Pan Su¹, Jiaxing Chen², Ronggang Yang², Jiawei Xiang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1883-1905, 2024, DOI:10.32604/cmes.2024.055942 - 27 September 2024

Abstract High-performance finite element research has always been a major focus of finite element method studies. This article introduces isogeometric analysis into the finite element method and proposes a new isogeometric finite element method. Firstly, the physical field is approximated by uniform B-spline interpolation, while geometry is represented by non-uniform rational B-spline interpolation. By introducing a transformation matrix, elements of types C⁰ and C¹ are constructed in the isogeometric finite element method. Subsequently, the corresponding calculation formats for one-dimensional bars, beams, and two-dimensional linear elasticity in the isogeometric finite element method are derived through variational principles and… More >

Haris Alam Zuberi¹, Madan Lal¹, Shivangi Verma¹, Nurul Amira Zainal^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1137-1163, 2024, DOI:10.32604/cmes.2024.055493 - 27 September 2024

Abstract Motivated by the widespread applications of nanofluids, a nanofluid model is proposed which focuses on uniform magnetohydrodynamic (MHD) boundary layer flow over a non-linear stretching sheet, incorporating the Casson model for blood-based nanofluid while accounting for viscous and Ohmic dissipation effects under the cases of Constant Surface Temperature (CST) and Prescribed Surface Temperature (PST). The study employs a two-phase model for the nanofluid, coupled with thermophoresis and Brownian motion, to analyze the effects of key fluid parameters such as thermophoresis, Brownian motion, slip velocity, Schmidt number, Eckert number, magnetic parameter, and non-linear stretching parameter on… More > Graphic Abstract

Tong Zu, Fengyong Li^*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1395-1417, 2024, DOI:10.32604/cmes.2024.055442 - 27 September 2024

Abstract False data injection attack (FDIA) can affect the state estimation of the power grid by tampering with the measured value of the power grid data, and then destroying the stable operation of the smart grid. Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams. Data-driven features, however, cannot effectively capture the differences between noisy data and attack samples. As a result, slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks. To address this problem, this paper designs a… More >

Zhenjiang Zhao¹, Lei Jiang¹, Ling Bai^2,*, Bo Pan³, Ling Zhou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1111-1136, 2024, DOI:10.32604/cmes.2024.055399 - 27 September 2024

Abstract The fluid’s viscosity significantly affects the performance of a centrifugal pump. The entropy production method and leakage are employed to analyze the performance changes under various viscosities by numerical simulation and validated by experiments. The results showed that increasing viscosity reduces both the pump head and efficiency. In addition, the optimal operating point shifts to the left. Leakage is influenced by vortex distribution in the front chamber and boundary layer thickness in wear-ring clearance, leading to an initial increase and subsequent decrease in leakage with increasing viscosity. The total entropy production inside the pump rises More >

Fehaid Alqahtani^*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1709-1724, 2024, DOI:10.32604/cmes.2024.054976 - 27 September 2024

Abstract With the rapid advancement in artificial intelligence (AI) and its application in the Internet of Things (IoT), intelligent technologies are being introduced in the medical field, giving rise to smart healthcare systems. The medical imaging data contains sensitive information, which can easily be stolen or tampered with, necessitating secure encryption schemes designed specifically to protect these images. This paper introduces an artificial intelligence-driven novel encryption scheme tailored for the secure transmission and storage of high-resolution medical images. The proposed scheme utilizes an artificial intelligence-based autoencoder to compress high-resolution medical images and to facilitate fast encryption… 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 >

Yongsheng Zhu^1,2,*, Chong Liu^3,4, Chunlei Chen⁵, Xiaoting Lyu^3,4, Zheng Chen^3,4, Bin Wang⁶, Fuqiang Hu^3,4, Hanxi Li^3,4, Jiao Dai^3,4, Baigen Cai¹, Wei Wang^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1305-1325, 2024, DOI:10.32604/cmes.2024.054820 - 27 September 2024

Abstract The development of Intelligent Railway Transportation Systems necessitates incorporating privacy-preserving mechanisms into AI models to protect sensitive information and enhance system efficiency. Federated learning offers a promising solution by allowing multiple clients to train models collaboratively without sharing private data. However, despite its privacy benefits, federated learning systems are vulnerable to poisoning attacks, where adversaries alter local model parameters on compromised clients and send malicious updates to the server, potentially compromising the global model’s accuracy. In this study, we introduce PMM (Perturbation coefficient Multiplied by Maximum value), a new poisoning attack method that perturbs model 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 >

Anshul Mahajan^*, Sunil K. Singla

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1623-1649, 2024, DOI:10.32604/cmes.2024.054468 - 27 September 2024

Abstract The identification of individuals through ear images is a prominent area of study in the biometric sector. Facial recognition systems have faced challenges during the COVID-19 pandemic due to mask-wearing, prompting the exploration of supplementary biometric measures such as ear biometrics. The research proposes a Deep Learning (DL) framework, termed DeepBio, using ear biometrics for human identification. It employs two DL models and five datasets, including IIT Delhi (IITD-I and IITD-II), annotated web images (AWI), mathematical analysis of images (AMI), and EARVN1. Data augmentation techniques such as flipping, translation, and Gaussian noise are applied to More >

Feyza Altunbey Özbay¹, Erdal Özbay², Farhad Soleimanian Gharehchopogh^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1067-1110, 2024, DOI:10.32604/cmes.2024.054334 - 27 September 2024

Abstract Artificial rabbits optimization (ARO) is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in nature. However, for solving optimization problems, the ARO algorithm shows slow convergence speed and can fall into local minima. To overcome these drawbacks, this paper proposes chaotic opposition-based learning ARO (COARO), an improved version of the ARO algorithm that incorporates opposition-based learning (OBL) and chaotic local search (CLS) techniques. By adding OBL to ARO, the convergence speed of the algorithm increases and it explores the search space better. Chaotic maps in CLS… More > Graphic Abstract