WEI WANG^1,#, YANRONG PEI^2,#, SHUI-HUA WANG¹, JUAN MANUEL GORRZ³, YU-DONG ZHANG^1,*

BIOCELL, Vol.47, No.2, pp. 373-384, 2023, DOI:10.32604/biocell.2023.025905

Abstract Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rapidly worldwide, posing an unignorable threat to the global economy and human health. It is a disease caused by severe acute respiratory syndrome coronavirus 2, a single-stranded RNA virus of the genus Betacoronavirus. This virus is highly infectious and relies on its angiotensin-converting enzyme 2-receptor to enter cells. With the increase in the number of confirmed COVID-19 diagnoses, the difficulty of diagnosis due to the lack of global healthcare resources becomes increasingly apparent. Deep learning-based computer-aided diagnosis models with high generalisability can effectively alleviate this pressure. Hyperparameter tuning is essential in… More >

A. Rama Mohan Rao¹, K. Lakshmi¹, Karthik Ganesan²

Structural Durability & Health Monitoring, Vol.9, No.2, pp. 99-128, 2013, DOI:10.32604/sdhm.2013.009.099

Abstract Development of efficient system identification techniques is highly relevant for large civil infrastructure for effective health monitoring, damage detection and vibration control. This paper presents a system identification scheme in time domain to estimate stiffness and damping parameters of structures using measured acceleration. Instead of solving the system identification problem as an inverse problem, we formulate it as an optimisation problem. Particle swarm optimisation (PSO) and its other variants has been a subject of research for the past few decades for solving complex optimisation problems. In this paper, a dynamic quantum behaved particle swarm optimisation algorithm (DQPSO) is proposed for… More >