Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (265)
  • Open Access

    ARTICLE

    Oscillatory Dynamics of a Spherical Solid in a Liquid in an Axisymmetric Variable Cross Section Channel

    Ivan Karpunin*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1219-1232, 2024, DOI:10.32604/fdmp.2024.051062

    Abstract The dynamics of a solid spherical body in an oscillating liquid flow in a vertical axisymmetric channel of variable cross section is experimentally studied. It is shown that the oscillating liquid leads to the generation of intense averaged flows in each of the channel segments. The intensity and direction of these flows depend on the dimensionless oscillating frequency. In the region of studied frequencies, the dynamics of the considered body is examined when the primary vortices emerging in the flow occupy the whole region in each segment. For a fixed frequency, an increase in the… More >

  • Open Access

    ARTICLE

    Modeling and Analysis of OFDMA-NOMA-RA Protocol Considering Imperfect SIC in Multi-User Uplink WLANs

    Hailing Yang1, Suoping Li1,2,*, Duo Peng2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5273-5294, 2024, DOI:10.32604/cmc.2024.050869

    Abstract To address the problems of network congestion and spectrum resources shortage in multi-user large-scale scenarios, this paper proposes a twice random access OFDMA-NOMA-RA protocol combining the advantages of orthogonal frequency division multiple access (OFDMA) and non-orthogonal multiple access (NOMA). The idea of this protocol is that OFMDA is used to divide the entire frequency field into multiple orthogonal resource units (RUs), and NOMA is used on each RU to enable more users to access the channel and improve spectrum efficiency. Based on the protocol designed in this paper, in the case of imperfect successive interference… More >

  • Open Access

    ARTICLE

    Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

    Haoyi Zhong, Yongjiang Zhao, Chang Gyoon Lim*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1757-1781, 2024, DOI:10.32604/cmes.2024.049208

    Abstract This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery (LiB) time series data. As the energy sector increasingly focuses on integrating distributed energy resources, Virtual Power Plants (VPP) have become a vital new framework for energy management. LiBs are key in this context, owing to their high-efficiency energy storage capabilities essential for VPP operations. However, LiBs are prone to various abnormal states like overcharging, over-discharging, and internal short circuits, which impede power transmission efficiency. Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and… More >

  • Open Access

    ARTICLE

    Dynamic Characteristics of Functionally Graded Timoshenko Beams by Improved Differential Quadrature Method

    Xiaojun Huang1, Liaojun Zhang2,*, Hanbo Cui1, Gaoxing Hu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1647-1668, 2024, DOI:10.32604/cmes.2024.049124

    Abstract This study proposes an effective method to enhance the accuracy of the Differential Quadrature Method (DQM) for calculating the dynamic characteristics of functionally graded beams by improving the form of discrete node distribution. Firstly, based on the first-order shear deformation theory, the governing equation of free vibration of a functionally graded beam is transformed into the eigenvalue problem of ordinary differential equations with respect to beam axial displacement, transverse displacement, and cross-sectional rotation angle by considering the effects of shear deformation and rotational inertia of the beam cross-section. Then, ignoring the shear deformation of the… More >

  • Open Access

    ARTICLE

    Comprehensive Analysis of Gender Classification Accuracy across Varied Geographic Regions through the Application of Deep Learning Algorithms to Speech Signals

    Abhishek Singhal*, Devendra Kumar Sharma

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 609-625, 2024, DOI:10.32604/csse.2023.046730

    Abstract This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions, employing a deep learning classification algorithm for speech signal analysis. In this study, speech samples are categorized for both training and testing purposes based on their geographical origin. Category 1 comprises speech samples from speakers outside of India, whereas Category 2 comprises live-recorded speech samples from Indian speakers. Testing speech samples are likewise classified into four distinct sets, taking into consideration both geographical origin and the language spoken by the speakers. Significantly, the results indicate a noticeable difference… More >

  • Open Access

    ARTICLE

    A Heuristic Radiomics Feature Selection Method Based on Frequency Iteration and Multi-Supervised Training Mode

    Zhigao Zeng1,2, Aoting Tang1,2, Shengqiu Yi1,2, Xinpan Yuan1,2, Yanhui Zhu1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2277-2293, 2024, DOI:10.32604/cmc.2024.047989

    Abstract Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for diagnosis. It has received great attention due to its huge application prospects in recent years. We can know that the number of features selected by the existing radiomics feature selection methods is basically about ten. In this paper, a heuristic feature selection method based on frequency iteration and multiple supervised training mode is proposed. Based on the combination between features, it decomposes all features layer by layer to select the optimal features for each layer, then fuses the optimal features More >

  • Open Access

    ARTICLE

    Desired Dynamic Equation for Primary Frequency Modulation Control of Gas Turbines

    Aimin Gao1, Xiaobo Cui2,*, Guoqiang Yu1, Jianjun Shu1, Tianhai Zhang1

    Energy Engineering, Vol.121, No.5, pp. 1347-1361, 2024, DOI:10.32604/ee.2023.045805

    Abstract Gas turbines play core roles in clean energy supply and the construction of comprehensive energy systems. The control performance of primary frequency modulation of gas turbines has a great impact on the frequency control of the power grid. However, there are some control difficulties in the primary frequency modulation control of gas turbines, such as the coupling effect of the fuel control loop and speed control loop, slow tracking speed, and so on. To relieve the abovementioned difficulties, a control strategy based on the desired dynamic equation proportional integral (DDE-PI) is proposed in this paper. More >

  • Open Access

    ARTICLE

    Image Fusion Using Wavelet Transformation and XGboost Algorithm

    Shahid Naseem1, Tariq Mahmood2,3, Amjad Rehman Khan2, Umer Farooq1, Samra Nawazish4, Faten S. Alamri5,*, Tanzila Saba2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 801-817, 2024, DOI:10.32604/cmc.2024.047623

    Abstract Recently, there have been several uses for digital image processing. Image fusion has become a prominent application in the domain of imaging processing. To create one final image that proves more informative and helpful compared to the original input images, image fusion merges two or more initial images of the same item. Image fusion aims to produce, enhance, and transform significant elements of the source images into combined images for the sake of human visual perception. Image fusion is commonly employed for feature extraction in smart robots, clinical imaging, audiovisual camera integration, manufacturing process monitoring,… More >

  • Open Access

    ARTICLE

    Uncertainty-Aware Physical Simulation of Neural Radiance Fields for Fluids

    Haojie Lian1, Jiaqi Wang1, Leilei Chen2,*, Shengze Li3, Ruochen Cao4, Qingyuan Hu5, Peiyun Zhao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1143-1163, 2024, DOI:10.32604/cmes.2024.048549

    Abstract This paper presents a novel framework aimed at quantifying uncertainties associated with the 3D reconstruction of smoke from 2D images. This approach reconstructs color and density fields from 2D images using Neural Radiance Field (NeRF) and improves image quality using frequency regularization. The NeRF model is obtained via joint training of multiple artificial neural networks, whereby the expectation and standard deviation of density fields and RGB values can be evaluated for each pixel. In addition, customized physics-informed neural network (PINN) with residual blocks and two-layer activation functions are utilized to input the density fields 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… More >

Displaying 1-10 on page 1 of 265. Per Page