Yawar Abbas¹, Aisha Ahmed Alarfaj², Ebtisam Abdullah Alabdulqader³, Asaad Algarni⁴, Ahmad Jalal^1,5, Hui Liu^6,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4759-4776, 2025, DOI:10.32604/cmc.2025.059224 - 06 March 2025

Abstract Human Activity Recognition (HAR) in drone-captured videos has become popular because of the interest in various fields such as video surveillance, sports analysis, and human-robot interaction. However, recognizing actions from such videos poses the following challenges: variations of human motion, the complexity of backdrops, motion blurs, occlusions, and restricted camera angles. This research presents a human activity recognition system to address these challenges by working with drones’ red-green-blue (RGB) videos. The first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while… More >

J. Wang^1,2, P. Simacek^1,2, S.G. Advani^1,2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.1, pp. 59-79, 2015, DOI:10.3970/cmes.2015.107.059

Abstract In Liquid Composite Molding (LCM) processes, resin is introduced into a stationary fiber reinforcement placed in the mold, until the reinforcement gets fully saturated with resin and all volatiles are vented out of the part. Finite element based software packages have been developed to simulate the mold filling process and eliminate expensive and tedious trial and error practices to arrive at a successful mold filling without any voids. However, the non-homogeneity of the fiber reinforcement material and its placement and layup in the mold creates a large degree of variability of flow patterns during the… More >