{"_buckets": {"deposit": "4be90a97-d525-450d-bb73-ee36f274e937"}, "_deposit": {"created_by": 6, "id": "6516", "owner": "10", "owners": [6], "pid": {"revision_id": 0, "type": "depid", "value": "6516"}, "status": "published"}, "_oai": {"id": "oai:nied-repo.bosai.go.jp:00006516", "sets": ["1686623598839"]}, "author_link": ["82", "1598", "95", "1825"], "control_number": "6516", "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2023-09-29", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "88", "bibliographicPageEnd": "31", "bibliographicPageStart": "25", "bibliographic_titles": [{"bibliographic_title": "防災科学技術研究所 研究報告", "bibliographic_titleLang": "ja"}, {"bibliographic_title": "Report of the National Research Institute for Earth Science and Disaster Resilience", "bibliographic_titleLang": "en"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "噴火様式の連続リアルタイムモニタリングはハザード評価に不可欠である．火山灰粒子の構成物比は噴火様式のプロキシとして用いられてきた．しかし，火山灰構成物比のリアルタイムモニタリングはまだ実現されていない．本研究では，畳み込みニューラルネットワーク（CNN）と RGB 顕微鏡写真を用いて，2014 年から2016 年にかけて噴出された阿蘇火山の火山灰粒子を分類した．我々は，2 つの火山灰試料の粒子を5 つのカテゴリに分類し，計512 枚の画像を用いてCNN アルゴリズムに基づく学習を行った．次に，学習させたCNN を用いて，6 試料の構成物解析を行った．その結果，CNN による構成物比は，実体顕微鏡観察に基づく分類結果と調和的であり，また顕微鏡写真中の518 個の粒子を3 分以内に分類することに成功した．以上から，RGB 顕微鏡写真とCNN を用いた構成物解析は，噴火の準リアルタイムモニタリングに適用可能であると結論できる．", "subitem_description_language": "ja", "subitem_description_type": "Abstract"}, {"subitem_description": "Real-time monitoring is vital for timely hazard evaluation during ongoing volcanic eruptions. The component fractions of volcanic ash particles have been used as a proxy for eruption style. However, continuous real-time monitoring of the components in airfall ash has not yet been realized, because manual classification is time-consuming and the criteria for the classification are subjective. In this study, we used a convolutional neural network (CNN) method to classify volcanic ash particles from the 2014?2016 activity at Aso volcano, Japan, using microphotographs taken as red-green-blue (RGB) images that capture the ash surface microstructures. We trained the CNN algorithm using 512 images of five categories of ash particles which were based on color, vesicularity, glassiness, alteration and crystal fragments from two ash samples.Component analysis was then undertaken on six ash samples using the trained CNN. The component fractions obtained by the trained CNN are consistent with those from a manual classification based on observations with a stereoscopic microscope. The trained CNN successfully classified 518 particles in the microphotographs within 3 min. Thus, we conclude that component analysis by the CNN method using RGB microphotographs could be applied to quasi-real-time monitoring of an ongoing eruption.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10001_identifier_registration": {"attribute_name": "ID登録", "attribute_value_mlt": [{"subitem_identifier_reg_text": "10.24732/NIED.00006516", "subitem_identifier_reg_type": "JaLC"}]}, "item_10001_publisher_8": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "防災科学技術研究所", "subitem_publisher_language": "ja"}]}, "item_10001_source_id_9": {"attribute_name": "収録物識別子", "attribute_value_mlt": [{"subitem_source_identifier": "1347-7471", "subitem_source_identifier_type": "EISSN"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "三輪, 学央", "creatorNameLang": "ja"}, {"creatorName": "ミワ, タカヒロ", "creatorNameLang": "ja-Kana"}, {"creatorName": "MIWA, Takahiro", "creatorNameLang": "en"}], "familyNames": [{"familyName": "三輪", "familyNameLang": "ja"}, {"familyName": "ミワ", "familyNameLang": "ja-Kana"}, {"familyName": "MIWA", "familyNameLang": "en"}], "givenNames": [{"givenName": "学央", "givenNameLang": "ja"}, {"givenName": "タカヒロ", "givenNameLang": "ja-Kana"}, {"givenName": "Takahiro", "givenNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "82", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "長井, 雅史", "creatorNameLang": "ja"}, {"creatorName": "ナガイ, マサシ", "creatorNameLang": "ja-Kana"}, {"creatorName": "NAGAI, Masashi", "creatorNameLang": "en"}], "familyNames": [{"familyName": "長井", "familyNameLang": "ja"}, {"familyName": "ナガイ", "familyNameLang": "ja-Kana"}, {"familyName": "NAGAI", "familyNameLang": "en"}], "givenNames": [{"givenName": "雅史", "givenNameLang": "ja"}, {"givenName": "マサシ", "givenNameLang": "ja-Kana"}, {"givenName": "Masashi", "givenNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "1598", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "上田, 英樹", "creatorNameLang": "ja"}, {"creatorName": "ウエダ, ヒデキ", "creatorNameLang": "ja-Kana"}, {"creatorName": "UEDA, Hideki", "creatorNameLang": "en"}], "familyNames": [{"familyName": "上田", "familyNameLang": "ja"}, {"familyName": "ウエダ", "familyNameLang": "ja-Kana"}, {"familyName": "UEDA", "familyNameLang": "en"}], "givenNames": [{"givenName": "英樹", "givenNameLang": "ja"}, {"givenName": "ヒデキ", "givenNameLang": "ja-Kana"}, {"givenName": "Hideki", "givenNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "95", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "横尾, 亮彦", "creatorNameLang": "ja"}, {"creatorName": "ヨコオ, アキヒコ", "creatorNameLang": "ja-Kana"}, {"creatorName": "YOKOO, Akihiko", "creatorNameLang": "en"}], "familyNames": [{"familyName": "横尾", "familyNameLang": "ja"}, {"familyName": "ヨコオ", "familyNameLang": "ja-Kana"}, {"familyName": "YOKOO", "familyNameLang": "en"}], "givenNames": [{"givenName": "亮彦", "givenNameLang": "ja"}, {"givenName": "アキヒコ", "givenNameLang": "ja-Kana"}, {"givenName": "Akihiko", "givenNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "1825", "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": "2023-09-01"}], "displaytype": "simple", "download_preview_message": "", "file_order": 0, "filename": "88-5.pdf", "filesize": [{"value": "961 KB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "application/pdf", "size": 961000.0, "url": {"url": "https://nied-repo.bosai.go.jp/record/6516/files/88-5.pdf"}, "version_id": "18857b81-fe64-4d6e-a179-49d1edf6f450"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "Volcanic ash particle, Machine learning, Convolutional neural network, RGB microphotograph, Volcano monitoring", "subitem_subject_language": "en", "subitem_subject_scheme": "Other"}, {"subitem_subject": "火山灰粒子, 機械学習, 畳み込みニューラルネットワーク, RGB 顕微鏡画像, 火山観測", "subitem_subject_language": "ja", "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": "article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "RGB 顕微鏡画像を用いた畳み込みニューラルネットワークによる火山灰粒子の分類 －進行する火山噴火のリアルタイムモニタリングに向けて－", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "RGB 顕微鏡画像を用いた畳み込みニューラルネットワークによる火山灰粒子の分類 －進行する火山噴火のリアルタイムモニタリングに向けて－", "subitem_title_language": "ja"}, {"subitem_title": "Classification of Volcanic Ash Particles with a Convolutional Neural Network on RGB Microphotographs: Towards Real-Time Monitoring of an Ongoing Eruption", "subitem_title_language": "en"}]}, "item_type_id": "10001", "owner": "6", "path": ["1686623598839"], "permalink_uri": "https://doi.org/10.24732/NIED.00006516", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2023-09-29"}, "publish_date": "2023-09-29", "publish_status": "0", "recid": "6516", "relation": {}, "relation_version_is_last": true, "title": ["RGB 顕微鏡画像を用いた畳み込みニューラルネットワークによる火山灰粒子の分類 －進行する火山噴火のリアルタイムモニタリングに向けて－"], "weko_shared_id": -1}