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  • Open Access

    ARTICLE

    Computing Resource Allocation for Blockchain-Based Mobile Edge Computing

    Wanbo Zhang1, Yuqi Fan1, Jun Zhang1, Xu Ding2,*, Jung Yoon Kim3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 863-885, 2024, DOI:10.32604/cmes.2024.047295

    Abstract Users and edge servers are not fully mutually trusted in mobile edge computing (MEC), and hence blockchain can be introduced to provide trustable MEC. In blockchain-based MEC, each edge server functions as a node in both MEC and blockchain, processing users’ tasks and then uploading the task related information to the blockchain. That is, each edge server runs both users’ offloaded tasks and blockchain tasks simultaneously. Note that there is a trade-off between the resource allocation for MEC and blockchain tasks. Therefore, the allocation of the resources of edge servers to the blockchain and the MEC is crucial for the… More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization of Aluminum Alloy Electric Bus Frame Connectors for Enhanced Durability

    Wenjun Zhou1,2, Mingzhi Yang1, Qian Peng2, Yong Peng1,*, Kui Wang1, Qiang Xiao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 735-755, 2024, DOI:10.32604/cmes.2024.047258

    Abstract The widespread adoption of aluminum alloy electric buses, known for their energy efficiency and eco-friendliness, faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel. This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries, necessitating robust frame protection. Our study aims to optimize the connectors of aluminum alloy bus frames, emphasizing durability, energy efficiency, and safety. This research delves into Multi-Objective Coordinated Optimization (MCO) techniques for lightweight design in aluminum alloy bus body connectors. Our goal is to enhance lightweighting, reinforce energy absorption, and improve deformation resistance in… More >

  • Open Access

    ARTICLE

    Blade Wrap Angle Impact on Centrifugal Pump Performance: Entropy Generation and Fluid-Structure Interaction Analysis

    Hayder Kareem Sakran1,2, Mohd Sharizal Abdul Aziz1,*, Chu Yee Khor3

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 109-137, 2024, DOI:10.32604/cmes.2024.047245

    Abstract The centrifugal pump is a prevalent power equipment widely used in different engineering patterns, and the impeller blade wrap angle significantly impacts its performance. A numerical investigation was conducted to analyze the influence of the blade wrap angle on flow characteristics and energy distribution of a centrifugal pump evaluated as a low specific speed with a value of 69. This study investigates six impeller models that possess varying blade wrap angles (95°, 105°, 115°, 125°, 135°, and 145°) that were created while maintaining the same volute and other geometrical characteristics. The investigation of energy loss was conducted to evaluate the… More > Graphic Abstract

    Blade Wrap Angle Impact on Centrifugal Pump Performance: Entropy Generation and Fluid-Structure Interaction Analysis

  • Open Access

    ARTICLE

    Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

    Wenxiang Dong, H. Vicky Zhao*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 139-170, 2024, DOI:10.32604/cmes.2024.047156

    Abstract Understanding and modeling individuals’ behaviors during epidemics is crucial for effective epidemic control. However, existing research ignores the impact of users’ irrationality on decision-making in the epidemic. Meanwhile, existing disease control methods often assume users’ full compliance with measures like mandatory isolation, which does not align with the actual situation. To address these issues, this paper proposes a prospect theory-based framework to model users’ decision-making process in epidemics and analyzes how irrationality affects individuals’ behaviors and epidemic dynamics. According to the analysis results, irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when… More >

  • Open Access

    ARTICLE

    Uniaxial Compressive Strength Prediction for Rock Material in Deep Mine Using Boosting-Based Machine Learning Methods and Optimization Algorithms

    Junjie Zhao, Diyuan Li*, Jingtai Jiang, Pingkuang Luo

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 275-304, 2024, DOI:10.32604/cmes.2024.046960

    Abstract Traditional laboratory tests for measuring rock uniaxial compressive strength (UCS) are tedious and time-consuming. There is a pressing need for more effective methods to determine rock UCS, especially in deep mining environments under high in-situ stress. Thus, this study aims to develop an advanced model for predicting the UCS of rock material in deep mining environments by combining three boosting-based machine learning methods with four optimization algorithms. For this purpose, the Lead-Zinc mine in Southwest China is considered as the case study. Rock density, P-wave velocity, and point load strength index are used as input variables, and UCS is regarded… More > Graphic Abstract

    Uniaxial Compressive Strength Prediction for Rock Material in Deep Mine Using Boosting-Based Machine Learning Methods and Optimization Algorithms

  • Open Access

    REVIEW

    A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

    Huaiguang Wu, Yibo Peng, Yaqiong He*, Jinlin Fan

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 77-108, 2024, DOI:10.32604/cmes.2024.046758

    Abstract In recent years, the number of smart contracts deployed on blockchain has exploded. However, the issue of vulnerability has caused incalculable losses. Due to the irreversible and immutability of smart contracts, vulnerability detection has become particularly important. With the popular use of neural network model, there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts. This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts. Subsequently, it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract detection. These… More > Graphic Abstract

    A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

  • Open Access

    ARTICLE

    An Approach for Human Posture Recognition Based on the Fusion PSE-CNN-BiGRU Model

    Xianghong Cao, Xinyu Wang, Xin Geng*, Donghui Wu, Houru An

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 385-408, 2024, DOI:10.32604/cmes.2024.046752

    Abstract This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit (PSE-CNN-BiGRU) fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home environments. Firstly, the deep convolutional network is integrated with the Mediapipe framework to extract high-precision, multi-dimensional information from the key points of the human skeleton, thereby obtaining a human posture feature set. Thereafter, a double-layer BiGRU algorithm is utilized to extract multi-layer, bidirectional temporal features from the human posture feature set, and a… More >

  • Open Access

    ARTICLE

    Study of the Ballistic Impact Behavior of Protective Multi-Layer Composite Armor

    Dongsheng Jia, Yingjie Xu*, Liangdi Wang, Jihong Zhu, Weihong Zhang

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 171-199, 2024, DOI:10.32604/cmes.2024.046703

    Abstract The abalone shell, a composite material whose cross-section is composed of inorganic and organic layers, has high strength and toughness. Inspired by the abalone shell, several multi-layer composite plates with different layer sequences and thicknesses are studied as bullet-proof material in this paper. To investigate the ballistic performance of this multi-layer structure, the complete characterization model and related material parameters of large deformation, failure and fracture of Al2O3 ceramics and Carbon Fiber Reinforced Polymer (CFRP) are studied. Then, 3D finite element models of the proposed composite plates with different layer sequences and thicknesses impacted by a 12.7 mm armor-piercing incendiary… More >

  • Open Access

    ARTICLE

    Unsteady MHD Casson Nanofluid Flow Past an Exponentially Accelerated Vertical Plate: An Analytical Strategy

    T. Aghalya, R. Tamizharasi*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 431-460, 2024, DOI:10.32604/cmes.2024.046635

    Abstract In this study, the characteristics of heat transfer on an unsteady magnetohydrodynamic (MHD) Casson nanofluid over an exponentially accelerated vertical porous plate with rotating effects were investigated. The flow was driven by the combined effects of the magnetic field, heat radiation, heat source/sink and chemical reaction. Copper oxide () and titanium oxide () are acknowledged as nanoparticle materials. The nondimensional governing equations were subjected to the Laplace transformation technique to derive closed-form solutions. Graphical representations are provided to analyze how changes in physical parameters, such as the magnetic field, heat radiation, heat source/sink and chemical reaction, affect the velocity, temperature… More >

  • Open Access

    ARTICLE

    The Lambert-G Family: Properties, Inference, and Applications

    Jamal N. Al Abbasi1, Ahmed Z. Afify2,*, Badr Alnssyan3,*, Mustafa S. Shama4,5

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 513-536, 2024, DOI:10.32604/cmes.2024.046533

    Abstract This study proposes a new flexible family of distributions called the Lambert-G family. The Lambert family is very flexible and exhibits desirable properties. Its three-parameter special sub-models provide all significant monotonic and non-monotonic failure rates. A special sub-model of the Lambert family called the Lambert-Lomax (LL) distribution is investigated. General expressions for the LL statistical properties are established. Characterizations of the LL distribution are addressed mathematically based on its hazard function. The estimation of the LL parameters is discussed using six estimation methods. The performance of this estimation method is explored through simulation experiments. The usefulness and flexibility of the… More >

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