Mohammed Debakla^1,*, Ali Mezaghrani¹, Khalifa Djemal², Imane Zouaneb¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-21, 2026, DOI:10.32604/cmc.2025.071927 - 09 December 2025

Abstract Magnetic Resonance Imaging (MRI) has a pivotal role in medical image analysis, for its ability in supporting disease detection and diagnosis. Fuzzy C-Means (FCM) clustering is widely used for MRI segmentation due to its ability to handle image uncertainty. However, the latter still has countless limitations, including sensitivity to initialization, susceptibility to local optima, and high computational cost. To address these limitations, this study integrates Grey Wolf Optimization (GWO) with FCM to enhance cluster center selection, improving segmentation accuracy and robustness. Moreover, to further refine optimization, Fuzzy Entropy Clustering was utilized for its distinctive features… More >

Yuang Chen^1,2, Yong Li^1,*, Fang Lin^1,2, Shuhan Lv^1,2, Jiaze Jiang^1,2

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-18, 2026, DOI:10.32604/cmc.2025.070990 - 09 December 2025

Abstract Aiming at the problem of potential information noise introduced during the generation of ghost feature maps in GhostNet, this paper proposes a novel lightweight neural network model called ResghostNet. This model constructs the Resghost Module by combining residual connections and Adaptive-SE Blocks, which enhances the quality of generated feature maps through direct propagation of original input information and selection of important channels before cheap operations. Specifically, ResghostNet introduces residual connections on the basis of the Ghost Module to optimize the information flow, and designs a weight self-attention mechanism combined with SE blocks to enhance feature More >

Tianyuan Qi¹, Junpeng Zhao^1,2,*, Chunjie Wang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 127-151, 2025, DOI:10.32604/cmes.2025.070769 - 30 October 2025

Abstract A major bottleneck in large-scale eigenfrequency topology optimization is the repeated solution of the generalized eigenvalue problem. This work presents an efficient graphics processing unit (GPU) solver for three-dimensional (3D) topology optimization that maximizes the fundamental eigenfrequency. The Successive Iteration of Analysis and Design (SIAD) framework is employed to avoid solving a full eigenproblem at every iteration. The sequential approximation of the eigenpairs is solved by the GPU-accelerated multigrid-preconditioned conjugate gradient (MGPCG) method to efficiently improve the eigenvectors along with the topological evolution. The cluster-mean approach is adopted to address the non-differentiability issue caused by… More > Graphic Abstract

Joon-Min Gil¹, Hyunsu Jeong¹, Jihun Kang^2,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2199-2213, 2025, DOI:10.32604/cmc.2025.061182 - 17 February 2025

Abstract In a cloud environment, graphics processing units (GPUs) are the primary devices used for high-performance computation. They exploit flexible resource utilization, a key advantage of cloud environments. Multiple users share GPUs, which serve as coprocessors of central processing units (CPUs) and are activated only if tasks demand GPU computation. In a container environment, where resources can be shared among multiple users, GPU utilization can be increased by minimizing idle time because the tasks of many users run on a single GPU. However, unlike CPUs and memory, GPUs cannot logically multiplex their resources. Additionally, GPU memory… More >

Fengju Zhang¹, Kai Zhu^2,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2353-2372, 2025, DOI:10.32604/cmc.2024.058944 - 17 February 2025

Abstract The Internet of Vehicles (IoV) has become an important direction in the field of intelligent transportation, in which vehicle positioning is a crucial part. SLAM (Simultaneous Localization and Mapping) technology plays a crucial role in vehicle localization and navigation. Traditional Simultaneous Localization and Mapping (SLAM) systems are designed for use in static environments, and they can result in poor performance in terms of accuracy and robustness when used in dynamic environments where objects are in constant movement. To address this issue, a new real-time visual SLAM system called MG-SLAM has been developed. Based on ORB-SLAM2,… More >

Xuesong Li¹, Shuting Wang^1,2, Nianmeng Luo^1,*, Aodi Yang¹, Xing Yuan¹, Xianda Xie^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1481-1514, 2025, DOI:10.32604/cmes.2024.058798 - 27 January 2025

Abstract Due to the high-order B-spline basis functions utilized in isogeometric analysis (IGA) and the repeatedly updating global stiffness matrix of topology optimization, Isogeometric topology optimization (ITO) intrinsically suffers from the computationally demanding process. In this work, we address the efficiency problem existing in the assembling stiffness matrix and sensitivity analysis using Bėzier element stiffness mapping. The Element-wise and Interaction-wise parallel computing frameworks for updating the global stiffness matrix are proposed for ITO with Bėzier element stiffness mapping, which differs from these ones with the traditional Gaussian integrals utilized. Since the explicit stiffness computation formula derived… More >

Priyambada Praharaj^1,*, Chandrakant R. Sonawane^2,*, Arunkumar Bongale²

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2021-2064, 2024, DOI:10.32604/cmes.2024.056289 - 31 October 2024

Abstract This paper represents a detailed and systematic review of one of the most ongoing applications of computational fluid dynamics (CFD) in biomedical applications. Beyond its various engineering applications, CFD has started to establish a presence in the biomedical field. Cardiac abnormality, a familiar health issue, is an essential point of investigation by research analysts. Diagnostic modalities provide cardiovascular structural information but give insufficient information about the hemodynamics of blood. The study of hemodynamic parameters can be a potential measure for determining cardiovascular abnormalities. Numerous studies have explored the rheological behavior of blood experimentally and numerically.… More >

Arshyn Altybay^1,2,*, Niyaz Tokmagambetov^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1867-1881, 2024, DOI:10.32604/cmes.2024.054892 - 27 September 2024

Abstract In this paper, we consider the numerical implementation of the 2D wave equation in isotropic-heterogeneous media. The stability analysis of the scheme using the von Neumann stability method has been studied. We conducted a study on modeling the propagation of acoustic waves in a heterogeneous medium and performed numerical simulations in various heterogeneous media at different time steps. Developed parallel code using Compute Unified Device Architecture (CUDA) technology and tested on domains of various sizes. Performance analysis showed that our parallel approach showed significant speedup compared to sequential code on the Central Processing Unit (CPU). More >

Zhenjiang Dong¹, Xin Ge¹, Yuehua Huang¹, Jiankuo Dong¹, Jiang Xu^2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4021-4044, 2024, DOI:10.32604/cmc.2024.049233 - 20 June 2024

Abstract This paper presents a comprehensive exploration into the integration of Internet of Things (IoT), big data analysis, cloud computing, and Artificial Intelligence (AI), which has led to an unprecedented era of connectivity. We delve into the emerging trend of machine learning on embedded devices, enabling tasks in resource-limited environments. However, the widespread adoption of machine learning raises significant privacy concerns, necessitating the development of privacy-preserving techniques. One such technique, secure multi-party computation (MPC), allows collaborative computations without exposing private inputs. Despite its potential, complex protocols and communication interactions hinder performance, especially on resource-constrained devices. Efforts… More >

Zhaohui Xia^1,3, Baichuan Gao³, Chen Yu^2,*, Haotian Han³, Haobo Zhang³, Shuting Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1103-1137, 2024, DOI:10.32604/cmes.2023.029177 - 17 November 2023

Abstract This paper aims to solve large-scale and complex isogeometric topology optimization problems that consume significant computational resources. A novel isogeometric topology optimization method with a hybrid parallel strategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equation solving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency of CPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload between CPU and GPU. To illustrate the advantages of the proposed method, three benchmark examples are tested to verify the hybrid parallel strategy More > Graphic Abstract