Titlebook: Information Technology in Disaster Risk Reduction; 6th IFIP WG 5.15 Int Jun Sasaki,Yuko Murayama,Plamena Zlateva Conference proceedings 202

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978-3-031-04172-3IFIP International Federation for Information Processing 2022

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Information Technology in Disaster Risk Reduction978-3-031-04170-9Series ISSN 1868-4238 Series E-ISSN 1868-422X

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IFIP Advances in Information and Communication Technologyhttp://image.papertrans.cn/i/image/465720.jpg

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Automatic Calculation of Damage Rate of Roofs Based on Image Segmentationroof surfaces based on image segmentation by deep learning, and the number of training data was increased. Our model calculated the rate of damage for up to 80% of roof data more accurately than the conventional assessment by a field investigator.

commonsense

Flood Disaster Mitigation System Adopting Meteorological Data and Geographic Information Systemsd on Urban Tank Model. Swiss Cheese Model, basin hydraulic control, necessity of information (software) and facilities (hardware) were adopted into the structure of the Iceberg Model. The test site of the system is planned in the basins of the Nogawa and Tama Rivers in Tama Area, Tokyo, Japan. This

Comprise

Flood Disaster Management System for Situation Awareness and Response Using Twitter Data during the half of the 2021 rainy season was experimentally used to evaluate this research and two of the areas reported to have had severe flooding in July and August 2021 based on Twitter data were also featured in an information report released by the United Nations Office for Coordination of Hu

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Analysis of Quote Retweets for COVID-19 State of Emergency Related Tweets Posted from Prefectural Gote of emergency posted from those accounts. We collected quote retweets for the top quote-retweeted tweets posted between January 1, 2020, and July 31, 2021, and classified them as either positive or negative.

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Leveraging Geospatial Technology in Disaster Managementment Information System (KSDMIS), a Geospatial Web Application for Collecting Data on Disaster Events. KSDMIS is a state-of-the-art technological disaster management technology with real-time infrastructure to collect & store data, analyse, communicate and auto-generate event-based Reports or Memora

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data are drawn from two large-scale samples of youth from the USA. Results of hierarchical regression analyses indicate that cyberbullying explained between 1 and 4?% unique variance in several outcomes (e.g., absenteeism, depression, grades in school) over and above traditional bullying. These resu