WEKO3
アイテム
{"_buckets": {"deposit": "4df294df-8b73-4cbe-98f8-9c69734f51f3"}, "_deposit": {"created_by": 3, "id": "4734", "owners": [3], "pid": {"revision_id": 0, "type": "depid", "value": "4734"}, "status": "published"}, "_oai": {"id": "oai:kyutech.repo.nii.ac.jp:00004734", "sets": ["20"]}, "author_link": ["17289", "17293", "17290", "17294", "27425", "17295", "17291"], "item_23_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2015-09-07", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "1280", "bibliographicPageStart": "1269", "bibliographic_titles": [{"bibliographic_title": "Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing2015"}]}]}, "item_23_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "In this paper, we provide a real nursing data set for mobile activity recognition that can be used for supervised machine learning, and big data combined the patient medical records and sensors attempted for 2 years, and also 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 balanced classification rate. 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_type": "Abstract"}]}, "item_23_description_5": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015), Sep. 7-11, Grand Front Osaka in Umeda, Osaka, Japan", "subitem_description_type": "Other"}]}, "item_23_description_60": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"subitem_description": "Conference Paper", "subitem_description_type": "Other"}]}, "item_23_full_name_3": {"attribute_name": "著者別名", "attribute_value_mlt": [{"affiliations": [{"affiliationNames": [{"affiliationName": "", "lang": "ja"}], "nameIdentifiers": []}], "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": "17293", "nameIdentifierScheme": "WEKO"}], "names": [{"name": "Ueda, Naonori"}]}, {"nameIdentifiers": [{"nameIdentifier": "17294", "nameIdentifierScheme": "WEKO"}], "names": [{"name": "Nohara, Yasunobu"}]}, {"nameIdentifiers": [{"nameIdentifier": "17295", "nameIdentifierScheme": "WEKO"}], "names": [{"name": "Nakashima, Naoki"}]}]}, "item_23_link_61": {"attribute_name": "研究者情報", "attribute_value_mlt": [{"subitem_link_text": "https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html", "subitem_link_url": "https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html"}]}, "item_23_publisher_7": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "ACM Press"}]}, "item_23_relation_12": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type": "isIdenticalTo", "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1145/2750858.2807533", "subitem_relation_type_select": "DOI"}}]}, "item_23_select_59": {"attribute_name": "査読の有無", "attribute_value_mlt": [{"subitem_select_item": "yes"}]}, "item_23_text_37": {"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_23_text_62": {"attribute_name": "連携ID", "attribute_value_mlt": [{"subitem_text_value": "5618"}]}, "item_23_version_type_58": {"attribute_name": "著者版フラグ", "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": [{"affiliationNameIdentifiers": [], "affiliationNames": [{"affiliationName": "", "affiliationNameLang": "ja"}]}], "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": [{"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"}]}, {"creatorNames": [{"creatorName": "上田, 修功"}], "nameIdentifiers": [{"nameIdentifier": "17289", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "野原, 康伸"}], "nameIdentifiers": [{"nameIdentifier": "17290", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "中島, 直樹"}], "nameIdentifiers": [{"nameIdentifier": "17291", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2016-12-19"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "UbiComp2015_1269.pdf", "filesize": [{"value": "561.2 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 561200.0, "url": {"label": "UbiComp2015_1269.pdf", "url": "https://kyutech.repo.nii.ac.jp/record/4734/files/UbiComp2015_1269.pdf"}, "version_id": "5d9c5b35-29ce-46b6-9b49-d2f876b974a8"}]}, "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": "domain-specific activity recognition", "subitem_subject_scheme": "Other"}, {"subitem_subject": "dataset", "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": "conference paper", "resourceuri": "http://purl.org/coar/resource_type/c_5794"}]}, "item_title": "Mobile Activity Recognition for a Whole Day: Recognizing Real Nursing Activity with a Big Dataset", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Mobile Activity Recognition for a Whole Day: Recognizing Real Nursing Activity with a Big Dataset"}]}, "item_type_id": "23", "owner": "3", "path": ["20"], "permalink_uri": "http://hdl.handle.net/10228/5954", "pubdate": {"attribute_name": "公開日", "attribute_value": "2016-12-19"}, "publish_date": "2016-12-19", "publish_status": "0", "recid": "4734", "relation": {}, "relation_version_is_last": true, "title": ["Mobile Activity Recognition for a Whole Day: Recognizing Real Nursing Activity with a Big Dataset"], "weko_shared_id": 3}
Mobile Activity Recognition for a Whole Day: Recognizing Real Nursing Activity with a Big Dataset
http://hdl.handle.net/10228/5954
http://hdl.handle.net/10228/5954ef322ebd-d728-4f54-8c48-137b11d43393
名前 / ファイル | ライセンス | アクション |
---|---|---|
UbiComp2015_1269.pdf (561.2 kB)
|
|
Item type | 会議発表論文 = Conference Paper(1) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
公開日 | 2016-12-19 | |||||||||||
資源タイプ | ||||||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
資源タイプ | conference paper | |||||||||||
タイトル | ||||||||||||
タイトル | Mobile Activity Recognition for a Whole Day: Recognizing Real Nursing Activity with a Big Dataset | |||||||||||
言語 | ||||||||||||
言語 | eng | |||||||||||
著者 |
井上, 創造
× 井上, 創造
WEKO
27425
× 上田, 修功× 野原, 康伸× 中島, 直樹 |
|||||||||||
抄録 | ||||||||||||
内容記述タイプ | Abstract | |||||||||||
内容記述 | In this paper, we provide a real nursing data set for mobile activity recognition that can be used for supervised machine learning, and big data combined the patient medical records and sensors attempted for 2 years, and also 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 balanced classification rate. 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. | |||||||||||
備考 | ||||||||||||
内容記述タイプ | Other | |||||||||||
内容記述 | 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015), Sep. 7-11, Grand Front Osaka in Umeda, Osaka, Japan | |||||||||||
書誌情報 |
Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing2015 p. 1269-1280, 発行日 2015-09-07 |
|||||||||||
出版社 | ||||||||||||
出版社 | ACM Press | |||||||||||
DOI | ||||||||||||
関連タイプ | isIdenticalTo | |||||||||||
識別子タイプ | DOI | |||||||||||
関連識別子 | https://doi.org/10.1145/2750858.2807533 | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | Mobile activity recognition | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | nursing activity | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | domain-specific activity recognition | |||||||||||
キーワード | ||||||||||||
主題Scheme | Other | |||||||||||
主題 | dataset | |||||||||||
出版タイプ | ||||||||||||
出版タイプ | VoR | |||||||||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
査読の有無 | ||||||||||||
値 | yes | |||||||||||
研究者情報 | ||||||||||||
https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html | ||||||||||||
連携ID | ||||||||||||
5618 | ||||||||||||
著者別名 | ||||||||||||
姓名 | Inoue, Sozo | |||||||||||
言語 | en | |||||||||||
姓名 | 井上, 創造 | |||||||||||
言語 | ja | |||||||||||
姓名 | イノウエ, ソウゾウ | |||||||||||
言語 | ja-Kana | |||||||||||
著者別名 | ||||||||||||
姓名 | Ueda, Naonori | |||||||||||
著者別名 | ||||||||||||
姓名 | Nohara, Yasunobu | |||||||||||
著者別名 | ||||||||||||
姓名 | Nakashima, Naoki |