Jun Yang^*, Nannan Wang, Jiang Wang, Yashuai Luo

Energy Engineering, Vol.120, No.9, pp. 2079-2096, 2023, DOI:10.32604/ee.2023.028653

Abstract Distribution networks denote important public infrastructure necessary for people’s livelihoods. However, extreme natural disasters, such as earthquakes, typhoons, and mudslides, severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life. Therefore, considering the requirements for distribution network disaster prevention and mitigation, there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions. This paper accesses multi-source data, presents the data quality improvement methods of distribution networks, and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory. Furthermore, the paper… More >

Shahzad Nazir¹, Muhammad Asif^1,*, Shahbaz Ahmad¹, Hanan Aljuaid², Shahbaz Ahmad¹, Yazeed Ghadi³, Zubair nawaz⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4755-4769, 2022, DOI:10.32604/cmc.2022.026145

Abstract Social media provide digitally interactional technologies to facilitate information sharing and exchanging individuals. Precisely, in case of disasters, a massive corpus is placed on platforms such as Twitter. Eyewitness accounts can benefit humanitarian organizations and agencies, but identifying the eyewitness Tweets related to the disaster from millions of Tweets is difficult. Different approaches have been developed to address this kind of problem. The recent state-of-the-art system was based on a manually created dictionary and this approach was further refined by introducing linguistic rules. However, these approaches suffer from limitations as they are dataset-dependent and not scalable. In this paper, we… More >

Yun-Jung Choi^1,#, Eun-jung Ko^2,#, Eun-Joo Choi^2,*, Youn-Joo Um^2,*

International Journal of Mental Health Promotion, Vol.23, No.3, pp. 385-393, 2021, DOI:10.32604/IJMHP.2021.015018

Abstract This study aims to contribute to improving mental health services and establishing a direction for disaster survivors by verifying the effectiveness of the TLS (Training for Life Skills) app, a mental health management mobile application. Altogether, 22 disaster survivors received access to the app (with guidance) for eight weeks; we analyzed its effectiveness by examining each participant’s electroencephalography data, which were collected while they were utilizing the app. The results of this study show that the use of the TLS app had a significant positive effect on emotional quotient, basic rhythm quotient (left brain, right brain), alpha blocking rate (left… More >

He Ping^∗

Computer Systems Science and Engineering, Vol.35, No.3, pp. 191-199, 2020, DOI:10.32604/csse.2020.35.191

Abstract In this paper, the rapid assessment method of casualties in earthquake disasters is studied and a casualty assessment model based on coupling factors is established from the perspective of factors affecting casualties in earthquake disasters. Taking Guangdong area as an example, the spatialization and quantification of casualty coupling factors in earthquake disasters are analyzed in detail. A software system is developed based on ARC Engine 10.1 platform. For the same earthquake case, different algorithms (algorithm model based on coupling factor and algorithm model based on building seismic vulnerability) are used to calculate the number of casualties in order to compare… More >