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  • Open Access

    ARTICLE

    Coupling Magneto-Electro-Elastic Multiscale Finite Element Method for Transient Responses of Heterogeneous MEE Structures

    Xiaolin Li1, Xinyue Li1, Liming Zhou2,*, Hangran Yang1, Xiaoqing Yuan1

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3821-3841, 2025, DOI:10.32604/cmc.2025.059937 - 06 March 2025

    Abstract Magneto-electro-elastic (MEE) materials are widely utilized across various fields due to their multi-field coupling effects. Consequently, investigating the coupling behavior of MEE composite materials is of significant importance. The traditional finite element method (FEM) remains one of the primary approaches for addressing such issues. However, the application of FEM typically necessitates the use of a fine finite element mesh to accurately capture the heterogeneous properties of the materials and meet the required computational precision, which inevitably leads to a reduction in computational efficiency. To enhance the computational accuracy and efficiency of the FEM for heterogeneous… More >

  • Open Access

    ARTICLE

    MMH-FE: A Multi-Precision and Multi-Sourced Heterogeneous Privacy-Preserving Neural Network Training Based on Functional Encryption

    Hao Li1,#, Kuan Shao1,#, Xin Wang2, Mufeng Wang3, Zhenyong Zhang1,2,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5387-5405, 2025, DOI:10.32604/cmc.2025.059718 - 06 March 2025

    Abstract Due to the development of cloud computing and machine learning, users can upload their data to the cloud for machine learning model training. However, dishonest clouds may infer user data, resulting in user data leakage. Previous schemes have achieved secure outsourced computing, but they suffer from low computational accuracy, difficult-to-handle heterogeneous distribution of data from multiple sources, and high computational cost, which result in extremely poor user experience and expensive cloud computing costs. To address the above problems, we propose a multi-precision, multi-sourced, and multi-key outsourcing neural network training scheme. Firstly, we design a multi-precision More >

  • Open Access

    REVIEW

    On Optimizing Resource Allocation: A Comparative Review of Resource Allocation Strategies in HetNets

    Jeta Dobruna1,2, Zana Limani Fazliu2,*, Iztok Humar1, Mojca Volk1

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2211-2245, 2025, DOI:10.32604/cmes.2025.059541 - 03 March 2025

    Abstract Resource allocation remains a challenging issue in communication networks, and its complexity is continuously increasing with the densification of the networks. With the evolution of new wireless technologies such as Fifth Generation (5G) and Sixth Generation (6G) mobile networks, the service level requirements have become stricter and more heterogeneous depending on the use case. In this paper, we review a large body of literature on various resource allocation schemes that are used in particular in mobile wireless communication networks and compare the proposed schemes in terms of performance indicators as well as techniques used. Our… More >

  • Open Access

    ARTICLE

    A Software Defect Prediction Method Using a Multivariate Heterogeneous Hybrid Deep Learning Algorithm

    Qi Fei1,2,*, Haojun Hu3, Guisheng Yin1, Zhian Sun2

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3251-3279, 2025, DOI:10.32604/cmc.2024.058931 - 17 February 2025

    Abstract Software defect prediction plays a critical role in software development and quality assurance processes. Effective defect prediction enables testers to accurately prioritize testing efforts and enhance defect detection efficiency. Additionally, this technology provides developers with a means to quickly identify errors, thereby improving software robustness and overall quality. However, current research in software defect prediction often faces challenges, such as relying on a single data source or failing to adequately account for the characteristics of multiple coexisting data sources. This approach may overlook the differences and potential value of various data sources, affecting the accuracy… More >

  • Open Access

    ARTICLE

    HNRNPC as a pan-cancer biomarker and therapeutic target involved in tumor progression and immune regulation

    YUEZHOU ZHANG1,#, ZHAO ZHANG2,#, JINXIN DONG1, CHANGAN LIU1,*

    Oncology Research, Vol.33, No.1, pp. 83-102, 2025, DOI:10.32604/or.2024.055866 - 20 December 2024

    Abstract Background: Aberrant expression of RNA-binding proteins (RBPs) has been linked to a variety of diseases, including hematological disorders, cardiovascular diseases, and multiple types of cancer. Heterogeneous nuclear ribonucleoprotein C (HNRNPC), a member belonging to the heterogeneous nuclear ribonucleoprotein (hnRNP) family, plays a pivotal role in nucleic acid metabolism. Previous studies have underscored the significance of HNRNPC in tumorigenesis; however, its specific role in malignant tumor progression remains inadequately characterized. Methods: We leveraged publicly available databases, including The Cancer Genome Atlas (TCGA), to explore the potential involvement of HNRNPC across various cancers. Additionally, we performed experimental… More > Graphic Abstract

    HNRNPC as a pan-cancer biomarker and therapeutic target involved in tumor progression and immune regulation

  • Open Access

    ARTICLE

    EGSNet: An Efficient Glass Segmentation Network Based on Multi-Level Heterogeneous Architecture and Boundary Awareness

    Guojun Chen*, Tao Cui, Yongjie Hou, Huihui Li

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3969-3987, 2024, DOI:10.32604/cmc.2024.056093 - 19 December 2024

    Abstract Existing glass segmentation networks have high computational complexity and large memory occupation, leading to high hardware requirements and time overheads for model inference, which is not conducive to efficiency-seeking real-time tasks such as autonomous driving. The inefficiency of the models is mainly due to employing homogeneous modules to process features of different layers. These modules require computationally intensive convolutions and weight calculation branches with numerous parameters to accommodate the differences in information across layers. We propose an efficient glass segmentation network (EGSNet) based on multi-level heterogeneous architecture and boundary awareness to balance the model performance… More >

  • Open Access

    PROCEEDINGS

    Multi-Scale Microstructure Manipulation of an Additively Manufactured CoCrNi Medium Entropy Alloy for Superior Mechanical Properties and Tunable Mechanical Anisotropy

    Chenze Li1, Manish Jain1,2, Qian Liu1, Zhuohan Cao1, Michael Ferry3, Jamie J. Kruzic1, Bernd Gludovatz1, Xiaopeng Li1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.011290

    Abstract Laser powder bed fusion (LPBF) additive manufacturing (AM) technology has become a versatile tool for producing new microstructures in metal components, offering novel mechanical properties for different applications. In this work, enhanced ductility (~55% elongation) and tunable mechanical anisotropy (ratio of ductility along vertical to horizontal orientation from ~0.2 to ~1) were achieved for a CoCrNi medium entropy alloy (MEA) by multi-scale synergistic microstructure manipulation (i.e., melt pool boundary, grain morphology and crystallographic texture) through adjusting key LPBF processing parameters (e.g., laser power and scan speed). By increasing the volumetric energy density (VED) from 68.3… More >

  • Open Access

    PROCEEDINGS

    Identification of the Anisotropic Thermal-Mechanical Properties of Sheet Metals Using the Virtual Fields Method

    Jiawei Fu1,2,*, Yahui Cai1, Bowen Zhang1, Zengxiang Qi1, Lehua Qi1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.013007

    Abstract The accurate characterization of the anisotropic thermal-mechanical constitutive properties of structural sheet metals at elevated temperatures and under nonuniform stress/strain states is crucial for the precise hot plastic forming and structural behavior evaluation of an engineering sheet part. Traditional thermal-mechanical testing methods rely on the assumption of states homogeneity, leading to a large number of tests required for the characterization of material anisotropy and nonlinearity at various high temperatures. In this work, a highly efficient identification method is proposed that allows the simultaneous characterization of the anisotropic yielding, strain hardening and elasto-plasticity thermal softening material More >

  • Open Access

    ARTICLE

    A Discrete Multi-Objective Squirrel Search Algorithm for Energy-Efficient Distributed Heterogeneous Permutation Flowshop with Variable Processing Speed

    Liang Zeng1,2,3, Ziyang Ding1, Junyang Shi1, Shanshan Wang1,2,3,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1757-1787, 2024, DOI:10.32604/cmc.2024.055574 - 15 October 2024

    Abstract In the manufacturing industry, reasonable scheduling can greatly improve production efficiency, while excessive resource consumption highlights the growing significance of energy conservation in production. This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed (DHPFSP-VPS), considering both the minimum makespan and total energy consumption (TEC) as objectives. A discrete multi-objective squirrel search algorithm (DMSSA) is proposed to solve the DHPFSP-VPS. DMSSA makes four improvements based on the squirrel search algorithm. Firstly, in terms of the population initialization strategy, four hybrid initialization methods targeting different objectives are proposed to enhance… More >

  • Open Access

    PROCEEDINGS

    Simulation of Underwater Explosion Shock Wave Propagation in Heterogeneous Fluid Field

    Yuntao Lei1, Wenbin Wu1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011365

    Abstract The underwater explosion could cause the serious damage to the naval ships. Investigating the underwater explosion problem is crucial for the development of marine military power. During the recent years, the underwater explosion dynamics in the homogeneous fluid field has been investigated by lots of researchers. However, there often exist sound speed thermoclines in the real ocean environment, which leads to a more complex fluid environment than the homogeneous fluid. The corresponding numerical calculations become more complicated. In order to fully understand the underwater explosion dynamics in the real ocean environment, we perform the numerical… More >

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