{"created":"2023-05-15T11:58:56.356197+00:00","id":5158,"links":{},"metadata":{"_buckets":{"deposit":"ad9eff6b-9728-4327-9436-2aaffb4f94d7"},"_deposit":{"created_by":3,"id":"5158","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"5158"},"status":"published"},"_oai":{"id":"oai:kyutech.repo.nii.ac.jp:00005158","sets":["8:24"]},"author_link":["27425","20695","20696","20697","27425","20699","20700","20701"],"control_number":"5158","item_1689815586683":{"attribute_name":"CRID","attribute_value_mlt":[{"subitem_relation_type":"isIdenticalTo","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://cir.nii.ac.jp/crid/1390282680270544000","subitem_relation_type_select":"URI"}}]},"item_21_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2016-11-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicPageEnd":"866","bibliographicPageStart":"853","bibliographicVolumeNumber":"24","bibliographic_titles":[{"bibliographic_title":"Journal of Information Processing","bibliographic_titleLang":"en"}]}]},"item_21_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In this paper, we 1) provide a real nursing data set for mobile activity recognition that can be used for supervised machine learning, 2) provide big data combined with the patient medical records and sensors attempted for 2 years, and also 3) propose a method for recognizing activities for a whole day utilizing prior knowledge about the activity segments in a day. Furthermore, we demonstrate data mining by applying our method to the bigger data with additional hospital data. In the proposed method, we 1) convert a set of segment timestamps into a prior probability of the activity segment by exploiting the concept of importance sampling, 2) obtain the likelihood of traditional recognition methods for each local time window within the segment range, and, 3) apply Bayesian estimation by marginalizing the conditional probability of estimating the activities for the segment samples. By evaluating with the dataset, the proposed method outperformed the traditional method without using the prior knowledge by 25.81% at maximum by a balanced classification rate, and outperformed by 6.5% the F-measure with accepting 1 hour of margin. Moreover, the proposed method significantly reduces duration errors of activity segments from 324.2 seconds of the traditional method to 74.6 seconds at maximum. We also demonstrate the data mining by applying our method to bigger data in a hospital.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_21_description_60":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"subitem_description":"Journal Article","subitem_description_type":"Other"}]},"item_21_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"affiliations":[{"affiliationNames":[{"lang":"ja"}]}],"familyNames":[{"familyName":"Inoue","familyNameLang":"en"},{"familyName":"井上","familyNameLang":"ja"},{"familyName":"イノウエ","familyNameLang":"ja-Kana"}],"givenNames":[{"givenName":"Sozo","givenNameLang":"en"},{"givenName":"創造","givenNameLang":"ja"},{"givenName":"ソウゾウ","givenNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"27425","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"90346825","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/nrid/1000090346825"},{"nameIdentifier":"9335840200","nameIdentifierScheme":"Scopus著者ID","nameIdentifierURI":"https://www.scopus.com/authid/detail.uri?authorId=9335840200"},{"nameIdentifier":"140","nameIdentifierScheme":"九工大研究者情報","nameIdentifierURI":"https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html"}],"names":[{"name":"Inoue, Sozo","nameLang":"en"},{"name":"井上, 創造","nameLang":"ja"},{"name":"イノウエ, ソウゾウ","nameLang":"ja-Kana"}]},{"nameIdentifiers":[{"nameIdentifier":"20699","nameIdentifierScheme":"WEKO"}],"names":[{"name":"上田,  修功","nameLang":"ja"}]},{"nameIdentifiers":[{"nameIdentifier":"20700","nameIdentifierScheme":"WEKO"}],"names":[{"name":"野原,  康伸","nameLang":"ja"}]},{"nameIdentifiers":[{"nameIdentifier":"20701","nameIdentifierScheme":"WEKO"}],"names":[{"name":"中島,  直樹","nameLang":"ja"}]}]},"item_21_link_62":{"attribute_name":"研究者情報","attribute_value_mlt":[{"subitem_link_url":"https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html"}]},"item_21_publisher_7":{"attribute_name":"出版社","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"item_21_relation_12":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isIdenticalTo","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.2197/ipsjjip.24.853","subitem_relation_type_select":"DOI"}}]},"item_21_rights_13":{"attribute_name":"著作権関連情報","attribute_value_mlt":[{"subitem_rights":"Copyright (c) 2016 by the Information Processing Society of Japan"},{"subitem_rights":"ここに掲載した著作物の利用に関する注意 本著作物の著作権は情報処理学会に帰属します。本著作物は著作権者である情報処理学会の許可のもとに掲載するものです。ご利用に当たっては「著作権法」ならびに「情報処理学会倫理綱領」に従うことをお願いいたします。 Notice for the use of this material The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the author (s) and the IPSJ. Please be complied with Copyright Law of Japan and the Code of Ethics of the IPSJ if any users wish to reproduce, make derivative work, distribute or make available to the public any part or whole thereof. All Rights Reserved, Copyright (C) Information Processing Society of Japan."}]},"item_21_select_59":{"attribute_name":"査読の有無","attribute_value_mlt":[{"subitem_select_item":"yes"}]},"item_21_source_id_8":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-6652","subitem_source_identifier_type":"EISSN"}]},"item_21_text_28":{"attribute_name":"論文ID（連携）","attribute_value_mlt":[{"subitem_text_value":"10308528"}]},"item_21_text_36":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Kyushu Institute of Technology"},{"subitem_text_value":"NTT Communication Science Laboratories"},{"subitem_text_value":"Kyushu University Hospital"},{"subitem_text_value":"Kyushu University Hospital"}]},"item_21_text_63":{"attribute_name":"連携ID","attribute_value_mlt":[{"subitem_text_value":"6316"}]},"item_21_version_type_58":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNames":[{}]}],"creatorNames":[{"creatorName":"Inoue, Sozo","creatorNameLang":"en"},{"creatorName":"井上, 創造","creatorNameLang":"ja"},{"creatorName":"イノウエ, ソウゾウ","creatorNameLang":"ja-Kana"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{},{},{}]},{"creatorNames":[{"creatorName":"Ueda, Naonori","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nohara, Yasunobu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nakashima, Naoki","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-09-06"}],"displaytype":"detail","filename":"jip_24_6_853.pdf","filesize":[{"value":"1.8 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"jip_24_6_853.pdf","url":"https://kyutech.repo.nii.ac.jp/record/5158/files/jip_24_6_853.pdf"},"version_id":"8d2ef371-9fba-43b3-adc7-1afbc0deaee3"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"mobile activity recognition","subitem_subject_scheme":"Other"},{"subitem_subject":"nursing activity","subitem_subject_scheme":"Other"},{"subitem_subject":"bigdata mining","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Recognizing and Understanding Nursing Activities for a Whole Day with a Big Dataset","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Recognizing and Understanding Nursing Activities for a Whole Day with a Big Dataset","subitem_title_language":"en"}]},"item_type_id":"21","owner":"3","path":["24"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2017-09-06"},"publish_date":"2017-09-06","publish_status":"0","recid":"5158","relation_version_is_last":true,"title":["Recognizing and Understanding Nursing Activities for a Whole Day with a Big Dataset"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2024-02-20T02:09:40.680352+00:00"}