Mairaj Bibi¹, Muhammad Shoaib Arif ², Yasir Nawaz³, Nabil Kerdid^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 537-569, 2025, DOI:10.32604/cmes.2025.070362 - 30 October 2025

Abstract This study develops a high-order computational scheme for analyzing unsteady tangent hyperbolic fluid flow with variable thermal conductivity, thermal radiation, and coupled heat and mass transfer effects. A modified two-stage Exponential Time Integrator is introduced for temporal discretization, providing second-order accuracy in time. A compact finite difference method is employed for spatial discretization, yielding sixth-order accuracy at most grid points. The proposed framework ensures numerical stability and convergence when solving stiff, nonlinear parabolic systems arising in fluid flow and heat transfer problems. The novelty of the work lies in combining exponential integrator schemes with compact… More >

Mubeen Sabir¹, Zeshan Aslam Khan^2,*, Muhammad Waqar², Khizer Mehmood¹, Muhammad Junaid Ali Asif Raja³, Naveed Ishtiaq Chaudhary⁴, Khalid Mehmood Cheema⁵, Muhammad Asif Zahoor Raja⁴, Muhammad Farhan Khan⁶, Syed Sohail Ahmed⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 807-855, 2025, DOI:10.32604/cmes.2025.068131 - 30 October 2025

Abstract Fingerprint classification is a biometric method for crime prevention. For the successful completion of various tasks, such as official attendance, banking transactions, and membership requirements, fingerprint classification methods require improvement in terms of accuracy, speed, and the interpretability of non-linear demographic features. Researchers have introduced several CNN-based fingerprint classification models with improved accuracy, but these models often lack effective feature extraction mechanisms and complex multineural architectures. In addition, existing literature primarily focuses on gender classification rather than accurately, efficiently, and confidently classifying hands and fingers through the interpretability of prominent features. This research seeks to… More >

Imran Ahmed^1,#, Misbah Ahmad^2,3,#, Gwanggil Jeon^4,5,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4237-4273, 2025, DOI:10.32604/cmc.2025.068319 - 23 October 2025

Abstract The rapid convergence of Information and Communication Technologies (ICT), driven by advancements in 5G/6G networks, cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT), is reshaping modern digital ecosystems. As massive, distributed data streams are generated across edge devices and network layers, there is a growing need for intelligent, privacy-preserving AI solutions that can operate efficiently at the network edge. Federated Learning (FL) enables decentralized model training without transferring sensitive data, addressing key challenges around privacy, bandwidth, and latency. Despite its benefits in enhancing efficiency, real-time analytics, and regulatory compliance, FL adoption faces… More >

Wan Mohd Faizal^1,2,*, Nurul Musfirah Mazlan^1,*, Shazril Imran Shaukat^3,4, Chu Yee Khor², Ab Hadi Mohd Haidiezul², Abdul Khadir Mohamad Syafiq²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1335-1369, 2025, DOI:10.32604/cmes.2025.068660 - 31 August 2025

Abstract Conventional oncology faces challenges such as suboptimal drug delivery, tumor heterogeneity, and therapeutic resistance, indicating a need for more personalized, and mechanistically grounded and predictive treatment strategies. This review explores the convergence of Computational Fluid Dynamics (CFD) and Machine Learning (ML) as an integrated framework to address these issues in modern cancer therapy. The paper discusses recent advancements where CFD models simulate complex tumor microenvironmental conditions, like interstitial fluid pressure (IFP) and drug perfusion, and ML enhances simulation workflows, automates image-based segmentation, and enhances predictive accuracy. The synergy between CFD and ML improves scalability and More >

Benjamin Wacker¹, Jan Christian Schlüter^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2191-2229, 2025, DOI:10.32604/cmes.2025.067397 - 31 August 2025

Abstract In this work, we re-investigate a classical mathematical model of untreated HIV infection suggested by Kirschner and introduce a novel non-standard finite-difference method for its numerical solution. As our first contribution, we establish non-negativity, boundedness of some solution components, existence globally in time, and uniqueness on a time interval for an arbitrary for the time-continuous problem which extends known results of Kirschner’s model in the literature. As our second analytical result, we establish different equilibrium states and examine their stability properties in the time-continuous setting or discuss some numerical tools to evaluate this question. Our More >

Umer Farooq¹, Nabil Kerdid^2,*, Yasir Nawaz³, Muhammad Shoaib Arif ⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 873-898, 2025, DOI:10.32604/cmes.2025.066800 - 31 July 2025

Abstract In this study, we proposed a numerical technique for solving time-dependent partial differential equations that arise in the electro-osmotic flow of Carreau fluid across a stationary plate based on a modified exponential integrator. The scheme is comprised of two explicit stages. One is the exponential integrator type stage, and the second is the Runge-Kutta type stage. The spatial-dependent terms are discretized using the compact technique. The compact scheme can achieve fourth or sixth-order spatial accuracy, while the proposed scheme attains second-order temporal accuracy. Also, a mathematical model for the electro-osmotic flow of Carreau fluid over… More >

Qian Zhu¹, Qian Kang¹, Tao Xu², Dengxiu Yu^3,*, Zhen Wang¹

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1855-1879, 2025, DOI:10.32604/cmc.2025.061913 - 16 April 2025

Abstract In this study, we present a deterministic convergence analysis of Gated Recurrent Unit (GRU) networks enhanced by a smoothing regularization technique. While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling, they remain prone to overfitting, particularly under noisy or limited training data. Traditional regularization, despite enforcing sparsity and accelerating optimization, introduces non-differentiable points in the error function, leading to oscillations during training. To address this, we propose a novel smoothing regularization framework that replaces the non-differentiable absolute function with a quadratic approximation, ensuring gradient continuity and stabilizing the optimization landscape. Theoretically, we rigorously… More >

Liming Yang^1,*, Linchang Han¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.010890

Abstract This work introduces an efficient improved discrete velocity method (IDVM) with inner iteration for simulating steady flows across all flow regimes. Building upon our prior implicit IDVM, this extension achieves a significantly enhanced convergence rate. In the previous method, simultaneous solution of the discrete velocity Boltzmann equation (DVBE) and corresponding macroscopic governing equations was performed. However, the computational cost was primarily driven by the DVBE calculations due to the substantial difference in the number of discrete distribution functions compared to macroscopic conservative variables. Additionally, the convergence rate was influenced by the predicted equilibrium state derived… More >

Muhammad Shoaib Arif^1,2,*, Kamaleldin Abodayeh¹, Yasir Nawaz²

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1213-1241, 2024, DOI:10.32604/cmes.2024.054819 - 27 September 2024

Abstract Fractal time-dependent issues in fluid dynamics provide a distinct difficulty in numerical analysis due to their complex characteristics, necessitating specialized computing techniques for precise and economical solutions. This study presents an innovative computational approach to tackle these difficulties. The main focus is applying the Fractal Runge-Kutta Method to model the time-dependent magnetohydrodynamic (MHD) Newtonian fluid with rescaled viscosity flow on Riga plates. An efficient computational scheme is proposed for handling fractal time-dependent problems in flow phenomena. The scheme is comprised of three stages and constructed using three different time levels. The stability of the scheme… More >

Abdelkader Mendas^*, Abdellah Mebrek, Zohra Mekranfar

Revue Internationale de Géomatique, Vol.33, pp. 383-398, 2024, DOI:10.32604/rig.2024.055321 - 25 September 2024

Abstract The main purpose of this work is to propose a methodology that considers the multicriteria and multi-actor aspects for assessing land suitability for agriculture. This involves offering a group spatial decision-making approach. The members of a multidisciplinary team can decide on the relative importance of the criteria and the ranking of alternatives. Each member provides his judgment and contributes in a distinct and identifiable manner to find a compromise solution. Twelve criteria (easily available water reserve, cation exchange capacity, electric conductivity, potential of hydrogen (pH), drainage, permeability, active limestone, soil texture, soil useful depth, slopes,… More >