{"_buckets": {"deposit": "d154bea1-d117-407f-8152-5b4c6312ab96"}, "_deposit": {"created_by": 17, "id": "2002206", "owner": "17", "owners": [17], "owners_ext": {"displayname": "図書情報係", "username": "repository"}, "pid": {"revision_id": 0, "type": "depid", "value": "2002206"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:02002206", "sets": ["322"]}, "author_link": [], "item_1615768549627": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_ab4af688f83e57aa", "subitem_version_type": "AM"}]}, "item_1629683748249": {"attribute_name": "日付", "attribute_value_mlt": [{"subitem_date_issued_datetime": "2023-11-01", "subitem_date_issued_type": "Available"}]}, "item_9_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2021-11-01", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "237", "bibliographicPageStart": "223", "bibliographicVolumeNumber": "175", "bibliographic_titles": [{"bibliographic_title": "Chemical Engineering Research and Design", "bibliographic_titleLang": "en"}]}]}, "item_9_description_4": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "Many model-based optimization methods have been proposed for chromatographic processes to ensure product quality and efficiency, but uncertainty of model parameters should be considered to assure robust design and operation. In this study, we developed a sequential Monte Carlo (SMC) parameter estimation method for chromatographic processes to estimate the parameter uncertainty rigorously within a reasonable amount of computation time. As an example, separation of glucose and fructose is considered. Through the example using artificial data, we confirmed that SMC can perform estimations more efficiently than the existing method, Markov chain Monte Carlo. Furthermore, through the example using lab-scale experimental data, we confirm that the time and effort for the sample analysis to identify the concentration of each component can be eliminated. We also examined the relationship between the number of cores and computation time for parallel implementation of SMC.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_9_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "Elsevier", "subitem_publisher_language": "en"}]}, "item_9_relation_43": {"attribute_name": "関連情報", "attribute_value_mlt": [{"subitem_relation_type": "isVersionOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1016/j.cherd.2021.09.003", "subitem_relation_type_select": "DOI"}}]}, "item_9_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/", "subitem_rights_language": "en"}]}, "item_9_source_id_7": {"attribute_name": "収録物識別子", "attribute_value_mlt": [{"subitem_source_identifier": "0263-8762", "subitem_source_identifier_type": "PISSN"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "embargoed access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_f1cf"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Yamamoto, Yota", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Yajima, Tomoyuki", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Kawajiri, Yoshiaki", "creatorNameLang": "en"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2023-11-01"}], "displaytype": "detail", "download_preview_message": "Download / Preview is available from 2023/10/31.", "file_order": 0, "filename": "manuscript_revised_diff.pdf", "filesize": [{"value": "2 MB"}], "format": "application/pdf", "future_date_message": "Download is available from 2023/10/31.", "is_thumbnail": false, "mimetype": "application/pdf", "size": 2000000.0, "url": {"objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/2002206/files/manuscript_revised_diff.pdf"}, "version_id": "6a7a4f98-54ac-4b02-9ffd-93c71f12b98c"}]}, "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": "Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method", "subitem_title_language": "en"}]}, "item_type_id": "40001", "owner": "17", "path": ["322"], "permalink_uri": "http://hdl.handle.net/2237/0002002206", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2022-03-11"}, "publish_date": "2022-03-11", "publish_status": "0", "recid": "2002206", "relation": {}, "relation_version_is_last": true, "title": ["Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method"], "weko_shared_id": -1}