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EDITORIAL

Danial Jahed Armaghani^1,*, Ahmed Salih Mohammed^2,3, Ramesh Murlidhar Bhatawdekar⁴, Pouyan Fakharian⁵, Ashutosh Kainthola⁶, Wael Imad Mahmood⁷
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2023-2027, 2024, DOI:10.32604/cmes.2023.031701
（This article belongs to the Special Issue: Computational Intelligent Systems for Solving Complex Engineering Problems: Principles and Applications)
Abstract This article has no abstract. More >

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Sheetal Sharma^1,2, Kamali Gupta¹, Deepali Gupta¹, Shalli Rani^1,*, Gaurav Dhiman^3,4,5,6,7,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2029-2059, 2024, DOI:10.32604/cmes.2023.029997
Abstract The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making them more intelligent and connected. However, this advancement comes with challenges related to the effectiveness of IoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensure their proper functionality. The success of smart systems relies on their seamless operation and ability to handle faults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore, sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments. To address… More >

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1343

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REVIEW

Hong Zhang^1,*, Haijian Shao²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2061-2102, 2024, DOI:10.32604/cmes.2023.030649
Abstract OpenAI and ChatGPT, as state-of-the-art language models driven by cutting-edge artificial intelligence technology, have gained widespread adoption across diverse industries. In the realm of computer vision, these models have been employed for intricate tasks including object recognition, image generation, and image processing, leveraging their advanced capabilities to fuel transformative breakthroughs. Within the gaming industry, they have found utility in crafting virtual characters and generating plots and dialogues, thereby enabling immersive and interactive player experiences. Furthermore, these models have been harnessed in the realm of medical diagnosis, providing invaluable insights and support to healthcare professionals in… More >

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ARTICLE

Othman S. Al-Heety^1,*, Zahriladha Zakaria^1,*, Ahmed Abu-Khadrah², Mahamod Ismail³, Sarmad Nozad Mahmood⁴, Mohammed Mudhafar Shakir⁵, Sameer Alani⁶, Hussein Alsariera¹
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2103-2127, 2024, DOI:10.32604/cmes.2023.029509
Abstract Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision. In this article, these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data. The framework integrates Kalman filtering and Q-learning. Unlike smoothing Kalman filtering, our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error. Unlike traditional Q-learning, our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from… More >

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397

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ARTICLE

Lianghao Hua^1,2, Jianfeng Zhang^1,*, Dejie Li³, Xiaobo Xi¹
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2129-2157, 2024, DOI:10.32604/cmes.2023.030535
Abstract With the increasing prevalence of high-order systems in engineering applications, these systems often exhibit significant disturbances and can be challenging to model accurately. As a result, the active disturbance rejection controller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmanned aerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances and the possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address these issues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neural network (RBFNN) with a More >

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391

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ARTICLE

Zonglin Li^1,2, Zhenyu Gao², Yijun Liu^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2159-2175, 2024, DOI:10.32604/cmes.2023.030920
Abstract The boundary element method (BEM) is a popular method for solving acoustic wave propagation problems, especially those in exterior domains, owing to its ease in handling radiation conditions at infinity. However, BEM models must meet the requirement of 6–10 elements per wavelength, using the conventional constant, linear, or quadratic elements. Therefore, a large storage size of memory and long solution time are often needed in solving higher-frequency problems. In this work, we propose two new types of enriched elements based on conventional constant boundary elements to improve the computational efficiency of the 2D acoustic BEM.… More >

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1428

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ARTICLE

Ying Zhang¹, Wei Li^1,*, Guidong Yang¹, Snezana Kirin²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2177-2199, 2024, DOI:10.32604/cmes.2023.030728
Abstract The Mean First-Passage Time (MFPT) and Stochastic Resonance (SR) of a stochastic tumor-immune model with noise perturbation are discussed in this paper. Firstly, considering environmental perturbation, Gaussian white noise and Gaussian colored noise are introduced into a tumor growth model under immune surveillance. As follows, the long-time evolution of the tumor characterized by the Stationary Probability Density (SPD) and MFPT is obtained in theory on the basis of the Approximated Fokker-Planck Equation (AFPE). Herein the recurrence of the tumor from the extinction state to the tumor-present state is more concerned in this paper. A more… More >

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760

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ARTICLE

Thi-Kien Dao¹, Trong-The Nguyen^1,2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2201-2237, 2024, DOI:10.32604/cmes.2023.029880
Abstract Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging and fundamental operations in various monitoring or tracking applications because the network deploys a large area and allocates the acquired location information to unknown devices. The metaheuristic approach is one of the most advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditional methods that often suffer from computational time problems and small network deployment scale. This study proposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on the siege mechanism… More >

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1749

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ARTICLE

Pengxin Li¹, Rong Wang^1,2,*, Wenjing Zhang¹, Yinuo Liu¹, Chenyue Xu¹
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2239-2255, 2024, DOI:10.32604/cmes.2023.030677
Abstract Human pose estimation aims to localize the body joints from image or video data. With the development of deep learning, pose estimation has become a hot research topic in the field of computer vision. In recent years, human pose estimation has achieved great success in multiple fields such as animation and sports. However, to obtain accurate positioning results, existing methods may suffer from large model sizes, a high number of parameters, and increased complexity, leading to high computing costs. In this paper, we propose a new lightweight feature encoder to construct a high-resolution network that… More >

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1116

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ARTICLE

Xiaozhou Xia¹, Changsheng Qin¹, Guangda Lu², Xin Gu^1,*, Qing Zhang¹
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2257-2276, 2024, DOI:10.32604/cmes.2023.031238
Abstract Accurate simulation of the cracking process caused by rust expansion of reinforced concrete (RC) structures plays an intuitive role in revealing the corrosion-induced failure mechanism. Considering the quasi-brittle fracture of concrete, the fracture phase field driven by the compressive-shear term is constructed and added to the traditional brittle fracture phase field model. The rationality of the proposed model is verified by a mixed fracture example under a shear displacement load. Then, the extended fracture phase model is applied to simulate the corrosion-induced cracking process of RC. The cracking patterns caused by non-uniform corrosion expansion are… More >

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2906

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ARTICLE

Cheng-Yeh Li, Jui-Hsiang Kao^*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2277-2304, 2024, DOI:10.32604/cmes.2023.030215
Abstract The performance of a water jet propulsion system is related to the inlet duct, rotor, stator, and nozzle. Generally, the flow inlet design must fit the bottom line of the hull, and the design of the inlet duct is often limited by stern space. The entire section, from the rotor to the nozzle through the stator, must be designed based on system integration in that the individual performance of these three components will influence each other. Particularly, the section from the rotor to the nozzle significantly impacts the performance of a water jet propulsion system.… More >

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534

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ARTICLE

Chenxi Xiu^1,2,*, Xihua Chu²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2305-2338, 2024, DOI:10.32604/cmes.2023.030194
Abstract This paper presents a micromechanics-based Cosserat continuum model for microstructured granular materials. By utilizing this model, the macroscopic constitutive parameters of granular materials with different microstructures are expressed as sums of microstructural information. The microstructures under consideration can be classified into three categories: a medium-dense microstructure, a dense microstructure consisting of one-sized particles, and a dense microstructure consisting of two-sized particles. Subsequently, the Cosserat elastoplastic model, along with its finite element formulation, is derived using the extended Drucker-Prager yield criteria. To investigate failure behaviors, numerical simulations of granular materials with different microstructures are conducted using… More >

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855

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ARTICLE

R. Saravanan^1,*, R. Muthaiah¹, A. Rajesh²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2339-2356, 2024, DOI:10.32604/cmes.2023.030898
Abstract This study develops an Enhanced Threshold Based Energy Detection approach (ETBED) for spectrum sensing in a cognitive radio network. The threshold identification method is implemented in the received signal at the secondary user based on the square law. The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing. Additionally, the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems. In the dynamic threshold, the signal ratio-based threshold is fixed. The threshold is computed by considering the Modified Black Widow Optimization… More >

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744

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ARTICLE

Shude Fu^1,2, Xinye Wu^1,2,*, Wenjie Wang³, Yixin Hu^1,3,*, Zhengke Li¹, Feng Jiang³
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2357-2382, 2024, DOI:10.32604/cmes.2023.031118
Abstract In this paper, given the shortcomings of jellyfish search algorithm with low search ability in the early stage and easy to fall into local optimal solution, this paper introduces adaptive weight function and elite strategy, improving the global search scope in the early stage and the ability to refine the local development in the later stage. In the numerical study, the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted, and the corresponding penalty method is used for constraint treatment. The test… More >

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ARTICLE

Xiangman Zhou^1,*, Jingping Qin¹, Zichuan Fu¹, Min Wang¹, Youlu Yuan¹, Junjian Fu¹, Haiou Zhang², Seyed Reza Elmi Hosseini^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2383-2401, 2024, DOI:10.32604/cmes.2023.029249
Abstract Finite element (FE) coupled thermal-mechanical analysis is widely used to predict the deformation and residual stress of wire arc additive manufacturing (WAAM) parts. In this study, an innovative single-layer multi-bead profile geometric modeling method through the isosceles trapezoid function is proposed to build the FE model of the WAAM process. Firstly, a straight-line model for overlapping beads based on the parabola function was established to calculate the optimal center distance. Then, the isosceles trapezoid-based profile was employed to replace the parabola profiles of the parabola-based overlapping model to establish an innovative isosceles trapezoid-based multi-bead overlapping… More >

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1047

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ARTICLE

Longteng Liang^1,2,3, Zhouquan Feng^2,4,*, Hongyi Zhang^2,4, Zhengqing Chen^2,4, Changzhao Qian^1,3
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2403-2419, 2024, DOI:10.32604/cmes.2023.031260
Abstract Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to their exceptional damping performance and durability. However, the existing constitutive models present challenges to the widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA) software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing a new constitutive model that is both easily understandable and user-friendly for FEA software. By utilizing numerical results obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture the nonlinear More >

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335

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ARTICLE

Fady Samann^1,2,*, Shavan Askar³
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2421-2444, 2024, DOI:10.32604/cmes.2023.031265
Abstract Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms. K-clustering algorithms are simplistic, with fast performance and relative accuracy. However, their implementation depends on the initial selection of clusters number (K), the initial clusters’ centers, and the clustering metric. This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time (LET) as a clustering metric. Realistic traffic flows were considered for three maps, namely Highway, Traffic Light junction, and Roundabout junction, to study the… More >

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310

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621

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ARTICLE

Duan Zhu^1,2, Zhende Zhu^1,2, Cong Zhang^1,2,*, Lun Dai^1,2, Baotian Wang^1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2445-2470, 2024, DOI:10.32604/cmes.2023.030847
Abstract Tunnel construction is susceptible to accidents such as loosening, deformation, collapse, and water inrush, especially under complex geological conditions like dense fault areas. These accidents can cause instability and damage to the tunnel. As a result, it is essential to conduct research on tunnel construction and grouting reinforcement technology in fault fracture zones to address these issues and ensure the safety of tunnel excavation projects. This study utilized the Xianglushan cross-fault tunnel to conduct a comprehensive analysis on the construction, support, and reinforcement of a tunnel crossing a fault fracture zone using the three-dimensional finite… More >

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390

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818

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ARTICLE

Wimonmas Bamrungsetthapong¹, Pramote Charongrattanasakul^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2471-2495, 2024, DOI:10.32604/cmes.2023.031433
Abstract This study presents the design of a modified attributed control chart based on a double sampling (DS) np chart applied in combination with generalized multiple dependent state (GMDS) sampling to monitor the mean life of the product based on the time truncated life test employing the Weibull distribution. The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing. Three control limit levels are used: the warning control limit, inner control limit, and outer control limit. Together, they enhance the capability for variation detection. A genetic… More >

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ARTICLE

Nasser Alalwan^1,*, Ahmed I. Taloba², Amr Abozeid³, Ahmed Ibrahim Alzahrani¹, Ali H. Al-Bayatti⁴
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2497-2517, 2024, DOI:10.32604/cmes.2023.029910
（This article belongs to the Special Issue: Intelligent Biomedical Image Processing and Computer Vision)
Abstract An illness known as pneumonia causes inflammation in the lungs. Since there is so much information available from various X-ray images, diagnosing pneumonia has typically proven challenging. To improve image quality and speed up the diagnosis of pneumonia, numerous approaches have been devised. To date, several methods have been employed to identify pneumonia. The Convolutional Neural Network (CNN) has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and radiology. However, these methods are complex, inefficient, and imprecise to analyze a big number of datasets. In this paper, a new hybrid… More >

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Hassen Louati^1,2, Ali Louati^3,*, Elham Kariri³, Slim Bechikh²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2519-2547, 2024, DOI:10.32604/cmes.2023.030806
（This article belongs to the Special Issue: Intelligent Biomedical Image Processing and Computer Vision)
Abstract Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues, particularly in the field of lung disease diagnosis. One promising avenue involves the use of chest X-Rays, which are commonly utilized in radiology. To fully exploit their potential, researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems. However, constructing and compressing these systems presents a significant challenge, as it relies heavily on the expertise of data scientists. To tackle this issue, we propose an automated approach that utilizes an evolutionary algorithm (EA) to optimize the design and compression More >

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756

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Hong Sun¹, Fangquan Yang², Peiwen Zhang^3,*, Yang Jiao⁴, Yunxiang Zhao⁵
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2549-2569, 2024, DOI:10.32604/cmes.2023.030131
（This article belongs to the Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
Abstract With the development of the integration of aviation safety and artificial intelligence, research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk management, but searching for an efficient and accurate risk assessment algorithm has become a challenge for the civil aviation industry. Therefore, an improved risk assessment algorithm (PS-AE-LSTM) based on long short-term memory network (LSTM) with autoencoder (AE) is proposed for the various supervised deep learning algorithms in flight safety that cannot adequately address the problem of the quality on risk level labels. Firstly, based on… More >

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378

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Refah Alotaibi¹, Mazen Nassar^2,3, Ahmed Elshahhat^4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2571-2596, 2024, DOI:10.32604/cmes.2023.030582
（This article belongs to the Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
Abstract A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing, bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is studied. In this research, using a progressive Type-II censored, various inferences of the MOL model parameters of life are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of the model parameters and various reliability measures are investigated. Against both symmetric and asymmetric loss functions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with the assumption of independent gamma… More >

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1483

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Zhihui Xu¹, Shuwen Shang², Yuntong Pu³, Xiaoyan Su^2,*, Hong Qian², Xiaolei Pan²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2597-2617, 2024, DOI:10.32604/cmes.2023.031247
（This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Abstract Cognitive Reliability and Error Analysis Method (CREAM) is widely used in human reliability analysis (HRA). It defines nine common performance conditions (CPCs), which represent the factors that may affect human reliability and are used to modify the cognitive failure probability (CFP). However, the levels of CPCs are usually determined by domain experts, which may be subjective and uncertain. What’s more, the classic CREAM assumes that the CPCs are independent, which is unrealistic. Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability More >

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Jinxi Guo¹, Kai Chen^1,2, Jiehui Liu¹, Yuhao Ma², Jie Wu^2,*, Yaochun Wu², Xiaofeng Xue³, Jianshen Li¹
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2619-2640, 2024, DOI:10.32604/cmes.2023.031360
（This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Abstract Intelligent diagnosis driven by big data for mechanical fault is an important means to ensure the safe operation of equipment. In these methods, deep learning-based machinery fault diagnosis approaches have received increasing attention and achieved some results. It might lead to insufficient performance for using transfer learning alone and cause misclassification of target samples for domain bias when building deep models to learn domain-invariant features. To address the above problems, a deep discriminative adversarial domain adaptation neural network for the bearing fault diagnosis model is proposed (DDADAN). In this method, the raw vibration data are… More >

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651

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Ke Yang¹, Meihua Xiao^2,*, Zehuan Li¹
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2641-2663, 2024, DOI:10.32604/cmes.2023.031458
（This article belongs to the Special Issue: Advances in Ambient Intelligence and Social Computing under uncertainty and indeterminacy: From Theory to Applications)
Abstract Fair exchange protocols play a critical role in enabling two distrustful entities to conduct electronic data exchanges in a fair and secure manner. These protocols are widely used in electronic payment systems and electronic contract signing, ensuring the reliability and security of network transactions. In order to address the limitations of current research methods and enhance the analytical capabilities for fair exchange protocols, this paper proposes a formal model for analyzing such protocols. The proposed model begins with a thorough analysis of fair exchange protocols, followed by the formal definition of fairness. This definition accurately… More >

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785

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Xiaoqiao Yang, Jialiang Sun^*, Dongping Jin
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2665-2689, 2024, DOI:10.32604/cmes.2023.031482
（This article belongs to the Special Issue: Structural Design and Optimization)
Abstract Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades and wings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumption has become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topology optimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By using the variable density method, lightweight design is achieved without compromising structural strength. The optimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivity filtering and projection to obtain a robust optimized More >

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390

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Fuliang Xu, Yong Luo, Chuanlong Sun, Hong Zhao^*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2691-2708, 2024, DOI:10.32604/cmes.2023.030940
（This article belongs to the Special Issue: Machine Learning Empowered Distributed Computing: Advance in Architecture, Theory and Practice)
Abstract In actual traffic scenarios, precise recognition of traffic participants, such as vehicles and pedestrians, is crucial for intelligent transportation. This study proposes an improved algorithm built on Mask-RCNN to enhance the ability of autonomous driving systems to recognize traffic participants. The algorithm incorporates long and short-term memory networks and the fused attention module (GSAM, GCT, and Spatial Attention Module) to enhance the algorithm’s capability to process both global and local information. Additionally, to increase the network’s initial operation stability, the original network activation function was replaced with Gaussian error linear unit. Experiments were conducted using More >

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642

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Guilin Wu^1,2, Shenghua Huang¹, Tingting Liu³, Zhuoni Yang³, Yuesong Wu², Guihong Wei¹, Peng Yu^1,*, Qilin Zhang⁴, Jun Feng⁴, Bo Zeng^5,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2709-2725, 2024, DOI:10.32604/cmes.2023.031399
（This article belongs to the Special Issue: Machine Learning Based Computational Mechanics)
Abstract Esophageal disease is a common disorder of the digestive system that can severely affect the quality of life and prognosis of patients. Esophageal stenting is an effective treatment that has been widely used in clinical practice. However, esophageal stents of different types and parameters have varying adaptability and effectiveness for patients, and they need to be individually selected according to the patient’s specific situation. The purpose of this study was to provide a reference for clinical doctors to choose suitable esophageal stents. We used 3D printing technology to fabricate esophageal stents with different ratios of… More >

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Jun Xu¹, Kai Bi¹, Yibin Lu^2,*, Tiantian Wang^2,3, Hang Zhang², Zeyuan Zheng³, Fushan Shi³, Yaxin Zheng³, Xiaoying Li², Jingping Yang³
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2727-2748, 2024, DOI:10.32604/cmes.2023.031341
（This article belongs to the Special Issue: Computer Modeling in Vehicle Aerodynamics)
Abstract The spread and removal of pollution sources, namely, cough-released droplets in three different areas (front, middle, and rear areas) of a fully-loaded passenger car in a high-speed train under different fresh air flow volume were studied using computational fluid dynamics (CFD) method. In addition, the structure of indoor flow fields was also analysed. The results show that the large eddies are more stable and flow faster in the air supply under Mode 2 (fresh air volume: 2200 m³/h) compared to Mode 1 (fresh air volume: 1100 m³/h). By analysing the spreading process of droplets sprayed at different locations… More >

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492

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Shimaa M. Amer¹, Ashraf A. M. Khalaf², Amr H. Hussein^3,4, Salman A. Alqahtani⁵, Mostafa H. Dahshan⁶, Hossam M. Kassem^3,4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2749-2767, 2024, DOI:10.32604/cmes.2023.029138
（This article belongs to the Special Issue: Artificial Intelligence of Things (AIoT): Emerging Trends and Challenges)
Abstract Side lobe level reduction (SLL) of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service (QOS) in recent and future wireless communication systems starting from 5G up to 7G. Furthermore, it improves the array gain and directivity, increasing the detection range and angular resolution of radar systems. This study proposes two highly efficient SLL reduction techniques. These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm (GA) to develop the Conv/GA and DConv/GA, respectively. The convolution process determines the element’s… More >

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1064

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Cuihong Li¹, Qiuwei Yang^2,3,*, Xi Peng^2,3
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2769-2791, 2024, DOI:10.32604/cmes.2023.030908
（This article belongs to the Special Issue: Failure Detection Algorithms, Methods and Models for Industrial Environments)
Abstract Shear-type structures are common structural forms in industrial and civil buildings, such as concrete and steel frame structures. Fault diagnosis of shear-type structures is an important topic to ensure the normal use of structures. The main drawback of existing damage assessment methods is that they require accurate structural finite element models for damage assessment. However, for many shear-type structures, it is difficult to obtain accurate FEM. In order to avoid finite element modeling, a model-free method for diagnosing shear structure defects is developed in this paper. This method only needs to measure a few low-order… More >

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812

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Se Li¹, Tiantang Yu^1,*, Tinh Quoc Bui²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2793-2808, 2024, DOI:10.32604/cmes.2023.030278
（This article belongs to the Special Issue: Theoretical and Computational Modeling of Advanced Materials and Structures)
Abstract Isogeometric analysis (IGA) is known to show advanced features compared to traditional finite element approaches. Using IGA one may accurately obtain the geometrically nonlinear bending behavior of plates with functional grading (FG). However, the procedure is usually complex and often is time-consuming. We thus put forward a deep learning method to model the geometrically nonlinear bending behavior of FG plates, bypassing the complex IGA simulation process. A long bidirectional short-term memory (BLSTM) recurrent neural network is trained using the load and gradient index as inputs and the displacement responses as outputs. The nonlinear relationship between More >

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Dengyong Zhang^1,2, Minzhi Yuan^1,2, Feng Li^1,2, Lebing Zhang^3,*, Yanqiang Sun⁴, Yiming Ling⁵
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2809-2824, 2024, DOI:10.32604/cmes.2023.029181
（This article belongs to the Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
Abstract Electrocardiogram (ECG) signal is one of the noninvasive physiological measurement techniques commonly used in cardiac diagnosis. However, in real scenarios, the ECG signal is susceptible to various noise erosion, which affects the subsequent pathological analysis. Therefore, the effective removal of the noise from ECG signals has become a top priority in cardiac diagnostic research. Aiming at the problem of incomplete signal shape retention and low signal-to-noise ratio (SNR) after denoising, a novel ECG denoising network, named attention-based residual dense shrinkage network (ARDSN), is proposed in this paper. Firstly, the shallow ECG characteristics are extracted by More >

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Qixin Lan¹, Binqiang Chen^1,*, Bin Yao¹, Wangpeng He²
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2825-2844, 2024, DOI:10.32604/cmes.2023.030378
（This article belongs to the Special Issue: AI and Machine Learning Modeling in Civil and Building Engineering)
Abstract The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the tool will generate significant noise and vibration, negatively impacting the accuracy of the forming and the surface integrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wear state and promptly replace any heavily worn tools to guarantee the quality of the cutting. The conventional tool wear monitoring models, which are based on machine learning, are specifically built for the intended cutting conditions. However, these models require retraining when… More >

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Raghunathan Krishankumar¹, Dhruva Sundararajan², K. S. Ravichandran², Edmundas Kazimieras Zavadskas^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2845-2872, 2024, DOI:10.32604/cmes.2023.029438
（This article belongs to the Special Issue: Linguistic Approaches for Multiple Criteria Decision Making and Applications)
Abstract Hydrogen is the new age alternative energy source to combat energy demand and climate change. Storage of hydrogen is vital for a nation’s growth. Works of literature provide different methods for storing the produced hydrogen, and the rational selection of a viable method is crucial for promoting sustainability and green practices. Typically, hydrogen storage is associated with diverse sustainable and circular economy (SCE) criteria. As a result, the authors consider the situation a multi-criteria decision-making (MCDM) problem. Studies infer that previous models for hydrogen storage method (HSM) selection (i) do not consider preferences in the… More >

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Yingui Qiu¹, Shuai Huang¹, Danial Jahed Armaghani², Biswajeet Pradhan³, Annan Zhou⁴, Jian Zhou^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2873-2897, 2024, DOI:10.32604/cmes.2023.029938
（This article belongs to the Special Issue: Meta-heuristic Algorithms in Materials Science and Engineering)
Abstract As massive underground projects have become popular in dense urban cities, a problem has arisen: which model predicts the best for Tunnel Boring Machine (TBM) performance in these tunneling projects? However, performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers. On the other hand, a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule. The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications. The previously-proposed intelligent techniques in this field… More >

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Ayla Ocak¹, Ümit Işıkdağ², Gebrail Bekdaş^1,*, Sinan Melih Nigdeli¹, Sanghun Kim³, Zong Woo Geem^4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2899-2924, 2024, DOI:10.32604/cmes.2023.030418
（This article belongs to the Special Issue: Meta-heuristic Algorithms in Materials Science and Engineering)
Abstract Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures. The base isolators may lose their damping capacity over time due to environmental or dynamic effects. This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-term isolator life. In this study, an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time. With the developed model, the required damping capacity of the isolator… More >

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Rabar H. Faraj^1,*, Hemn Unis Ahmed^2,3, Hardi Saadullah Fathullah⁴, Alan Saeed Abdulrahman², Farid Abed⁵
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2925-2954, 2024, DOI:10.32604/cmes.2023.029392
（This article belongs to the Special Issue: Meta-heuristic Algorithms in Materials Science and Engineering)
Abstract Plain concrete is strong in compression but brittle in tension, having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures, even when steel reinforcing is present. In order to address these challenges, short polymer fibers are randomly dispersed in a cement-based matrix to form a highly ductile engineered cementitious composite (ECC). This material exhibits high ductility under tensile forces, with its tensile strain being several hundred times greater than conventional concrete. Since concrete is inherently weak in tension, the tensile strain capacity (TSC) has become one of the most… More >

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Ziqiang Bai¹, Wenzhen Qu^2,*, Guanghua Wu^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2955-2972, 2024, DOI:10.32604/cmes.2023.031474
（This article belongs to the Special Issue: New Trends on Meshless Method and Numerical Analysis)
Abstract In the past decade, notable progress has been achieved in the development of the generalized finite difference method (GFDM). The underlying principle of GFDM involves dividing the domain into multiple sub-domains. Within each sub-domain, explicit formulas for the necessary partial derivatives of the partial differential equations (PDEs) can be obtained through the application of Taylor series expansion and moving-least square approximation methods. Consequently, the method generates a sparse coefficient matrix, exhibiting a banded structure, making it highly advantageous for large-scale engineering computations. In this study, we present the application of the GFDM to numerically solve More >

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Andrew Omame^1,2,*, Mujahid Abbas^3,6, Dumitru Baleanu^4,5,6
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2973-3012, 2024, DOI:10.32604/cmes.2023.029681
（This article belongs to the Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics-II)
Abstract A patient co-infected with COVID-19 and viral hepatitis B can be at more risk of severe complications than the one infected with a single infection. This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19. The model is fitted to real COVID-19 data from Pakistan. The proposed model incorporates logistic growth and saturated incidence functions. Rigorous analyses using the tools of stochastic calculus, are performed to study appropriate conditions for the existence of unique global solutions, stationary distribution in the More >

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Chunlin Xiong^1,2, Zhengqiu Weng^3,4,*, Jia Liu¹, Liang Gu², Fayez Alqahtani⁵, Amr Gafar⁶, Pradip Kumar Sharma⁷
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 3013-3032, 2024, DOI:10.32604/cmes.2023.031088
（This article belongs to the Special Issue: Information Security and Trust Issues in the Digital World)
Abstract With the development of hardware devices and the upgrading of smartphones, a large number of users save privacy-related information in mobile devices, mainly smartphones, which puts forward higher demands on the protection of mobile users’ privacy information. At present, mobile user authentication methods based on human-computer interaction have been extensively studied due to their advantages of high precision and non-perception, but there are still shortcomings such as low data collection efficiency, untrustworthy participating nodes, and lack of practicability. To this end, this paper proposes a privacy-enhanced mobile user authentication method with motion sensors, which mainly… More >

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Chunlei Ruan^1,2,*, Cengceng Dong¹, Kunfeng Liang³, Zhijun Liu¹, Xinru Bao¹
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 3033-3049, 2024, DOI:10.32604/cmes.2023.030607
（This article belongs to the Special Issue: Peridynamics and its Current Progress)
Abstract Using Euler’s first-order explicit (EE) method and the peridynamic differential operator (PDDO) to discretize the time and internal crystal-size derivatives, respectively, the Euler’s first-order explicit method–peridynamic differential operator (EE–PDDO) was obtained for solving the one-dimensional population balance equation in crystallization. Four different conditions during crystallization were studied: size-independent growth, size-dependent growth in a batch process, nucleation and size-independent growth, and nucleation and size-dependent growth in a continuous process. The high accuracy of the EE–PDDO method was confirmed by comparing it with the numerical results obtained using the second-order upwind and HR-van methods. The method is More >

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Muwei Jian^1,2,*, Yue Jin¹, Hui Yu³
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 3051-3063, 2024, DOI:10.32604/cmes.2023.030236
（This article belongs to the Special Issue: Deep Learning based Computational Methods for Abnormality Detection in Human Medical Images)
Abstract Universal lesion detection (ULD) methods for computed tomography (CT) images play a vital role in the modern clinical medicine and intelligent automation. It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks. However, 3D CT blocks necessitate significantly higher hardware resources during the learning phase. Therefore, efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks. In this paper, we propose a ULD network with the enhanced temporal correlation for this purpose, named TCE-Net. The designed TCE module is More >

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