Haoxuanye Ji^*, Zhiliang Chen, Pengfei Jiang, Ziyue Wang, Ting Yu, Wei Zhang

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071880 - 12 January 2026

Abstract Foreign body classification on coal conveyor belts is a critical component of intelligent coal mining systems. Previous approaches have primarily utilized convolutional neural networks (CNNs) to effectively integrate spatial and semantic information. However, the performance of CNN-based methods remains limited in classification accuracy, primarily due to insufficient exploration of local image characteristics. Unlike CNNs, Vision Transformer (ViT) captures discriminative features by modeling relationships between local image patches. However, such methods typically require a large number of training samples to perform effectively. In the context of foreign body classification on coal conveyor belts, the limited availability… More >

Charlotte Olivia Namagembe, Mohamad Ibrahim, Md Arafatur Rahman^*, Prashant Pillai

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.070316 - 09 December 2025

Abstract The rapid proliferation of commercial unmanned aerial vehicles (UAVs) has revolutionized fields such as precision agriculture and disaster response. However, their heavy reliance on GPS navigation leaves them highly vulnerable to spoofing attacks, with potentially severe consequences. To mitigate this threat, we present a machine learning-driven framework for real-time GPS spoofing detection, designed with a balance of detection accuracy and computational efficiency. Our work is distinguished by the creation of a comprehensive dataset of 10,000 instances that integrates both simulated and real-world data, enabling robust and generalizable model development. A comprehensive evaluation of multiple classification More >

Jiahui Song, Yuepeng Zhang, Wenhao Yuan^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.069918 - 10 November 2025

Abstract Synthetic speech detection is an essential task in the field of voice security, aimed at identifying deceptive voice attacks generated by text-to-speech (TTS) systems or voice conversion (VC) systems. In this paper, we propose a synthetic speech detection model called TFTransformer, which integrates both local and global features to enhance detection capabilities by effectively modeling local and global dependencies. Structurally, the model is divided into two main components: a front-end and a back-end. The front-end of the model uses a combination of SincLayer and two-dimensional (2D) convolution to extract high-level feature maps (HFM) containing local… More >

Yanting Zhang¹, Qiyue Liu^1,2, Chuanzhao Tian^1,2,*, Xuewen Li¹, Na Yang¹, Feng Zhang¹, Hongyue Zhang³

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-25, 2026, DOI:10.32604/cmc.2025.068403 - 10 November 2025

Abstract High-resolution remote sensing images (HRSIs) are now an essential data source for gathering surface information due to advancements in remote sensing data capture technologies. However, their significant scale changes and wealth of spatial details pose challenges for semantic segmentation. While convolutional neural networks (CNNs) excel at capturing local features, they are limited in modeling long-range dependencies. Conversely, transformers utilize multihead self-attention to integrate global context effectively, but this approach often incurs a high computational cost. This paper proposes a global-local multiscale context network (GLMCNet) to extract both global and local multiscale contextual information from HRSIs.… More >

Victor De Araujo^1,2,3,*, Pedro Jardim^3,4, Poliana Pessôa³, Juliano Vasconcelos^2,5, Matheus Souza⁶, José Garcia⁷, Jozef Švajlenka⁸, André Christoforo^3,1

Journal of Renewable Materials, Vol.13, No.12, pp. 2479-2524, 2025, DOI:10.32604/jrm.2025.02025-0127 - 23 December 2025

Abstract Finger-joint lumber is a sustainable building product commercialized as a structural solution for beams, pillars and other thin flat load-bearing elements. This study aims to study finger-joint lumber and its industry to promote this engineered wood product. The first research stage assessed the collection of publications on finger-joint lumber available globally, in which a structured protocol was developed to prospect studies based on two complementary methodologies: PRISMA 2020 using Scopus and Web of Science databases, and Snowball using both forward and backward models to complete with additional literature. The second research stage assessed finger-joint lumber… More >

Abdullrahman A. Al-Shamma’a¹, Hassan M. Hussein Farh^1,*, Ridwan Taiwo², Al-Wesabi Ibrahim³, Abdulrhman Alshaabani¹, Saad Mekhilef ⁴, Mohamed A. Mohamed^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1303-1347, 2025, DOI:10.32604/cmes.2025.071302 - 26 November 2025

Abstract Optimal sizing and allocation of distributed generators (DGs) have become essential computational challenges in improving the performance, efficiency, and reliability of electrical distribution networks. Despite extensive research, existing approaches often face algorithmic limitations such as slow convergence, premature stagnation in local minima, or suboptimal accuracy in determining optimal DG placement and capacity. This study presents a comprehensive scientometric and systematic review of global research focused on computer-based modelling and algorithmic optimization for renewable DG sizing and placement. It integrates both quantitative and qualitative analyses of the scholarly landscape, mapping influential research domains, co-authorship structures, the More >

Muhammad Farman^1,2,3,*, Noreen Asghar⁴, Muhammad Umer Saleem⁴, Kottakkaran Sooppy Nisar^5,6, Kamyar Hosseini^1,2,7, Mohamed Hafez^8,9

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 721-751, 2025, DOI:10.32604/cmes.2025.069541 - 30 October 2025

Abstract Smoking is harmful to the lungs and has numerous effects on our bodies. This leads to decreased lung function, which increases the lungs’ susceptibility to asthma triggers. In this paper, we develop a new fractional-order model and investigate the impact of smoking on the progression of asthma by using the Caputo operator to analyze different factors. Using the Banach contraction principle, the existence and uniqueness of solutions are established, and the positivity and boundedness of the model are proved. The model further incorporates different stages of smoking to account for incubation periods and other latent… More >

Ming Chen^1,*, Yanfei Niu², Ping Qi¹, Fucheng Wang¹

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5015-5035, 2025, DOI:10.32604/cmc.2025.067951 - 23 October 2025

Abstract This research addresses the critical challenge of enhancing satellite images captured under low-light conditions, which suffer from severely degraded quality, including a lack of detail, poor contrast, and low usability. Overcoming this limitation is essential for maximizing the value of satellite imagery in downstream computer vision tasks (e.g., spacecraft on-orbit connection, spacecraft surface repair, space debris capture) that rely on clear visual information. Our key novelty lies in an unsupervised generative adversarial network featuring two main contributions: (1) an improved U-Net (IU-Net) generator with multi-scale feature fusion in the contracting path for richer semantic feature… More >

Ali Raza^1,*, Asad Ullah², Eugénio M. Rocha¹, Dumitru Baleanu³, Hala H. Taha⁴, Emad Fadhal^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3433-3461, 2025, DOI:10.32604/cmes.2025.069655 - 30 September 2025

Abstract This study investigates the transmission dynamics of conjunctivitis using stochastic delay differential equations (SDDEs). A delayed stochastic model is formulated by dividing the population into five distinct compartments: susceptible, exposed, infected, environmental irritants, and recovered individuals. The model undergoes thorough analytical examination, addressing key dynamical properties including positivity, boundedness, existence, and uniqueness of solutions. Local and global stability around the equilibrium points is studied with respect to the basic reproduction number. The existence of a unique global positive solution for the stochastic delayed model is established. In addition, a stochastic nonstandard finite difference scheme is More >

Yi Guan¹, Pengpeng Zhi^2,3,*, Zhonglai Wang^1,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3343-3368, 2025, DOI:10.32604/cmes.2025.069515 - 30 September 2025

Abstract Variable-fidelity (VF) surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity (HF) simulations with reduced computational power. A key challenge to building a VF model is devising an adaptive model updating strategy that jointly selects additional low-fidelity (LF) and/or HF samples. The additional samples must enhance the model accuracy while maximizing the computational efficiency. We propose ISMA-VFEEI, a global optimization framework that integrates an Improved Slime-Mould Algorithm (ISMA) and a Variable-Fidelity Expected Extension Improvement (VFEEI) learning function to construct a VF surrogate model efficiently. First, A cost-aware VFEEI More >