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  • Open Access

    ARTICLE

    Adaptive Predefined-Time Backstepping Control for Grid Connected Photovoltaic Inverter

    Jiarui Zhang1, Dan Liu2,*, Kan Cao2, Ping Xiong2, Xiaotong Ji3, Yanze Xu1, Yunfei Mu1

    Energy Engineering, Vol.121, No.8, pp. 2065-2083, 2024, DOI:10.32604/ee.2024.050342

    Abstract The system performance of grid-connected photovoltaic (PV) has a serious impact on the grid stability. To improve the control performance and shorten the convergence time, a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic. The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect. To address the “computational explosion problem” in the design process of backstepping control, dynamic surface control is adopted to avoid the analytical calculations of virtual control. The disturbances of the PV system are estimated and More >

  • Open Access

    ARTICLE

    FFRA: A Fine-Grained Function-Level Framework to Reduce the Attack Surface

    Xingxing Zhang1, Liang Liu1,*, Yu Fan1, Qian Zhou2

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 969-987, 2024, DOI:10.32604/csse.2024.046615

    Abstract System calls are essential interfaces that enable applications to access and utilize the operating system’s services and resources. Attackers frequently exploit application’s vulnerabilities and misuse system calls to execute malicious code, aiming to elevate privileges and so on. Consequently, restricting the misuse of system calls becomes a crucial measure in ensuring system security. It is an effective method known as reducing the attack surface. Existing attack surface reduction techniques construct a global whitelist of system calls for the entire lifetime of the application, which is coarse-grained. In this paper, we propose a Fine-grained Function-level framework… More >

  • Open Access

    ARTICLE

    Finite Element Analysis for Magneto-Convection Heat Transfer Performance in Vertical Wavy Surface Enclosure: Fin Size Impact

    Md. Fayz-Al-Asad1,4, F. Mebarek-Oudina2,*, H. Vaidya3, Md. Shamim Hasan4, Md. Manirul Alam Sarker4, A. I. Ismail5

    Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 817-837, 2024, DOI:10.32604/fhmt.2024.050814

    Abstract The goal of this paper is to represent a numerical study of magnetohydrodynamic mixed convection heat transfer in a lid-driven vertical wavy enclosure with a fin attached to the bottom wall. We use a finite element method based on Galerkin weighted residual (GWR) techniques to set up the appropriate governing equations for the present flow model. We have conducted a parametric investigation to examine the impact of Hartmann and Richardson numbers on the flow pattern and heat transmission features inside a wavy cavity. We graphically represent the numerical results, such as isotherms, streamlines, velocity profiles,… More >

  • Open Access

    ARTICLE

    Film Flow of Nano-Micropolar Fluid with Dissipation Effect

    Abuzar Abid Siddiqui1, Mustafa Turkyilmazoglu2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2487-2512, 2024, DOI:10.32604/cmes.2024.050525

    Abstract The physical problem of the thin film flow of a micropolar fluid over a dynamic and inclined substrate under the influence of gravitational and thermal forces in the presence of nanoparticles is formulated. Five different types of nanoparticle samples are accounted for in this current study, namely gold Au, silver Ag, molybdenum disulfide MoS2, aluminum oxide Al2O3, and silicon dioxide SiO2. Blood, a micropolar fluid, serves as the common base fluid. An exact closed-form solution for this problem is derived for the first time in the literature. The results are particularly validated against those for the Newtonian fluid… More >

  • Open Access

    ARTICLE

    Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

    Djeldjli Halima1,*, Benatiallah Djelloul1, Ghasri Mehdi2, Tanougast Camel3, Benatiallah Ali4, Benabdelkrim Bouchra1

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4725-4740, 2024, DOI:10.32604/cmc.2024.051002

    Abstract When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step. This study examined three approaches (ANN, GA-ANN, and ANFIS) for estimating daily global solar radiation (GSR) in the south of Algeria: Adrar, Ouargla, and Bechar. The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve the ANN model. The GA-ANN and ANFIS models performed better than the standalone ANN-based model, with GA-ANN being better suited for forecasting in all sites, and it performed the best with the best values in the… More > Graphic Abstract

    Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

  • Open Access

    ARTICLE

    Multiscale and Auto-Tuned Semi-Supervised Deep Subspace Clustering and Its Application in Brain Tumor Clustering

    Zhenyu Qian1, Yizhang Jiang1, Zhou Hong1, Lijun Huang2, Fengda Li3, KhinWee Lai6, Kaijian Xia4,5,6,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4741-4762, 2024, DOI:10.32604/cmc.2024.050920

    Abstract In this paper, we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering (MAS-DSC) algorithm, aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data, particularly in the field of medical imaging. Traditional deep subspace clustering algorithms, which are mostly unsupervised, are limited in their ability to effectively utilize the inherent prior knowledge in medical images. Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process, thereby enhancing the discriminative power of the feature representations. Additionally, the multi-scale feature extraction… More > Graphic Abstract

    Multiscale and Auto-Tuned Semi-Supervised Deep Subspace Clustering and Its Application in Brain Tumor Clustering

  • Open Access

    ARTICLE

    Fine-Grained Ship Recognition Based on Visible and Near-Infrared Multimodal Remote Sensing Images: Dataset, Methodology and Evaluation

    Shiwen Song, Rui Zhang, Min Hu*, Feiyao Huang

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5243-5271, 2024, DOI:10.32604/cmc.2024.050879

    Abstract Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security. Currently, with the emergence of massive high-resolution multi-modality images, the use of multi-modality images for fine-grained recognition has become a promising technology. Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples. The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features. The attention mechanism helps the model to pinpoint the key information in the image, resulting in a… More >

  • Open Access

    ARTICLE

    Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

    Widad Elbakri1, Maheyzah Md. Siraj1,*, Bander Ali Saleh Al-rimy1, Sultan Noman Qasem2, Tawfik Al-Hadhrami3

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3725-3756, 2024, DOI:10.32604/cmc.2024.048105

    Abstract Cloud computing environments, characterized by dynamic scaling, distributed architectures, and complex workloads, are increasingly targeted by malicious actors. These threats encompass unauthorized access, data breaches, denial-of-service attacks, and evolving malware variants. Traditional security solutions often struggle with the dynamic nature of cloud environments, highlighting the need for robust Adaptive Cloud Intrusion Detection Systems (CIDS). Existing adaptive CIDS solutions, while offering improved detection capabilities, often face limitations such as reliance on approximations for change point detection, hindering their precision in identifying anomalies. This can lead to missed attacks or an abundance of false alarms, impacting overall… More >

  • Open Access

    ARTICLE

    Optimization Study of Active-Passive Heating System Parameters in Village Houses in the Southern Xinjiang Province

    Xiaodan Wu1, Jie Li1,*, Yongbin Cai2, Sihui Huang1

    Energy Engineering, Vol.121, No.7, pp. 1963-1990, 2024, DOI:10.32604/ee.2024.048477

    Abstract Aiming at the problems of large energy consumption and serious pollution of winter heating existing in the rural buildings in Southern Xinjiang, a combined active-passive heating system was proposed, and the simulation software was used to optimize the parameters of the system, according to the parameters obtained from the optimization, a test platform was built and winter heating test was carried out. The simulation results showed that the thickness of the air layer of 75 mm, the total area of the vent holes of 0.24 m, and the thickness of the insulation layer of 120… More >

  • Open Access

    ARTICLE

    Analysis of Calcined Red Mud Properties and Related Mortar Performances

    Zhengfan Lyu1,3, Yulin Li2,3, Mengmeng Fan1,3,*, Yan Huang1, Chenguang Li2

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 901-913, 2024, DOI:10.32604/fdmp.2023.043512

    Abstract Red mud (RM) is a low-activity industrial solid waste, and its utilization as a resource is currently a hot topic. In this study, the micro characteristics of red mud at different calcination temperatures were analyzed using X-ray diffraction and scanning electron microscopy. The performance of calcined red mud was determined through mortar strength tests. Results indicate that high-temperature calcination can change the mineral composition and microstructure of red mud, and increase the surface roughness and specific surface area. At the optimal temperature of 700°C, the addition of calcined red mud still leads to a decrease More > Graphic Abstract

    Analysis of Calcined Red Mud Properties and Related Mortar Performances

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