{"created":"2023-05-15T12:36:05.469659+00:00","id":963,"links":{},"metadata":{"_buckets":{"deposit":"cdab1a90-ffc6-40a0-ba0f-073cfff66dcb"},"_deposit":{"created_by":2,"id":"963","owners":[2],"pid":{"revision_id":0,"type":"depid","value":"963"},"status":"published"},"_oai":{"id":"oai:kutarr.kochi-tech.ac.jp:00000963","sets":["16:21"]},"author_link":["2582"],"item_5_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2009-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"5","bibliographic_titles":[{"bibliographic_title":"Society for Social Management Systems Internet Journal"}]}]},"item_5_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Recently in Japan, people concern about the uncertainty of social damage due to extreme strong-wind. There are examples such as the loss of property with collapsed houses. In order to prevent the damage from the disaster caused from extreme strong-winds, it needs to obtain the newest knowledge and empirics about the uncertainty. That is not only the hazard of extreme strong-winds that is the grade of probable damage, but also the occurrence probability of extreme strong-winds. The paper collects the past event of extreme strong-winds and the remarkable loss experienced in Japan. Using the statistics of the maximum instantaneous wind velocity at the last few decades in Japan, it estimates the occurrence probability of strong-winds exceeded more than the domestic standard level in order to resist strong-winds. It actually applies a few remarkable regions in Japan. It comments the usefulness of the model to estimate them and the managing index for the risk of extreme strong-winds.","subitem_description_type":"Abstract"}]},"item_5_publisher_36":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Society for Social Management Systems"}]},"item_5_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2432-552X","subitem_source_identifier_type":"ISSN"}]},"item_5_version_type_19":{"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":[{"creatorNames":[{"creatorName":"Yasuno, Takato"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-02-13"}],"displaytype":"detail","filename":"SMS09-135.pdf","filesize":[{"value":"1.5 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"SMS09-135.pdf","url":"https://kutarr.kochi-tech.ac.jp/record/963/files/SMS09-135.pdf"},"version_id":"01ed45fe-16dc-4f01-b962-b286336f9f11"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"monitoring tasumaki hazard","subitem_subject_scheme":"Other"},{"subitem_subject":"marginal probability indices","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":"Estimating Occurrence Probability and Loss Index to Manage the Social Risk of Strong-Winds","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Estimating Occurrence Probability and Loss Index to Manage the Social Risk of Strong-Winds"}]},"item_type_id":"5","owner":"2","path":["21"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-02-06"},"publish_date":"2018-02-06","publish_status":"0","recid":"963","relation_version_is_last":true,"title":["Estimating Occurrence Probability and Loss Index to Manage the Social Risk of Strong-Winds"],"weko_creator_id":"2","weko_shared_id":-1},"updated":"2023-05-16T01:17:22.328384+00:00"}