Abdul Ahad^1,2, Ira Puspitasari^1,3,*, Jiangbin Zheng², Shamsher Ullah⁴, Farhan Ullah⁵, Sheikh Tahir Bakhsh⁶, Ivan Miguel Pires^7,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5115-5134, 2025, DOI:10.32604/cmc.2025.062605 - 06 March 2025

Abstract This research explores the use of Fuzzy K-Nearest Neighbor (F-KNN) and Artificial Neural Networks (ANN) for predicting heart stroke incidents, focusing on the impact of feature selection methods, specifically Chi-Square and Best First Search (BFS). The study demonstrates that BFS significantly enhances the performance of both classifiers. With BFS preprocessing, the ANN model achieved an impressive accuracy of 97.5%, precision and recall of 97.5%, and an Receiver Operating Characteristics (ROC) area of 97.9%, outperforming the Chi-Square-based ANN, which recorded an accuracy of 91.4%. Similarly, the F-KNN model with BFS achieved an accuracy of 96.3%, precision More >

Tarak Dhaouadi¹, Hichem Mrabet^1,2,*, Adeeb Alhomoud³, Abderrazak Jemai^1,4

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4535-4554, 2025, DOI:10.32604/cmc.2025.060935 - 06 March 2025

Abstract The increasing adoption of Industrial Internet of Things (IIoT) systems in smart manufacturing is leading to raise cyberattack numbers and pressing the requirement for intrusion detection systems (IDS) to be effective. However, existing datasets for IDS training often lack relevance to modern IIoT environments, limiting their applicability for research and development. To address the latter gap, this paper introduces the HiTar-2024 dataset specifically designed for IIoT systems. As a consequence, that can be used by an IDS to detect imminent threats. Likewise, HiTar-2024 was generated using the AREZZO simulator, which replicates realistic smart manufacturing scenarios.… More >

Shitharth Selvarajan^1,2,3,*, Hariprasath Manoharan⁴, Taher Al-Shehari⁵, Hussain Alsalman⁶, Taha Alfakih⁷

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4339-4369, 2025, DOI:10.32604/cmc.2025.056100 - 06 March 2025

Abstract This research presents an analysis of smart grid units to enhance connected units’ security during data transmissions. The major advantage of the proposed method is that the system model encompasses multiple aspects such as network flow monitoring, data expansion, control association, throughput, and losses. In addition, all the above-mentioned aspects are carried out with neural networks and adaptive optimizations to enhance the operation of smart grid networks. Moreover, the quantitative analysis of the optimization algorithm is discussed concerning two case studies, thereby achieving early convergence at reduced complexities. The suggested method ensures that each communication More >

Meng-Hua Yen^1,*, Nilamadhab Mishra^2,*, Win-Jet Luo³, Chu-En Lin¹

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1839-1855, 2025, DOI:10.32604/cmc.2025.060903 - 17 February 2025

Abstract The Internet of Everything (IoE) coupled with Proactive Artificial Intelligence (AI)-Based Learning Agents (PLAs) through a cloud processing system is an idea that connects all computing resources to the Internet, making it possible for these devices to communicate with one another. Technologies featured in the IoE include embedding, networking, and sensing devices. To achieve the intended results of the IoE and ease life for everyone involved, sensing devices and monitoring systems are linked together. The IoE is used in several contexts, including intelligent cars’ protection, navigation, security, and fuel efficiency. The Smart Things Monitoring System… More >

Ruoxin Li^1,*, Shaoxiong Wu¹, Fengping Deng¹, Zhongli Tian¹, Hua Cai¹, Xiang Li¹, Xu Xu¹, Qi Liu^2,3

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2969-2984, 2025, DOI:10.32604/cmc.2025.060230 - 17 February 2025

Abstract Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and… More >

Yuanjun Qu, Xiameng Si^*, Haiyan Kang, Hanlin Zhou

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3111-3130, 2025, DOI:10.32604/cmc.2024.057368 - 17 February 2025

Abstract With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, its anonymity has provided new ways for Ponzi schemes to commit fraud, posing significant risks to investors. Current research still has some limitations, for example, Ponzi schemes are difficult to detect in the early stages of smart contract deployment, and data imbalance is not considered. In addition, there is room for improving the detection accuracy. To address the above issues, this paper proposes LT-SPSD… More >

Francesco Tornabene^*, Matteo Viscoti, Rossana Dimitri

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1767-1838, 2025, DOI:10.32604/cmes.2024.058842 - 27 January 2025

Abstract Recent engineering applications increasingly adopt smart materials, whose mechanical responses are sensitive to magnetic and electric fields. In this context, new and computationally efficient modeling strategies are essential to predict the multiphysic behavior of advanced structures accurately. Therefore, the manuscript presents a higher-order formulation for the static analysis of laminated anisotropic magneto-electro-elastic doubly-curved shell structures. The fundamental relations account for the full coupling between the electric field, magnetic field, and mechanical elasticity. The configuration variables are expanded along the thickness direction using a generalized formulation based on the Equivalent Layer-Wise approach. Higher-order polynomials are selected,… More >

Francesco Tornabene^*, Matteo Viscoti, Rossana Dimitri

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1697-1765, 2025, DOI:10.32604/cmes.2025.058841 - 27 January 2025

Abstract This study presents a generalized two-dimensional model for evaluating the stationary hygro-thermo-mechanical response of laminated shell structures made of advanced materials. It introduces a generalized kinematic model, enabling the assessment of arbitrary values of temperature variation and mass concentration variation for the unvaried configuration at the top and bottom surfaces. This is achieved through the Equivalent Layer-Wise description of the unknown field variable using higher-order polynomials and zigzag functions. In addition, an elastic foundation is modeled utilizing the Winkler-Pasternak theory. The fundamental equations, derived from the total free energy of the system, are solved analytically… More > Graphic Abstract

Muhammad Nazim^1,2,*, Abdul Ghafoor^3,*, Abida Hussain⁴, Mehwish Tabassum⁵, Aamir Nawaz⁶, Muhammad Ahmad⁷, Murad Muhammad^1,2, Muqarrab Ali⁴

Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 65-99, 2025, DOI:10.32604/phyton.2025.058970 - 24 January 2025

Abstract In recent years, the world has faced rising global temperatures, accumulative pollution, and energy crises, stimulating scientists worldwide to strive for eco-friendly and cost-effective solutions. Biochar has materialized as a favorable tool for environmental remediation, indicating efficacy as an efficient sorbent substance for both inorganic and organic pollutants in environmental field. These unique properties exclude improved surface functionality, porous morphology, large specific surface area (SSA), cation exchange capacity (CEC), robust adsorption capabilities, environmental stability, and embedded micronutrients. Biochar exhibited potential characteristics for environmental oversight, greenhouse gas (GHG) emission reduction, and soil fertility improvement. This review… More >

Min-kyeong Kim¹, Yeong Geol Lee², Won-Hee Park^2,*, Su-hwan Yun², Tae-Soon Kwon², Duckhee Lee²

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1277-1293, 2025, DOI:10.32604/cmc.2024.058386 - 03 January 2025

Abstract Urban railways are vital means of public transportation in Korea. More than 30% of metropolitan residents use the railways, and this proportion is expected to increase. To enhance safety, the government has mandated the installation of closed-circuit televisions in all carriages by 2024. However, cameras still monitored humans. To address this limitation, we developed a dataset of risk factors and a smart detection system that enables an immediate response to any abnormal behavior and intensive monitoring thereof. We created an innovative learning dataset that takes into account seven unique risk factors specific to Korean railway More >