https://openalex.org/W6634094483","https://openalex.org/W6654706306","https://openalex.org/W6666688880","https://openalex.org/W6676395854","https://openalex.org/W6682035786","https://openalex.org/W6683704275","https://openalex.org/W6686258256","https://openalex.org/W6686529441","https://openalex.org/W6688612899"],"related_works":["https://openalex.org/W2765080098","https://openalex.org/W2385749422","https://openalex.org/W2355290145","https://openalex.org/W2353465659","https://openalex.org/W2009888974","https://openalex.org/W2355539379","https://openalex.org/W2056341223","https://openalex.org/W4231410700","https://openalex.org/W4237770763","https://openalex.org/W2811014843"],"abstract_inverted_index":{"Existing":[0],"human":[1,92],"activity":[2,93],"recognition":[3],"models":[4],"in":[5,56,67,99,135,150],"people":[6],"centric":[7],"sensing":[8],"have":[9,107],"explored":[10],"different":[11,30,57],"features":[12,106],"of":[13,25,51,91,126,146,154],"the":[14,23,49,84,89,100,104,113,117,122,127,144,147,152],"mobile":[15,159],"phone":[16,31,139],"data":[17,27,35,54,157],"to":[18,65,74,87],"achieve":[19],"considerable":[20],"accuracy.":[21],"However,":[22],"heterogeneity":[24,153],"such":[26],"caused":[28],"by":[29,45,80],"carrying":[32,140],"modes":[33],"during":[34],"collection":[36],"process":[37],"remains":[38],"a":[39,108],"challenge.":[40],"It":[41,95],"has":[42,96],"been":[43,97],"observed":[44],"us":[46],"that":[47,103,121],"although":[48],"waveform":[50],"tri-axial":[52,155],"accelerometer":[53,156],"varies":[55],"modes,":[58,141],"its":[59],"sparseness":[60,85,105,148],"within":[61],"segmented":[62],"frames":[63],"tends":[64],"preserve":[66],"general.":[68],"In":[69,115],"this":[70],"paper,":[71],"we":[72],"propose":[73],"adopt":[75],"an":[76],"augmented":[77],"feature":[78],"set":[79],"taking":[81],"into":[82],"account":[83],"measurement":[86,124],"improve":[88],"robustness":[90],"classification.":[94],"shown":[98],"experiment":[101,118],"results":[102,119,125],"high":[109],"importance":[110],"ranking":[111],"among":[112],"list.":[114],"addition,":[116],"show":[120],"AUC":[123],"Random":[128],"Forest":[129],"model":[130],"can":[131],"be":[132],"improved":[133],"both":[134],"single":[136],"and":[137],"mixed":[138],"which":[142],"justify":[143],"effectiveness":[145],"measure":[149],"addressing":[151],"on":[158],"phones.":[160]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
