CMESOpen Access

Computer Modeling in Engineering & Sciences

ISSN:1526-1492(print)
ISSN:1526-1506(online)
Publication Frequency:Monthly

  • Online
    Articles

    3196

  • on board
    editors

    131

Table of Content


About the Journal

This journal publishes original research papers of reasonable permanent value, in the areas of computational mechanics, computational physics, computational chemistry, and computational biology, pertinent to solids, fluids, gases, biomaterials, and other continua. Various length scales (quantum, nano, micro, meso, and macro), and various time scales (picoseconds to hours) are of interest. Papers which deal with multi-physics problems, as well as those which deal with the interfaces of mechanics, chemistry, and biology, are particularly encouraged. New computational approaches, and more efficient algorithms, which eventually make near-real-time computations possible, are welcome. Original papers dealing with new methods such as meshless methods, and mesh-reduction methods are sought.

Indexing and Abstracting

Science Citation Index (Web of Science): 2021 Impact Factor 2.027; Current Contents: Engineering, Computing & Technology; Scopus Citescore (Impact per Publication 2021): 2.5; SNIP (Source Normalized Impact per Paper 2021): 0.617; RG Journal Impact (average over last three years); Engineering Index (Compendex); Applied Mechanics Reviews; Cambridge Scientific Abstracts: Aerospace and High Technology, Materials Sciences & Engineering, and Computer & Information Systems Abstracts Database; CompuMath Citation Index; INSPEC Databases; Mathematical Reviews; MathSci Net; Mechanics; Science Alert; Science Navigator; Zentralblatt fur Mathematik; Portico, etc...

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Mathematical Aspects of Computational Biology and Bioinformatics

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 1-3, 2023, DOI:10.32604/cmes.2023.026471
    (This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Edge Intelligence with Distributed Processing of DNNs: A Survey

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 5-42, 2023, DOI:10.32604/cmes.2023.023684
    (This article belongs to this Special Issue: Artificial Intelligence for Mobile Edge Computing in IoT)
    Abstract With the rapid development of deep learning, the size of data sets and deep neural networks (DNNs) models are also booming. As a result, the intolerable long time for models’ training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually. Moreover, devices stay idle in the scenario of edge computing (EC), which presents a waste of resources since they can share the pressure of the busy devices but they do not. To address the problem, the strategy leveraging distributed processing has been applied to load computation tasks from a single processor to a group of… More >

  • Open Access

    ARTICLE

    Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 43-61, 2023, DOI:10.32604/cmes.2023.022716
    (This article belongs to this Special Issue: Computer Methods in Bio-mechanics and Biomedical Engineering)
    Abstract This paper aims to investigate and present the numerical investigation of airflow characteristics using Turbulent Kinetic Energy (TKE) to characterize the upper airway with obstructive sleep apnea (OSA) under inhale and exhale breathing conditions. The importance of TKE under both breathing conditions is that it show an accurate method in expressing the severity of flow in sleep disorder. Computational fluid dynamics simulate the upper airway’s airflow via steady-state Reynolds-averaged Navier-Stokes (RANS) with k–ω shear stress transport (SST) turbulence model. The three-dimensional (3D) airway model is created based on the CT scan images of an actual patient, meshed with 1.29 million… More >

    Graphic Abstract

    Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

  • Open Access

    ARTICLE

    The Effects of the Particle Size Ratio on the Behaviors of Binary Granular Materials

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 63-85, 2023, DOI:10.32604/cmes.2023.025062
    Abstract The particle size ratio (PSR) is an important parameter for binary granular materials, which may affect the microstructure and macro behaviors of granular materials. However, the effect of particle ratio on granular assemblies with different arrangements is still unclear. To explore and further clarify the effect of PSR in different packing structures, three types of numerical samples with regular, layered, and random packing are designed. Numerical results show that PSR has significant effects on binary granular samples with regular packing. The larger the PSR, the stronger the strength, the larger the modulus, and the smaller the angle between the shear… More >

  • Open Access

    ARTICLE

    A Novel Light Weight CNN Framework Integrated with Marine Predator Optimization for the Assessment of Tear Film-Lipid Layer Patterns

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 87-106, 2023, DOI:10.32604/cmes.2023.023384
    Abstract Tear film, the outermost layer of the eye, is a complex and dynamic structure responsible for tear production. The tear film lipid layer is a vital component of the tear film that provides a smooth optical surface for the cornea and wetting the ocular surface. Dry eye syndrome (DES) is a symptomatic disease caused by reduced tear production, poor tear quality, or excessive evaporation. Its diagnosis is a difficult task due to its multifactorial etiology. Out of several clinical tests available, the evaluation of the interference patterns of the tear film lipid layer forms a potential tool for DES diagnosis.… More >

  • Open Access

    ARTICLE

    Implementation of Rapid Code Transformation Process Using Deep Learning Approaches

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 107-134, 2023, DOI:10.32604/cmes.2023.024018
    Abstract Our previous work has introduced the newly generated program using the code transformation model GPT-2, verifying the generated programming codes through simhash (SH) and longest common subsequence (LCS) algorithms. However, the entire code transformation process has encountered a time-consuming problem. Therefore, the objective of this study is to speed up the code transformation process significantly. This paper has proposed deep learning approaches for modifying SH using a variational simhash (VSH) algorithm and replacing LCS with a piecewise longest common subsequence (PLCS) algorithm to faster the verification process in the test phase. Besides the code transformation model GPT-2, this study has… More >

    Graphic Abstract

    Implementation of Rapid Code Transformation Process Using Deep Learning Approaches

  • Open Access

    ARTICLE

    A New Hybrid Hierarchical Parallel Algorithm to Enhance the Performance of Large-Scale Structural Analysis Based on Heterogeneous Multicore Clusters

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 135-155, 2023, DOI:10.32604/cmes.2023.025166
    Abstract Heterogeneous multicore clusters are becoming more popular for high-performance computing due to their great computing power and cost-to-performance effectiveness nowadays. Nevertheless, parallel efficiency degradation is still a problem in large-scale structural analysis based on heterogeneous multicore clusters. To solve it, a hybrid hierarchical parallel algorithm (HHPA) is proposed on the basis of the conventional domain decomposition algorithm (CDDA) and the parallel sparse solver. In this new algorithm, a three-layer parallelization of the computational procedure is introduced to enable the separation of the communication of inter-nodes, heterogeneous-core-groups (HCGs) and inside-heterogeneous-core-groups through mapping computing tasks to various hardware layers. This approach can… More >

  • Open Access

    ARTICLE

    Topic Controlled Steganography via Graph-to-Text Generation

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 157-176, 2023, DOI:10.32604/cmes.2023.025082
    Abstract Generation-based linguistic steganography is a popular research area of information hiding. The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to. However, in the course of our experiment, we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text, which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases, and that the topic of generated texts is uncontrollable, so there is still room for improvement in concealment. In this paper,… More >

  • Open Access

    ARTICLE

    Health Monitoring of Milling Tool Inserts Using CNN Architectures Trained by Vibration Spectrograms

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 177-199, 2023, DOI:10.32604/cmes.2023.025516
    Abstract In-process damage to a cutting tool degrades the surface finish of the job shaped by machining and causes a significant financial loss. This stimulates the need for Tool Condition Monitoring (TCM) to assist detection of failure before it extends to the worse phase. Machine Learning (ML) based TCM has been extensively explored in the last decade. However, most of the research is now directed toward Deep Learning (DL). The “Deep” formulation, hierarchical compositionality, distributed representation and end-to-end learning of Neural Nets need to be explored to create a generalized TCM framework to perform efficiently in a high-noise environment of cross-domain… More >

  • Open Access

    ARTICLE

    Design of a Computational Heuristic to Solve the Nonlinear Liénard Differential Model

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 201-221, 2023, DOI:10.32604/cmes.2023.025094
    Abstract In this study, the design of a computational heuristic based on the nonlinear Liénard model is presented using the efficiency of artificial neural networks (ANNs) along with the hybridization procedures of global and local search approaches. The global search genetic algorithm (GA) and local search sequential quadratic programming scheme (SQPS) are implemented to solve the nonlinear Liénard model. An objective function using the differential model and boundary conditions is designed and optimized by the hybrid computing strength of the GA-SQPS. The motivation of the ANN procedures along with GA-SQPS comes to present reliable, feasible and precise frameworks to tackle stiff… More >

  • Open Access

    ARTICLE

    DuFNet: Dual Flow Network of Real-Time Semantic Segmentation for Unmanned Driving Application of Internet of Things

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 223-239, 2023, DOI:10.32604/cmes.2023.024742
    (This article belongs to this Special Issue: Artificial Intelligence for Mobile Edge Computing in IoT)
    Abstract The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology. Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis. Semantic segmentation is also a challenging technology for image understanding and scene parsing. We focused on the challenging task of real-time semantic segmentation in this paper. In this paper, we proposed a novel fast architecture for real-time semantic segmentation named DuFNet. Starting from the existing work of Bilateral Segmentation Network (BiSeNet), DuFNet proposes a novel Semantic Information Flow (SIF) structure for context information… More >

    Graphic Abstract

    DuFNet: Dual Flow Network of Real-Time Semantic Segmentation for Unmanned Driving Application of Internet of Things

  • Open Access

    ARTICLE

    Vessels Segmentation in Angiograms Using Convolutional Neural Network: A Deep Learning Based Approach

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 241-255, 2023, DOI:10.32604/cmes.2023.019644
    (This article belongs to this Special Issue: Bio-inspired Computer Modelling: Theories and Applications in Engineering and Sciences)
    Abstract Coronary artery disease (CAD) has become a significant cause of heart attack, especially among those 40 years old or younger. There is a need to develop new technologies and methods to deal with this disease. Many researchers have proposed image processing-based solutions for CAD diagnosis, but achieving highly accurate results for angiogram segmentation is still a challenge. Several different types of angiograms are adopted for CAD diagnosis. This paper proposes an approach for image segmentation using Convolution Neural Networks (CNN) for diagnosing coronary artery disease to achieve state-of-the-art results. We have collected the 2D X-ray images from the hospital, and… More >

  • Open Access

    ARTICLE

    Stochastic Analysis for the Dynamics of a Poliovirus Epidemic Model

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 257-275, 2023, DOI:10.32604/cmes.2023.023231
    (This article belongs to this Special Issue: Bio-inspired Computer Modelling: Theories and Applications in Engineering and Sciences)
    Abstract Most developing countries such as Afghanistan, Pakistan, India, Bangladesh, and many more are still fighting against poliovirus. According to the World Health Organization, approximately eighteen million people have been infected with poliovirus in the last two decades. In Asia, still, some countries are suffering from the virus. The stochastic behavior of the poliovirus through the transition probabilities and non-parametric perturbation with fundamental properties are studied. Some basic properties of the deterministic model are studied, equilibria, local stability around the stead states, and reproduction number. Euler Maruyama, stochastic Euler, and stochastic Runge-Kutta study the behavior of complex stochastic differential equations. The… More >

  • Open Access

    ARTICLE

    Modifications of the Optimal Auxiliary Function Method to Fractional Order Fornberg-Whitham Equations

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 277-291, 2023, DOI:10.32604/cmes.2023.022289
    (This article belongs to this Special Issue: Fractal-Fractional Models for Engineering & Sciences)
    Abstract In this paper, we present a new modification of the newly developed semi-analytical method named the Optimal Auxilary Function Method (OAFM) for fractional-order equations using the Caputo operator, which is named FOAFM. The mathematical theory of FOAFM is presented and the effectiveness of this method is proven by using it with well-known Fornberg-Whitham Equations (FWE). The FOAFM results are compared with other method results along with their exact solutions with the help of tables and plots to prove the validity of FOAFM. A rapidly convergent series solution is obtained from FOAFM and is validated by comparison with other results. The… More >

  • Open Access

    ARTICLE

    Application of Zero-Watermarking for Medical Image in Intelligent Sensor Network Security

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 293-321, 2023, DOI:10.32604/cmes.2023.022308
    (This article belongs to this Special Issue: AI-Driven Engineering Applications)
    Abstract The field of healthcare is considered to be the most promising application of intelligent sensor networks. However, the security and privacy protection of medical images collected by intelligent sensor networks is a hot problem that has attracted more and more attention. Fortunately, digital watermarking provides an effective method to solve this problem. In order to improve the robustness of the medical image watermarking scheme, in this paper, we propose a novel zero-watermarking algorithm with the integer wavelet transform (IWT), Schur decomposition and image block energy. Specifically, we first use IWT to extract low-frequency information and divide them into non-overlapping blocks,… More >

  • Open Access

    ARTICLE

    Iris Liveness Detection Using Fragmental Energy of Haar Transformed Iris Images Using Ensemble of Machine Learning Classifiers

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 323-345, 2023, DOI:10.32604/cmes.2023.023674
    (This article belongs to this Special Issue: AI-Driven Engineering Applications)
    Abstract Contactless verification is possible with iris biometric identification, which helps prevent infections like COVID-19 from spreading. Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses, replayed the video, and print attacks. The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness. Seven assorted feature creation ways are studied in the presented solutions, and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.… More >

    Graphic Abstract

    Iris Liveness Detection Using Fragmental Energy of Haar Transformed Iris Images Using Ensemble of Machine Learning Classifiers

  • Open Access

    ARTICLE

    Differentiate Xp11.2 Translocation Renal Cell Carcinoma from Computed Tomography Images and Clinical Data with ResNet-18 CNN and XGBoost

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 347-362, 2023, DOI:10.32604/cmes.2023.024909
    (This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract This study aims to apply ResNet-18 convolutional neural network (CNN) and XGBoost to preoperative computed tomography (CT) images and clinical data for distinguishing Xp11.2 translocation renal cell carcinoma (Xp11.2 tRCC) from common subtypes of renal cell carcinoma (RCC) in order to provide patients with individualized treatment plans. Data from 45 patients with Xp11.2 tRCC from January 2007 to December 2021 are collected. Clear cell RCC (ccRCC), papillary RCC (pRCC), or chromophobe RCC (chRCC) can be detected from each patient. CT images are acquired in the following three phases: unenhanced, corticomedullary, and nephrographic. A unified framework is proposed for the classification… More >

  • Open Access

    ARTICLE

    Soft Tissue Feature Tracking Based on Deep Matching Network

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 363-379, 2023, DOI:10.32604/cmes.2023.025217
    (This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract Research in the field of medical image is an important part of the medical robot to operate human organs. A medical robot is the intersection of multi-disciplinary research fields, in which medical image is an important direction and has achieved fruitful results. In this paper, a method of soft tissue surface feature tracking based on a depth matching network is proposed. This method is described based on the triangular matching algorithm. First, we construct a self-made sample set for training the depth matching network from the first N frames of speckle matching data obtained by the triangle matching algorithm. The… More >

    Graphic Abstract

    Soft Tissue Feature Tracking Based on Deep Matching Network

  • Open Access

    ARTICLE

    MDNN: Predicting Student Engagement via Gaze Direction and Facial Expression in Collaborative Learning

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 381-401, 2023, DOI:10.32604/cmes.2023.023234
    (This article belongs to this Special Issue: Humanized Computing and Reasoning in Teaching and Learning)
    Abstract Prediction of students’ engagement in a Collaborative Learning setting is essential to improve the quality of learning. Collaborative learning is a strategy of learning through groups or teams. When cooperative learning behavior occurs, each student in the group should participate in teaching activities. Researchers showed that students who are actively involved in a class gain more. Gaze behavior and facial expression are important nonverbal indicators to reveal engagement in collaborative learning environments. Previous studies require the wearing of sensor devices or eye tracker devices, which have cost barriers and technical interference for daily teaching practice. In this paper, student engagement… More >

  • Open Access

    ARTICLE

    Qualia Role-Based Quantity Relation Extraction for Solving Algebra Story Problems

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 403-419, 2023, DOI:10.32604/cmes.2023.023242
    (This article belongs to this Special Issue: Humanized Computing and Reasoning in Teaching and Learning)
    Abstract A qualia role-based entity-dependency graph (EDG) is proposed to represent and extract quantity relations for solving algebra story problems stated in Chinese. Traditional neural solvers use end-to-end models to translate problem texts into math expressions, which lack quantity relation acquisition in sophisticated scenarios. To address the problem, the proposed method leverages EDG to represent quantity relations hidden in qualia roles of math objects. Algorithms were designed for EDG generation and quantity relation extraction for solving algebra story problems. Experimental result shows that the proposed method achieved an average accuracy of 82.2% on quantity relation extraction compared to 74.5% of baseline… More >

  • Open Access

    ARTICLE

    Lightweight Design of Commercial Vehicle Cab Based on Fatigue Durability

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 421-445, 2023, DOI:10.32604/cmes.2023.024133
    (This article belongs to this Special Issue: AI and Machine Learning Modeling in Civil and Building Engineering)
    Abstract To better improve the lightweight and fatigue durability performance of the tractor cab, a multi-objective lightweight design of the cab was carried out in this study. First, the finite element model of the cab with counterweight loading was established and then confirmed by the physical testing, and use the inertial relief method to obtain stress distribution under unit load. The cab-frame rigid-flexible coupling multi-body dynamics model was built by Adams/car software. Taking the cab airbag mount displacement and acceleration signals acquired on the proving ground as the desired signals and obtaining the fatigue analysis load spectrum through Femfat-Lab virtual iteration.… More >

    Graphic Abstract

    Lightweight Design of Commercial Vehicle Cab Based on Fatigue Durability

  • Open Access

    ARTICLE

    Structural Damage Identification System Suitable for Old Arch Bridge in Rural Regions: Random Forest Approach

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 447-469, 2023, DOI:10.32604/cmes.2023.022699
    (This article belongs to this Special Issue: AI and Machine Learning Modeling in Civil and Building Engineering)
    Abstract A huge number of old arch bridges located in rural regions are at the peak of maintenance. The health monitoring technology of the long-span bridge is hardly applicable to the small-span bridge, owing to the absence of technical resources and sufficient funds in rural regions. There is an urgent need for an economical, fast, and accurate damage identification solution. The authors proposed a damage identification system of an old arch bridge implemented with a machine learning algorithm, which took the vehicle-induced response as the excitation. A damage index was defined based on wavelet packet theory, and a machine learning sample… More >

  • Open Access

    ARTICLE

    A Convolutional Autoencoder Based Fault Detection Method for Metro Railway Turnout

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 471-485, 2023, DOI:10.32604/cmes.2023.024033
    (This article belongs to this Special Issue: AI and Machine Learning Modeling in Civil and Building Engineering)
    Abstract Railway turnout is one of the critical equipment of Switch & Crossing (S&C) Systems in railway, related to the train’s safety and operation efficiency. With the advancement of intelligent sensors, data-driven fault detection technology for railway turnout has become an important research topic. However, little research in the literature has investigated the capability of data-driven fault detection technology for metro railway turnout. This paper presents a convolutional autoencoder-based fault detection method for the metro railway turnout considering human field inspection scenarios. First, the one-dimensional original time-series signal is converted into a two-dimensional image by data pre-processing and 2D representation. Next,… More >

  • Open Access

    ARTICLE

    Non-Cooperative Behavior Management in Large-Scale Group Decision-Making Considering the Altruistic Behaviors of Experts and Its Application in Emergency Alternative Selection

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 487-515, 2023, DOI:10.32604/cmes.2023.024014
    (This article belongs to this Special Issue: Linguistic Approaches for Multiple Criteria Decision Making and Applications)
    Abstract Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns, leading to non-cooperative behaviors during the consensus-reaching process. Many studies on non-cooperative behavior management assumed that the maximum degree of cooperation of experts is to totally accept the revisions suggested by the moderator, which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process. In addition, when grouping a large group into subgroups by clustering methods, existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously. In this study, we introduce a… More >

  • Open Access

    ARTICLE

    Logformer: Cascaded Transformer for System Log Anomaly Detection

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 517-529, 2023, DOI:10.32604/cmes.2023.025774
    (This article belongs to this Special Issue: Information Security Practice and Experience: Advances and Challenges)
    Abstract Modern large-scale enterprise systems produce large volumes of logs that record detailed system runtime status and key events at key points. These logs are valuable for analyzing performance issues and understanding the status of the system. Anomaly detection plays an important role in service management and system maintenance, and guarantees the reliability and security of online systems. Logs are universal semi-structured data, which causes difficulties for traditional manual detection and pattern-matching algorithms. While some deep learning algorithms utilize neural networks to detect anomalies, these approaches have an over-reliance on manually designed features, resulting in the effectiveness of anomaly detection depending… More >

  • Open Access

    ARTICLE

    Secure Downlink Transmission Strategies against Active Eavesdropping in NOMA Systems: A Zero-Sum Game Approach

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 531-553, 2023, DOI:10.32604/cmes.2023.024531
    (This article belongs to this Special Issue: Cyberspace Intelligent Mapping and Situational Awareness)
    Abstract Non-orthogonal multiple access technology (NOMA), as a potentially promising technology in the 5G/B5G era, suffers from ubiquitous security threats due to the broadcast nature of the wireless medium. In this paper, we focus on artificial-signal-assisted and relay-assisted secure downlink transmission schemes against external eavesdropping in the context of physical layer security, respectively. To characterize the non-cooperative confrontation around the secrecy rate between the legitimate communication party and the eavesdropper, their interactions are modeled as a two-person zero-sum game. The existence of the Nash equilibrium of the proposed game models is proved, and the pure strategy Nash equilibrium and mixed-strategy Nash… More >

  • Open Access

    ARTICLE

    Aggregate Point Cloud Geometric Features for Processing

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 555-571, 2023, DOI:10.32604/cmes.2023.024470
    (This article belongs to this Special Issue: Recent Advances in Virtual Reality)
    Abstract As 3D acquisition technology develops and 3D sensors become increasingly affordable, large quantities of 3D point cloud data are emerging. How to effectively learn and extract the geometric features from these point clouds has become an urgent problem to be solved. The point cloud geometric information is hidden in disordered, unstructured points, making point cloud analysis a very challenging problem. To address this problem, we propose a novel network framework, called Tree Graph Network (TGNet), which can sample, group, and aggregate local geometric features. Specifically, we construct a Tree Graph by explicit rules, which consists of curves extending in all… More >

  • Open Access

    ARTICLE

    Monocular Depth Estimation with Sharp Boundary

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 573-592, 2023, DOI:10.32604/cmes.2023.023424
    (This article belongs to this Special Issue: Recent Advances in Virtual Reality)
    Abstract Monocular depth estimation is the basic task in computer vision. Its accuracy has tremendous improvement in the decade with the development of deep learning. However, the blurry boundary in the depth map is a serious problem. Researchers find that the blurry boundary is mainly caused by two factors. First, the low-level features, containing boundary and structure information, may be lost in deep networks during the convolution process. Second, the model ignores the errors introduced by the boundary area due to the few portions of the boundary area in the whole area, during the backpropagation. Focusing on the factors mentioned above.… More >

  • Open Access

    ARTICLE

    Topology Optimization for Steady-State Navier-Stokes Flow Based on Parameterized Level Set Based Method

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 593-619, 2023, DOI:10.32604/cmes.2023.023978
    (This article belongs to this Special Issue: New Trends in Structural Optimization)
    Abstract In this paper, we consider solving the topology optimization for steady-state incompressible Navier-Stokes problems via a new topology optimization method called parameterized level set method, which can maintain a relatively smooth level set function with a local optimality condition. The objective of topology optimization is to find an optimal configuration of the fluid and solid materials that minimizes power dissipation under a prescribed fluid volume fraction constraint. An artificial friction force is added to the Navier-Stokes equations to apply the no-slip boundary condition. Although a great deal of work has been carried out for topology optimization of fluid flow in… More >

  • Open Access

    ARTICLE

    A Spacecraft Equipment Layout Optimization Method for Diverse and Competitive Design

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 621-654, 2023, DOI:10.32604/cmes.2023.025143
    (This article belongs to this Special Issue: New Trends in Structural Optimization)
    Abstract The spacecraft equipment layout optimization design (SELOD) problems with complicated performance constraints and diversity are studied in this paper. The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases effectively. However, these local optimal solutions are too difficult to jump out of their current relative geometry relationships, significantly limiting their further improvement in performance indicators. Therefore, considering the geometric diversity of layout schemes is put forward to alleviate this limitation. First, similarity measures, including modified cosine similarity and gaussian kernel function similarity, are introduced into the layout optimization process. Then the optimization produces… More >

  • Open Access

    ARTICLE

    2D Minimum Compliance Topology Optimization Based on a Region Partitioning Strategy

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 655-683, 2023, DOI:10.32604/cmes.2023.025153
    (This article belongs to this Special Issue: New Trends in Structural Optimization)
    Abstract This paper presents an extended sequential element rejection and admission (SERA) topology optimization method with a region partitioning strategy. Based on the partitioning of a design domain into solid regions and weak regions, the proposed optimization method sequentially implements finite element analysis (FEA) in these regions. After standard FEA in the solid regions, the boundary displacement of the weak regions is constrained using the numerical solution of the solid regions as Dirichlet boundary conditions. This treatment can alleviate the negative effect of the material interpolation model of the topology optimization method in the weak regions, such as the condition number… More >

    Graphic Abstract

    2D Minimum Compliance Topology Optimization Based on a Region Partitioning Strategy

  • Open Access

    ARTICLE

    Ergonomic Reliability Assessment of VDT System for Operation Design Based on Improved BPNN and HCR under Special Circumstances

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 685-707, 2023, DOI:10.32604/cmes.2023.025058
    (This article belongs to this Special Issue: Computer-Aided Structural Integrity and Safety Assessment)
    Abstract Ergonomic reliability plays a significant role in the safe operation of devices. With the spread of infectious diseases around the world, in work environments with high loads and high infection rates, medical staff work in a state of high self-protection. The use of visual display terminal (VDT) for medical equipment has undergone fundamental changes, and the traditional medical equipment human-machine interface design needs to be improved. After the completion of design and development, a VDT design enters the experimental testing stage, which has significant limitations for simulating the work of medical staff in the high-load and high-infection environments. The testing… More >

  • Open Access

    ARTICLE

    Modeling, Analysis and Simulation of a High-Efficiency Battery Control System

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 709-732, 2023, DOI:10.32604/cmes.2023.024236
    (This article belongs to this Special Issue: Artificial Intelligence in Renewable Energy and Storage Systems)
    Abstract This paper explains step-by-step modeling and simulation of the full circuits of a battery control system and connected together starting from the AC input source to the battery control and storage system. The three-phase half-controlled rectifier has been designed to control and convert the AC power into DC power. In addition, two types of direct current converters have been used in this paper which are a buck and bidirectional DC/DC converters. These systems adjust the output voltage to be lower or higher than the input voltage. In the buck converters, the main switch operates in conduction or cut-off mode and… More >

  • Open Access

    ARTICLE

    Numerical Simulation Analysis of the Transformer Fire Extinguishing Process with a High-Pressure Water Mist System under Different Conditions

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 733-747, 2023, DOI:10.32604/cmes.2023.022155
    (This article belongs to this Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)
    Abstract To thoroughly study the extinguishing effect of a high-pressure water mist fire extinguishing system when a transformer fire occurs, a 3D experimental model of a transformer is established in this work by employing Fire Dynamics Simulator (FDS) software. More specifically, by setting different parameters, the process of the high-pressure water mist fire extinguishing system with the presence of both diverse ambient temperatures and water mist sprinkler laying conditions is simulated. In addition, the fire extinguishing effect of the employed high-pressure water mist system with the implementation of different strategies is systematically analyzed. The extracted results show that a fire source… More >

    Graphic Abstract

    Numerical Simulation Analysis of the Transformer Fire Extinguishing Process with a High-Pressure Water Mist System under Different Conditions

  • Open Access

    ARTICLE

    Short-Term Power Load Forecasting with Hybrid TPA-BiLSTM Prediction Model Based on CSSA

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 749-765, 2023, DOI:10.32604/cmes.2023.023865
    (This article belongs to this Special Issue: Models of Computation: Specification, Implementation and Challenges)
    Abstract Since the existing prediction methods have encountered difficulties in processing the multiple influencing factors in short-term power load forecasting, we propose a bidirectional long short-term memory (BiLSTM) neural network model based on the temporal pattern attention (TPA) mechanism. Firstly, based on the grey relational analysis, datasets similar to forecast day are obtained. Secondly, the bidirectional LSTM layer models the data of the historical load, temperature, humidity, and date-type and extracts complex relationships between data from the hidden row vectors obtained by the BiLSTM network, so that the influencing factors (with different characteristics) can select relevant information from different time steps… More >

  • Open Access

    ARTICLE

    Exploiting the Direct Link in IRS Assisted NOMA Networks with Hardware Impairments

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 767-785, 2023, DOI:10.32604/cmes.2023.025300
    (This article belongs to this Special Issue: Recent Advances in Backscatter and Intelligent Reflecting Surface Communications for 6G-enabled Internet of Things Networks)
    Abstract Hardware impairments (HI) are always present in low-cost wireless devices. This paper investigates the outage behaviors of intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) networks by taking into account the impact of HI. Specifically, we derive the approximate and asymptotic expressions of the outage probability for the IRS-NOMA-HI networks. Based on the asymptotic results, the diversity orders under perfect self-interference cancellation and imperfect self-interference cancellation scenarios are obtained to evaluate the performance of the considered network. In addition, the system throughput of IRS-NOMA-HI is discussed in delay-limited mode. The obtained results are provided to verify the accuracy of… More >

  • Open Access

    ARTICLE

    Image Semantic Segmentation for Autonomous Driving Based on Improved U-Net

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 787-801, 2023, DOI:10.32604/cmes.2023.025119
    (This article belongs to this Special Issue: Computing Methods for Industrial Artificial Intelligence)
    Abstract Image semantic segmentation has become an essential part of autonomous driving. To further improve the generalization ability and the robustness of semantic segmentation algorithms, a lightweight algorithm network based on Squeeze-and-Excitation Attention Mechanism (SE) and Depthwise Separable Convolution (DSC) is designed. Meanwhile, Adam-GC, an Adam optimization algorithm based on Gradient Compression (GC), is proposed to improve the training speed, segmentation accuracy, generalization ability and stability of the algorithm network. To verify and compare the effectiveness of the algorithm network proposed in this paper, the trained network model is used for experimental verification and comparative test on the Cityscapes semantic segmentation… More >

  • Open Access

    ARTICLE

    Isogeometric Analysis of Longitudinal Displacement of a Simplified Tunnel Model Based on Elastic Foundation Beam

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 803-824, 2023, DOI:10.32604/cmes.2023.024833
    (This article belongs to this Special Issue: Integration of Geometric Modeling and Numerical Simulation)
    Abstract Serious uneven settlement of the tunnel may directly cause safety problems. At this stage, the deformation of the tunnel is predicted and analyzed mainly by numerical simulation, while the commonly used finite element method (FEM) uses low-order continuous elements. Therefore, the accuracy of tunnel settlement prediction is not enough. In this paper, a method is proposed to study the vertical deformation of the tunnel by using the combination of isogeometric analysis (IGA) and Bézier extraction operator. Compared with the traditional IGA method, this method can be easily integrated into the existing FEM framework, and ensure the same accuracy. A numerical… More >

  • Open Access

    ARTICLE

    A Geometrically Exact Triangular Shell Element Based on Reproducing Kernel DMS-Splines

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 825-860, 2023, DOI:10.32604/cmes.2023.022774
    (This article belongs to this Special Issue: Integration of Geometric Modeling and Numerical Simulation)
    Abstract To model a multibody system composed of shell components, a geometrically exact Kirchhoff-Love triangular shell element is proposed. The middle surface of the shell element is described by using the DMS-splines, which can exactly represent arbitrary topology piecewise polynomial triangular surfaces. The proposed shell element employs only nodal displacement and can automatically maintain C1 continuity properties at the element boundaries. A reproducing DMS-spline kernel skill is also introduced to improve computation stability and accuracy. The proposed triangular shell element based on reproducing kernel DMS-splines can achieve an almost optimal convergent rate. Finally, the proposed shell element is validated via three… More >

    Graphic Abstract

    A Geometrically Exact Triangular Shell Element Based on Reproducing Kernel DMS-Splines

  • Open Access

    ARTICLE

    Multi-Source Data Privacy Protection Method Based on Homomorphic Encryption and Blockchain

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 861-881, 2023, DOI:10.32604/cmes.2023.025159
    (This article belongs to this Special Issue: Emerging Trends on Blockchain: Architecture and Dapp Ecosystem)
    Abstract Multi-Source data plays an important role in the evolution of media convergence. Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data. However, it also faces serious problems in terms of protecting user and data privacy. Many privacy protection methods have been proposed to solve the problem of privacy leakage during the process of data sharing, but they suffer from two flaws: 1) the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain; 2) the inability to solve… More >

    Graphic Abstract

    Multi-Source Data Privacy Protection Method Based on Homomorphic Encryption and Blockchain

  • Open Access

    ARTICLE

    Metric Identification of Vertices in Polygonal Cacti

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 883-899, 2023, DOI:10.32604/cmes.2023.025162
    (This article belongs to this Special Issue: Resolvability Parameters and their Applications)
    Abstract The distance between two vertices u and v in a connected graph G is the number of edges lying in a shortest path (geodesic) between them. A vertex x of G performs the metric identification for a pair (u, v) of vertices in G if and only if the equality between the distances of u and v with x implies that u = v (That is, the distance between u and x is different from the distance between v and x). The minimum number of vertices performing the metric identification for every pair of vertices in G defines the metric… More >

  • Open Access

    ARTICLE

    On Riemann-Type Weighted Fractional Operators and Solutions to Cauchy Problems

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 901-919, 2023, DOI:10.32604/cmes.2023.024029
    (This article belongs to this Special Issue: Applications of Fractional Operators in Modeling Real-world Problems: Theory, Computation, and Applications)
    Abstract In this paper, we establish the new forms of Riemann-type fractional integral and derivative operators. The novel fractional integral operator is proved to be bounded in Lebesgue space and some classical fractional integral and differential operators are obtained as special cases. The properties of new operators like semi-group, inverse and certain others are discussed and its weighted Laplace transform is evaluated. Fractional integro-differential free-electron laser (FEL) and kinetic equations are established. The solutions to these new equations are obtained by using the modified weighted Laplace transform. The Cauchy problem and a growth model are designed as applications along with graphical… More >

  • Open Access

    ARTICLE

    Study of Fractional Order Dynamical System of Viral Infection Disease under Piecewise Derivative

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 921-941, 2023, DOI:10.32604/cmes.2023.025769
    (This article belongs to this Special Issue: Applications of Fractional Operators in Modeling Real-world Problems: Theory, Computation, and Applications)
    Abstract This research aims to understand the fractional order dynamics of the deadly Nipah virus (NiV) disease. We focus on using piecewise derivatives in the context of classical and singular kernels of power operators in the Caputo sense to investigate the crossover behavior of the considered dynamical system. We establish some qualitative results about the existence and uniqueness of the solution to the proposed problem. By utilizing the Newtonian polynomials interpolation technique, we recall a powerful algorithm to interpret the numerical findings for the aforesaid model. Here, we remark that the said viral infection is caused by an RNA type virus… More >

    Graphic Abstract

    Study of Fractional Order Dynamical System of Viral Infection Disease under Piecewise Derivative

  • Open Access

    ARTICLE

    On the Mean Value of High-Powers of a Special Character Sum Modulo a Prime

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 943-953, 2023, DOI:10.32604/cmes.2023.024363
    (This article belongs to this Special Issue: Application of Computer Tools in the Study of Mathematical Problems)
    Abstract In this paper, we use the elementary methods, the properties of Dirichlet character sums and the classical Gauss sums to study the estimation of the mean value of high-powers for a special character sum modulo a prime, and derive an exact computational formula. It can be conveniently programmed by the “Mathematica” software, by which we can get the exact results easily. More >

  • Open Access

    ARTICLE

    Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 955-979, 2023, DOI:10.32604/cmes.2023.025021
    (This article belongs to this Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
    Abstract Information about the relative importance of each criterion or the weights of criteria can have a significant influence on the ultimate rank of alternatives. Accordingly, assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems. Three methods are commonly used for assessing the weights of criteria: objective, subjective, and integrated methods. In this study, an objective approach is proposed to assess the weights of criteria, called SPC method (Symmetry Point of Criterion). This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence… More >

    Graphic Abstract

    Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm

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