A study on the relationship between flood safety awareness and vulnerability/resilience.

This study aimed to investigate the relationship between flood safety awareness and the vulnerability/resilience associated with flood damage, focusing on the characteristics of regions that have experienced floods. Specifically, this study addresses the following research questions: (1) How does flood safety awareness vary among regions with different levels of vulnerability and resilience? (2) What patterns emerge in the relationship between regional characteristics and residents' flood safety awareness? A fuzzy analysis was used by selecting structural and social indicators to analyze vulnerability and resilience. A survey was conducted for each region to assess flood safety awareness among residents.

Construction of Asbestos Slate Deep-Learning Training-Data Model Based on Drone Images.

The detection of asbestos roof slate by drone is necessary to avoid the safety risks and costs associated with visual inspection. Moreover, the use of deep-learning models increases the speed as well as reduces the cost of analyzing the images provided by the drone. In this study, we developed a comprehensive learning model using supervised and unsupervised classification techniques for the accurate classification of roof slate.