Home / Journals / CMES / Vol.138, No.2, 2024
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  • Open AccessOpen Access

    EDITORIAL

    Introduction to the Special Issue on Computer Modeling for Smart Cities Applications

    Wenbing Zhao1,*, Chenxi Huang2, Yizhang Jiang3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1015-1017, 2024, DOI:10.32604/cmes.2023.031566
    (This article belongs to this Special Issue: Computer Modeling for Smart Cities Applications)
    Abstract This article has no abstract. More >

  • Open AccessOpen Access

    REVIEW

    A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

    Pavlo Mykytyn1,2,*, Marcin Brzozowski1, Zoya Dyka1,2, Peter Langendoerfer1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1019-1050, 2024, DOI:10.32604/cmes.2023.029075
    (This article belongs to this Special Issue: Issues and Challenges in Futuristic Aerial-Ground Networks)
    Abstract The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this survey is to extensively review… More >

  • Open AccessOpen Access

    ARTICLE

    An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

    Shazia Shamas1, Surya Narayan Panda1,*, Ishu Sharma1,*, Kalpna Guleria1, Aman Singh2,3,4, Ahmad Ali AlZubi5, Mallak Ahmad AlZubi6
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712
    Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarm intelligent techniques. The techniques… More >

  • Open AccessOpen Access

    ARTICLE

    Study on Evacuation Strategy of Commercial High-Rise Building under Fire Based on FDS and Pathfinder

    Zheng Yan1, Ying Wang1,*, Longxiao Chao1, Jian Guo2
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1077-1102, 2024, DOI:10.32604/cmes.2023.030023
    Abstract With the development of economy and society and the growth of population, the high-rise and multi-function of commercial buildings have become an international trend. But it also poses huge fire hazards. Most of the existing studies’ research objects are predominantly high-rise residential buildings, without considering the impact of different functional zones (Standard floor, entertainment zone, office zone, equipment room and so on) and personnel distribution of commercial buildings evacuation. And the influence of using elevators to carry evacuees on the refuge floor on personnel evacuation is rarely studied. In this work, the fire scenario of the Yangtze River International Conference… More >

  • Open AccessOpen Access

    ARTICLE

    A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

    Zhaohui Xia1,3, Baichuan Gao3, Chen Yu2,*, Haotian Han3, Haobo Zhang3, Shuting Wang3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1103-1137, 2024, DOI:10.32604/cmes.2023.029177
    Abstract This paper aims to solve large-scale and complex isogeometric topology optimization problems that consume significant computational resources. A novel isogeometric topology optimization method with a hybrid parallel strategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equation solving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency of CPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload between CPU and GPU. To illustrate the advantages of the proposed method, three benchmark examples are tested to verify the hybrid parallel strategy in this paper. The results… More >

    Graphic Abstract

    A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

  • Open AccessOpen Access

    ARTICLE

    Deep Structure Optimization for Incremental Hierarchical Fuzzy Systems Using Improved Differential Evolution Algorithm

    Yue Zhu, Tao Zhao*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1139-1158, 2024, DOI:10.32604/cmes.2023.030178
    Abstract The optimization of the rule base of a fuzzy logic system (FLS) based on evolutionary algorithm has achieved notable results. However, due to the diversity of the deep structure in the hierarchical fuzzy system (HFS) and the correlation of each sub fuzzy system, the uncertainty of the HFS's deep structure increases. For the HFS, a large number of studies mainly use fixed structures, which cannot be selected automatically. To solve this problem, this paper proposes a novel approach for constructing the incremental HFS. During system design, the deep structure and the rule base of the HFS are encoded separately. Subsequently,… More >

  • Open AccessOpen Access

    ARTICLE

    The Analysis of the Correlation between SPT and CPT Based on CNN-GA and Liquefaction Discrimination Research

    Ruihan Bai1, Feng Shen2,*, Zihao Zhao3, Zhiping Zhang4, Qisi Yu4
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1159-1182, 2024, DOI:10.32604/cmes.2023.029562
    Abstract The objective of this study is to investigate the methods for soil liquefaction discrimination. Typically, predicting soil liquefaction potential involves conducting the standard penetration test (SPT), which requires field testing and can be time-consuming and labor-intensive. In contrast, the cone penetration test (CPT) provides a more convenient method and offers detailed and continuous information about soil layers. In this study, the feature matrix based on CPT data is proposed to predict the standard penetration test blow count N. The feature matrix comprises the CPT characteristic parameters at specific depths, such as tip resistance qc, sleeve resistance fs, and depth H.… More >

  • Open AccessOpen Access

    ARTICLE

    Two-Way Neural Network Performance Prediction Model Based on Knowledge Evolution and Individual Similarity

    Xinzheng Wang1,2,*, Bing Guo1, Yan Shen3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1183-1206, 2024, DOI:10.32604/cmes.2023.029552
    Abstract Predicting students’ academic achievements is an essential issue in education, which can benefit many stakeholders, for instance, students, teachers, managers, etc. Compared with online courses such as MOOCs, students’ academic-related data in the face-to-face physical teaching environment is usually sparsity, and the sample size is relatively small. It makes building models to predict students’ performance accurately in such an environment even more challenging. This paper proposes a Two-Way Neural Network (TWNN) model based on the bidirectional recurrent neural network and graph neural network to predict students’ next semester’s course performance using only their previous course achievements. Extensive experiments on a… More >

    Graphic Abstract

    Two-Way Neural Network Performance Prediction Model Based on Knowledge Evolution and Individual Similarity

  • Open AccessOpen Access

    ARTICLE

    A Combustion Model for Explosive Charge Affected by a Bottom Gap in the Launch Environment

    Shibo Wu1, Weidong Chen1,*, Jingxin Ma2, Lan Liu1, Shengzhuo Lu1, Honglin Meng1, Xiquan Song3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1207-1236, 2024, DOI:10.32604/cmes.2023.029471
    Abstract Launch safety of explosive charges has become an urgent problem to be solved by all countries in the world as launch situation of ammunition becomes consistently worse. However, the existing numerical models have different defects. This paper formulates an efficient computational model of the combustion of an explosive charge affected by a bottom gap in the launch environment in the context of the material point method. The current temperature is computed accurately from the heat balance equation, and different physical states of the explosive charges are considered through various equations of state. Microcracks in the explosive charges are described with… More >

    Graphic Abstract

    A Combustion Model for Explosive Charge Affected by a Bottom Gap in the Launch Environment

  • Open AccessOpen Access

    ARTICLE

    Algorithm Selection Method Based on Coupling Strength for Partitioned Analysis of Structure-Piezoelectric-Circuit Coupling

    Daisuke Ishihara*, Naoto Takayama
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1237-1258, 2024, DOI:10.32604/cmes.2023.030211
    Abstract In this study, we propose an algorithm selection method based on coupling strength for the partitioned analysis of structure-piezoelectric-circuit coupling, which includes two types of coupling or inverse and direct piezoelectric coupling and direct piezoelectric and circuit coupling. In the proposed method, implicit and explicit formulations are used for strong and weak coupling, respectively. Three feasible partitioned algorithms are generated, namely (1) a strongly coupled algorithm that uses a fully implicit formulation for both types of coupling, (2) a weakly coupled algorithm that uses a fully explicit formulation for both types of coupling, and (3) a partially strongly coupled and… More >

  • Open AccessOpen Access

    ARTICLE

    Optimization of Cooperative Relaying Molecular Communications for Nanomedical Applications

    Eman S. Attia1, Ashraf A. M. Khalaf1, Fathi E. Abd El-Samie2, Saied M. Abd El-atty2,*, Konstantinos A. Lizos3,#, Osama Alfarraj4, Heba M. El-Hoseny5
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1259-1275, 2024, DOI:10.32604/cmes.2023.028990
    Abstract Recently, nano-systems based on molecular communications via diffusion (MCvD) have been implemented in a variety of nanomedical applications, most notably in targeted drug delivery system (TDDS) scenarios. Furthermore, because the MCvD is unreliable and there exists molecular noise and inter symbol interference (ISI), cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells, especially if the separation distance between the nano transmitter and nano receiver is increased. In this work, we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme, while accounting for blood flow effects… More >

  • Open AccessOpen Access

    ARTICLE

    An 8-Node Plane Hybrid Element for Structural Mechanics Problems Based on the Hellinger-Reissner Variational Principle

    Haonan Li1, Wei Wang2, Quan Shen1, Linquan Yao1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1277-1299, 2024, DOI:10.32604/cmes.2023.030508
    Abstract The finite element method (FEM) plays a valuable role in computer modeling and is beneficial to the mechanical design of various structural parts. However, the elements produced by conventional FEM are easily inaccurate and unstable when applied. Therefore, developing new elements within the framework of the generalized variational principle is of great significance. In this paper, an 8-node plane hybrid finite element with 15 parameters (PH-Q8-) is developed for structural mechanics problems based on the Hellinger-Reissner variational principle. According to the design principle of Pian, 15 unknown parameters are adopted in the selection of stress modes to avoid the zero… More >

  • Open AccessOpen Access

    ARTICLE

    Microstrip Patch Antenna with an Inverted T-Type Notch in the Partial Ground for Breast Cancer Detections

    Nure Alam Chowdhury1, Lulu Wang2,*, Md Shazzadul Islam3, Linxia Gu1, Mehmet Kaya1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1301-1322, 2024, DOI:10.32604/cmes.2023.030844
    Abstract This study designs a microstrip patch antenna with an inverted T-type notch in the partial ground to detect tumor cells inside the human breast. The size of the current antenna is small enough (18 mm × 21 mm × 1.6 mm) to distribute around the breast phantom. The operating frequency has been observed from 6–14 GHz with a minimum return loss of −61.18 dB and the maximum gain of current proposed antenna is 5.8 dBi which is flexible with respect to the size of antenna. After the distribution of eight antennas around the breast phantom, the return loss curves were observed in the presence and absence of tumor cells inside… More >

    Graphic Abstract

    Microstrip Patch Antenna with an Inverted T-Type Notch in the Partial Ground for Breast Cancer Detections

  • Open AccessOpen Access

    ARTICLE

    Prediction of Porous Media Fluid Flow with Spatial Heterogeneity Using Criss-Cross Physics-Informed Convolutional Neural Networks

    Jiangxia Han1,2, Liang Xue1,2,*, Ying Jia3, Mpoki Sam Mwasamwasa1,2, Felix Nanguka4, Charles Sangweni5, Hailong Liu3, Qian Li3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1323-1340, 2024, DOI:10.32604/cmes.2023.031093
    (This article belongs to this Special Issue: Modeling of Fluids Flow in Unconventional Reservoirs)
    Abstract Recent advances in deep neural networks have shed new light on physics, engineering, and scientific computing. Reconciling the data-centered viewpoint with physical simulation is one of the research hotspots. The physics-informed neural network (PINN) is currently the most general framework, which is more popular due to the convenience of constructing NNs and excellent generalization ability. The automatic differentiation (AD)-based PINN model is suitable for the homogeneous scientific problem; however, it is unclear how AD can enforce flux continuity across boundaries between cells of different properties where spatial heterogeneity is represented by grid cells with different physical properties. In this work,… More >

  • Open AccessOpen Access

    ARTICLE

    Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

    Mohamed Zarouan1, Ibrahim M. Mehedi1,2,*, Shaikh Abdul Latif3, Md. Masud Rana4
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1341-1364, 2024, DOI:10.32604/cmes.2023.030037
    (This article belongs to this Special Issue: Failure Detection Algorithms, Methods and Models for Industrial Environments)
    Abstract Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamless operation of the system. Current industrial processes are getting smarter with the emergence of Industry 4.0. Specifically, various modernized industrial processes have been equipped with quite a few sensors to collect process-based data to find faults arising or prevailing in processes along with monitoring the status of processes. Fault diagnosis of rotating machines serves a main role in the engineering field and industrial production. Due to the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experience and human knowledge, intellectual… More >

  • Open AccessOpen Access

    ARTICLE

    3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

    Dun Cao1, Jia Ru1, Jian Qin1, Amr Tolba2, Jin Wang1, Min Zhu3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1365-1384, 2024, DOI:10.32604/cmes.2023.030260
    (This article belongs to this Special Issue: Computer Modelling for Safer Built Environment and Smart Cities)
    Abstract Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles, people, transportation infrastructure, and networks, thereby realizing a more intelligent and efficient transportation system. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topological structure of IoV to have the high space and time complexity. Network modeling and structure recognition for 3D roads can benefit the description of topological changes for IoV. This paper proposes a 3D general road model based on discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on… More >

  • Open AccessOpen Access

    ARTICLE

    Fractal Fractional Order Operators in Computational Techniques for Mathematical Models in Epidemiology

    Muhammad Farman1,2,4, Ali Akgül3,9,*, Mir Sajjad Hashemi5, Liliana Guran6,7, Amelia Bucur8,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1385-1403, 2024, DOI:10.32604/cmes.2023.028803
    (This article belongs to this Special Issue: Recent Developments on Computational Biology-I)
    Abstract New fractional operators, the COVID-19 model has been studied in this paper. By using different numerical techniques and the time fractional parameters, the mechanical characteristics of the fractional order model are identified. The uniqueness and existence have been established. The model’s Ulam-Hyers stability analysis has been found. In order to justify the theoretical results, numerical simulations are carried out for the presented method in the range of fractional order to show the implications of fractional and fractal orders. We applied very effective numerical techniques to obtain the solutions of the model and simulations. Also, we present conditions of existence for… More >

  • Open AccessOpen Access

    ARTICLE

    Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

    Muhammad Shoaib Arif1,2,*, Kamaleldin Abodayeh1, Yasir Nawaz2
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1405-1425, 2024, DOI:10.32604/cmes.2023.028946
    (This article belongs to this Special Issue: Recent Developments on Computational Biology-I)
    Abstract This work aimed to construct an epidemic model with fuzzy parameters. Since the classical epidemic model does not elaborate on the successful interaction of susceptible and infective people, the constructed fuzzy epidemic model discusses the more detailed versions of the interactions between infective and susceptible people. The next-generation matrix approach is employed to find the reproduction number of a deterministic model. The sensitivity analysis and local stability analysis of the system are also provided. For solving the fuzzy epidemic model, a numerical scheme is constructed which consists of three time levels. The numerical scheme has an advantage over the existing… More >

  • Open AccessOpen Access

    ARTICLE

    Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset

    Mohammed Abdalsalam1,*, Chunlin Li1, Abdelghani Dahou2, Natalia Kryvinska3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1427-1467, 2024, DOI:10.32604/cmes.2023.029911
    (This article belongs to this Special Issue: Advanced Machine Learning for Big Data Analytics in Natural Language Processing)
    Abstract One of the biggest dangers to society today is terrorism, where attacks have become one of the most significant risks to international peace and national security. Big data, information analysis, and artificial intelligence (AI) have become the basis for making strategic decisions in many sensitive areas, such as fraud detection, risk management, medical diagnosis, and counter-terrorism. However, there is still a need to assess how terrorist attacks are related, initiated, and detected. For this purpose, we propose a novel framework for classifying and predicting terrorist attacks. The proposed framework posits that neglected text attributes included in the Global Terrorism Database… More >

  • Open AccessOpen Access

    ARTICLE

    Threshold-Based Software-Defined Networking (SDN) Solution for Healthcare Systems against Intrusion Attacks

    Laila M. Halman, Mohammed J. F. Alenazi*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1469-1483, 2024, DOI:10.32604/cmes.2023.028077
    (This article belongs to this Special Issue: Smart and Secure Solutions for Medical Industry)
    Abstract The healthcare sector holds valuable and sensitive data. The amount of this data and the need to handle, exchange, and protect it, has been increasing at a fast pace. Due to their nature, software-defined networks (SDNs) are widely used in healthcare systems, as they ensure effective resource utilization, safety, great network management, and monitoring. In this sector, due to the value of the data, SDNs face a major challenge posed by a wide range of attacks, such as distributed denial of service (DDoS) and probe attacks. These attacks reduce network performance, causing the degradation of different key performance indicators (KPIs)… More >

    Graphic Abstract

    Threshold-Based Software-Defined Networking (SDN) Solution for Healthcare Systems against Intrusion Attacks

  • Open AccessOpen Access

    ARTICLE

    Flow Breakdown of Hybrid Nanofluid on a Rigid Surface with Power Law Fluid as Lubricated Layers

    Mirza Naveed Jahangeer Baig1, Nadeem Salamat1, Sohail Nadeem2,3,*, Naeem Ullah2, Mohamed Bechir Ben Hamida4,5,6, Hassan Ali Ghazwani7, Sayed M. Eldin8, A. S. Al-Shafay9
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1485-1499, 2024, DOI:10.32604/cmes.2023.029351
    (This article belongs to this Special Issue: Numerical Modeling and Simulations on Non-Newtonian Flow Problems)
    Abstract This work investigates an oblique stagnation point flow of hybrid nanofluid over a rigid surface with power law fluid as lubricated layers. Copper (Cu) and Silver (Ag) solid particles are used as hybrid particles acting in water H2O as a base fluid. The mathematical formulation of flow configuration is presented in terms of differential system that is nonlinear in nature. The thermal aspects of the flow field are also investigated by assuming the surface is a heated surface with a constant temperature T. Numerical solutions to the governing mathematical model are calculated by the RK45 algorithm. The results based on… More >

  • Open AccessOpen Access

    ARTICLE

    Mechanism of Thermally Radiative Prandtl Nanofluids and Double-Diffusive Convection in Tapered Channel on Peristaltic Flow with Viscous Dissipation and Induced Magnetic Field

    Yasir Khan1, Safia Akram2,*, Maria Athar3, Khalid Saeed4, Alia Razia2, A. Alameer1
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1501-1520, 2024, DOI:10.32604/cmes.2023.029878
    (This article belongs to this Special Issue: Numerical Modeling and Simulations on Non-Newtonian Flow Problems)
    Abstract The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applications in medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In this paper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of a Prandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation and an induced magnetic field. The equations for the current flow scenario are developed, incorporating relevant assumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and double diffusion on public health is… More >

  • Open AccessOpen Access

    ARTICLE

    A Novel Accurate Method for Multi-Term Time-Fractional Nonlinear Diffusion Equations in Arbitrary Domains

    Tao Hu1, Cheng Huang2, Sergiy Reutskiy3,*, Jun Lu4, Ji Lin5,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1521-1548, 2024, DOI:10.32604/cmes.2023.030449
    (This article belongs to this Special Issue: Advances on Mesh and Dimension Reduction Methods)
    Abstract A novel accurate method is proposed to solve a broad variety of linear and nonlinear (1+1)-dimensional and (2+1)- dimensional multi-term time-fractional partial differential equations with spatial operators of anisotropic diffusivity. For (1+1)-dimensional problems, analytical solutions that satisfy the boundary requirements are derived. Such solutions are numerically calculated using the trigonometric basis approximation for (2+1)-dimensional problems. With the aid of these analytical or numerical approximations, the original problems can be converted into the fractional ordinary differential equations, and solutions to the fractional ordinary differential equations are approximated by modified radial basis functions with time-dependent coefficients. An efficient backward substitution strategy that… More >

  • Open AccessOpen Access

    ARTICLE

    An Intelligent Sensor Data Preprocessing Method for OCT Fundus Image Watermarking Using an RCNN

    Jialun Lin1, Qiong Chen1,2,3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1549-1561, 2024, DOI:10.32604/cmes.2023.029631
    (This article belongs to this Special Issue: AI-Driven Intelligent Sensor Networks: Key Enabling Theories, Architectures, Modeling, and Techniques)
    Abstract Watermarks can provide reliable and secure copyright protection for optical coherence tomography (OCT) fundus images. The effective image segmentation is helpful for promoting OCT image watermarking. However, OCT images have a large amount of low-quality data, which seriously affects the performance of segmentation methods. Therefore, this paper proposes an effective segmentation method for OCT fundus image watermarking using a rough convolutional neural network (RCNN). First, the rough-set-based feature discretization module is designed to preprocess the input data. Second, a dual attention mechanism for feature channels and spatial regions in the CNN is added to enable the model to adaptively select… More >

  • Open AccessOpen Access

    ARTICLE

    Strategic Contracting for Software Upgrade Outsourcing in Industry 4.0

    Cheng Wang1,2,*, Zhuowei Zheng1
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1563-1592, 2024, DOI:10.32604/cmes.2023.031103
    (This article belongs to this Special Issue: Computing Methods for Industrial Artificial Intelligence)
    Abstract The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software to enhance production efficiency. In this rapidly evolving market, software development is an ongoing process that must be tailored to meet the dynamic needs of enterprises. However, internal research and development can be prohibitively expensive, driving many enterprises to outsource software development and upgrades to external service providers. This paper presents a software upgrade outsourcing model for enterprises and service providers that accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverse selection due to asymmetric information about the… More >

  • Open AccessOpen Access

    ARTICLE

    Results Involving Partial Differential Equations and Their Solution by Certain Integral Transform

    Rania Saadah1, Mohammed Amleh1, Ahmad Qazza1, Shrideh Al-Omari2,*, Ahmet Ocak Akdemir3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1593-1616, 2024, DOI:10.32604/cmes.2023.029180
    (This article belongs to this Special Issue: On Innovative Ideas in Pure and Applied Mathematics with Applications)
    Abstract In this study, we aim to investigate certain triple integral transform and its application to a class of partial differential equations. We discuss various properties of the new transform including inversion, linearity, existence, scaling and shifting, etc. Then, we derive several results enfolding partial derivatives and establish a multi-convolution theorem. Further, we apply the aforementioned transform to some classical functions and many types of partial differential equations involving heat equations, wave equations, Laplace equations, and Poisson equations as well. Moreover, we draw some figures to illustrate 3-D contour plots for exact solutions of some selected examples involving different values in… More >

  • Open AccessOpen Access

    ARTICLE

    An Adaptive Hybrid Optimization Strategy for Resource Allocation in Network Function Virtualization

    Chumei Wen1, Delu Zeng2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1617-1636, 2024, DOI:10.32604/cmes.2023.029864
    (This article belongs to this Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
    Abstract With the rapid development of Network Function Virtualization (NFV), the problem of low resource utilization in traditional data centers is gradually being addressed. However, existing research does not optimize both local and global allocation of resources in data centers. Hence, we propose an adaptive hybrid optimization strategy that combines dynamic programming and neural networks to improve resource utilization and service quality in data centers. Our approach encompasses a service function chain simulation generator, a parallel architecture service system, a dynamic programming strategy for maximizing the utilization of local server resources, a neural network for predicting the global utilization rate of… More >

  • Open AccessOpen Access

    ARTICLE

    Improved STN Models and Heuristic Rules for Cooperative Scheduling in Automated Container Terminals

    Hongyan Xia, Jin Zhu*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1637-1661, 2024, DOI:10.32604/cmes.2023.029576
    (This article belongs to this Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
    Abstract Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to cope with the development trend of large-scale ships. In order to improve the solution efficiency of the existing space-time network (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guided vehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balance constraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added to acquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added to… More >

  • Open AccessOpen Access

    ARTICLE

    Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

    Jianfeng Zhao1,2, Yunliang Huo1,2, Ji Xiong1,*, Junbo Liu1,2, Zhixing Guo1, Qingxian Li3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1663-1678, 2024, DOI:10.32604/cmes.2023.030584
    (This article belongs to this Special Issue: Advanced Computational Models for Decision-Making of Complex Systems in Engineering)
    Abstract To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform, a case-based reasoning framework is proposed. Specifically, a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties. In addition, AHP (Analytic Hierarchy Process) and entropy weight method are integrated to provide features weight, where both user preferences and comprehensive impact of the index have been concerned. Grey relation analysis is used to obtain the similarity of a new problem and alternative cases. Finally, a platform is also… More >

  • Open AccessOpen Access

    ARTICLE

    A Differential Privacy Federated Learning Scheme Based on Adaptive Gaussian Noise

    Sanxiu Jiao1, Lecai Cai2,*, Xinjie Wang1, Kui Cheng2, Xiang Gao3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1679-1694, 2024, DOI:10.32604/cmes.2023.030512
    (This article belongs to this Special Issue: Federated Learning Algorithms, Approaches, and Systems for Internet of Things)
    Abstract As a distributed machine learning method, federated learning (FL) has the advantage of naturally protecting data privacy. It keeps data locally and trains local models through local data to protect the privacy of local data. The federated learning method effectively solves the problem of artificial Smart data islands and privacy protection issues. However, existing research shows that attackers may still steal user information by analyzing the parameters in the federated learning training process and the aggregation parameters on the server side. To solve this problem, differential privacy (DP) techniques are widely used for privacy protection in federated learning. However, adding… More >

    Graphic Abstract

    A Differential Privacy Federated Learning Scheme Based on Adaptive Gaussian Noise

  • Open AccessOpen Access

    ARTICLE

    Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain

    Xiaodong Yang1,4, Runze Diao1,*, Tao Liu2, Haoqi Wen1, Caifen Wang3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1695-1712, 2024, DOI:10.32604/cmes.2023.029461
    (This article belongs to this Special Issue: The Bottleneck of Blockchain Techniques: Scalability, Security and Privacy Protection)
    Abstract The carbon trading market can promote “carbon peaking” and “carbon neutrality” at low cost, but carbon emission quotas face attacks such as data forgery, tampering, counterfeiting, and replay in the electricity trading market. Certificateless signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrow based on identity cryptography. However, most certificateless signatures still suffer from various security flaws. We present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature schemes. To ensure the integrity and verifiability of electricity carbon quota trading, we… More >

  • Open AccessOpen Access

    ARTICLE

    “Half of the Node Records Are Forged?”: The Problem of Node Records Forgery in Ethereum Network

    Yang Liu1,2,*, Zhiyuan Lin1, Yuxi Zhang1, Lin Jiang1,*, Xuan Wang1,3
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1713-1729, 2024, DOI:10.32604/cmes.2023.030468
    (This article belongs to this Special Issue: The Bottleneck of Blockchain Techniques: Scalability, Security and Privacy Protection)
    Abstract Ethereum, currently the most widely utilized smart contracts platform, anchors the security of myriad smart contracts upon its own robustness. Its foundational peer-to-peer network facilitates a dependable node connection mechanism, whereas an efficient data-sharing protocol constitutes as the bedrock of Blockchain network security. In this paper, we propose NodeHunter, an Ethereum network detector implemented through the application of simulation technology, which is capable of aggregating all node records within the network and the interconnectedness between them. Utilizing this connection information, NodeHunter can procure more comprehensive insights for network status analysis compared to preceding detection methodologies. Throughout a three-month period of… More >

  • Open AccessOpen Access

    ARTICLE

    Enhancing IoT Data Security with Lightweight Blockchain and Okamoto Uchiyama Homomorphic Encryption

    Mohanad A. Mohammed*, Hala B. Abdul Wahab
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1731-1748, 2024, DOI:10.32604/cmes.2023.030528
    (This article belongs to this Special Issue: The Bottleneck of Blockchain Techniques: Scalability, Security and Privacy Protection)
    Abstract Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system challenges. Concurrently, the Internet of Things (IoT) has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services, ultimately enhancing human lives. This paper presents a new approach utilizing lightweight blockchain technology, effectively reducing the computational burden typically associated with conventional blockchain systems. By integrating this lightweight blockchain with IoT systems, substantial reductions in implementation time and computational complexity can be achieved. Moreover, the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm, renowned for… More >

  • Open AccessOpen Access

    ARTICLE

    Multidomain Correlation-Based Multidimensional CSI Tensor Generation for Device-Free Wi-Fi Sensing

    Liufeng Du1,*, Shaoru Shang1, Linghua Zhang2, Chong Li1, Jianing Yang3, Xiyan Tian1
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1749-1767, 2024, DOI:10.32604/cmes.2023.030144
    (This article belongs to this Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Due to the fine-grained communication scenarios characterization and stability, Wi-Fi channel state information (CSI) has been increasingly applied to indoor sensing tasks recently. Although spatial variations are explicitly reflected in CSI measurements, the representation differences caused by small contextual changes are easily submerged in the fluctuations of multipath effects, especially in device-free Wi-Fi sensing. Most existing data solutions cannot fully exploit the temporal, spatial, and frequency information carried by CSI, which results in insufficient sensing resolution for indoor scenario changes. As a result, the well-liked machine learning (ML)-based CSI sensing models still struggling with stable performance. This paper formulates a… More >

  • Open AccessOpen Access

    ARTICLE

    System Reliability Analysis Method Based on T-S FTA and HE-BN

    Qing Xia1, Yonghua Li2,*, Dongxu Zhang2, Yufeng Wang2
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1769-1794, 2024, DOI:10.32604/cmes.2023.030724
    (This article belongs to this Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract For high-reliability systems in military, aerospace, and railway fields, the challenges of reliability analysis lie in dealing with unclear failure mechanisms, complex fault relationships, lack of fault data, and uncertainty of fault states. To overcome these problems, this paper proposes a reliability analysis method based on T-S fault tree analysis (T-S FTA) and Hyper-ellipsoidal Bayesian network (HE-BN). The method describes the connection between the various system fault events by T-S fuzzy gates and translates them into a Bayesian network (BN) model. Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation, a reliability modeling method… More >

  • Open AccessOpen Access

    ARTICLE

    Adaptive H Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

    Xiuhui Diao1, Pengfei Wang1,2,*, Weidong Li2, Xianwu Chu2, Yunming Wang2
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1795-1812, 2024, DOI:10.32604/cmes.2023.030008
    (This article belongs to this Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract To solve the problem of data fusion for prior information such as track information and train status in train positioning, an adaptive H filtering algorithm with combination constraint is proposed, which fuses prior information with other sensor information in the form of constraints. Firstly, the train precise track constraint method of the train is proposed, and the plane position constraint and train motion state constraints are analysed. A model for combining prior information with constraints is established. Then an adaptive H filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor. Finally, the positioning… More >

  • Open AccessOpen Access

    ARTICLE

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

    Xiaoyan Su1,*, Shuwen Shang1, Zhihui Xu2, Hong Qian1, Xiaolei Pan1
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957
    (This article belongs to this Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the… More >

    Graphic Abstract

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

  • Open AccessOpen Access

    ARTICLE

    Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-Speed Wire Rod Finishing Mills

    Cunsong Wang1, Ningze Tang1, Quanling Zhang1,*, Lixin Gao2, Haichen Yin3, Hao Peng4
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1827-1847, 2024, DOI:10.32604/cmes.2023.030970
    (This article belongs to this Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise. As complex system-level equipment, it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring. To solve the above problems, an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper. First, based on its mechanical structure, time and frequency domain analysis are improved in fault feature extraction. The approach of combining virtual value, peak value with kurtosis value index, is adopted in time domain analysis. Speed adjustment and side… More >

  • Open AccessOpen Access

    ARTICLE

    Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

    Ping Li1, Kefeng Guo2,*, Feng Zhou1, Xueling Wang3, Yuzhen Huang4
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1849-1864, 2024, DOI:10.32604/cmes.2023.029801
    (This article belongs to this Special Issue: Edge Computing Enabled Internet of Drones)
    Abstract Integrated satellite unmanned aerial vehicle relay networks (ISUAVRNs) have become a prominent topic in recent years. This paper investigates the average secrecy capacity (ASC) for reconfigurable intelligent surface (RIS)-enabled ISUAVRNs. Especially, an eve is considered to intercept the legitimate information from the considered secrecy system. Besides, we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent. Furthermore, to gain insightful results of the major parameters on the ASC in high signal-to-noise ratio regime, the approximate investigations are further gotten, which give an efficient method to value the secrecy analysis. At last,… More >

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    ARTICLE

    Energy Efficiency Maximization in Mobile Edge Computing Networks via IRS assisted UAV Communications

    Ying Zhang1, Weiming Niu2, Supu Xiu1,3, Guangchen Mu3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1865-1884, 2024, DOI:10.32604/cmes.2023.030114
    (This article belongs to this Special Issue: Edge Computing Enabled Internet of Drones)
    Abstract In this paper, we investigate the energy efficiency maximization for mobile edge computing (MEC) in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communications. In particular, UAV can collect the computing tasks of the terrestrial users and transmit the results back to them after computing. We jointly optimize the users’ transmitted beamforming and uploading ratios, the phase shift matrix of IRS, and the UAV trajectory to improve the energy efficiency. The formulated optimization problem is highly non-convex and difficult to be solved directly. Therefore, we decompose the original problem into three sub-problems. We first propose the successive convex approximation… More >

  • Open AccessOpen Access

    ARTICLE

    Outage Analysis of Optimal UAV Cooperation with IRS via Energy Harvesting Enhancement Assisted Computational Offloading

    Baofeng Ji1,2,3,*, Ying Wang1,2,3, Weixing Wang1, Shahid Mumtaz4, Charalampos Tsimenidis4
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1885-1905, 2024, DOI:10.32604/cmes.2023.030872
    (This article belongs to this Special Issue: Edge Computing Enabled Internet of Drones)
    Abstract The utilization of mobile edge computing (MEC) for unmanned aerial vehicle (UAV) communication presents a viable solution for achieving high reliability and low latency communication. This study explores the potential of employing intelligent reflective surfaces (IRS) and UAVs as relay nodes to efficiently offload user computing tasks to the MEC server system model. Specifically, the user node accesses the primary user spectrum, while adhering to the constraint of satisfying the primary user peak interference power. Furthermore, the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes, namely time switching (TS) and power splitting… More >

  • Open AccessOpen Access

    ARTICLE

    Decision Making Based on Valued Fuzzy Superhypergraphs

    Mohammad Hamidi1,*, Florentin Smarandache2, Mohadeseh Taghinezhad1
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1907-1923, 2024, DOI:10.32604/cmes.2023.030284
    (This article belongs to this Special Issue: Advances in Ambient Intelligence and Social Computing under uncertainty and indeterminacy: From Theory to Applications)
    Abstract This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy (hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept. We have modeled the fuzzy superhypergraphs as complex superhypernetworks in order to make a relation between labeled objects in the form of details and generalities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzes them in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole to the whole group of objects at the same time.… More >

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    ARTICLE

    The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

    Huzaira Razzaque1, Shahzaib Ashraf1,*, Muhammad Naeem2, Yu-Ming Chu3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1925-1950, 2024, DOI:10.32604/cmes.2023.030030
    (This article belongs to this Special Issue: Advances in Ambient Intelligence and Social Computing under uncertainty and indeterminacy: From Theory to Applications)
    Abstract Spherical q-linear Diophantine fuzzy sets (Sq-LDFSs) proved more effective for handling uncertainty and vagueness in multi-criteria decision-making (MADM). It does not only cover the data in two variable parameters but is also beneficial for three parametric data. By Pythagorean fuzzy sets, the difference is calculated only between two parameters (membership and non-membership). According to human thoughts, fuzzy data can be found in three parameters (membership uncertainty, and non-membership). So, to make a compromise decision, comparing Sq-LDFSs is essential. Existing measures of different fuzzy sets do, however, can have several flaws that can lead to counterintuitive results. For instance, they treat… More >

  • Open AccessOpen Access

    ARTICLE

    A Novel Method for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

    Salma Khan1, Muhammad Gulistan1, Nasreen Kausar2, Seifedine Kadry3,4,5, Jungeun Kim6,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1951-1979, 2024, DOI:10.32604/cmes.2023.030896
    (This article belongs to this Special Issue: Advances in Ambient Intelligence and Social Computing under uncertainty and indeterminacy: From Theory to Applications)
    Abstract Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons, including leisure, pleasure, or business. A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set (ROFHS) to enhance the formal representation of human thought processes and evaluate tourism carrying capacity. This approach can capture the imprecision and ambiguity often present in human perception. With the advanced mathematical tools in this field, the study has also incorporated the Einstein aggregation operator and score function into the ROFHS values to support multi-attribute decision-making algorithms. By implementing… More >

  • Open AccessOpen Access

    ARTICLE

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

    Shaik Mahaboob Basha1,*, Victor Hugo C. de Albuquerque2, Samia Allaoua Chelloug3,*, Mohamed Abd Elaziz4,5,6,7, Shaik Hashmitha Mohisin8, Suhail Parvaze Pathan9
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1981-2004, 2024, DOI:10.32604/cmes.2023.031425
    (This article belongs to this Special Issue: Intelligent Biomedical Image Processing and Computer Vision)
    Abstract Manual investigation of chest radiography (CXR) images by physicians is crucial for effective decision-making in COVID-19 diagnosis. However, the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning techniques. This study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies, including normal cases. Texture information is extracted using gray co-occurrence matrix (GLCM)-based features, while vessel-like features are obtained using Frangi, Sato, and Meijering filters. Machine learning models employing Decision Tree (DT) and Random Forest (RF) approaches are designed to categorize CXR images into common lung infections, lung… More >

    Graphic Abstract

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

  • Open AccessOpen Access

    ARTICLE

    Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad Hoc Networks Using Blockchain Based Smart Contracts

    Abdulatif Alabdulatif1,*, Mada Alharbi1, Abir Mchergui2, Tarek Moulahi3,4
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 2005-2022, 2024, DOI:10.32604/cmes.2023.029769
    (This article belongs to this Special Issue: Intelligent Blockchain for the Internet of Things)
    Abstract The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management efficiency. Revolutionary advanced technology, such as Intelligent Transportation Systems (ITS), enables improved traffic management, helps eliminate congestion, and supports a safer environment. ITS provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road users. However, ITS suffers from routing issues at the network layer when utilising Vehicular Ad Hoc Networks (VANETs). This is because each vehicle plays the role of a router in this network, which leads to a… More >

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