Sunil K. Singh¹, Sudhakar Kumar^1,*, Manraj Singh¹, Savita Gupta², Razaz Waheeb Attar³, Varsha Arya^4,5, Ahmed Alhomoud⁶, Brij B. Gupta^7,8,9

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3927-3941, 2025, DOI:10.32604/cmc.2025.059643 - 03 July 2025

Abstract As quantum computing continues to advance, traditional cryptographic methods are increasingly challenged, particularly when it comes to securing critical systems like Supervisory Control and Data Acquisition (SCADA) systems. These systems are essential for monitoring and controlling industrial operations, making their security paramount. A key threat arises from Shor’s algorithm, a powerful quantum computing tool that can compromise current hash functions, leading to significant concerns about data integrity and confidentiality. To tackle these issues, this article introduces a novel Quantum-Resistant Hash Algorithm (QRHA) known as the Modular Hash Learning Algorithm (MHLA). This algorithm is meticulously crafted… More >

Nisa Nacar Çıkan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3279-3327, 2025, DOI:10.32604/cmes.2025.065442 - 30 June 2025

Abstract This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks (UPDNs), focusing on the complex 123-Bus test system. Three scenarios are investigated: (1) simultaneous power loss reduction and voltage profile improvement, (2) minimization of voltage and current unbalance indices under various operational cases, and (3) multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index, active power loss, and current unbalance index. Unlike previous research that oftensimplified system components, this work maintains all equipment, including capacitor banks, transformers, and voltage regulators, to ensure realistic results. The study evaluates twelve metaheuristic More >

Siti Ramadhani^1,2, Lestari Handayani², Theam Foo Ng³, Sumayyah Dzulkifly¹, Roziana Ariffin^4,5, Haldi Budiman⁶, Shir Li Wang^1,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2711-2765, 2025, DOI:10.32604/cmes.2025.062709 - 30 June 2025

Abstract In recent years, feature selection (FS) optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification. This work reviews FS and classification methods that utilize evolutionary algorithms (EAs) for gene expression profiles in cancer or medical applications based on research motivations, challenges, and recommendations. Relevant studies were retrieved from four major academic databases–IEEE, Scopus, Springer, and ScienceDirect–using the keywords ‘cancer classification’, ‘optimization’, ‘FS’, and ‘gene expression profile’. A total of 67 papers were finally selected with key advancements identified as follows: (1) The majority of papers… More > Graphic Abstract

Ibrahim T. Teke^1,2, Ahmet H. Ertas^2,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 243-264, 2025, DOI:10.32604/cmc.2025.066086 - 09 June 2025

Abstract This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting, runner system optimization, and structural analysis to significantly enhance the performance of injection-molded parts. At its core, the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles, leading to improvements in both mechanical strength and material efficiency. The design optimization is validated through a series of rigorous experimental tests, including three-point bending and torsion tests performed on key-socket frames, ensuring that the optimized designs meet practical performance requirements. A critical innovation of… More >

Salman A. Khan^1,*, Mohamed Mohandes^2,3, Shafiqur Rehman³, Ali Al-Shaikhi^2,4, Kashif Iqbal¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 553-581, 2025, DOI:10.32604/cmc.2025.064560 - 09 June 2025

Abstract Wind energy has emerged as a potential replacement for fossil fuel-based energy sources. To harness maximum wind energy, a crucial decision in the development of an efficient wind farm is the optimal layout design. This layout defines the specific locations of the turbines within the wind farm. The process of finding the optimal locations of turbines, in the presence of various technical and technological constraints, makes the wind farm layout design problem a complex optimization problem. This problem has traditionally been solved with nature-inspired algorithms with promising results. The performance and convergence of nature-inspired algorithms… More >

Mahmood Ul Haq¹, Muhammad Athar Javed Sethi¹, Sadique Ahmad², Naveed Ahmad³, Muhammad Shahid Anwar^4,*, Alpamis Kutlimuratov⁵

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1-24, 2025, DOI:10.32604/cmc.2025.063341 - 09 June 2025

Abstract Face recognition has emerged as one of the most prominent applications of image analysis and understanding, gaining considerable attention in recent years. This growing interest is driven by two key factors: its extensive applications in law enforcement and the commercial domain, and the rapid advancement of practical technologies. Despite the significant advancements, modern recognition algorithms still struggle in real-world conditions such as varying lighting conditions, occlusion, and diverse facial postures. In such scenarios, human perception is still well above the capabilities of present technology. Using the systematic mapping study, this paper presents an in-depth review More >

Ghulam E Mustafa Abro^1,*, Altaf Mugheri^2,#, Zain Anwar Ali^3,#

Revue Internationale de Géomatique, Vol.34, pp. 301-331, 2025, DOI:10.32604/rig.2025.065595 - 05 June 2025

Abstract Swarm intelligence, derived from the collective behaviour of biological entities, is a novel methodology for overseeing satellite constellations within decentralized control systems. Conventional centralized control systems in satellite constellations encounter constraints in scalability, resilience, and fault tolerance, particularly in extensive constellations. This research examines the use of swarm-based multi-agent systems and distributed algorithms for efficient communication, collision avoidance, and collaborative task execution in satellite constellations. We provide a comprehensive study of current swarm control algorithms, their relevance to satellite systems, and identify areas requiring further research. Principal subjects encompass decentralized decision-making, self-organization, adaptive communication protocols, More >

Pravinkumar Bhujangrao Landge¹, Yashpal Singh¹, Hitesh Mohapatra², Seyyed Ahmad Edalatpanah^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1661-1688, 2025, DOI:10.32604/cmes.2025.065599 - 30 May 2025

Abstract Internet of things networks often suffer from early node failures and short lifespan due to energy limits. Traditional routing methods are not enough. This work proposes a new hybrid algorithm called ACOGA. It combines Ant Colony Optimization (ACO) and the Greedy Algorithm (GA). ACO finds smart paths while Greedy makes quick decisions. This improves energy use and performance. ACOGA outperforms Hybrid Energy-Efficient (HEE) and Adaptive Lossless Data Compression (ALDC) algorithms. After 500 rounds, only 5% of ACOGA’s nodes are dead, compared to 15% for HEE and 20% for ALDC. The network using ACOGA runs for More >

Irbek Morgoev¹, Roman Klyuev^2,*, Angelika Morgoeva¹

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1381-1399, 2025, DOI:10.32604/cmes.2025.064502 - 30 May 2025

Abstract Non-technical losses (NTL) of electric power are a serious problem for electric distribution companies. The solution determines the cost, stability, reliability, and quality of the supplied electricity. The widespread use of advanced metering infrastructure (AMI) and Smart Grid allows all participants in the distribution grid to store and track electricity consumption. During the research, a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption readings. This model is an ensemble meta-algorithm (stacking) that generalizes the algorithms of random… More >

Peicheng Shi^1,*, Li Yang¹, Xinlong Dong¹, Heng Qi², Aixi Yang³

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3877-3917, 2025, DOI:10.32604/cmc.2025.063205 - 19 May 2025

Abstract As the number and complexity of sensors in autonomous vehicles continue to rise, multimodal fusion-based object detection algorithms are increasingly being used to detect 3D environmental information, significantly advancing the development of perception technology in autonomous driving. To further promote the development of fusion algorithms and improve detection performance, this paper discusses the advantages and recent advancements of multimodal fusion-based object detection algorithms. Starting from single-modal sensor detection, the paper provides a detailed overview of typical sensors used in autonomous driving and introduces object detection methods based on images and point clouds. For image-based detection… More >