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  • Open Access

    ARTICLE

    A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions

    Qixin Lan, Binqiang Chen*, Bin Yao

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 2017-2037, 2023, DOI:10.32604/cmes.2023.025307 - 06 February 2023

    Abstract Many kinds of electrical equipment are used in civil and building engineering. The motor is one of the main power components of this electrical equipment, which can provide stable power output. During the long-term use of motors, various motor faults may occur, which affects the normal use of electrical equipment and even causes accidents. It is significant to apply fault diagnosis for the motors at the construction site. Aiming at the problem that signal data of faulty motor lack diversity, this research designs a multi-layer perceptron Wasserstein generative adversarial network, which is used to enhance… More >

  • Open Access

    ARTICLE

    Robust Image Watermarking Using LWT and Stochastic Gradient Firefly Algorithm

    Sachin Sharma1,*, Meena Malik2, Chander Prabha3, Amal Al-Rasheed4, Mona Alduailij4, Sultan Almakdi5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 393-407, 2023, DOI:10.32604/cmc.2023.033536 - 06 February 2023

    Abstract Watermarking of digital images is required in diversified applications ranging from medical imaging to commercial images used over the web. Usually, the copyright information is embossed over the image in the form of a logo at the corner or diagonal text in the background. However, this form of visible watermarking is not suitable for a large class of applications. In all such cases, a hidden watermark is embedded inside the original image as proof of ownership. A large number of techniques and algorithms are proposed by researchers for invisible watermarking. In this paper, we focus… More >

  • Open Access

    ARTICLE

    Hybrid Watermarking and Encryption Techniques for Securing Medical Images

    Amel Ali Alhussan1,*, Hanaa A. Abdallah2, Sara Alsodairi2, Abdelhamied A. Ateya3

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 403-416, 2023, DOI:10.32604/csse.2023.035048 - 20 January 2023

    Abstract Securing medical data while transmission on the network is required because it is sensitive and life-dependent data. Many methods are used for protection, such as Steganography, Digital Signature, Cryptography, and Watermarking. This paper introduces a novel robust algorithm that combines discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD) digital image-watermarking algorithms. The host image is decomposed using a two-dimensional DWT (2D-DWT) to approximate low-frequency sub-bands in the embedding process. Then the sub-band low-high (LH) is decomposed using 2D-DWT to four new sub-bands. The resulting sub-band low-high (LH1) is decomposed using 2D-DWT… More >

  • Open Access

    ARTICLE

    Anomaly Detection Based on Discrete Wavelet Transformation for Insider Threat Classification

    Dong-Wook Kim1, Gun-Yoon Shin1, Myung-Mook Han2,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 153-164, 2023, DOI:10.32604/csse.2023.034589 - 20 January 2023

    Abstract Unlike external attacks, insider threats arise from legitimate users who belong to the organization. These individuals may be a potential threat for hostile behavior depending on their motives. For insider detection, many intrusion detection systems learn and prevent known scenarios, but because malicious behavior has similar patterns to normal behavior, in reality, these systems can be evaded. Furthermore, because insider threats share a feature space similar to normal behavior, identifying them by detecting anomalies has limitations. This study proposes an improved anomaly detection methodology for insider threats that occur in cybersecurity in which a discrete… More >

  • Open Access

    ARTICLE

    The Effects of the Particle Size Ratio on the Behaviors of Binary Granular Materials

    Deze Yang, Xihua Chu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 63-85, 2023, DOI:10.32604/cmes.2023.025062 - 05 January 2023

    Abstract The particle size ratio (PSR) is an important parameter for binary granular materials, which may affect the microstructure and macro behaviors of granular materials. However, the effect of particle ratio on granular assemblies with different arrangements is still unclear. To explore and further clarify the effect of PSR in different packing structures, three types of numerical samples with regular, layered, and random packing are designed. Numerical results show that PSR has significant effects on binary granular samples with regular packing. The larger the PSR, the stronger the strength, the larger the modulus, and the smaller… More >

  • Open Access

    ARTICLE

    Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

    Mohanapriya Marimuthu1, Santhosh Rajendran2, Reshma Radhakrishnan2, Kalpana Rengarajan3, Shahzada Khurram4, Shafiq Ahmad5, Abdelaty Edrees Sayed5, Muhammad Shafiq6,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4729-4745, 2023, DOI:10.32604/cmc.2023.033020 - 28 December 2022

    Abstract Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved… More >

  • Open Access

    ARTICLE

    A Study on the Physical Properties of Banana Straw Based on the Discrete Element Method

    Sen Zhang1, Jie Jiang2,3,*, Yuedong Wang4

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1159-1172, 2023, DOI:10.32604/fdmp.2022.024070 - 30 November 2022

    Abstract To improve the application of discrete element models (DEM) to the design of agricultural crushers, in this study a new highly accurate model is elaborated. The model takes into account the fiber structure, porous nature of the material and the leaf sheath coating structure. Dedicated experimental tests are conducted to determine the required “intrinsic” and basic contact parameters of the considered banana straw materials. A large number of bonding parameters are examined in relation to the particle aggregation model in order to characterize different actual banana straws. Using the particle surface energy contact model, the More > Graphic Abstract

    A Study on the Physical Properties of Banana Straw Based on the Discrete Element Method

  • Open Access

    ARTICLE

    Numerical Simulation of Dust Removal in the Cyclone Collector of a Straw Crusher Based on a Discrete Phase Model

    Zhuang Wu1,2, Chang Su1,2,*, Hua Xu1,2, Liu Wang1,2

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1143-1157, 2023, DOI:10.32604/fdmp.2022.022496 - 30 November 2022

    Abstract The cyclone dust collector is an important subsystem of straw crushers used in agriculture. In the present study, a new type of dust collector with involute morphology is proposed to obtain better dust removal efficiency with respect to that of classical tangential and spiral dust collectors. A discrete phase model (DPM) method is used in synergy with a turbulence model, and the SIMPLE algorithm to simulate the flow field inside the dust collector and the related particle dynamics. It is shown that the internal flow field features a primary swirl, a secondary swirl and blockage More > Graphic Abstract

    Numerical Simulation of Dust Removal in the Cyclone Collector of a Straw Crusher Based on a Discrete Phase Model

  • Open Access

    ARTICLE

    Topology Optimization for Harmonic Excitation Structures with Minimum Length Scale Control Using the Discrete Variable Method

    Hongliang Liu1, Peijin Wang1, Yuan Liang2,*, Kai Long3, Dixiong Yang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1941-1964, 2023, DOI:10.32604/cmes.2023.024921 - 23 November 2022

    Abstract Continuum topology optimization considering the vibration response is of great value in the engineering structure design. The aim of this study is to address the topological design optimization of harmonic excitation structures with minimum length scale control to facilitate structural manufacturing. A structural topology design based on discrete variables is proposed to avoid localized vibration modes, gray regions and fuzzy boundaries in harmonic excitation topology optimization. The topological design model and sensitivity formulation are derived. The requirement of minimum size control is transformed into a geometric constraint using the discrete variables. Consequently, thin bars, small… More >

  • Open Access

    ARTICLE

    ELM-Based Shape Adaptive DCT Compression Technique for Underwater Image Compression

    M. Jamuna Rani1,*, C. Vasanthanayaki2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1953-1970, 2023, DOI:10.32604/csse.2023.028713 - 03 November 2022

    Abstract Underwater imagery and transmission possess numerous challenges like lower signal bandwidth, slower data transmission bit rates, Noise, underwater blue/green light haze etc. These factors distort the estimation of Region of Interest and are prime hurdles in deploying efficient compression techniques. Due to the presence of blue/green light in underwater imagery, shape adaptive or block-wise compression techniques faces failures as it becomes very difficult to estimate the compression levels/coefficients for a particular region. This method is proposed to efficiently deploy an Extreme Learning Machine (ELM) model-based shape adaptive Discrete Cosine Transformation (DCT) for underwater images. Underwater More >

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