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  • Open Access


    Lithium-Ion Battery Pack Based on Fuzzy Logic Control Research on Multi-Layer Equilibrium Circuits

    Tiezhou Wu, Yukan Zhang*

    Energy Engineering, Vol.121, No.8, pp. 2231-2255, 2024, DOI:10.32604/ee.2024.049883

    Abstract In order to solve the problem of inconsistent energy in the charging and discharging cycles of lithium-ion battery packs, a new multilayer equilibrium topology is designed in this paper. The structure adopts a hierarchical structure design, which includes intra-group equilibrium, primary inter-group equilibrium and secondary inter-group equilibrium. This structure greatly increases the number of equilibrium paths for lithium-ion batteries, thus shortening the time required for equilibrium, and improving the overall efficiency. In terms of control strategy, fuzzy logic control (FLC) is chosen to control the size of the equilibrium current during the equilibrium process. We… More >

  • Open Access


    A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks

    Huiyan Zhao1, Xuezhong Chen1, Zhijian Hu2,*, Man Chen1, Bo Xiong3, Jianying Yang1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1313-1330, 2024, DOI:10.32604/fdmp.2024.048840

    Abstract Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis, a model is developed to predict the related well production rate. This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales, as well as the flow characteristics in different types of thin layers (tight sandstone gas, shale gas, and coalbed gas). Moreover, a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir. A… More > Graphic Abstract

    A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks

  • Open Access


    Recommendation System Based on Perceptron and Graph Convolution Network

    Zuozheng Lian1,2, Yongchao Yin1, Haizhen Wang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3939-3954, 2024, DOI:10.32604/cmc.2024.049780

    Abstract The relationship between users and items, which cannot be recovered by traditional techniques, can be extracted by the recommendation algorithm based on the graph convolution network. The current simple linear combination of these algorithms may not be sufficient to extract the complex structure of user interaction data. This paper presents a new approach to address such issues, utilizing the graph convolution network to extract association relations. The proposed approach mainly includes three modules: Embedding layer, forward propagation layer, and score prediction layer. The embedding layer models users and items according to their interaction information and… More >

  • Open Access


    Intelligent Machine Learning Based Brain Tumor Segmentation through Multi-Layer Hybrid U-Net with CNN Feature Integration

    Sharaf J. Malebary*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1301-1317, 2024, DOI:10.32604/cmc.2024.047917

    Abstract Brain tumors are a pressing public health concern, characterized by their high mortality and morbidity rates. Nevertheless, the manual segmentation of brain tumors remains a laborious and error-prone task, necessitating the development of more precise and efficient methodologies. To address this formidable challenge, we propose an advanced approach for segmenting brain tumor Magnetic Resonance Imaging (MRI) images that harnesses the formidable capabilities of deep learning and convolutional neural networks (CNNs). While CNN-based methods have displayed promise in the realm of brain tumor segmentation, the intricate nature of these tumors, marked by irregular shapes, varying sizes,… More >

  • Open Access


    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 More >

  • Open Access


    A Weighted Multi-Layer Analytics Based Model for Emoji Recommendation

    Amira M. Idrees1,*, Abdul Lateef Marzouq Al-Solami2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1115-1133, 2024, DOI:10.32604/cmc.2023.046457

    Abstract The developed system for eye and face detection using Convolutional Neural Networks (CNN) models, followed by eye classification and voice-based assistance, has shown promising potential in enhancing accessibility for individuals with visual impairments. The modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the system. This research significantly contributes to the field of accessibility technology by integrating computer vision, natural language processing, and voice technologies. By leveraging these advancements, the developed system offers a practical and efficient solution for assisting blind individuals. The modular… More >

  • Open Access


    Efficient Object Segmentation and Recognition Using Multi-Layer Perceptron Networks

    Aysha Naseer1, Nouf Abdullah Almujally2, Saud S. Alotaibi3, Abdulwahab Alazeb4, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1381-1398, 2024, DOI:10.32604/cmc.2023.042963

    Abstract Object segmentation and recognition is an imperative area of computer vision and machine learning that identifies and separates individual objects within an image or video and determines classes or categories based on their features. The proposed system presents a distinctive approach to object segmentation and recognition using Artificial Neural Networks (ANNs). The system takes RGB images as input and uses a k-means clustering-based segmentation technique to fragment the intended parts of the images into different regions and label them based on their characteristics. Then, two distinct kinds of features are obtained from the segmented images More >

  • Open Access


    Detecting Phishing Using a Multi-Layered Social Engineering Framework

    Kofi Sarpong Adu-Manu*, Richard Kwasi Ahiable

    Journal of Cyber Security, Vol.5, pp. 13-32, 2023, DOI:10.32604/jcs.2023.043359

    Abstract As businesses develop and expand with a significant volume of data, data protection and privacy become increasingly important. Research has shown a tremendous increase in phishing activities during and after COVID-19. This research aimed to improve the existing approaches to detecting phishing activities on the internet. We designed a multi-layered phish detection algorithm to detect and prevent phishing applications on the internet using URLs. In the algorithm, we considered technical dimensions of phishing attack prevention and mitigation on the internet. In our approach, we merge, Phishtank, Blacklist, Blocklist, and Whitelist to form our framework. A More >

  • Open Access


    Multi-Layer Deep Sparse Representation for Biological Slice Image Inpainting

    Haitao Hu1, Hongmei Ma2, Shuli Mei1,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3813-3832, 2023, DOI:10.32604/cmc.2023.041416

    Abstract Biological slices are an effective tool for studying the physiological structure and evolution mechanism of biological systems. However, due to the complexity of preparation technology and the presence of many uncontrollable factors during the preparation processing, leads to problems such as difficulty in preparing slice images and breakage of slice images. Therefore, we proposed a biological slice image small-scale corruption inpainting algorithm with interpretability based on multi-layer deep sparse representation, achieving the high-fidelity reconstruction of slice images. We further discussed the relationship between deep convolutional neural networks and sparse representation, ensuring the high-fidelity characteristic of… More >

  • Open Access


    A Shape Optimization Approach for 3D Doubly-Periodic Multi-Layered Systems

    Haibo Chen1,*, Fuhang Jiang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09414

    Abstract Acoustic wave propagation has been the subject of many studies in engineering and physics. Researchers have shown an increased interest in recent years in the acoustic scattering of periodic systems, such as phononic crystals and metamaterials [1]. These artificial periodic systems possess some particular acoustic characteristics including noise control, waveguides and negative refraction, which manifest excellent potential applicability in acoustic engineering. Based on the isogeometric acoustic boundary element method (BEM) [2], an efficient shape optimization approach is proposed in this research for threedimensional doubly-periodic multi-layered systems. The interfaces between different acoustic mediums are infinite doubly… More >

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