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  • Open Access

    ARTICLE

    Analyze the Performance of Electroactive Anticorrosion Coating of Medical Magnesium Alloy Using Deep Learning

    Yashan Feng1, Yafang Tian1, Yongxin Yang1, Yufang Zhang1, Haiwei Guo1, Jing’an Li2,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 263-278, 2024, DOI:10.32604/cmc.2024.047004

    Abstract Electroactive anticorrosion coatings are specialized surface treatments that prevent or minimize corrosion. The study employs strategic thermodynamic equilibrium calculations to pioneer a novel factor in corrosion protection. A first-time proposal, the total acidity (TA) potential of the hydrogen (pH) concept significantly shapes medical magnesium alloys. These coatings are meticulously designed for robust corrosion resistance, blending theoretical insights and practical applications to enhance our grasp of corrosion prevention mechanisms and establish a systematic approach to coating design. The groundbreaking significance of this study lies in its innovative integration of the TA/pH concept, which encompasses the TA/pH ratio of the chemical environment.… More >

  • Open Access

    ARTICLE

    MIDNet: Deblurring Network for Material Microstructure Images

    Jiaxiang Wang1, Zhengyi Li1, Peng Shi1, Hongying Yu2, Dongbai Sun1,3,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1187-1204, 2024, DOI:10.32604/cmc.2024.046929

    Abstract Scanning electron microscopy (SEM) is a crucial tool in the field of materials science, providing valuable insights into the microstructural characteristics of materials. Unfortunately, SEM images often suffer from blurriness caused by improper hardware calibration or imaging automation errors, which present challenges in analyzing and interpreting material characteristics. Consequently, rectifying the blurring of these images assumes paramount significance to enable subsequent analysis. To address this issue, we introduce a Material Images Deblurring Network (MIDNet) built upon the foundation of the Nonlinear Activation Free Network (NAFNet). MIDNet is meticulously tailored to address the blurring in images capturing the microstructure of materials.… More >

  • Open Access

    ARTICLE

    A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

    Naglaa F. Soliman1, Fatma E. Fadl-Allah2, Walid El-Shafai3,4,*, Mahmoud I. Aly2, Maali Alabdulhafith1, Fathi E. Abd El-Samie1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 201-241, 2024, DOI:10.32604/cmc.2024.046757

    Abstract The efficient transmission of images, which plays a large role in wireless communication systems, poses a significant challenge in the growth of multimedia technology. High-quality images require well-tuned communication standards. The Single Carrier Frequency Division Multiple Access (SC-FDMA) is adopted for broadband wireless communications, because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio (PAPR). Data transmission through open-channel networks requires much concentration on security, reliability, and integrity. The data need a space away from unauthorized access, modification, or deletion. These requirements are to be fulfilled by digital image watermarking and encryption. This paper is mainly… More >

  • Open Access

    ARTICLE

    Automated Algorithms for Detecting and Classifying X-Ray Images of Spine Fractures

    Fayez Alfayez*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1539-1560, 2024, DOI:10.32604/cmc.2024.046443

    Abstract This paper emphasizes a faster digital processing time while presenting an accurate method for identifying spine fractures in X-ray pictures. The study focuses on efficiency by utilizing many methods that include picture segmentation, feature reduction, and image classification. Two important elements are investigated to reduce the classification time: Using feature reduction software and leveraging the capabilities of sophisticated digital processing hardware. The researchers use different algorithms for picture enhancement, including the Wiener and Kalman filters, and they look into two background correction techniques. The article presents a technique for extracting textural features and evaluates three picture segmentation algorithms and three… More >

  • Open Access

    ARTICLE

    Multimodal Social Media Fake News Detection Based on Similarity Inference and Adversarial Networks

    Fangfang Shan1,2,*, Huifang Sun1,2, Mengyi Wang1,2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 581-605, 2024, DOI:10.32604/cmc.2024.046202

    Abstract As social networks become increasingly complex, contemporary fake news often includes textual descriptions of events accompanied by corresponding images or videos. Fake news in multiple modalities is more likely to create a misleading perception among users. While early research primarily focused on text-based features for fake news detection mechanisms, there has been relatively limited exploration of learning shared representations in multimodal (text and visual) contexts. To address these limitations, this paper introduces a multimodal model for detecting fake news, which relies on similarity reasoning and adversarial networks. The model employs Bidirectional Encoder Representation from Transformers (BERT) and Text Convolutional Neural… More >

  • Open Access

    ARTICLE

    DCFNet: An Effective Dual-Branch Cross-Attention Fusion Network for Medical Image Segmentation

    Chengzhang Zhu1,2, Renmao Zhang1, Yalong Xiao1,2,*, Beiji Zou1, Xian Chai1, Zhangzheng Yang1, Rong Hu3, Xuanchu Duan4

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1103-1128, 2024, DOI:10.32604/cmes.2024.048453

    Abstract Automatic segmentation of medical images provides a reliable scientific basis for disease diagnosis and analysis. Notably, most existing methods that combine the strengths of convolutional neural networks (CNNs) and Transformers have made significant progress. However, there are some limitations in the current integration of CNN and Transformer technology in two key aspects. Firstly, most methods either overlook or fail to fully incorporate the complementary nature between local and global features. Secondly, the significance of integrating the multi-scale encoder features from the dual-branch network to enhance the decoding features is often disregarded in methods that combine CNN and Transformer. To address… More >

  • Open Access

    ARTICLE

    Aerodynamic Features of High-Speed Maglev Trains with Different Marshaling Lengths Running on a Viaduct under Crosswinds

    Zun-Di Huang1, Zhen-Bin Zhou1,2,3, Ning Chang1, Zheng-Wei Chen2,3,*, Su-Mei Wang2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 975-996, 2024, DOI:10.32604/cmes.2024.047664

    Abstract The safety and stability of high-speed maglev trains traveling on viaducts in crosswinds critically depend on their aerodynamic characteristics. Therefore, this paper uses an improved delayed detached eddy simulation (IDDES) method to investigate the aerodynamic features of high-speed maglev trains with different marshaling lengths under crosswinds. The effects of marshaling lengths (varying from 3-car to 8-car groups) on the train’s aerodynamic performance, surface pressure, and the flow field surrounding the train were investigated using the three-dimensional unsteady compressible Navier-Stokes (N-S) equations. The results showed that the marshaling lengths had minimal influence on the aerodynamic performance of the head and middle… More > Graphic Abstract

    Aerodynamic Features of High-Speed Maglev Trains with Different Marshaling Lengths Running on a Viaduct under Crosswinds

  • Open Access

    ARTICLE

    An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

    Qing Zhu1,*, Linlin Gu1,2, Huijie Lin1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 577-591, 2024, DOI:10.32604/cmes.2023.043307

    Abstract With the rapid development of electric power systems, load estimation plays an important role in system operation and planning. Usually, load estimation techniques contain traditional, time series, regression analysis-based, and machine learning-based estimation. Since the machine learning-based method can lead to better performance, in this paper, a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed. First, an image fingerprint construction is proposed for training data. After the data preprocessing, the training data matrix is constructed by the cyclic shift and cubic spline interpolation. Then, the linear mapping and the gray-color transformation method are proposed to… More >

  • Open Access

    ARTICLE

    Microwave–Induced Thermo-Responsive Shape Memory Polyurethane/MWCNTs Composites and Improved their Shape Memory and Mechanical Properties

    KRISHAN KUMAR PATEL, RAJESH PUROHIT

    Journal of Polymer Materials, Vol.36, No.1, pp. 23-37, 2019, DOI:10.32381/JPM.2019.36.01.3

    Abstract Microwave (MV)-induced thermo-responsive shape memory thermoplastic polyurethane (SMTPU)/ MWCNT composites were prepared in micro-compounder. Composites containing different amount of multiwall Carbon nanotube (MWCNT) varying from 0 to 1.5 phr in SMTPU matrix were prepared. Maximum stretching strength, recovery force and tensile strength for 1.5 CNTPU (1.5 phr MWCNT in SMTPU matrix) was increased by 120%, 100% and 24% respectively as compared to SMTPU. MV-induced shape memory is a novel approach for fast, clean and remote heating during operation. MWCNT is strong absorber of microwave irradiation so that SMTPU/ MWCNTs nanocomposites successfully triggered by microwave. More >

  • Open Access

    ARTICLE

    Schiff’s base of Fe3O4 @chitosan with 4,4'- diselenobisbenzaldehyde: Preparation, characterization and its catalytic activity for oxidation of sulphides

    RAFAT SABA*, MOHD. KASHIF AZIZ, GHULAM MUSTAFA, ARPIT SRIVASTAVA, SHEKHAR SRIVASTAVA*

    Journal of Polymer Materials, Vol.38, No.1-2, pp. 153-166, 2021, DOI:10.32381/JPM.2021.38.1-2.12

    Abstract We have synthesized Schiff’s base of Fe3 O4 @chitosan with 4,4'-diselenobisbenzaldehyde (Fe3O4 @CSSe) composite and used it as acatalyst for the oxidation of sulfides, having some advantageous properties such as eco-friendly, cost-effective and highly efficient magnetic biocatalyst of selenium. The synthesized schiff’s base was characterized by different physical characterization techniques such as Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), Vibrating sample magnetometer (VSM)and Dynamic light scattering (DLS). Further, we used the resulting schiff’s base as a catalyst in the presence of a green oxidant (H2 O2 ) to oxidize sulfides to corresponding sulfoxides at room temperature. It has been… More >

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