Mitra Madanchian^1,*, Hamed Taherdoost^1,2,3,4

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2133-2159, 2024, DOI:10.32604/cmc.2024.057094 - 18 November 2024

Abstract This comparative review explores the dynamic and evolving landscape of artificial intelligence (AI)-powered innovations within high-tech research and development (R&D). It delves into both theoretical models and practical applications across a broad range of industries, including biotechnology, automotive, aerospace, and telecommunications. By examining critical advancements in AI algorithms, machine learning, deep learning models, simulations, and predictive analytics, the review underscores the transformative role AI has played in advancing theoretical research and shaping cutting-edge technologies. The review integrates both qualitative and quantitative data derived from academic studies, industry reports, and real-world case studies to showcase the… More >

Maenghyo Cho¹, Jinbok Choi², Hee Yuel Roh³

CMES-Computer Modeling in Engineering & Sciences, Vol.33, No.1, pp. 17-48, 2008, DOI:10.3970/cmes.2008.033.017

Abstract The framework for the linkage between geometric modeling and an analysis based on the NURBS technology is developed in this study. In the present study, The NURBS surfaces were generated by interpolating a given set of data points or by extracting the necessary information to construct the NURBS surface from the IGES format file which was generated by the commercial CAD systems. Numerical examples showed the rate of displacement convergence for the various parameter-izations of the NURBS surface. Quadric surface, which is generated exactly by NURBS representation, was considered. One of the important advantages of More >