{"_buckets": {"deposit": "336d2a23-f2e9-4377-b1b9-73c90904bf6f"}, "_deposit": {"id": "6123", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "6123"}, "status": "published"}, "_oai": {"id": "oai:nied-repo.bosai.go.jp:00006123", "sets": []}, "author_link": [], "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2022-12-09", "bibliographicIssueDateType": "Issued"}, "bibliographic_titles": [{"bibliographic_title": "2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI 2022)", "bibliographic_titleLang": "ja"}, {"bibliographic_title": "2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)", "bibliographic_titleLang": "en"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "The damage caused by natural disasters and ac-cidents is increasing every year. To reduce such damage from spreading, it is important to detect an accident promptly. How ever, current sensing systems are difficult to use because they have narrow coverage and are specialized in few detectable accidents. In this paper, we propose a method to detect disasters and accidents by calculating the degree of an anomaly in human flow by treating a common human flow as a single large sensor. Human flow can be assumed to have typical patterns in people’s daily life, such as going to work and leaving work. Developing an anomaly detection method of human flow can lead to the discovery of any hidden causes such as accidents and disasters. In this paper, we study a method that aims to detect anomalies in human flow, considering the operational status of railways as an example. We confirm that our method can detect the actual suspension of operations.", "subitem_description_language": "ja", "subitem_description_type": "Other"}, {"subitem_description": "The damage caused by natural disasters and ac-cidents is increasing every year. To reduce such damage from spreading, it is important to detect an accident promptly. How ever, current sensing systems are difficult to use because they have narrow coverage and are specialized in few detectable accidents. In this paper, we propose a method to detect disasters and accidents by calculating the degree of an anomaly in human flow by treating a common human flow as a single large sensor. Human flow can be assumed to have typical patterns in people’s daily life, such as going to work and leaving work. Developing an anomaly detection method of human flow can lead to the discovery of any hidden causes such as accidents and disasters. In this paper, we study a method that aims to detect anomalies in human flow, considering the operational status of railways as an example. We confirm that our method can detect the actual suspension of operations.", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10001_publisher_8": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "IEEE", "subitem_publisher_language": "en"}]}, "item_10001_relation_14": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "10.1109/RAAI56146.2022.10092981"}}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Kim SeongIn", "creatorNameLang": "ja"}, {"creatorName": "SeongIn Kim", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "澁谷長史", "creatorNameLang": "ja"}, {"creatorName": "Takeshi Shibuya", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "取出新吾", "creatorNameLang": "ja"}, {"creatorName": "Shingo Toride", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "遠藤靖典", "creatorNameLang": "ja"}, {"creatorName": "Yasunori Endo", "creatorNameLang": "en"}]}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_title": "A Human-Flow Analysis Based on PCA: A Case Study on Population Data near Railway", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "A Human-Flow Analysis Based on PCA: A Case Study on Population Data near Railway", "subitem_title_language": "ja"}, {"subitem_title": "A Human-Flow Analysis Based on PCA: A Case Study on Population Data near Railway", "subitem_title_language": "en"}]}, "item_type_id": "40001", "owner": "1", "path": ["1670839190650"], "permalink_uri": "https://nied-repo.bosai.go.jp/records/6123", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2023-07-24"}, "publish_date": "2023-07-24", "publish_status": "0", "recid": "6123", "relation": {}, "relation_version_is_last": true, "title": ["A Human-Flow Analysis Based on PCA: A Case Study on Population Data near Railway"], "weko_shared_id": -1}