{"created":"2023-05-15T15:02:12.519761+00:00","id":84361,"links":{},"metadata":{"_buckets":{"deposit":"1fdccba3-0a45-4da4-923c-7dce57560826"},"_deposit":{"created_by":1,"id":"84361","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"84361"},"status":"published"},"_oai":{"id":"oai:repo.qst.go.jp:00084361","sets":["10:28"]},"author_link":["1018878","1018881","1018880","1018876","1018877","1018879"],"item_10005_date_7":{"attribute_name":"発表年月日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2021-12-11","subitem_date_issued_type":"Issued"}]},"item_10005_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Laser Induced Breakdown Spectroscopy (LIBS) has been considered as powerful technique that can able to monitor molten debris, which arose from the accident at Fukushima Daiichi Nuclear Power Station in 2011. Although the LIBS is a point measurement technique, it has been used as elemental surface mapping technique in many fields, because it allows user to realize fast spatial scanning without any sample preparation. However, depending on spatial resolution of measurement and investigating area, it is necessary to carry out large number of measurements. Due to the size and complexity of the dataset, analysis of such dataset is challenging and it requires considerable computational effort. Therefore, various strategies and methods have been proposed to obtain qualitative and quantitative information from the dataset. In this paper, we will focus on Multivariate Curve Resolution – Alternating Least Squares (MCR-ALS) approach to obtain elemental distribution of a simulated fuel debris sample.","subitem_description_type":"Abstract"}]},"item_10005_description_6":{"attribute_name":"会議概要（会議名, 開催地, 会期, 主催者等）","attribute_value_mlt":[{"subitem_description":"Symposium on Applications of Advanced Measurement Technologies","subitem_description_type":"Other"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Munkhbat, Batsaikhan"}],"nameIdentifiers":[{"nameIdentifier":"1018876","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Karino, Takahiro"}],"nameIdentifiers":[{"nameIdentifier":"1018877","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Shibata, Takuya"}],"nameIdentifiers":[{"nameIdentifier":"1018878","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Morihisa, Saeki"}],"nameIdentifiers":[{"nameIdentifier":"1018879","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Akaoka, Katsuaki"}],"nameIdentifiers":[{"nameIdentifier":"1018880","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Morihisa, Saeki","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"1018881","nameIdentifierScheme":"WEKO"}]}]},"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 object","resourceuri":"http://purl.org/coar/resource_type/c_c94f"}]},"item_title":"Spectral Decomposition of LIBS Dataset using Multivariate Curve Resolution Approach","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Spectral Decomposition of LIBS Dataset using Multivariate Curve Resolution Approach"}]},"item_type_id":"10005","owner":"1","path":["28"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-11-30"},"publish_date":"2021-11-30","publish_status":"0","recid":"84361","relation_version_is_last":true,"title":["Spectral Decomposition of LIBS Dataset using Multivariate Curve Resolution Approach"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-05-15T18:28:59.406762+00:00"}