Meenakshi S. Patil^1,*, Rajesh B. Ghongade², Hemant B. Dhonde³

Journal on Artificial Intelligence, Vol.7, pp. 289-300, 2025, DOI:10.32604/jai.2025.069500 - 12 September 2025

Abstract This study seeks to establish a novel, semi-automatic system that utilizes Industry 4.0 principles to effectively determine both acceptable and rejectable concrete cubes with regard to their failure modes, significantly contributing to the dependability of concrete quality evaluations. The study utilizes image processing and machine learning (ML) methods, namely object detection models such as YOLOv8 and Convolutional Neural Networks (CNNs), to evaluate images of concrete cubes. These models are trained and validated on an extensive database of annotated images from real-world and laboratory conditions. Preliminary results indicate a good performance in the classification of concrete More >

Mohamed Abdel-Mongy¹, Mudassir Iqbal², M. Farag³, Ahmed. M. Yosri^1,*, Fahad Alsharari¹, Saif Eldeen A. S. Yousef⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 525-543, 2024, DOI:10.32604/cmes.2024.052505 - 20 August 2024

Abstract Alkali-activated materials/geopolymer (AAMs), due to their low carbon emission content, have been the focus of recent studies on ecological concrete. In terms of performance, fly ash and slag are preferred materials for precursors for developing a one-part geopolymer. However, determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely reported. Therefore, in this study, machine learning methods such as artificial neural networks (ANN) and gene expression programming (GEP) models were developed using MATLAB and GeneXprotools, respectively, for the prediction of compressive strength under variable input materials and content… More >

Sadaqat Ullah Khan¹, Afzal Ahmed^1,*, Sajjad Ali², Ayesha Ayub², Ahmed Shuja¹, Muhammad Ahsan Shahid¹

Journal of Renewable Materials, Vol.9, No.5, pp. 1013-1029, 2021, DOI:10.32604/jrm.2021.014344 - 20 February 2021

Abstract Scrapped tires from vehicles are produced in large quantities. Despite numerous existing uses of scrapped tires, a large quantity ends up at the landfill sites, which contributes to environmental degradation. The development of more applications of scrapped tire usage can reduce the disposal of tires at landfill sites. This research proposes a novel use of scrapped tires by using the strips taken from scrapped tires in replacement of steel bars as reinforcement. Manhole covers were produced using scrapped tires by completely replacing the steel with scrapped tires. Four different samples of manhole covers were prepared… More >