Hariharasakthisudhan Ponnarengan^1,*, Sivakumar Rajendran², Vikas Khalkar³, Gunapriya Devarajan⁴, Logesh Kamaraj⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 1-48, 2025, DOI:10.32604/cmes.2024.056605 - 17 December 2024

Abstract The purpose of this review is to explore the intersection of computational engineering and biomedical science, highlighting the transformative potential this convergence holds for innovation in healthcare and medical research. The review covers key topics such as computational modelling, bioinformatics, machine learning in medical diagnostics, and the integration of wearable technology for real-time health monitoring. Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems, while machine learning algorithms have improved the accuracy of disease prediction and diagnosis. The synergy between bioinformatics and computational techniques has led to breakthroughs in More >

Alireza Sarebanha^1,*, Andreas H. Schellenberg², Matthew J. Schoettler³, Gilberto Mosqueda⁴, Stephen A. Mahin^†

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 693-717, 2019, DOI:10.32604/cmes.2019.04846

Abstract Hybrid simulation can be a cost effective approach for dynamic testing of structural components at full scale while capturing the system level response through interactions with a numerical model. The dynamic response of a seismically isolated structure depends on the combined characteristics of the ground motion, bearings, and superstructure. Therefore, dynamic full-scale system level tests of isolated structures under realistic dynamic loading conditions are desirable towards a holistic validation of this earthquake protection strategy. Moreover, bearing properties and their ultimate behavior have been shown to be highly dependent on rate-of-loading and scale size effects, especially… More >