Kumar Abhishek^1,*, Sheikh Badar ud din Tahir²

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1391-1409, 2023, DOI:10.32604/cmc.2023.035894

Abstract Human verification and activity analysis (HVAA) are primarily employed to observe, track, and monitor human motion patterns using red-green-blue (RGB) images and videos. Interpreting human interaction using RGB images is one of the most complex machine learning tasks in recent times. Numerous models rely on various parameters, such as the detection rate, position, and direction of human body components in RGB images. This paper presents robust human activity analysis for event recognition via the extraction of contextual intelligence-based features. To use human interaction image sequences as input data, we first perform a few denoising steps. Then, human-to-human analyses are employed… More >

Fatema Nafa^1,*, Amal Babour², Austin Melton³

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 639-652, 2022, DOI:10.32604/cmes.2022.020084

Abstract The importance of prerequisites for education has recently become a promising research direction. This work proposes a statistical model for measuring dependencies in learning resources between knowledge units. Instructors are expected to present knowledge units in a semantically well-organized manner to facilitate students’ understanding of the material. The proposed model reveals how inner concepts of a knowledge unit are dependent on each other and on concepts not in the knowledge unit. To help understand the complexity of the inner concepts themselves, WordNet is included as an external knowledge base in this model. The goal is to develop a model that… More >