Home / Journals / CMES / Vol.136, No.3, 2023
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  • Open AccessOpen Access

    ARTICLE

    Interactive Restoration of Three-Dimensional Implicit Surface with Irregular Parts

    Jiayu Ren1,*, Yoshihisa Fujita2, Susumu Nakata2
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2111-2125, 2023, DOI:10.32604/cmes.2023.025970 - 09 March 2023
    Abstract Implicit surface generation based on the interpolation of surface points is one of the well-known modeling methods in the area of computer graphics. Several methods for the implicit surface reconstruction from surface points have been proposed on the basis of radial basis functions, a weighted sum of local functions, splines, wavelets, and combinations of them. However, if the surface points contain errors or are sparsely distributed, irregular components, such as curvature-shaped redundant bulges and unexpectedly generated high-frequency components, are commonly seen. This paper presents a framework for restoring irregular components generated on and around surfaces. More >

  • Open AccessOpen Access

    REVIEW

    A Survey of Convolutional Neural Network in Breast Cancer

    Ziquan Zhu, Shui-Hua Wang, Yu-Dong Zhang*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2127-2172, 2023, DOI:10.32604/cmes.2023.025484 - 09 March 2023
    (This article belongs to the Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract Problems: For people all over the world, cancer is one of the most feared diseases. Cancer is one of the major obstacles to improving life expectancy in countries around the world and one of the biggest causes of death before the age of 70 in 112 countries. Among all kinds of cancers, breast cancer is the most common cancer for women. The data showed that female breast cancer had become one of the most common cancers. Aims: A large number of clinical trials have proved that if breast cancer is diagnosed at an early stage, it… More >

    Graphic Abstract

    A Survey of Convolutional Neural Network in Breast Cancer

  • Open AccessOpen Access

    REVIEW

    Application of U-Net and Optimized Clustering in Medical Image Segmentation: A Review

    Jiaqi Shao1,#, Shuwen Chen1,2,3,#,*, Jin Zhou1,#, Huisheng Zhu1, Ziyi Wang1, Mackenzie Brown4,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2173-2219, 2023, DOI:10.32604/cmes.2023.025499 - 09 March 2023
    (This article belongs to the Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract As a mainstream research direction in the field of image segmentation, medical image segmentation plays a key role in the quantification of lesions, three-dimensional reconstruction, region of interest extraction and so on. Compared with natural images, medical images have a variety of modes. Besides, the emphasis of information which is conveyed by images of different modes is quite different. Because it is time-consuming and inefficient to manually segment medical images only by professional and experienced doctors. Therefore, large quantities of automated medical image segmentation methods have been developed. However, until now, researchers have not developed… More >

  • Open AccessOpen Access

    ARTICLE

    Research on Short-Term Load Forecasting of Distribution Stations Based on the Clustering Improvement Fuzzy Time Series Algorithm

    Jipeng Gu1, Weijie Zhang1, Youbing Zhang1,*, Binjie Wang1, Wei Lou2, Mingkang Ye3, Linhai Wang3, Tao Liu4
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2221-2236, 2023, DOI:10.32604/cmes.2023.025396 - 09 March 2023
    Abstract An improved fuzzy time series algorithm based on clustering is designed in this paper. The algorithm is successfully applied to short-term load forecasting in the distribution stations. Firstly, the K-means clustering method is used to cluster the data, and the midpoint of two adjacent clustering centers is taken as the dividing point of domain division. On this basis, the data is fuzzed to form a fuzzy time series. Secondly, a high-order fuzzy relation with multiple antecedents is established according to the main measurement indexes of power load, which is used to predict the short-term trend More >

  • Open AccessOpen Access

    ARTICLE

    Adaptive Boundary and Semantic Composite Segmentation Method for Individual Objects in Aerial Images

    Ying Li1,2, Guanghong Gong1, Dan Wang1, Ni Li1,3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2237-2265, 2023, DOI:10.32604/cmes.2023.025193 - 09 March 2023
    Abstract There are two types of methods for image segmentation. One is traditional image processing methods, which are sensitive to details and boundaries, yet fail to recognize semantic information. The other is deep learning methods, which can locate and identify different objects, but boundary identifications are not accurate enough. Both of them cannot generate entire segmentation information. In order to obtain accurate edge detection and semantic information, an Adaptive Boundary and Semantic Composite Segmentation method (ABSCS) is proposed. This method can precisely semantic segment individual objects in large-size aerial images with limited GPU performances. It includes… More >

    Graphic Abstract

    Adaptive Boundary and Semantic Composite Segmentation Method for Individual Objects in Aerial Images

  • Open AccessOpen Access

    ARTICLE

    A Double Adaptive Random Spare Reinforced Sine Cosine Algorithm

    Abdelazim G. Hussien1,2, Guoxi Liang3, Huiling Chen4,*, Haiping Lin5,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2267-2289, 2023, DOI:10.32604/cmes.2023.024247 - 09 March 2023
    Abstract Many complex optimization problems in the real world can easily fall into local optimality and fail to find the optimal solution, so more new techniques and methods are needed to solve such challenges. Metaheuristic algorithms have received a lot of attention in recent years because of their efficient performance and simple structure. Sine Cosine Algorithm (SCA) is a recent Metaheuristic algorithm that is based on two trigonometric functions Sine & Cosine. However, like all other metaheuristic algorithms, SCA has a slow convergence and may fail in sub-optimal regions. In this study, an enhanced version of More >

  • Open AccessOpen Access

    ARTICLE

    Automated Classification of Snow-Covered Solar Panel Surfaces Based on Deep Learning Approaches

    Abdullah Ahmed Al-Dulaimi1,*, Muhammet Tahir Guneser1, Alaa Ali Hameed2, Mohammad Shukri Salman3
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2291-2319, 2023, DOI:10.32604/cmes.2023.026065 - 09 March 2023
    Abstract Recently, the demand for renewable energy has increased due to its environmental and economic needs. Solar panels are the mainstay for dealing with solar energy and converting it into another form of usable energy. Solar panels work under suitable climatic conditions that allow the light photons to access the solar cells, as any blocking of sunlight on these cells causes a halt in the panels work and restricts the carry of these photons. Thus, the panels are unable to work under these conditions. A layer of snow forms on the solar panels due to snowfall… More >

    Graphic Abstract

    Automated Classification of Snow-Covered Solar Panel Surfaces Based on Deep Learning Approaches

  • Open AccessOpen Access

    ARTICLE

    A Systematic Approach for Exploring Underground Environment Using LiDAR-Based System

    Tareq Alhmiedat1,2,*, Ashraf M. Marei1,2, Saleh Albelwi1,2, Anas Bushnag2, Wassim Messoudi2, Abdelrahman Osman Elfaki2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2321-2344, 2023, DOI:10.32604/cmes.2023.025641 - 09 March 2023
    Abstract Agricultural projects in different parts of the world depend on underground water wells. Recently, there have been many unfortunate incidents in which children have died in abandoned underground wells. Providing topographical information for these wells is a prerequisite to protecting people from the dangers of falling into them, especially since most of these wells become buried over time. Many solutions have been developed recently, most with the aim of exploring these well areas. However, these systems suffer from several limitations, including high complexity, large size, or inefficiency. This paper focuses on the development of a… More >

  • Open AccessOpen Access

    ARTICLE

    Research on Adaptive TSSA-HKRVM Model for Regression Prediction of Crane Load Spectrum

    Dong Qing1,*, Qi Song1, Shuangyun Huang2, Gening Xu1
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2345-2370, 2023, DOI:10.32604/cmes.2023.026552 - 09 March 2023
    Abstract For the randomness of crane working load leading to the decrease of load spectrum prediction accuracy with time, an adaptive TSSA-HKRVM model for crane load spectrum regression prediction is proposed. The heterogeneous kernel relevance vector machine model (HKRVM) with comprehensive expression ability is established using the complementary advantages of various kernel functions. The combination strategy consisting of refraction reverse learning, golden sine, and Cauchy mutation + logistic chaotic perturbation is introduced to form a multi-strategy improved sparrow algorithm (TSSA), thus optimizing the relevant parameters of HKRVM. The adaptive updating mechanism of the heterogeneous kernel RVM… More >

  • Open AccessOpen Access

    ARTICLE

    On a Novel Extended Lomax Distribution with Asymmetric Properties and Its Statistical Applications

    Aisha Fayomi1, Christophe Chesneau2,*, Farrukh Jamal3, Ali Algarni1
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2371-2403, 2023, DOI:10.32604/cmes.2023.027000 - 09 March 2023
    Abstract In this article, we highlight a new three-parameter heavy-tailed lifetime distribution that aims to extend the modeling possibilities of the Lomax distribution. It is called the extended Lomax distribution. The considered distribution naturally appears as the distribution of a transformation of a random variable following the logweighted power distribution recently introduced for percentage or proportion data analysis purposes. As a result, its cumulative distribution has the same functional basis as that of the Lomax distribution, but with a novel special logarithmic term depending on several parameters. The modulation of this logarithmic term reveals new types… More >

  • Open AccessOpen Access

    ARTICLE

    Anomaly Detection of UAV State Data Based on Single-Class Triangular Global Alignment Kernel Extreme Learning Machine

    Feisha Hu1, Qi Wang1,*, Haijian Shao1,2, Shang Gao1, Hualong Yu1
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2405-2424, 2023, DOI:10.32604/cmes.2023.026732 - 09 March 2023
    Abstract Unmanned Aerial Vehicles (UAVs) are widely used and meet many demands in military and civilian fields. With the continuous enrichment and extensive expansion of application scenarios, the safety of UAVs is constantly being challenged. To address this challenge, we propose algorithms to detect anomalous data collected from drones to improve drone safety. We deployed a one-class kernel extreme learning machine (OCKELM) to detect anomalies in drone data. By default, OCKELM uses the radial basis (RBF) kernel function as the kernel function of the model. To improve the performance of OCKELM, we choose a Triangular Global More >

    Graphic Abstract

    Anomaly Detection of UAV State Data Based on Single-Class Triangular Global Alignment Kernel Extreme Learning Machine

  • Open AccessOpen Access

    ARTICLE

    Many-Objective Optimization-Based Task Scheduling in Hybrid Cloud Environments

    Mengkai Zhao1, Zhixia Zhang2, Tian Fan1, Wanwan Guo1, Zhihua Cui1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2425-2450, 2023, DOI:10.32604/cmes.2023.026671 - 09 March 2023
    Abstract Due to the security and scalability features of hybrid cloud architecture, it can better meet the diverse requirements of users for cloud services. And a reasonable resource allocation solution is the key to adequately utilize the hybrid cloud. However, most previous studies have not comprehensively optimized the performance of hybrid cloud task scheduling, even ignoring the conflicts between its security privacy features and other requirements. Based on the above problems, a many-objective hybrid cloud task scheduling optimization model (HCTSO) is constructed combining risk rate, resource utilization, total cost, and task completion time. Meanwhile, an opposition-based More >

  • Open AccessOpen Access

    ARTICLE

    A Novel Method to Enhance the Inversion Speed and Precision of the NMR T2 Spectrum by the TSVD Based Linearized Bregman Iteration

    Yiguo Chen1,2,3,*, Congjun Feng1,2, Yonghong He3, Zhijun Chen3, Xiaowei Fan3, Chao Wang3, Xinmin Ge4
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2451-2463, 2023, DOI:10.32604/cmes.2023.021145 - 09 March 2023
    (This article belongs to the Special Issue: Modeling of Fluids Flow in Unconventional Reservoirs)
    Abstract The low-field nuclear magnetic resonance (NMR) technique has been used to probe the pore size distribution and the fluid composition in geophysical prospecting and related fields. However, the speed and accuracy of the existing numerical inversion methods are still challenging due to the ill-posed nature of the first kind Fredholm integral equation and the contamination of the noises. This paper proposes a novel inversion algorithm to accelerate the convergence and enhance the precision using empirical truncated singular value decompositions (TSVD) and the linearized Bregman iteration. The L1 penalty term is applied to construct the objective More >

    Graphic Abstract

    A Novel Method to Enhance the Inversion Speed and Precision of the NMR T<sub>2</sub> Spectrum by the TSVD Based Linearized Bregman Iteration

  • Open AccessOpen Access

    ARTICLE

    SepFE: Separable Fusion Enhanced Network for Retinal Vessel Segmentation

    Yun Wu1, Ge Jiao1,2,*, Jiahao Liu1
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2465-2485, 2023, DOI:10.32604/cmes.2023.026189 - 09 March 2023
    (This article belongs to the Special Issue: Artificial Intelligence for Mobile Edge Computing in IoT)
    Abstract The accurate and automatic segmentation of retinal vessels from fundus images is critical for the early diagnosis and prevention of many eye diseases, such as diabetic retinopathy (DR). Existing retinal vessel segmentation approaches based on convolutional neural networks (CNNs) have achieved remarkable effectiveness. Here, we extend a retinal vessel segmentation model with low complexity and high performance based on U-Net, which is one of the most popular architectures. In view of the excellent work of depth-wise separable convolution, we introduce it to replace the standard convolutional layer. The complexity of the proposed model is reduced… More >

  • Open AccessOpen Access

    ARTICLE

    A Study on the Nonlinear Caputo-Type Snakebite Envenoming Model with Memory

    Pushpendra Kumar1,*, Vedat Suat Erturk2, V. Govindaraj1, Dumitru Baleanu3,4,5
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2487-2506, 2023, DOI:10.32604/cmes.2023.026009 - 09 March 2023
    (This article belongs to the Special Issue: Advanced Numerical Methods for Fractional Differential Equations)
    Abstract In this article, we introduce a nonlinear Caputo-type snakebite envenoming model with memory. The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractional-order sense. The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector (L1-PC) scheme with error estimation and stability analysis. The proof of the existence and positivity of the solution is given by using the fixed point theory. From the necessary simulations, we justify that the first-time implementation of the proposed method on an epidemic model shows that the scheme More >

  • Open AccessOpen Access

    ARTICLE

    Predicting the Thickness of an Excavation Damaged Zone around the Roadway Using the DA-RF Hybrid Model

    Yuxin Chen1, Weixun Yong1, Chuanqi Li2, Jian Zhou1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2507-2526, 2023, DOI:10.32604/cmes.2023.025714 - 09 March 2023
    (This article belongs to the Special Issue: Computational Intelligent Systems for Solving Complex Engineering Problems: Principles and Applications)
    Abstract After the excavation of the roadway, the original stress balance is destroyed, resulting in the redistribution of stress and the formation of an excavation damaged zone (EDZ) around the roadway. The thickness of EDZ is the key basis for roadway stability discrimination and support structure design, and it is of great engineering significance to accurately predict the thickness of EDZ. Considering the advantages of machine learning (ML) in dealing with high-dimensional, nonlinear problems, a hybrid prediction model based on the random forest (RF) algorithm is developed in this paper. The model used the dragonfly algorithm… More >

  • Open AccessOpen Access

    ARTICLE

    Novel Hybrid XGBoost Model to Forecast Soil Shear Strength Based on Some Soil Index Tests

    Ehsan Momeni1, Biao He2, Yasin Abdi3,*, Danial Jahed Armaghani4
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2527-2550, 2023, DOI:10.32604/cmes.2023.026531 - 09 March 2023
    (This article belongs to the Special Issue: Computational Intelligent Systems for Solving Complex Engineering Problems: Principles and Applications)
    Abstract When building geotechnical constructions like retaining walls and dams is of interest, one of the most important factors to consider is the soil’s shear strength parameters. This study makes an effort to propose a novel predictive model of shear strength. The study implements an extreme gradient boosting (XGBoost) technique coupled with a powerful optimization algorithm, the salp swarm algorithm (SSA), to predict the shear strength of various soils. To do this, a database consisting of 152 sets of data is prepared where the shear strength (τ) of the soil is considered as the model output… More >

  • Open AccessOpen Access

    ARTICLE

    Three Dimensional Coupling between Elastic and Thermal Fields in the Static Analysis of Multilayered Composite Shells

    Salvatore Brischetto*, Roberto Torre, Domenico Cesare
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2551-2594, 2023, DOI:10.32604/cmes.2023.026312 - 09 March 2023
    (This article belongs to the Special Issue: Theoretical and Computational Modeling of Advanced Materials and Structures)
    Abstract This new work aims to develop a full coupled thermomechanical method including both the temperature profile and displacements as primary unknowns of the model. This generic full coupled 3D exact shell model permits the thermal stress investigation of laminated isotropic, composite and sandwich structures. Cylindrical and spherical panels, cylinders and plates are analyzed in orthogonal mixed curved reference coordinates. The 3D equilibrium relations and the 3D Fourier heat conduction equation for spherical shells are coupled and they trivially can be simplified in those for plates and cylindrical panels. The exponential matrix methodology is used to… More >

  • Open AccessOpen Access

    ARTICLE

    COVID-19 Detection Based on 6-Layered Explainable Customized Convolutional Neural Network

    Jiaji Wang1,#, Shuwen Chen1,2,3,#,*, Yu Cao1,#, Huisheng Zhu1, Dimas Lima4,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2595-2616, 2023, DOI:10.32604/cmes.2023.025804 - 09 March 2023
    (This article belongs to the Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
    Abstract This paper presents a 6-layer customized convolutional neural network model (6L-CNN) to rapidly screen out patients with COVID-19 infection in chest CT images. This model can effectively detect whether the target CT image contains images of pneumonia lesions. In this method, 6L-CNN was trained as a binary classifier using the dataset containing CT images of the lung with and without pneumonia as a sample. The results show that the model improves the accuracy of screening out COVID-19 patients. Compared to other methods, the performance is better. In addition, the method can be extended to other More >

  • Open AccessOpen Access

    ARTICLE

    Adaptive Backdoor Attack against Deep Neural Networks

    Honglu He, Zhiying Zhu, Xinpeng Zhang*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2617-2633, 2023, DOI:10.32604/cmes.2023.025923 - 09 March 2023
    (This article belongs to the Special Issue: Cyberspace Intelligent Mapping and Situational Awareness)
    Abstract In recent years, the number of parameters of deep neural networks (DNNs) has been increasing rapidly. The training of DNNs is typically computation-intensive. As a result, many users leverage cloud computing and outsource their training procedures. Outsourcing computation results in a potential risk called backdoor attack, in which a welltrained DNN would perform abnormally on inputs with a certain trigger. Backdoor attacks can also be classified as attacks that exploit fake images. However, most backdoor attacks design a uniform trigger for all images, which can be easily detected and removed. In this paper, we propose… More >

  • Open AccessOpen Access

    ARTICLE

    STPGTN–A Multi-Branch Parameters Identification Method Considering Spatial Constraints and Transient Measurement Data

    Shuai Zhang, Liguo Weng*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2635-2654, 2023, DOI:10.32604/cmes.2023.025405 - 09 March 2023
    (This article belongs to the Special Issue: Machine Learning-Guided Intelligent Modeling with Its Industrial Applications)
    Abstract Transmission line (TL) Parameter Identification (PI) method plays an essential role in the transmission system. The existing PI methods usually have two limitations: (1) These methods only model for single TL, and can not consider the topology connection of multiple branches for simultaneous identification. (2) Transient bad data is ignored by methods, and the random selection of terminal section data may cause the distortion of PI and have serious consequences. Therefore, a multi-task PI model considering multiple TLs’ spatial constraints and massive electrical section data is proposed in this paper. The Graph Attention Network module More >

    Graphic Abstract

    STPGTN–A Multi-Branch Parameters Identification Method Considering Spatial Constraints and Transient Measurement Data

  • Open AccessOpen Access

    ARTICLE

    Numerical Simulation of Low Cycle Fatigue Behavior of Ti2AlNb Alloy Subcomponents

    Yanju Wang1, Zhenyu Zhu2, Aixue Sha1, Wenfeng Hao3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2655-2676, 2023, DOI:10.32604/cmes.2023.025749 - 09 March 2023
    (This article belongs to the Special Issue: Mechanical Reliability of Advanced Materials and Structures for Harsh Applications)
    Abstract Many titanium alloy subcomponents are subjected to fatigue loading in aerospace engineering, resulting in fatigue failure. The fatigue behavior of Ti2AlNb alloy subcomponents was investigated based on the Seeger fatigue life theory and the improved Lemaitre damage evolution theory. Firstly, the finite element models of the standard openhole specimen and Y-section subcomponents have been established by ABAQUS. The damage model parameters were determined by fatigue tests, and the reliability of fatigue life simulation results of the Ti2AlNb alloy standard open-hole specimen was verified. Meanwhile, the fatigue life of Ti2AlNb alloy Y-section subcomponents was predicted. Under the same More >

  • Open AccessOpen Access

    ARTICLE

    Boundary Element Analysis for Mode III Crack Problems of Thin-Walled Structures from Micro- to Nano-Scales

    Bingrui Ju1, Wenzhen Qu1,2,*, Yan Gu1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2677-2690, 2023, DOI:10.32604/cmes.2023.025886 - 09 March 2023
    (This article belongs to the Special Issue: Advances on Mesh and Dimension Reduction Methods)
    Abstract This paper develops a new numerical framework for mode III crack problems of thin-walled structures by integrating multiple advanced techniques in the boundary element literature. The details of special crack-tip elements for displacement and stress are derived. An exponential transformation technique is introduced to accurately calculate the nearly singular integral, which is the key task of the boundary element simulation of thin-walled structures. Three numerical experiments with different types of cracks are provided to verify the performance of the present numerical framework. Numerical results demonstrate that the present scheme is valid for mode III crack More >

  • Open AccessOpen Access

    ARTICLE

    Refined Aerodynamic Test of Wide-Bodied Aircraft and Its Application

    Dawei Liu, Zhiwei Jin, Xin Peng*, Gang Liu, Yue Zhang
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2691-2713, 2023, DOI:10.32604/cmes.2023.026048 - 09 March 2023
    (This article belongs to the Special Issue: Vibration Control and Utilization)
    Abstract The large dual-channel wide-bodied aircraft has a long range and a high cruise Mach number. Therefore, its aerodynamic design requires a high level of wind tunnel test refinement. Based on the requirements of aerodynamic design for the future wide-bodied aircraft and the characteristics of high-speed wind tunnel tests, the error theory is introduced to analyze the factors affecting the accuracy of the test data. This study carries out a series of research on the improvement of refined aerodynamic test technology in an FL-26 wind tunnel, including design and optimization of the support system of wide-bodied… More >

  • Open AccessOpen Access

    ARTICLE

    ABAQUS and ANSYS Implementations of the Peridynamics-Based Finite Element Method (PeriFEM) for Brittle Fractures

    Fei Han*, Zhibin Li, Jianyu Zhang, Zhiying Liu, Chen Yao, Wenping Han
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2715-2740, 2023, DOI:10.32604/cmes.2023.026922 - 09 March 2023
    (This article belongs to the Special Issue: Peridynamics and its Current Progress)
    Abstract In this study, we propose the first unified implementation strategy for peridynamics in commercial finite element method (FEM) software packages based on their application programming interface using the peridynamics-based finite element method (PeriFEM). Using ANSYS and ABAQUS as examples, we present the numerical results and implementation details of PeriFEM in commercial FEM software. PeriFEM is a reformulation of the traditional FEM for solving peridynamic equations numerically. It is considered that the non-local features of peridynamics yet possesses the same computational framework as the traditional FEM. Therefore, this implementation benefits from the consistent computational frameworks of… More >

  • Open AccessOpen Access

    ARTICLE

    HVAC Optimal Control Based on the Sensitivity Analysis: An Improved SA Combination Method Based on a Neural Network

    Lifan Zhao1,2, Zetian Huang1,2, Qiming Fu1,2,3,*, Nengwei Fang4, Bin Xing4, Jianping Chen2,3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2741-2758, 2023, DOI:10.32604/cmes.2023.025500 - 09 March 2023
    (This article belongs to the Special Issue: Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
    Abstract Aiming at optimizing the energy consumption of HVAC, an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis (SA), named the sensitivity analysis combination method (SAC). Based on the SA, neural network and the related settings about energy conservation of HVAC systems, such as cooling water temperature, chilled water temperature and supply air temperature, were optimized. Moreover, based on the data of the existing HVAC system, various optimal control methods of HVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS. The results show that the proposed More >

  • Open AccessOpen Access

    ARTICLE

    MAQMC: Multi-Agent Deep Q-Network for Multi-Zone Residential HVAC Control

    Zhengkai Ding1,2, Qiming Fu1,2,*, Jianping Chen2,3,4,*, You Lu1,2, Hongjie Wu1, Nengwei Fang4, Bin Xing4
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2759-2785, 2023, DOI:10.32604/cmes.2023.026091 - 09 March 2023
    (This article belongs to the Special Issue: Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
    Abstract The optimization of multi-zone residential heating, ventilation, and air conditioning (HVAC) control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads. Deep reinforcement learning (DRL) methods have recently been proposed to address the HVAC control problem. However, the application of single-agent DRL for multi-zone residential HVAC control may lead to non-convergence or slow convergence. In this paper, we propose MAQMC (Multi-Agent deep Q-network for multi-zone residential HVAC Control) to address this challenge with the goal of minimizing energy consumption while maintaining occupants’ thermal comfort. MAQMC… More >

  • Open AccessOpen Access

    ARTICLE

    Adaptive Time Slot Resource Allocation in SWIPT IoT Networks

    Yunong Yang1, Yuexia Zhang2,3,*, Zhihai Zhuo2
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2787-2813, 2023, DOI:10.32604/cmes.2023.027351 - 09 March 2023
    (This article belongs to the Special Issue: Recent Advances in Backscatter and Intelligent Reflecting Surface Communications for 6G-enabled Internet of Things Networks)
    Abstract The rapid advancement of Internet of Things (IoT) technology has brought convenience to people’s lives; however further development of IoT faces serious challenges, such as limited energy and shortage of network spectrum resources. To address the above challenges, this study proposes a simultaneous wireless information and power transfer IoT adaptive time slot resource allocation (SIATS) algorithm. First, an adaptive time slot consisting of periods for sensing, information transmission, and energy harvesting is designed to ensure that the minimum energy harvesting requirement is met while the maximum uplink and downlink throughputs are obtained. Second, the optimal… More >

  • Open AccessOpen Access

    ARTICLE

    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

    Min Hu1,2,3, Zhimin Chen4, Yuan Xia4, Liping Zhang1,2,3,*, Qiuhua Tang1,2,3
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2815-2840, 2023, DOI:10.32604/cmes.2023.027146 - 09 March 2023
    (This article belongs to the Special Issue: Computing Methods for Industrial Artificial Intelligence)
    Abstract The multi-skill resource-constrained project scheduling problem (MS-RCPSP) is a significant management science problem that extends from the resource-constrained project scheduling problem (RCPSP) and is integrated with a real project and production environment. To solve MS-RCPSP, it is an efficient method to use dispatching rules combined with a parallel scheduling mechanism to generate a scheduling scheme. This paper proposes an improved gene expression programming (IGEP) approach to explore newly dispatching rules that can broadly solve MS-RCPSP. A new backward traversal decoding mechanism, and several neighborhood operators are applied in IGEP. The backward traversal decoding mechanism dramatically More >

    Graphic Abstract

    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

  • Open AccessOpen Access

    ARTICLE

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

    Wenchao Yi, Zhilei Lin, Yong Chen, Zhi Pei*, Jiansha Lu
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2841-2860, 2023, DOI:10.32604/cmes.2023.027055 - 09 March 2023
    (This article belongs to the Special Issue: Computing Methods for Industrial Artificial Intelligence)
    Abstract Effective constrained optimization algorithms have been proposed for engineering problems recently. It is common to consider constraint violation and optimization algorithm as two separate parts. In this study, a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems. Based on the improved pbest selection method, an adaptive differential evolution approach is proposed, which helps the population jump out of the infeasible region. If all the individuals are infeasible, the top 5% of infeasible individuals are selected. In addition, a modified truncated ε-level method is proposed to avoid trapping in infeasible More >

    Graphic Abstract

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

  • Open AccessOpen Access

    ARTICLE

    A New Kind of Generalized Pythagorean Fuzzy Soft Set and Its Application in Decision-Making

    Xiaoyan Wang1, Ahmed Mostafa Khalil2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2861-2871, 2023, DOI:10.32604/cmes.2023.026021 - 09 March 2023
    (This article belongs to the Special Issue: Decision making Modeling, Methods and Applications of Advanced Fuzzy Theory in Engineering and Science)
    Abstract The aim of this paper is to introduce the concept of a generalized Pythagorean fuzzy soft set (GPFSS), which is a combination of the generalized fuzzy soft sets and Pythagorean fuzzy sets. Several of important operations of GPFSS including complement, restricted union, and extended intersection are discussed. The basic properties of GPFSS are presented. Further, an algorithm of GPFSSs is given to solve the fuzzy soft decision-making. Finally, a comparative analysis between the GPFSS approach and some existing approaches is provided to show their reliability over them. More >

  • Open AccessOpen Access

    ARTICLE

    Floyd-Warshall Algorithm Based on Picture Fuzzy Information

    Shaista Habib1, Aqsa Majeed1, Muhammad Akram2,*, Mohammed M. Ali Al-Shamiri3,4
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2873-2894, 2023, DOI:10.32604/cmes.2023.026294 - 09 March 2023
    (This article belongs to the Special Issue: Decision making Modeling, Methods and Applications of Advanced Fuzzy Theory in Engineering and Science)
    Abstract The Floyd-Warshall algorithm is frequently used to determine the shortest path between any pair of nodes. It works well for crisp weights, but the problem arises when weights are vague and uncertain. Let us take an example of computer networks, where the chosen path might no longer be appropriate due to rapid changes in network conditions. The optimal path from among all possible courses is chosen in computer networks based on a variety of parameters. In this paper, we design a new variant of the Floyd-Warshall algorithm that identifies an All-Pair Shortest Path (APSP) in More >

    Graphic Abstract

    Floyd-Warshall Algorithm Based on Picture Fuzzy Information

  • Open AccessOpen Access

    ARTICLE

    Behavioral Decision-Making of Key Stakeholders in Public-Private Partnerships: A Hybrid Method and Benefit Distribution Study

    Guoshuai Sun1,2,3, Wanyi Zhang1, Jiuying Dong4,*, Shuping Wan2, Jiao Feng5
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2895-2934, 2023, DOI:10.32604/cmes.2023.025652 - 09 March 2023
    (This article belongs to the Special Issue: Decision making Modeling, Methods and Applications of Advanced Fuzzy Theory in Engineering and Science)
    Abstract Public-private partnerships (PPPs) have been used by governments around the world to procure and construct infrastructural amenities. It relies on private sector expertise and funding to achieve this lofty objective. However, given the uncertainties of project management, transparency, accountability, and expropriation, this phenomenon has gained tremendous attention in recent years due to the important role it plays in curbing infrastructural deficits globally. Interestingly, the reasonable benefit distribution scheme in a PPP project is related to the behavior decision-making of the government and social capital, as well as the performance of the project. In this paper,… More >

  • Open AccessOpen Access

    ARTICLE

    AWSD: An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

    Xiang Su1, Nan Li1,*, Yuedi Hu1, Haisheng Li2
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2935-2956, 2023, DOI:10.32604/cmes.2023.026083 - 09 March 2023
    (This article belongs to the Special Issue: Integration of Geometric Modeling and Numerical Simulation)
    Abstract This paper introduces an aircraft wing simulation data set (AWSD) created by an automatic workflow based on creating models, meshing, simulating the wing flight flow field solution, and parameterizing solution results. AWSD is a flexible, independent wing collection of simulations with specific engineering requirements. The data set is applicable to handle computer geometry processing tasks. In contrast to the existing 3D model data set, there are some advantages the scale of this data set is not limited by the collection source, the data files have high quality, no defects, redundancy, and other problems, and the… More >

    Graphic Abstract

    AWSD: An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

  • Open AccessOpen Access

    ARTICLE

    New Perspective to Isogeometric Analysis: Solving Isogeometric Analysis Problem by Fitting Load Function

    Jingwen Ren1, Hongwei Lin1,2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2957-2984, 2023, DOI:10.32604/cmes.2023.025983 - 09 March 2023
    (This article belongs to the Special Issue: Integration of Geometric Modeling and Numerical Simulation)
    Abstract Isogeometric analysis (IGA) is introduced to establish the direct link between computer-aided design and analysis. It is commonly implemented by Galerkin formulations (isogeometric Galerkin, IGA-G) through the use of nonuniform rational B-splines (NURBS) basis functions for geometric design and analysis. Another promising approach, isogeometric collocation (IGA-C), working directly with the strong form of the partial differential equation (PDE) over the physical domain defined by NURBS geometry, calculates the derivatives of the numerical solution at the chosen collocation points. In a typical IGA, the knot vector of the NURBS numerical solution is only determined by the… More >

    Graphic Abstract

    New Perspective to Isogeometric Analysis: Solving Isogeometric Analysis Problem by Fitting Load Function

  • Open AccessOpen Access

    ARTICLE

    BC-PC-Share: Blockchain-Based Patient-Centric Data Sharing Scheme for PHRs in Cloud Computing

    Caihui Lan1, Haifeng Li2,3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2985-3010, 2023, DOI:10.32604/cmes.2023.026321 - 09 March 2023
    (This article belongs to the Special Issue: Emerging Trends on Blockchain: Architecture and Dapp Ecosystem)
    Abstract Sharing of personal health records (PHR) in cloud computing is an essential functionality in the healthcare system. However, how to securely, efficiently and flexibly share PHRs data of the patient in a multi-receiver setting has not been well addressed. For instance, since the trust domain of the cloud server is not identical to the data owner or data user, the semi-trust cloud service provider may intentionally destroy or tamper shared PHRs data of user or only transform partial ciphertext of the shared PHRs or even return wrong computation results to save its storage and computation… More >

  • Open AccessOpen Access

    ARTICLE

    Metric Basis of Four-Dimensional Klein Bottle

    Ali N. A. Koam1, Ali Ahmad2,*, Maryam Salem Alatawi3, Muhammad Azeem4, Muhammad Faisal Nadeem5
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3011-3024, 2023, DOI:10.32604/cmes.2023.024764 - 09 March 2023
    (This article belongs to the Special Issue: Resolvability Parameters and their Applications)
    Abstract The Metric of a graph plays an essential role in the arrangement of different dimensional structures and finding their basis in various terms. The metric dimension of a graph is the selection of the minimum possible number of vertices so that each vertex of the graph is distinctively defined by its vector of distances to the set of selected vertices. This set of selected vertices is known as the metric basis of a graph. In applied mathematics or computer science, the topic of metric basis is considered as locating number or locating set, and it… More >

  • Open AccessOpen Access

    ARTICLE

    Analysis and Numerical Computations of the Multi-Dimensional, Time-Fractional Model of Navier-Stokes Equation with a New Integral Transformation

    Yuming Chu1, Saima Rashid2, Khadija Tul Kubra2, Mustafa Inc3,4,*, Zakia Hammouch5, M. S. Osman6,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3025-3060, 2023, DOI:10.32604/cmes.2023.025470 - 09 March 2023
    (This article belongs to the Special Issue: Applications of Fractional Operators in Modeling Real-world Problems: Theory, Computation, and Applications)
    Abstract The analytical solution of the multi-dimensional, time-fractional model of Navier-Stokes equation using the triple and quadruple Elzaki transform decomposition method is presented in this article. The aforesaid model is analyzed by employing Caputo fractional derivative. We deliberated three stimulating examples that correspond to the triple and quadruple Elzaki transform decomposition methods, respectively. The findings illustrate that the established approaches are extremely helpful in obtaining exact and approximate solutions to the problems. The exact and estimated solutions are delineated via numerical simulation. The proposed analysis indicates that the projected configuration is extremely meticulous, highly efficient, and More >

  • Open AccessOpen Access

    ARTICLE

    Experimental and Numerical Analysis of the Influence of Microchannel Size and Structure on Boiling Heat Transfer

    Ningbo Guo, Xianming Gao*, Duanling Li, Jixing Zhang, Penghui Yin, Mengyi Hua
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3061-3082, 2023, DOI:10.32604/cmes.2023.026657 - 09 March 2023
    (This article belongs to the Special Issue: Thermofluid Topology Optimization)
    Abstract Computational fluid dynamics was used and a numerical simulation analysis of boiling heat transfer in microchannels with three depths and three cross-sectional profiles was conducted. The heat transfer coefficient and bubble generation process of three microchannel structures with a width of 80 μm and a depth of 40, 60, and 80 μm were compared during the boiling process, and the factors influencing bubble generation were studied. A visual test bench was built, and test substrates of different sizes were prepared using a micro-nano laser. During the test, the behavior characteristics of the bubbles on the More >

  • Open AccessOpen Access

    ARTICLE

    Easy to Calibrate: Marker-Less Calibration of Multiview Azure Kinect

    Sunyoung Bu1, Suwon Lee2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3083-3096, 2023, DOI:10.32604/cmes.2023.024460 - 09 March 2023
    (This article belongs to the Special Issue: Application of Computer Tools in the Study of Mathematical Problems)
    Abstract Reconstructing a three-dimensional (3D) environment is an indispensable technique to make augmented reality and augmented virtuality feasible. A Kinect device is an efficient tool for reconstructing 3D environments, and using multiple Kinect devices enables the enhancement of reconstruction density and expansion of virtual spaces. To employ multiple devices simultaneously, Kinect devices need to be calibrated with respect to each other. There are several schemes available that calibrate 3D images generated from multiple Kinect devices, including the marker detection method. In this study, we introduce a markerless calibration technique for Azure Kinect devices that avoids the More >

    Graphic Abstract

    Easy to Calibrate: Marker-Less Calibration of Multiview Azure Kinect

  • Open AccessOpen Access

    ARTICLE

    Multi-Stage Improvement of Marine Predators Algorithm and Its Application

    Chuandong Qin, Baole Han*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3097-3119, 2023, DOI:10.32604/cmes.2023.026643 - 09 March 2023
    (This article belongs to the Special Issue: Application of Computer Tools in the Study of Mathematical Problems)
    Abstract The metaheuristic algorithms are widely used in solving the parameters of the optimization problem. The marine predators algorithm (MPA) is a novel population-based intelligent algorithm. Although MPA has shown a talented foraging strategy, it still needs a balance of exploration and exploitation. Therefore, a multi-stage improvement of marine predators algorithm (MSMPA) is proposed in this paper. The algorithm retains the advantage of multi-stage search and introduces a linear flight strategy in the middle stage to enhance the interaction between predators. Predators further away from the historical optimum are required to move, increasing the exploration capability… More >

    Graphic Abstract

    Multi-Stage Improvement of Marine Predators Algorithm and Its Application

  • Open AccessOpen Access

    ARTICLE

    On Time Fractional Partial Differential Equations and Their Solution by Certain Formable Transform Decomposition Method

    Rania Saadeh1, Ahmad Qazza1, Aliaa Burqan1, Shrideh Al-Omari2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3121-3139, 2023, DOI:10.32604/cmes.2023.026313 - 09 March 2023
    (This article belongs to the Special Issue: On Innovative Ideas in Pure and Applied Mathematics with Applications)
    Abstract This paper aims to investigate a new efficient method for solving time fractional partial differential equations. In this orientation, a reliable formable transform decomposition method has been designed and developed, which is a novel combination of the formable integral transform and the decomposition method. Basically, certain accurate solutions for time-fractional partial differential equations have been presented. The method under concern demands more simple calculations and fewer efforts compared to the existing methods. Besides, the posed formable transform decomposition method has been utilized to yield a series solution for given fractional partial differential equations. Moreover, several More >

  • Open AccessOpen Access

    ARTICLE

    Aggregation Operators for Decision Making Based on q-Rung Orthopair Fuzzy Hypersoft Sets: An Application in Real Estate Project

    Salma Khan1, Muhammad Gulistan1, Nasreen Kausar2, Dragan Pamucar3, Tzung-Pei Hong4,5, Hafiz Abdul Wahab1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3141-3156, 2023, DOI:10.32604/cmes.2023.026169 - 09 March 2023
    (This article belongs to the Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
    Abstract In this paper, a decision-making problem with a q-rung orthopair fuzzy hypersoft environment is developed, and two operators of ordered weighted average and induced ordered weighted average are developed. Several fundamental features are also derived. The induced ordered weighted average operator is essential in a q-ROFH environment as the induced ordered aggregation operators are special cases of the existing aggregation operators that already exist in q-ROFH environments. The main function of these operators is to help decision-makers gain a complete understanding of uncertain facts. The proposed aggregation operator is applied to a decision-making problem, with More >

    Graphic Abstract

    Aggregation Operators for Decision Making Based on q-Rung Orthopair Fuzzy Hypersoft Sets: An Application in Real Estate Project

  • Open AccessOpen Access

    ARTICLE

    Interpolation Technique for the Underwater DEM Generated by an Unmanned Surface Vessel

    Shiwei Qin, Zili Dai*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3157-3172, 2023, DOI:10.32604/cmes.2023.026874 - 09 March 2023
    (This article belongs to the Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
    Abstract High-resolution underwater digital elevation models (DEMs) are important for water and soil conservation, hydrological analysis, and river channel dredging. In this work, the underwater topography of the Panjing River in Shanghai, China, was measured by an unmanned surface vessel. Five different interpolation methods were used to generate the underwater DEM and their precision and applicability for different underwater landforms were analyzed through cross-validation. The results showed that there was a positive correlation between the interpolation error and the terrain surface roughness. The five interpolation methods were all appropriate for the survey area, but their accuracy More >

  • Open AccessOpen Access

    ARTICLE

    Reliability-Based Topology Optimization of Fail-Safe Structures Using Moving Morphable Bars

    Xuan Wang1,2, Yuankun Shi2, Van-Nam Hoang3, Zeng Meng2,*, Kai Long4,*, Yuesheng Wang1
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3173-3195, 2023, DOI:10.32604/cmes.2023.025501 - 09 March 2023
    (This article belongs to the Special Issue: Advanced Methods for Uncertainty-oriented Structural Analysis and Design Optimization)
    Abstract This paper proposes an effective reliability design optimization method for fail-safe topology optimization (FSTO) considering uncertainty based on the moving morphable bars method to establish the ideal balance between cost and robustness, reliability and structural safety. To this end, a performance measure approach (PMA)-based double-loop optimization algorithm is developed to minimize the relative volume percentage while achieving the reliability criterion. To ensure the compliance value of the worst failure case can better approximate the quantified design requirement, a p-norm constraint approach with correction parameter is introduced. Finally, the significance of accounting for uncertainty in the More >

    Graphic Abstract

    Reliability-Based Topology Optimization of Fail-Safe Structures Using Moving Morphable Bars

  • Open AccessOpen Access

    ARTICLE

    The Flipping-Free Full-Parallax Tabletop Integral Imaging with Enhanced Viewing Angle Based on Space-Multiplexed Voxel Screen and Compound Lens Array

    Peiren Wang1,*, Jinqiang Bi1, Zilong Li1, Xue Han1, Zhengyang Li2, Xiaozheng Wang3
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3197-3211, 2023, DOI:10.32604/cmes.2023.024305 - 09 March 2023
    (This article belongs to the Special Issue: Recent Advances in Virtual Reality)
    Abstract Tabletop integral imaging display with a more realistic and immersive experience has always been a hot spot in three-dimensional imaging technology, widely used in biomedical imaging and visualization to enhance medical diagnosis. However, the traditional structural characteristics of integral imaging display inevitably introduce the flipping effect outside the effective viewing angle. Here, a full-parallax tabletop integral imaging display without the flipping effect based on space-multiplexed voxel screen and compound lens array is demonstrated, and two holographic functional screens with different parameters are optically designed and fabricated. To eliminate the flipping effect in the reconstruction process,… More >

    Graphic Abstract

    The Flipping-Free Full-Parallax Tabletop Integral Imaging with Enhanced Viewing Angle Based on Space-Multiplexed Voxel Screen and Compound Lens Array

  • Open AccessOpen Access

    ARTICLE

    UOUU: User-Object Distance and User-User Distance Combined Method for Collaboration Task

    Xiangdong Li, Pengfei Wang*, Hanfei Xia, Yuting Niu
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3213-3238, 2023, DOI:10.32604/cmes.2023.023895 - 09 March 2023
    (This article belongs to the Special Issue: Recent Advances in Virtual Reality)
    Abstract Augmented reality superimposes digital information onto objects in the physical world and enables multi-user collaboration. Despite that previous proxemic interaction research has explored many applications of user-object distance and user-user distance in an augmented reality context, respectively, and combining both types of distance can improve the efficiency of users’ perception and interaction with task objects and collaborators by providing users with insight into spatial relations of user-task object and user-user, less is concerned about how the two types of distances can be simultaneously adopted to assist collaboration tasks across multi-users. To fulfill the gap, we… More >

    Graphic Abstract

    UOUU: User-Object Distance and User-User Distance Combined Method for Collaboration Task

  • Open AccessOpen Access

    ARTICLE

    Energy-Efficient UAVs Coverage Path Planning Approach

    Gamil Ahmed1, Tarek Sheltami1,*, Ashraf Mahmoud1, Ansar Yasar2
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3239-3263, 2023, DOI:10.32604/cmes.2023.022860 - 09 March 2023
    (This article belongs to the Special Issue: Digital Twins in Smart Transportation and Mobility)
    Abstract Unmanned aerial vehicles (UAVs), commonly known as drones, have drawn significant consideration thanks to their agility, mobility, and flexibility features. They play a crucial role in modern reconnaissance, inspection, intelligence, and surveillance missions. Coverage path planning (CPP) which is one of the crucial aspects that determines an intelligent system’s quality seeks an optimal trajectory to fully cover the region of interest (ROI). However, the flight time of the UAV is limited due to a battery limitation and may not cover the whole region, especially in large region. Therefore, energy consumption is one of the most… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

    Hao Zhu1, Chao Sun2,*, Qunfeng Zheng2, Qinghai Zhao1,3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3265-3283, 2023, DOI:10.32604/cmes.2023.025777 - 09 March 2023
    (This article belongs to the Special Issue: Cooperative ML/DL and Intelligent Networks towards Vehicle Health Monitoring System (VHMS))
    Abstract Electric vehicle charging identification and positioning is critically important to achieving automatic charging. In terms of the problem of automatic charging for electric vehicles, a dual recognition and positioning method based on deep learning is proposed. The method is divided into two parts: global recognition and localization and local recognition and localization. In the specific implementation process, the collected pictures of electric vehicle charging attitude are classified and labeled. It is trained with the improved YOLOv4 network model and the corresponding detection model is obtained. The contour of the electric vehicle is extracted by the… More >

    Graphic Abstract

    Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

  • Open AccessOpen Access

    ARTICLE

    PoQ-Consensus Based Private Electricity Consumption Forecasting via Federated Learning

    Yiqun Zhu1, Shuxian Sun1, Chunyu Liu1, Xinyi Tian1, Jingyi He2, Shuai Xiao2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3285-3297, 2023, DOI:10.32604/cmes.2023.026691 - 09 March 2023
    (This article belongs to the Special Issue: AI-IoT-Blockchain Integrated Computational Intelligence for Solving Complex Engineering Problems)
    Abstract With the rapid development of artificial intelligence and computer technology, grid corporations have also begun to move towards comprehensive intelligence and informatization. However, data-based informatization can bring about the risk of privacy exposure of fine-grained information such as electricity consumption data. The modeling of electricity consumption data can help grid corporations to have a more thorough understanding of users’ needs and their habits, providing better services for users. Nevertheless, users’ electricity consumption data is sensitive and private. In order to achieve highly efficient analysis of massive private electricity consumption data without direct access, a blockchain-based… More >

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