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  • Open Access

    ARTICLE

    A Hybrid Level Set Optimization Design Method of Functionally Graded Cellular Structures Considering Connectivity

    Yan Dong1,2, Kang Zhao1, Liang Gao1, Hao Li1,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1-18, 2024, DOI:10.32604/cmc.2024.048870

    Abstract With the continuous advancement in topology optimization and additive manufacturing (AM) technology, the capability to fabricate functionally graded materials and intricate cellular structures with spatially varying microstructures has grown significantly. However, a critical challenge is encountered in the design of these structures–the absence of robust interface connections between adjacent microstructures, potentially resulting in diminished efficiency or macroscopic failure. A Hybrid Level Set Method (HLSM) is proposed, specifically designed to enhance connectivity among non-uniform microstructures, contributing to the design of functionally graded cellular structures. The HLSM introduces a pioneering algorithm for effectively blending heterogeneous microstructure interfaces. Initially, an interpolation algorithm is… More >

  • Open Access

    ARTICLE

    Ghost Module Based Residual Mixture of Self-Attention and Convolution for Online Signature Verification

    Fangjun Luan1,2,3, Xuewen Mu1,2,3, Shuai Yuan1,2,3,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 695-712, 2024, DOI:10.32604/cmc.2024.048502

    Abstract Online Signature Verification (OSV), as a personal identification technology, is widely used in various industries. However, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. To address these issues, we propose a novel approach for online signature verification, using a one-dimensional Ghost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolution with a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residual structure is introduced to leverage both self-attention and convolution mechanisms for capturing global feature information and extracting local information, effectively complementing whole and local signature features and mitigating… More >

  • Open Access

    ARTICLE

    Smartphone-Based Wi-Fi Analysis for Bus Passenger Counting

    Mohammed Alatiyyah*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 875-907, 2024, DOI:10.32604/cmc.2024.047790

    Abstract In the contemporary era of technological advancement, smartphones have become an indispensable part of individuals’ daily lives, exerting a pervasive influence. This paper presents an innovative approach to passenger counting on buses through the analysis of Wi-Fi signals emanating from passengers’ mobile devices. The study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels, thereby addressing a crucial aspect of public transportation. The proposed system comprises three crucial elements: Signal capture, data filtration, and the calculation and estimation of passenger numbers. The pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts… More >

  • Open Access

    ARTICLE

    Reinforcement Learning Based Quantization Strategy Optimal Assignment Algorithm for Mixed Precision

    Yuejiao Wang, Zhong Ma*, Chaojie Yang, Yu Yang, Lu Wei

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 819-836, 2024, DOI:10.32604/cmc.2024.047108

    Abstract The quantization algorithm compresses the original network by reducing the numerical bit width of the model, which improves the computation speed. Because different layers have different redundancy and sensitivity to data bit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determine the optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantization can effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In this paper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to low bit width is proposed,… More >

  • Open Access

    ARTICLE

    Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm

    Parth Khandelwal1, Harshit2, Indranil Manna1,3,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1727-1755, 2024, DOI:10.32604/cmc.2024.042752

    Abstract Metallic alloys for a given application are usually designed to achieve the desired properties by devising experiments based on experience, thermodynamic and kinetic principles, and various modeling and simulation exercises. However, the influence of process parameters and material properties is often non-linear and non-colligative. In recent years, machine learning (ML) has emerged as a promising tool to deal with the complex interrelation between composition, properties, and process parameters to facilitate accelerated discovery and development of new alloys and functionalities. In this study, we adopt an ML-based approach, coupled with genetic algorithm (GA) principles, to design novel copper alloys for achieving… More > Graphic Abstract

    Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm

  • Open Access

    ARTICLE

    Circ_0053943 complexed with IGF2BP3 drives uveal melanoma progression via regulating N6-methyladenosine modification of Epidermal growth factor receptor

    ANDI ZHAO1,2,#, YUE WANG3,#, ZIJIN WANG1,2, QING SHAO1,2, QI GONG1,2, HUI ZHU1,2, SHIYA SHEN1,2, HU LIU1,2,*, XUEJUAN CHEN1,2,*

    Oncology Research, Vol.32, No.5, pp. 983-998, 2024, DOI:10.32604/or.2024.045972

    Abstract Numerous studies have characterized the critical role of circular RNAs (circRNAs) as regulatory factors in the progression of multiple cancers. However, the biological functions of circRNAs and their underlying molecular mechanisms in the progression of uveal melanoma (UM) remain enigmatic. In this study, we identified a novel circRNA, circ_0053943, through re-analysis of UM microarray data and quantitative RT-PCR. Circ_0053943 was found to be upregulated in UM and to promote the proliferation and metastatic ability of UM cells in both in vitro and in vivo settings. Mechanistically, circ_0053943 was observed to bind to the KH1 and KH2 domains of insulin-like growth… More > Graphic Abstract

    <i>Circ_0053943</i> complexed with IGF2BP3 drives uveal melanoma progression via regulating N6-methyladenosine modification of <i>Epidermal growth factor receptor</i>

  • Open Access

    ARTICLE

    Application of the CatBoost Model for Stirred Reactor State Monitoring Based on Vibration Signals

    Xukai Ren1,2,*, Huanwei Yu2, Xianfeng Chen2, Yantong Tang2, Guobiao Wang1,*, Xiyong Du2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 647-663, 2024, DOI:10.32604/cmes.2024.048782

    Abstract Stirred reactors are key equipment in production, and unpredictable failures will result in significant economic losses and safety issues. Therefore, it is necessary to monitor its health state. To achieve this goal, in this study, five states of the stirred reactor were firstly preset: normal, shaft bending, blade eccentricity, bearing wear, and bolt looseness. Vibration signals along x, y and z axes were collected and analyzed in both the time domain and frequency domain. Secondly, 93 statistical features were extracted and evaluated by ReliefF, Maximal Information Coefficient (MIC) and XGBoost. The above evaluation results were then fused by D-S evidence… More >

  • Open Access

    ARTICLE

    Random Forest-Based Fatigue Reliability-Based Design Optimization for Aeroengine Structures

    Xue-Qin Li1, Lu-Kai Song2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 665-684, 2024, DOI:10.32604/cmes.2024.048445

    Abstract Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function, leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy. In this case, by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory, a random forest (RF) model is presented to enhance the computing efficiency of reliability degree; moreover, by embedding the RF model into multilevel optimization model, an efficient RF-assisted fatigue reliability-based design optimization framework is developed. Regarding the low-cycle fatigue reliability-based design optimization of… More >

  • Open Access

    ARTICLE

    Dynamic Response of Foundations during Startup of High-Frequency Tunnel Equipment

    Dawei Ruan1, Mingwei Hu1,2,3,4,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 821-844, 2024, DOI:10.32604/cmes.2024.048392

    Abstract The specialized equipment utilized in long-line tunnel engineering is evolving towards large-scale, multifunctional, and complex orientations. The vibration caused by the high-frequency units during regular operation is supported by the foundation of the units, and the magnitude of vibration and the operating frequency fluctuate in different engineering contexts, leading to variations in the dynamic response of the foundation. The high-frequency units yield significantly diverse outcomes under different startup conditions and times, resulting in failure to meet operational requirements, influencing the normal function of the tunnel, and causing harm to the foundation structure, personnel, and property in severe cases. This article… More >

  • Open Access

    ARTICLE

    Multi-Stage Multidisciplinary Design Optimization Method for Enhancing Complete Artillery Internal Ballistic Firing Performance

    Jipeng Xie1,2, Guolai Yang1,*, Liqun Wang1, Lei Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 793-819, 2024, DOI:10.32604/cmes.2024.048174

    Abstract To enhance the comprehensive performance of artillery internal ballistics—encompassing power, accuracy, and service life—this study proposed a multi-stage multidisciplinary design optimization (MS-MDO) method. First, the comprehensive artillery internal ballistic dynamics (AIBD) model, based on propellant combustion, rotation band engraving, projectile axial motion, and rifling wear models, was established and validated. This model was systematically decomposed into subsystems from a system engineering perspective. The study then detailed the MS-MDO methodology, which included Stage I (MDO stage) employing an improved collaborative optimization method for consistent design variables, and Stage II (Performance Optimization) focusing on the independent optimization of local design variables and… More >

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