Open Access

EDITORIAL

Carlo Cattani¹, Haci Mehmet Baskonus^2,*, Armando Ciancio³
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2261-2264, 2024, DOI:10.32604/cmes.2024.050209 - 11 March 2024
（This article belongs to the Special Issue: Recent Developments on Computational Biology-I)
Abstract This article has no abstract. More >

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S. Dickson¹, S. Padmasekaran¹, Pushpendra Kumar^2,*, Kottakkaran Sooppy Nisar³, Hamidreza Marasi⁴
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2265-2287, 2024, DOI:10.32604/cmes.2023.030286 - 11 March 2024
（This article belongs to the Special Issue: Recent Developments on Computational Biology-I)
Abstract This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQI_cRVW and SQIRV models, considering the delay in converting susceptible individuals into infected ones. The significant delays eventually resulted in the pandemic’s containment. To ensure the safety of the host population, this concept integrates quarantine and the COVID-19 vaccine. We investigate the stability of the proposed models. The fundamental reproduction number influences stability conditions. According to our findings, asymptomatic cases considerably impact the prevalence of Omicron infection in the community. The real data of the Omicron variant from Chennai, Tamil Nadu, India, is More >

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Saima Rashid^1,2,*, Fahd Jarad^3,4
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2289-2327, 2024, DOI:10.32604/cmes.2023.028773 - 11 March 2024
（This article belongs to the Special Issue: Recent Developments on Computational Biology-I)
Abstract Because of the features involved with their varied kernels, differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues. In this paper, we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels. In this approach, the overall population was separated into five cohorts. Furthermore, the descriptive behavior of the system was investigated, including prerequisites for the positivity of solutions, invariant domain of the solution, presence and stability of equilibrium points, and sensitivity analysis. We included a stochastic More >

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REVIEW

Debiao Meng^1,2,*, Yipeng Guo^1,2, Yihe Xu³, Shiyuan Yang^1,2,*, Yongqiang Guo⁴, Lidong Pan⁴, Xinkai Guo²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2329-2359, 2024, DOI:10.32604/cmes.2024.047507 - 11 March 2024
（This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Abstract The escalating need for reliability analysis (RA) and reliability-based design optimization (RBDO) within engineering challenges has prompted the advancement of saddlepoint approximation methods (SAM) tailored for such problems. This article offers a detailed overview of the general SAM and summarizes the method characteristics first. Subsequently, recent enhancements in the SAM theoretical framework are assessed. Notably, the mean value first-order saddlepoint approximation (MVFOSA) bears resemblance to the conceptual framework of the mean value second-order saddlepoint approximation (MVSOSA); the latter serves as an auxiliary approach to the former. Their distinction is rooted in the varying expansion orders… More >

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REVIEW

Xiaofang Kang^1,2,*, Qiwen Huang¹, Zongqin Wu¹, Jianjun Tang¹, Xueqin Jiang¹, Shancheng Lei³
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2361-2398, 2024, DOI:10.32604/cmes.2023.043936 - 11 March 2024
（This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Abstract Tuned mass damper inerter (TMDI) is a device that couples traditional tuned mass dampers (TMD) with an inertial device. The inertial device produces resistance proportional to the relative acceleration at its two ends through its “inertial” constant. Due to its unique mechanical properties, TMDI has received widespread attention and application in the past twenty years. As different configurations are required in different practical situations, TMDI is still active in the research on vibration control and energy harvesting in structures. This paper provides a comprehensive review of the research status of TMDI. This work first examines… More >

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REVIEW

Yanqiong Zhang, Xianwei Jiang^*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2399-2450, 2024, DOI:10.32604/cmes.2023.045731 - 11 March 2024
Abstract Sign language, a visual-gestural language used by the deaf and hard-of-hearing community, plays a crucial role in facilitating communication and promoting inclusivity. Sign language recognition (SLR), the process of automatically recognizing and interpreting sign language gestures, has gained significant attention in recent years due to its potential to bridge the communication gap between the hearing impaired and the hearing world. The emergence and continuous development of deep learning techniques have provided inspiration and momentum for advancing SLR. This paper presents a comprehensive and up-to-date analysis of the advancements, challenges, and opportunities in deep learning-based sign… More >

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REVIEW

Yuming Tang^1,#, Yitian Zhang^2,#, Tao Niu¹, Zhen Li^2,3,*, Zijian Zhang^1,3, Huaping Chen⁴, Long Zhang⁴
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2451-2477, 2024, DOI:10.32604/cmes.2024.030084 - 11 March 2024
（This article belongs to the Special Issue: Machine Learning Empowered Distributed Computing: Advance in Architecture, Theory and Practice)
Abstract Federated Learning (FL), as an emergent paradigm in privacy-preserving machine learning, has garnered significant interest from scholars and engineers across both academic and industrial spheres. Despite its innovative approach to model training across distributed networks, FL has its vulnerabilities; the centralized server-client architecture introduces risks of single-point failures. Moreover, the integrity of the global model—a cornerstone of FL—is susceptible to compromise through poisoning attacks by malicious actors. Such attacks and the potential for privacy leakage via inference starkly undermine FL’s foundational privacy and security goals. For these reasons, some participants unwilling use their private data… More >

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494

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ARTICLE

Mingzhe Huang, Mi Xiao^*, Liang Gao, Mian Zhou, Wei Sha, Jinhao Zhang
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2479-2505, 2024, DOI:10.32604/cmes.2023.045735 - 11 March 2024
Abstract Cellular thin-shell structures are widely applied in ultralightweight designs due to their high bearing capacity and strength-to-weight ratio. In this paper, a full-scale isogeometric topology optimization (ITO) method based on Kirchhoff–Love shells for designing cellular tshin-shell structures with excellent damage tolerance ability is proposed. This method utilizes high-order continuous nonuniform rational B-splines (NURBS) as basis functions for Kirchhoff–Love shell elements. The geometric and analysis models of thin shells are unified by isogeometric analysis (IGA) to avoid geometric approximation error and improve computational accuracy. The topological configurations of thin-shell structures are described by constructing the effective More >

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ARTICLE

Wangchen Yan^1,*, Jinbao Yang¹, Xin Luo²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2507-2524, 2024, DOI:10.32604/cmes.2023.044709 - 11 March 2024
Abstract Transfer learning could reduce the time and resources required by the training of new models and be therefore important for generalized applications of the trained machine learning algorithms. In this study, a transfer learning-enhanced convolutional neural network (CNN) was proposed to identify the gross weight and the axle weight of moving vehicles on the bridge. The proposed transfer learning-enhanced CNN model was expected to weigh different bridges based on a small amount of training datasets and provide high identification accuracy. First of all, a CNN algorithm for bridge weigh-in-motion (B-WIM) technology was proposed to identify… More >

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565

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ARTICLE

Wuyang Fan, Shisheng Zhong^*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2525-2555, 2024, DOI:10.32604/cmes.2023.046951 - 11 March 2024
Abstract The dynamic balance assessment during the assembly of the coordinator gyroscope significantly impacts the guidance accuracy of precision-guided equipment. In dynamic balance debugging, reliance on rudimentary counterweight empirical formulas persists, resulting in suboptimal debugging accuracy and an increased repetition rate. To mitigate this challenge, we present a multi-head residual graph attention network (ResGAT) model, designed to predict dynamic balance counterweights with high precision. In this research, we employ graph neural networks for interaction feature extraction from assembly graph data. An SDAE-GPC model is designed for the assembly condition classification to derive graph data inputs for More >

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ARTICLE

Sharaf Alzoubi¹, Laith Abualigah^{2,3,4,5,6,7,8,*}, Mohamed Sharaf⁹, Mohammad Sh. Daoud¹⁰, Nima Khodadadi¹¹, Heming Jia¹²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2557-2604, 2024, DOI:10.32604/cmes.2023.045170 - 11 March 2024
Abstract This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm (SSOA). The SSOA combines the principles of swarm intelligence and synergistic cooperation to search for optimal solutions efficiently. A synergistic cooperation mechanism is employed, where particles exchange information and learn from each other to improve their search behaviors. This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities. Furthermore, adaptive mechanisms, such as dynamic parameter adjustment and diversification strategies, are incorporated to balance exploration and exploitation. By leveraging the collaborative nature of swarm intelligence and More >

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ARTICLE

Jungpil Shin^1,*, Md. Al Mehedi Hasan², Abu Saleh Musa Miah¹, Kota Suzuki¹, Koki Hirooka¹
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2605-2625, 2024, DOI:10.32604/cmes.2023.046334 - 11 March 2024
Abstract Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing communities. In Japan, approximately 360,000 individuals with hearing and speech disabilities rely on Japanese Sign Language (JSL) for communication. However, existing JSL recognition systems have faced significant performance limitations due to inherent complexities. In response to these challenges, we present a novel JSL recognition system that employs a strategic fusion approach, combining joint skeleton-based handcrafted features and pixel-based deep learning features. Our system incorporates two distinct streams: the first stream extracts crucial handcrafted features, emphasizing the capture of hand and body… More >

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ARTICLE

Tarek Sheltami^1,*, Gamil Ahmed¹, Ansar Yasar²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2627-2647, 2024, DOI:10.32604/cmes.2023.044973 - 11 March 2024
Abstract Recently, Internet of Drones (IoD) has garnered significant attention due to its widespread applications. However, deploying IoD for area coverage poses numerous limitations and challenges. These include interference between neighboring drones, the need for directional antennas, and altitude restrictions for drones. These challenges necessitate the development of efficient solutions. This research paper presents a cooperative decision-making approach for an efficient IoD deployment to address these challenges effectively. The primary objective of this study is to achieve an efficient IoD deployment strategy that maximizes the coverage region while minimizing interference between neighboring drones. In deployment problem,… More >

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ARTICLE

Asier Garmendia-Orbegozo¹, Jose David Nunez-Gonzalez^1,*, Miguel Angel Anton²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2649-2671, 2024, DOI:10.32604/cmes.2024.045912 - 11 March 2024
Abstract In a network environment composed of different types of computing centers that can be divided into different layers (clod, edge layer, and others), the interconnection between them offers the possibility of peer-to-peer task offloading. For many resource-constrained devices, the computation of many types of tasks is not feasible because they cannot support such computations as they do not have enough available memory and processing capacity. In this scenario, it is worth considering transferring these tasks to resource-rich platforms, such as Edge Data Centers or remote cloud servers. For different reasons, it is more exciting and… More >

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ARTICLE

Yan Wang^*, You Lu, Yuqing Zhou, Zhijian Zhao
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2673-2703, 2024, DOI:10.32604/cmes.2023.046743 - 11 March 2024
Abstract Indoor positioning is a key technology in today’s intelligent environments, and it plays a crucial role in many application areas. This paper proposed an unscented Kalman filter (UKF) based on the maximum correntropy criterion (MCC) instead of the minimum mean square error criterion (MMSE). This innovative approach is applied to the loose coupling of the Inertial Navigation System (INS) and Ultra-Wideband (UWB). By introducing the maximum correntropy criterion, the MCCUKF algorithm dynamically adjusts the covariance matrices of the system noise and the measurement noise, thus enhancing its adaptability to diverse environmental localization requirements. Particularly in… More >

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364

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ARTICLE

Xinci Zhou, Jin Zhu^*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2705-2727, 2024, DOI:10.32604/cmes.2024.046363 - 11 March 2024
Abstract As the number of automated guided vehicles (AGVs) within automated container terminals (ACT) continues to rise, conflicts have become more frequent. Addressing point and edge conflicts of AGVs, a multi-AGV conflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards. For larger terminal maps and complex environments, the grid method is employed to model AGVs’ road networks. An improved bounded conflict-based search (IBCBS) algorithm tailored to ACT is proposed, leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search More >

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ARTICLE

Wenfeng Zheng¹, Siyu Lu¹, Zhuohang Cai¹, Ruiyang Wang¹, Lei Wang², Lirong Yin^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2729-2745, 2024, DOI:10.32604/cmes.2023.046692 - 11 March 2024
Abstract In the field of natural language processing (NLP), there have been various pre-training language models in recent years, with question answering systems gaining significant attention. However, as algorithms, data, and computing power advance, the issue of increasingly larger models and a growing number of parameters has surfaced. Consequently, model training has become more costly and less efficient. To enhance the efficiency and accuracy of the training process while reducing the model volume, this paper proposes a first-order pruning model PAL-BERT based on the ALBERT model according to the characteristics of question-answering (QA) system and language More >

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ARTICLE

Haitao Liu^1,2,*, Jiaming Wang¹, Xiuliang Zhang¹, Yanji Jiang², Qian Xiao¹
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2747-2772, 2024, DOI:10.32604/cmes.2024.047129 - 11 March 2024
Abstract The expansion chamber serves as the primary silencing structure within the exhaust pipeline. However, it can also act as a sound-emitting structure when subjected to airflow. This article presents a hybrid method for numerically simulating and analyzing the unsteady flow and aerodynamic noise in an expansion chamber under the influence of airflow. A fluid simulation model is established, utilizing the Large Eddy Simulation (LES) method to calculate the unsteady flow within the expansion chamber. The simulation results effectively capture the development and changes of the unsteady flow and vorticity inside the cavity, exhibiting a high… More >

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Long Chen¹, Ting Li¹, Liang Liu¹, Wenshuo Wang^2,*, Xiaoxiao Du³, Wei Wang³
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2773-2806, 2024, DOI:10.32604/cmes.2024.046641 - 11 March 2024
Abstract This study explores the implementation of computed tomography (CT) reconstruction and simulation techniques for patient-specific valves, aiming to dissect the mechanical attributes of calcified valves within transcatheter heart valve replacement (TAVR) procedures. In order to facilitate this exploration, it derives pertinent formulas for 3D multi-material isogeometric hyperelastic analysis based on Hounsfield unit (HU) values, thereby unlocking foundational capabilities for isogeometric analysis in calcified aortic valves. A series of uniaxial and biaxial tensile tests is executed to obtain an accurate constitutive model for calcified active valves. To mitigate discretization errors, methodologies for reconstructing volumetric parametric models, More >

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ARTICLE

Xue Liang^1,2, Linjuan Wang^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2807-2834, 2024, DOI:10.32604/cmes.2024.046770 - 11 March 2024
Abstract The peridynamics (PD), as a promising nonlocal continuum mechanics theory, shines in solving discontinuous problems. Up to now, various numerical methods, such as the peridynamic mesh-free particle method (PD-MPM), peridynamic finite element method (PD-FEM), and peridynamic boundary element method (PD-BEM), have been proposed. PD-BEM, in particular, outperforms other methods by eliminating spurious boundary softening, efficiently handling infinite problems, and ensuring high computational accuracy. However, the existing PD-BEM is constructed exclusively for bond-based peridynamics (BBPD) with fixed Poisson’s ratio, limiting its applicability to crack propagation problems and scenarios involving infinite or semi-infinite problems. In this paper,… More >

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Muhammad Akbar^1,2, Huali Pan^1,*, Jiangcheng Huang³, Bilal Ahmed⁴, Guoqiang Ou¹
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2835-2863, 2024, DOI:10.32604/cmes.2024.046993 - 11 March 2024
Abstract The present work aims to assess earthquake-induced earth-retaining (ER) wall displacement. This study is on the dynamics analysis of various earth-retaining wall designs in hollow precast concrete panels, reinforcement concrete facing panels, and gravity-type earth-retaining walls. The finite element (FE) simulations utilized a 3D plane strain condition to model full-scale ER walls and numerous nonlinear dynamics analyses. The seismic performance of different models, which includes reinforcement concrete panels and gravity-type and hollow precast concrete ER walls, was simulated and examined using the FE approach. It also displays comparative studies such as stress distribution, deflection of… More >

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Yuantian Qin^1,2, Yucheng Zhang^1,*, Vadim V. Silberschmidt²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2865-2891, 2024, DOI:10.32604/cmes.2024.046113 - 11 March 2024
Abstract This paper proposes a novel approach for identifying distributed dynamic loads in the time domain. Using polynomial and modal analysis, the load is transformed into modal space for coefficient identification. This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force, thereby achieving dimensionality reduction. The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain. Firstly, the algorithm establishes a recursion scheme based on convolution integral, enabling it to identify loads with a long history More >

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ARTICLE

Shen Yan¹, Dajiang Geng^2,*, Ning Dai³, Mingjian Long², Zhicheng Bai²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2893-2915, 2024, DOI:10.32604/cmes.2024.046931 - 11 March 2024
Abstract According to the design specifications, the construction of extended piles involves traversing the tunnel’s upper region and extending to the underlying rock layer. To address this challenge, a subterranean transfer structure spanning multiple subway tunnels was proposed. Deliberating on the function of piles in the transfer structure as springs with axial and bending stiffness, and taking into account the force balance and deformation coordination conditions of beams and plates within the transfer structure, we established a simplified mechanical model that incorporates soil stratification by combining it with the Winkler elastic foundation beam model. The resolved… More >

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395

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Jinlong Yang, Kwang-Hee Lee, Chul-Hee Lee^*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2917-2946, 2024, DOI:10.32604/cmes.2024.046740 - 11 March 2024
Abstract Cavitation is a common issue in pumps, causing a decrease in pump head, a fall in volumetric efficiency, and an intensification of outlet flow pulsation. It is one of the main hazards that affect the regular operation of the pump. Research on pump cavitation mainly focuses on mixed flow pumps, jet pumps, external spur gear pumps, etc. However, there are few cavitation studies on external herringbone gear pumps. In addition, pumps with different working principles significantly differ in the flow and complexity of the internal flow field. Therefore, it is urgent to study the cavitation… More >

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Di Peng^1,2, Guoqing Chen¹, Jiale Yan^1,*, Shiping Wang^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2947-2964, 2024, DOI:10.32604/cmes.2024.047265 - 11 March 2024
Abstract Cavitation is a prevalent phenomenon within the domain of ship and ocean engineering, predominantly occurring in the tail flow fields of high-speed rotating propellers and on the surfaces of high-speed underwater vehicles. The re-entrant jet and compression wave resulting from the collapse of cavity vapour are pivotal factors contributing to cavity instability. Concurrently, these phenomena significantly modulate the evolution of cavitation flow. In this paper, numerical investigations into cloud cavitation over a Clark-Y hydrofoil were conducted, utilizing the Large Eddy Simulation (LES) turbulence model and the Volume of Fluid (VOF) method within the OpenFOAM framework. More >

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Kai Jiang, Bin Cao^*, Jing Fan
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2965-2984, 2024, DOI:10.32604/cmes.2023.046348 - 11 March 2024
（This article belongs to the Special Issue: Machine Learning Empowered Distributed Computing: Advance in Architecture, Theory and Practice)
Abstract Multimodal sentiment analysis utilizes multimodal data such as text, facial expressions and voice to detect people’s attitudes. With the advent of distributed data collection and annotation, we can easily obtain and share such multimodal data. However, due to professional discrepancies among annotators and lax quality control, noisy labels might be introduced. Recent research suggests that deep neural networks (DNNs) will overfit noisy labels, leading to the poor performance of the DNNs. To address this challenging problem, we present a Multimodal Robust Meta Learning framework (MRML) for multimodal sentiment analysis to resist noisy labels and correlate More >

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Yuanle Chen¹, Haobo Wang¹, Chunyu Liu¹, Linyi Wang², Jiaxin Liu¹, Wei Wu^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2985-3009, 2024, DOI:10.32604/cmes.2023.046837 - 11 March 2024
（This article belongs to the Special Issue: Machine Learning Empowered Distributed Computing: Advance in Architecture, Theory and Practice)
Abstract Recently, there have been significant advancements in the study of semantic communication in single-modal scenarios. However, the ability to process information in multi-modal environments remains limited. Inspired by the research and applications of natural language processing across different modalities, our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos. Specifically, we propose a deep learning-based Multi-Modal Mutual Enhancement Video Semantic Communication system, called M3E-VSC. Built upon a Vector Quantized Generative Adversarial Network (VQGAN), our system aims to leverage mutual enhancement among different modalities by using text as the main More >

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Rui Wang¹, Yao Zhou^3,*, Guangchun Luo¹, Peng Chen², Dezhong Peng^3,4
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3011-3027, 2024, DOI:10.32604/cmes.2023.047065 - 11 March 2024
（This article belongs to the Special Issue: Machine Learning Empowered Distributed Computing: Advance in Architecture, Theory and Practice)
Abstract Time series anomaly detection is crucial in various industrial applications to identify unusual behaviors within the time series data. Due to the challenges associated with annotating anomaly events, time series reconstruction has become a prevalent approach for unsupervised anomaly detection. However, effectively learning representations and achieving accurate detection results remain challenging due to the intricate temporal patterns and dependencies in real-world time series. In this paper, we propose a cross-dimension attentive feature fusion network for time series anomaly detection, referred to as CAFFN. Specifically, a series and feature mixing block is introduced to learn representations More >

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Yizhao Wang^*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3029-3045, 2024, DOI:10.32604/cmes.2024.046270 - 11 March 2024
（This article belongs to the Special Issue: Machine Learning Based Computational Mechanics)
Abstract Near-fault impulsive ground-shaking is highly destructive to engineering structures, so its accurate identification ground-shaking is a top priority in the engineering field. However, due to the lack of a comprehensive consideration of the ground-shaking characteristics in traditional methods, the generalization and accuracy of the identification process are low. To address these problems, an impulsive ground-shaking identification method combined with deep learning named PCA-LSTM is proposed. Firstly, ground-shaking characteristics were analyzed and ground-shaking the data was annotated using Baker’s method. Secondly, the Principal Component Analysis (PCA) method was used to extract the most relevant features related More >

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Xinyu Zhang¹, Wenjie Xia², Yang Wang^3,4, Liang Wang^1,*, Xiaofeng Liu¹
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3047-3061, 2024, DOI:10.32604/cmes.2023.046922 - 11 March 2024
（This article belongs to the Special Issue: Computational Design and Modeling of Advanced Composites and Structures)
Abstract Graphene aerogel (GA), as a novel solid material, has shown great potential in engineering applications due to its unique mechanical properties. In this study, the mechanical performance of GA under high-velocity projectile impacts is thoroughly investigated using full-atomic molecular dynamics (MD) simulations. The study results show that the porous structure and density are key factors determining the mechanical response of GA under impact loading. Specifically, the impact-induced penetration of the projectile leads to the collapse of the pore structure, causing stretching and subsequent rupture of covalent bonds in graphene sheets. Moreover, the effects of temperature More >

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Dan Zhao¹, Yang You², Chuanwen Luo^3,*, Ting Chen^4,*, Yang Liu⁵
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3063-3083, 2024, DOI:10.32604/cmes.2023.045400 - 11 March 2024
（This article belongs to the Special Issue: Privacy-Preserving Technologies for Large-scale Artificial Intelligence)
Abstract In recent years, the research field of data collection under local differential privacy (LDP) has expanded its focus from elementary data types to include more complex structural data, such as set-value and graph data. However, our comprehensive review of existing literature reveals that there needs to be more studies that engage with key-value data collection. Such studies would simultaneously collect the frequencies of keys and the mean of values associated with each key. Additionally, the allocation of the privacy budget between the frequencies of keys and the means of values for each key does not… More >

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Jinbo Yang¹, Hai Huang¹, Lailai Yin², Jiaxing Qu³, Wanjuan Xie^4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3085-3099, 2024, DOI:10.32604/cmes.2023.045417 - 11 March 2024
（This article belongs to the Special Issue: Privacy-Preserving Technologies for Large-scale Artificial Intelligence)
Abstract Diagnosing multi-stage diseases typically requires doctors to consider multiple data sources, including clinical symptoms, physical signs, biochemical test results, imaging findings, pathological examination data, and even genetic data. When applying machine learning modeling to predict and diagnose multi-stage diseases, several challenges need to be addressed. Firstly, the model needs to handle multimodal data, as the data used by doctors for diagnosis includes image data, natural language data, and structured data. Secondly, privacy of patients’ data needs to be protected, as these data contain the most sensitive and private information. Lastly, considering the practicality of the… More >

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Mohammad Mehedi Hassan^1,*, Salman A. AlQahtani², Mabrook S. AlRakhami¹, Ahmed Zohier Elhendi³
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3101-3123, 2024, DOI:10.32604/cmes.2024.047940 - 11 March 2024
（This article belongs to the Special Issue: Intelligent Medical Decision Support Systems: Methods and Applications)
Abstract In the current landscape of the COVID-19 pandemic, the utilization of deep learning in medical imaging, especially in chest computed tomography (CT) scan analysis for virus detection, has become increasingly significant. Despite its potential, deep learning’s “black box” nature has been a major impediment to its broader acceptance in clinical environments, where transparency in decision-making is imperative. To bridge this gap, our research integrates Explainable AI (XAI) techniques, specifically the Local Interpretable Model-Agnostic Explanations (LIME) method, with advanced deep learning models. This integration forms a sophisticated and transparent framework for COVID-19 identification, enhancing the capability… More >

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Xingli Wu^1,#, Huchang Liao^1,#, Shuxian Sun¹, Zhengjun Wan^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3125-3146, 2024, DOI:10.32604/cmes.2023.047031 - 11 March 2024
（This article belongs to the Special Issue: Linguistic Approaches for Multiple Criteria Decision Making and Applications)
Abstract Agricultural investment project selection is a complex multi-criteria decision-making problem, as agricultural projects are easily influenced by various risk factors, and the evaluation information provided by decision-makers usually involves uncertainty and inconsistency. Existing literature primarily employed direct preference elicitation methods to address such issues, necessitating a great cognitive effort on the part of decision-makers during evaluation, specifically, determining the weights of criteria. In this study, we propose an indirect preference elicitation method, known as a preference disaggregation method, to learn decision-maker preference models from decision examples. To enhance evaluation ease, decision-makers merely need to compare… More >

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Yifan Huang¹, Zikang Zhou^1,2, Mingyu Li¹, Xuedong Luo^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3147-3165, 2024, DOI:10.32604/cmes.2024.045947 - 11 March 2024
（This article belongs to the Special Issue: Bio-inspired Optimization in Engineering and Sciences)
Abstract Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management. In this study, Tuna Swarm Optimization (TSO), Whale Optimization Algorithm (WOA), and Cuckoo Search (CS) were used to optimize two hyperparameters in support vector regression (SVR). Based on these methods, three hybrid models to predict peak particle velocity (PPV) for bench blasting were developed. Eighty-eight samples were collected to establish the PPV database, eight initial blasting parameters were chosen as input parameters for the prediction model, and the PPV was the output parameter. As predictive performance evaluation indicators, the coefficient of More >

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Shijun Zhao¹, Qing Zhang², Yusong Miao¹, Weizhao Zhang³, Xinbo Zhao¹, Wei Xu^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3167-3187, 2024, DOI:10.32604/cmes.2023.045015 - 11 March 2024
（This article belongs to the Special Issue: New Trends on Meshless Method and Numerical Analysis)
Abstract The surrounding rock of roadways exhibits intricate characteristics of discontinuity and heterogeneity. To address these complexities, this study employs non-local Peridynamics (PD) theory and reconstructs the kernel function to represent accurately the spatial decline of long-range force. Additionally, modifications to the traditional bond-based PD model are made. By considering the micro-structure of coal-rock materials within a uniform discrete model, heterogeneity characterized by bond random pre-breaking is introduced. This approach facilitates the proposal of a novel model capable of handling the random distribution characteristics of material heterogeneity, rendering the PD model suitable for analyzing the deformation… More >

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Chein-Shan Liu¹, Chung-Lun Kuo¹, Chih-Wen Chang^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3189-3208, 2024, DOI:10.32604/cmes.2023.046002 - 11 March 2024
（This article belongs to the Special Issue: New Trends on Meshless Method and Numerical Analysis)
Abstract To solve the Laplacian problems, we adopt a meshless method with the multiquadric radial basis function (MQ-RBF) as a basis whose center is distributed inside a circle with a fictitious radius. A maximal projection technique is developed to identify the optimal shape factor and fictitious radius by minimizing a merit function. A sample function is interpolated by the MQ-RBF to provide a trial coefficient vector to compute the merit function. We can quickly determine the optimal values of the parameters within a preferred rage using the golden section search algorithm. The novel method provides the More >

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Weiya Shi^1,*, Shaowen Zhang², Shiqiang Zhang²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3209-3231, 2024, DOI:10.32604/cmes.2023.044863 - 11 March 2024
（This article belongs to the Special Issue: Machine Learning-Guided Intelligent Modeling with Its Industrial Applications)
Abstract In recent years, there has been extensive research on object detection methods applied to optical remote sensing images utilizing convolutional neural networks. Despite these efforts, the detection of small objects in remote sensing remains a formidable challenge. The deep network structure will bring about the loss of object features, resulting in the loss of object features and the near elimination of some subtle features associated with small objects in deep layers. Additionally, the features of small objects are susceptible to interference from background features contained within the image, leading to a decline in detection accuracy.… More >

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Xianfeng Cao¹, Meihua Yao², Yahui Zhang^3,*, Xiaofeng Hu⁴, Chuanxun Wu³
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3233-3253, 2024, DOI:10.32604/cmes.2023.030773 - 11 March 2024
（This article belongs to the Special Issue: Computing Methods for Industrial Artificial Intelligence)
Abstract As the take-off of China’s macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of the most important components of heavy vehicles, the transmission front and middle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control More >

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Peng Liao¹, Chaoge Liu², Jie Yin^1,3,*, Zhi Wang², Xiang Cui²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3255-3285, 2024, DOI:10.32604/cmes.2024.043855 - 11 March 2024
（This article belongs to the Special Issue: The Bottleneck of Blockchain Techniques: Scalability, Security and Privacy Protection)
Abstract Digital assets have boomed over the past few years with the emergence of Non-fungible Tokens (NFTs). To be specific, the total trading volume of digital assets reached an astounding $55.5 billion in 2022. Nevertheless, numerous security concerns have been raised by the rapid expansion of the NFT ecosystem. NFT holders are exposed to a plethora of scams and traps, putting their digital assets at risk of being lost. However, academic research on NFT security is scarce, and the security issues have aroused rare attention. In this study, the NFT ecological process is comprehensively explored. This… More >

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Yanzhong Sun¹, Xiaoni Du^1,*, Shufen Niu², Xiaodong Yang²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3287-3310, 2024, DOI:10.32604/cmes.2023.043589 - 11 March 2024
（This article belongs to the Special Issue: The Bottleneck of Blockchain Techniques: Scalability, Security and Privacy Protection)
Abstract Traditional email systems can only achieve one-way communication, which means only the receiver is allowed to search for emails on the email server. In this paper, we propose a blockchain-based certificateless bidirectional authenticated searchable encryption model for a cloud email system named certificateless authenticated bidirectional searchable encryption (CL-BSE) by combining the storage function of cloud server with the communication function of email server. In the new model, not only can the data receiver search for the relevant content by generating its own trapdoor, but the data owner also can retrieve the content in the same… More >

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Shujiang Xu^1,2,*, Ziye Wang^1,2, Lianhai Wang^1,2, Miodrag J. Mihaljević^1,2,3, Shuhui Zhang^1,2, Wei Shao^1,2, Qizheng Wang^1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3311-3327, 2024, DOI:10.32604/cmes.2023.046164 - 11 March 2024
（This article belongs to the Special Issue: The Bottleneck of Blockchain Techniques: Scalability, Security and Privacy Protection)
Abstract Blockchain technology, with its attributes of decentralization, immutability, and traceability, has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes. However, transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain. Due to its inability to meet the demands of high-frequency trading, blockchain cannot be adopted in many scenarios. To improve the transaction capacity, researchers have proposed some on-chain scaling technologies, including lightning networks, directed acyclic graph technology, state channels, and sharding mechanisms, in which sharding emerges as a potential scaling technology. Nevertheless, excessive… More >

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Kuosheng Jiang¹, Chengrui Han¹, Yasheng Chang^2,3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3329-3352, 2024, DOI:10.32604/cmes.2024.046729 - 11 March 2024
（This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Abstract Angular contact ball bearings have been widely used in machine tool spindles, and the bearing preload plays an important role in the performance of the spindle. In order to solve the problems of the traditional optimal preload prediction method limited by actual conditions and uncertainties, a roller bearing preload test method based on the improved D-S evidence theory multi-sensor fusion method was proposed. First, a novel controllable preload system is proposed and evaluated. Subsequently, multiple sensors are employed to collect data on the bearing parameters during preload application. Finally, a multisensor fusion algorithm is used More >

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Murugan Palanikumar¹, Nasreen Kausar^2,*, Dragan Pamucar^3,4, Seifedine Kadry^5,6,7,*, Chomyong Kim⁸, Yunyoung Nam⁹
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3353-3385, 2024, DOI:10.32604/cmes.2024.031439 - 11 March 2024
（This article belongs to the Special Issue: Advances in Ambient Intelligence and Social Computing under uncertainty and indeterminacy: From Theory to Applications)
Abstract In this article, multiple attribute decision-making problems are solved using the vague normal set (VNS). It is possible to generalize the vague set (VS) and q-rung fuzzy set (FS) into the q-rung vague set (VS). A log q-rung normal vague weighted averaging (log q-rung NVWA), a log q-rung normal vague weighted geometric (log q-rung NVWG), a log generalized q-rung normal vague weighted averaging (log Gq-rung NVWA), and a log generalized q-rung normal vague weighted geometric (log Gq-rung NVWG) operator are discussed in this article. A description is provided of the scoring function, accuracy function and operational laws of the log q-rung… More >

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Nazik Alturki¹, Raed Alharthi², Muhammad Umer^3,*, Oumaima Saidani¹, Amal Alshardan¹, Reemah M. Alhebshi⁴, Shtwai Alsubai⁵, Ali Kashif Bashir^6,7,8,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3387-3415, 2024, DOI:10.32604/cmes.2023.044700 - 11 March 2024
（This article belongs to the Special Issue: Intelligent Blockchain for the Internet of Things)
Abstract The concept of smart houses has grown in prominence in recent years. Major challenges linked to smart homes are identification theft, data safety, automated decision-making for IoT-based devices, and the security of the device itself. Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features. This paper proposes a smart home system based on ensemble learning of random forest (RF) and convolutional neural networks (CNN) for programmed decision-making tasks, such as categorizing gadgets… More >

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Muhammad Shoaib Arif^1,2,*, Kamaleldin Abodayeh¹, Yasir Nawaz²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3417-3434, 2024, DOI:10.32604/cmes.2024.046944 - 11 March 2024
（This article belongs to the Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics-II)
Abstract This study focuses on the urgent requirement for improved accuracy in disease modeling by introducing a new computational framework called the Hybrid SIR-Fuzzy Model. By integrating the traditional Susceptible-Infectious-Recovered (SIR) model with fuzzy logic, our method effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model parameters. The main aim of this research is to provide a model for disease transmission using fuzzy theory, which can successfully address uncertainty in mathematical modeling. Our main emphasis is on the imprecise transmission rate parameter, utilizing a three-part… More >

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Oulfa Harrat^1,*, Yazid Hadidane¹, S. M. Anas^2,*, Nadhim Hamah Sor^3,4, Ahmed Farouk Deifalla⁵, Paul O. Awoyera⁶, Nadia Gouider¹
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3435-3465, 2024, DOI:10.32604/cmes.2023.044950 - 11 March 2024
（This article belongs to the Special Issue: Recent Advances in Computational Methods for Performance Assessment of Engineering Structures and Materials against Dynamic Loadings)
Abstract Given their numerous functional and architectural benefits, such as improved bearing capacity and increased resistance to elastic instability modes, cold-formed steel (CFS) built-up sections have become increasingly developed and used in recent years, particularly in the construction industry. This paper presents an analytical and numerical study of assembled CFS two single channel-shaped columns with different slenderness and configurations (back-to-back, face-to-face, and box). These columns were joined by double-row rivets for the back-to-back and box configurations, whereas they were welded together for the face-to-face design. The built-up columns were filled with ordinary concrete of good strength.… More >

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Yan Wang^*, Siwen Li, Na Wei
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3467-3493, 2024, DOI:10.32604/cmes.2024.046454 - 11 March 2024
（This article belongs to the Special Issue: Recent Advances in Computational Methods for Performance Assessment of Engineering Structures and Materials against Dynamic Loadings)
Abstract A novel approach for analyzing coupled vibrations between vehicles and bridges is presented, taking into account spatiotemporal effects and mechanical phenomena resulting from vehicle braking. Efficient modeling and solution of bridge vibrations induced by vehicle deceleration are realized using this method. The method’s validity and reliability are substantiated through numerical examples. A simply supported beam bridge with a corrugated steel web is taken as an example and the effects of parameters such as the initial vehicle speed, braking acceleration, braking location, and road surface roughness on the mid-span displacement and impact factor of the bridge… More >

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Weiliang Gao¹, Shixu Jia², Tingting Zhao^2,3,*, Zhiyong Wang²
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3495-3511, 2024, DOI:10.32604/cmes.2023.046188 - 11 March 2024
（This article belongs to the Special Issue: Recent Advances in Computational Methods for Performance Assessment of Engineering Structures and Materials against Dynamic Loadings)
Abstract The mechanical properties of interfacial transition zones (ITZs) have traditionally been simplified by reducing the stiffness of cement in previous simulation methods. A novel approach based on the discrete element method (DEM) has been developed for modeling concrete. This new approach efficiently simulates the meso-structure of ITZs, accurately capturing their heterogeneous properties. Validation against established uniaxial compression experiments confirms the precision of this model. The proposed model can model the process of damage evolution containing cracks initiation, propagation and penetration. Under increasing loads, cracks within ITZs progressively accumulate, culminating in macroscopic fractures that traverse the More >

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Nazik Alturki¹, Abdulaziz Altamimi², Muhammad Umer^3,*, Oumaima Saidani¹, Amal Alshardan¹, Shtwai Alsubai⁴, Marwan Omar⁵, Imran Ashraf^6,*
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3513-3534, 2024, DOI:10.32604/cmes.2023.045868 - 11 March 2024
（This article belongs to the Special Issue: AI-Based Tools for Precision Medicine Solutions)
Abstract Chronic kidney disease (CKD) is a major health concern today, requiring early and accurate diagnosis. Machine learning has emerged as a powerful tool for disease detection, and medical professionals are increasingly using ML classifier algorithms to identify CKD early. This study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California, UC Irvine Machine Learning repository. The research introduces TrioNet, an ensemble model combining extreme gradient boosting, random forest, and extra tree classifier, which excels in providing highly accurate predictions for CKD. Furthermore, K nearest neighbor (KNN) More >

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