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Md Naeem Hossain¹, Md Mustafizur Rahman^1,2,*, Devarajan Ramasamy¹
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 951-996, 2024, DOI:10.32604/cmes.2024.056022
Abstract Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence, there is a growing demand for advanced fault diagnosis technologies to mitigate the impact of these limitations on unplanned vehicular downtime caused by unanticipated vehicle breakdowns. Due to vehicles’ increasingly complex and autonomous nature, there is a growing urgency to investigate novel diagnosis methodologies for improving safety, reliability, and maintainability. While Artificial Intelligence (AI) has provided a great opportunity in this area, a systematic review of the feasibility and application of AI for Vehicle Fault Diagnosis (VFD)… More >

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Rajan Aravind^1,2, Sundararajan Natarajan¹, Krishnankutty Jayakumar², Ratna Kumar Annabattula^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 997-1032, 2024, DOI:10.32604/cmes.2024.053047
Abstract Understanding the probabilistic nature of brittle materials due to inherent dispersions in their mechanical properties is important to assess their reliability and safety for sensitive engineering applications. This is all the more important when elements composed of brittle materials are exposed to dynamic environments, resulting in catastrophic fatigue failures. The authors propose the application of a non-intrusive polynomial chaos expansion method for probabilistic studies on brittle materials undergoing fatigue fracture when geometrical parameters and material properties are random independent variables. Understanding the probabilistic nature of fatigue fracture in brittle materials is crucial for ensuring the… More >

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Jiayu Ren^1,*, Susumu Nakata²
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1033-1046, 2024, DOI:10.32604/cmes.2024.054238
Abstract Three-dimensional surfaces are typically modeled as implicit surfaces. However, direct rendering of implicit surfaces is not simple, especially when such surfaces contain finely detailed shapes. One approach is ray-casting, where the field of the implicit surface is assumed to be piecewise polynomials defined on the grid of a rectangular domain. A critical issue for direct rendering based on ray-casting is the computational cost of finding intersections between surfaces and rays. In particular, ray-casting requires many function evaluations along each ray, severely slowing the rendering speed. In this paper, a method is proposed to achieve direct More >

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Zhenshuai Wan^1,2,*, Longwang Yue², Yanfeng Wang², Pu Zhao²
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1047-1065, 2024, DOI:10.32604/cmes.2024.053773
Abstract Hydraulic actuators are highly nonlinear when they are subjected to different types of model uncertainties and dynamic disturbances. These unfavorable factors adversely affect the control performance of the hydraulic actuator. Although various control methods have been employed to improve the tracking precision of the dynamic system, optimizing and adjusting control gain to mitigate the hydraulic actuator model uncertainties remains elusive. This study presents an adaptive back-stepping sliding mode controller (ABSMC) to enhance the trajectory tracking precision, where the virtual control law is constructed to replace the position error. The adaptive control theory is introduced in More >

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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
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 >

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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
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 >

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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
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 >

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Sonal Nirwal^1,3,*, Ernian Pan^1,2,*, Chih-Ping Lin^1,2, Quoc Kinh Tran¹
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1165-1191, 2024, DOI:10.32604/cmes.2024.054255
Abstract Magneto-electro-elastic (MEE) materials are a specific class of advanced smart materials that simultaneously manifest the coupling behavior under electric, magnetic, and mechanical loads. This unique combination of properties allows MEE materials to respond to mechanical, electric, and magnetic stimuli, making them versatile for various applications. This paper investigates the static and time-harmonic field solutions induced by the surface load in a three-dimensional (3D) multilayered transversally isotropic (TI) linear MEE layered solid. Green’s functions corresponding to the applied uniform load (in both horizontal and vertical directions) are derived using the Fourier-Bessel series (FBS) system of vector… More >

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Mudasar Zafar^1,2,3,*, Hamzah Sakidin¹, Abida Hussain¹, Loshini Thiruchelvam⁴, Mikhail Sheremet⁵, Iskandar Dzulkarnain³, Roslinda Nazar⁶, Abdullah Al-Yaari¹, Rizwan Safdar^7,8
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1193-1211, 2024, DOI:10.32604/cmes.2024.049259
（This article belongs to the Special Issue: Numerical Modeling and Simulations on Non-Newtonian Flow Problems)
Abstract This study aims to formulate a steady-state mathematical model for a three-dimensional permeable enclosure (cavity) to determine the oil extraction rate using three distinct nanoparticles, SiO₂, Al₂O₃, and Fe₂O₃, in unconventional oil reservoirs. The simulation is conducted for different parameters of volume fractions, porosities, and mass flow rates to determine the optimal oil recovery. The impact of nanoparticles on relative permeability ( and water is also investigated. The simulation process utilizes the finite volume ANSYS Fluent. The study results showed that when the mass flow rate at the inlet is low, oil recovery goes up. In addition, More >

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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
（This article belongs to the Special Issue: New Trends on Meshless Method and Numerical Analysis)
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 >

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Jianhua Liu^*, Peng Xie, Jiajia Liu, Xiaoguang Tu
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1243-1273, 2024, DOI:10.32604/cmes.2024.054002
（This article belongs to the Special Issue: Edge Computing Enabled Internet of Drones)
Abstract In mobile edge computing, unmanned aerial vehicles (UAVs) equipped with computing servers have emerged as a promising solution due to their exceptional attributes of high mobility, flexibility, rapid deployment, and terrain agnosticism. These attributes enable UAVs to reach designated areas, thereby addressing temporary computing swiftly in scenarios where ground-based servers are overloaded or unavailable. However, the inherent broadcast nature of line-of-sight transmission methods employed by UAVs renders them vulnerable to eavesdropping attacks. Meanwhile, there are often obstacles that affect flight safety in real UAV operation areas, and collisions between UAVs may also occur. To solve… More >

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Khalilallah Memarzadeh¹, Hamed Kazemipoor^1,*, Mohammad Fallah¹, Babak Farhang Moghaddam²
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1275-1304, 2024, DOI:10.32604/cmes.2024.050306
（This article belongs to the Special Issue: Advances in Ambient Intelligence and Social Computing under uncertainty and indeterminacy: From Theory to Applications)
Abstract Motivated by a critical issue of airline planning process, this paper addresses a new two-stage scenario-based robust optimization in operational airline planning to cope with uncertainty and possible flight disruptions. Following the route network scheme and generated flight timetables, aircraft maintenance routing and crew scheduling are critical factors in airline planning and operations cost management. This study considers the simultaneous assignment of aircraft fleet and crew to the scheduled flight while satisfying a set of operational constraints, rules, and regulations. Considering multiple locations for airline maintenance and crew bases, we solve the problem of integrated… More >

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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
（This article belongs to the Special Issue: Privacy-Preserving Technologies for Large-scale Artificial Intelligence)
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 >

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Jin Zhou, Minjie Shao^*, Ye Tian, Qi Xia^*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1327-1345, 2024, DOI:10.32604/cmes.2024.054059
（This article belongs to the Special Issue: Advanced Structural Optimization Methods and their Applications in Designing Metamaterials)
Abstract By analyzing the results of compliance minimization of thermoelastic structures, we observed that microstructures play an important role in this optimization problem. Then, we propose to use a multiple variable cutting (M–VCUT) level set-based model of microstructures to solve the concurrent two–scale topology optimization of thermoelastic structures. A microstructure is obtained by combining multiple virtual microstructures that are derived respectively from multiple microstructure prototypes, thus giving more diversity of microstructure and more flexibility in design optimization. The effective mechanical properties of microstructures are computed in an off-line phase by using the homogenization method, and then More >

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Daasara Keshavamurthy Archana¹, Doddabhadrappla Gowda Prakasha¹, Pundikala Veeresha², Kottakkaran Sooppy Nisar^3,4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1347-1363, 2024, DOI:10.32604/cmes.2024.053916
（This article belongs to the Special Issue: Analytical and Numerical Solution of the Fractional Differential Equation)
Abstract This study intends to examine the analytical solutions to the resulting one-dimensional differential equation of a cancer tumor model in the frame of time-fractional order with the Caputo-fractional operator employing a highly efficient methodology called the -homotopy analysis transform method. So, the preferred approach effectively found the analytic series solution of the proposed model. The procured outcomes of the present framework demonstrated that this method is authentic for obtaining solutions to a time-fractional-order cancer model. The results achieved graphically specify that the concerned paradigm is dependent on arbitrary order and parameters and also disclose the More >

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Muhammad Altaf Khan^1,*, Mahmoud H. DarAssi², Irfan Ahmad³, Noha Mohammad Seyam⁴, Ebraheem Alzahrani⁵
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1365-1394, 2024, DOI:10.32604/cmes.2024.053681
（This article belongs to the Special Issue: Analytical and Numerical Solution of the Fractional Differential Equation)
Abstract A mathematical model is designed to investigate Tuberculosis (TB) disease under the vaccination, treatment, and environmental impact with real cases. First, we introduce the model formulation in non-integer order derivative and then, extend the model into fractional order derivative. The fractional system’s existence, uniqueness, and other relevant properties are shown. Then, we study the stability analysis of the equilibrium points. The disease-free equilibrium (DFE) is locally asymptotically stable (LAS) when . Further, we show the global asymptotical stability (GAS) of the endemic equilibrium (EE) for and for . The existence of bifurcation analysis in the More >

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Tong Zu, Fengyong Li^*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1395-1417, 2024, DOI:10.32604/cmes.2024.055442
（This article belongs to the Special Issue: Advances in Reliable Artificial Intelligence for Monitoring and Predictive Maintenance of Industrial Equipment)
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 >

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Muhammad Tashfeen¹, Fazal Dayan¹, Muhammad Aziz Ur Rehman¹, Thabet Abdeljawad^2,3,4,5,*, Aiman Mukheimer²
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1419-1446, 2024, DOI:10.32604/cmes.2024.053242
（This article belongs to the Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics-II)
Abstract This study analyzes the transmission of typhoid fever caused by Salmonella typhi using a mathematical model that highlights the significance of delay in its effectiveness. Time delays can affect the nature of patterns and slow down the emergence of patterns in infected population density. The analyzed model is expanded with the equilibrium analysis, reproduction number, and stability analysis. This study aims to establish and explore the non-standard finite difference (NSFD) scheme for the typhoid fever virus transmission model with a time delay. In addition, the forward Euler method and Runge-Kutta method of order 4 (RK-4)… More >

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Ana Hermosilla^1,2,*, Jorge Gallego-Madrid¹, Pedro Martinez-Julia³, Jordi Ortiz⁴, Ved P. Kafle³, Antonio Skarmeta^1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1447-1471, 2024, DOI:10.32604/cmes.2024.053379
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract As 5th Generation (5G) and Beyond 5G (B5G) networks become increasingly prevalent, ensuring not only network security but also the security and reliability of the applications, the so-called network applications, becomes of paramount importance. This paper introduces a novel integrated model architecture, combining a network application validation framework with an AI-driven reactive system to enhance security in real-time. The proposed model leverages machine learning (ML) and artificial intelligence (AI) to dynamically monitor and respond to security threats, effectively mitigating potential risks before they impact the network infrastructure. This dual approach not only validates the functionality… More >

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Ye-Seul Kil^1,#, Yu-Ran Jeon^1,#, Sun-Jin Lee¹, Il-Gu Lee^1,2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1473-1493, 2024, DOI:10.32604/cmes.2024.052637
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract With the rise of remote work and the digital industry, advanced cyberattacks have become more diverse and complex in terms of attack types and characteristics, rendering them difficult to detect with conventional intrusion detection methods. Signature-based intrusion detection methods can be used to detect attacks; however, they cannot detect new malware. Endpoint detection and response (EDR) tools are attracting attention as a means of detecting attacks on endpoints in real-time to overcome the limitations of signature-based intrusion detection techniques. However, EDR tools are restricted by the continuous generation of unnecessary logs, resulting in poor detection… More >

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Seung-Ju Han, Seong-Su Yoon, Ieck-Chae Euom^*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1495-1518, 2024, DOI:10.32604/cmes.2024.053457
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract The rapid proliferation of Internet of Things (IoT) technology has facilitated automation across various sectors. Nevertheless, this advancement has also resulted in a notable surge in cyberattacks, notably botnets. As a result, research on network analysis has become vital. Machine learning-based techniques for network analysis provide a more extensive and adaptable approach in comparison to traditional rule-based methods. In this paper, we propose a framework for analyzing communications between IoT devices using supervised learning and ensemble techniques and present experimental results that validate the efficacy of the proposed framework. The results indicate that using the More >

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Il Hwan Ji¹, Ju Hyeon Lee¹, Seungho Jeon², Jung Taek Seo^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1519-1549, 2024, DOI:10.32604/cmes.2024.053437
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract In the early days of IoT’s introduction, it was challenging to introduce encryption communication due to the lack of performance of each component, such as computing resources like CPUs and batteries, to encrypt and decrypt data. Because IoT is applied and utilized in many important fields, a cyberattack on IoT can result in astronomical financial and human casualties. For this reason, the application of encrypted communication to IoT has been required, and the application of encrypted communication to IoT has become possible due to improvements in the computing performance of IoT devices and the development… More >

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Bum-Sok Kim¹, Hye-Won Suk¹, Yong-Hoon Choi², Dae-Sung Moon³, Min-Suk Kim^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1551-1574, 2024, DOI:10.32604/cmes.2024.052375
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract Currently, cybersecurity threats such as data breaches and phishing have been on the rise due to the many different attack strategies of cyber attackers, significantly increasing risks to individuals and organizations. Traditional security technologies such as intrusion detection have been developed to respond to these cyber threats. Recently, advanced integrated cybersecurity that incorporates Artificial Intelligence has been the focus. In this paper, we propose a response strategy using a reinforcement-learning-based cyber-attack-defense simulation tool to address continuously evolving cyber threats. Additionally, we have implemented an effective reinforcement-learning-based cyber-attack scenario using Cyber Battle Simulation, which is a… More >

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GyuHyun Jeon¹, Hojun Jin¹, Ju Hyeon Lee¹, Seungho Jeon², Jung Taek Seo^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1575-1622, 2024, DOI:10.32604/cmes.2024.053465
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract The Internet of Wearable Things (IoWT) or Wearable Internet of Things (WIoT) is a new paradigm that combines IoT and wearable technology. Advances in IoT technology have enabled the miniaturization of sensors embedded in wearable devices and the ability to communicate data and access real-time information over low-power mobile networks. IoWT devices are highly interdependent with mobile devices. However, due to their limited processing power and bandwidth, IoWT devices are vulnerable to cyberattacks due to their low level of security. Threat modeling and frameworks for analyzing cyber threats against existing IoT or low-power protocols have… More >

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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
（This article belongs to the Special Issue: Artificial Intelligence Emerging Trends and Sustainable Applications in Image Processing and Computer Vision)
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 >

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Mohamed A. Mahdi¹, Suliman Mohamed Fati^2,*, Mohamed A.G. Hazber¹, Shahanawaj Ahamad³, Sawsan A. Saad⁴
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1651-1671, 2024, DOI:10.32604/cmes.2024.052291
（This article belongs to the Special Issue: Emerging Artificial Intelligence Technologies and Applications)
Abstract Cyberbullying, a critical concern for digital safety, necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces. To tackle this challenge, our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers (BERT) base model (cased), originally pretrained in English. This model is uniquely adapted to recognize the intricate nuances of Arabic online communication, a key aspect often overlooked in conventional cyberbullying detection methods. Our model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media (SM) tweets showing a notable… More >

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Khawaja Tahir Mehmood^1,2,*, Shahid Atiq¹, Intisar Ali Sajjad³, Muhammad Majid Hussain⁴, Malik M. Abdul Basit²
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1673-1708, 2024, DOI:10.32604/cmes.2024.053903
（This article belongs to the Special Issue: Emerging Technologies in Information Security )
Abstract Software-Defined Networking (SDN), with segregated data and control planes, provides faster data routing, stability, and enhanced quality metrics, such as throughput (T_h), maximum available bandwidth (B_d(max)), data transfer (D_Transfer), and reduction in end-to-end delay (D_(E-E)). This paper explores the critical work of deploying SDN in large­scale Data Center Networks (DCNs) to enhance its Quality of Service (QoS) parameters, using logically distributed control configurations. There is a noticeable increase in Delay_(E-E) when adopting SDN with a unified (single) control structure in big DCNs to handle Hypertext Transfer Protocol (HTTP) requests causing a reduction in network quality parameters (B_d(max), T_h, D_Transfer, D_(E-E),… More >

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Fehaid Alqahtani^*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1709-1724, 2024, DOI:10.32604/cmes.2024.054976
（This article belongs to the Special Issue: Emerging Technologies in Information Security )
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 >

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Tareq Hamadneh^1,2, Khalid Kaabneh³, Omar Alssayed⁴, Kei Eguchi^5,*, Zeinab Monrazeri⁶, Mohammad Dehghani⁶
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1725-1808, 2024, DOI:10.32604/cmes.2024.053236
（This article belongs to the Special Issue: Swarm and Metaheuristic Optimization for Applied Engineering Application)
Abstract In this article, a novel metaheuristic technique named Far and Near Optimization (FNO) is introduced, offering versatile applications across various scientific domains for optimization tasks. The core concept behind FNO lies in integrating global and local search methodologies to update the algorithm population within the problem-solving space based on moving each member to the farthest and nearest member to itself. The paper delineates the theory of FNO, presenting a mathematical model in two phases: (i) exploration based on the simulation of the movement of a population member towards the farthest member from itself and (ii)… More >

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Rachid Djoudjou^1,*, Abdeljlil Chihaoui Hedhibi³, Kamel Touileb¹, Abousoufiane Ouis¹, Sahbi Boubaker², Hani Said Abdo^4,5
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1809-1825, 2024, DOI:10.32604/cmes.2024.053621
（This article belongs to the Special Issue: Swarm and Metaheuristic Optimization for Applied Engineering Application)
Abstract There are several advantages to the MIG (Metal Inert Gas) process, which explains its increased use in various welding sectors, such as automotive, marine, and construction. A variant of the MIG process, where the same equipment is employed except for the deposition of a thin layer of flux before the welding operation, is the AMIG (Activated Metal Inert Gas) technique. This study focuses on investigating the impact of physical properties of individual metallic oxide fluxes for 304L stainless steel welding joint morphology and to what extent it can help determine a relationship among weld depth… More >

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Xinchang Zhang¹, Xiaokang Pan², Rongjie Zhu³, Runda Guan², Zhongfeng Qiu⁴, Biao Song^5,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1827-1846, 2024, DOI:10.32604/cmes.2024.054298
（This article belongs to the Special Issue: Lightweight Methods and Resource-efficient Computing Solutions)
Abstract Identification of ocean eddies from a large amount of ocean data provided by satellite measurements and numerical simulations is crucial, while the academia has invented many traditional physical methods with accurate detection capability, but their detection computational efficiency is low. In recent years, with the increasing application of deep learning in ocean feature detection, many deep learning-based eddy detection models have been developed for more effective eddy detection from ocean data. But it is difficult for them to precisely fit some physical features implicit in traditional methods, leading to inaccurate identification of ocean eddies. In… More >

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Oluwaseun Peter Ige^1,2, Keng Hoon Gan^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1847-1865, 2024, DOI:10.32604/cmes.2024.053373
（This article belongs to the Special Issue: Lightweight Methods and Resource-efficient Computing Solutions)
Abstract Feature selection is a crucial technique in text classification for improving the efficiency and effectiveness of classifiers or machine learning techniques by reducing the dataset’s dimensionality. This involves eliminating irrelevant, redundant, and noisy features to streamline the classification process. Various methods, from single feature selection techniques to ensemble filter-wrapper methods, have been used in the literature. Metaheuristic algorithms have become popular due to their ability to handle optimization complexity and the continuous influx of text documents. Feature selection is inherently multi-objective, balancing the enhancement of feature relevance, accuracy, and the reduction of redundant features. This… More >

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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
（This article belongs to the Special Issue: Scientific Computing and Its Application to Engineering Problems)
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 >

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Open Access

ARTICLE

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
（This article belongs to the Special Issue: Scientific Computing and Its Application to Engineering Problems)
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 >

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