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  • Open Access


    Enhancing Hygrothermal Performance in Multi-Zone Constructions through Phase Change Material Integration

    Abir Abboud1, Zakaria Triki1, Rachid Djeffal2, Sidi Mohammed El Amine Bekkouche2, Hichem Tahraoui1,3,4, Abdeltif Amrane4, Aymen Amin Assadi5, Lotfi Khozami5, Jie Zhang6,*

    Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 769-789, 2024, DOI:10.32604/fhmt.2024.050330

    Abstract As buildings evolve to meet the challenges of energy efficiency and indoor comfort, phase change materials (PCM) emerge as a promising solution due to their ability to store and release latent heat. This paper explores the transformative impact of incorporating PCM on the hygrothermal dynamics of multi-zone constructions. The study focuses on analyzing heat transfer, particularly through thermal conduction, in a wall containing PCM. A novel approach was proposed, wherein the studied system (sensitive balance) interacts directly with a latent balance to realistically define the behavior of specific humidity and mass flow rates. In addition, More >

  • Open Access


    Time Parameter Based Low-Energy Data Encryption Method for Mobile Applications

    Li-Woei Chen1, Kun-Lin Tsai2,*, Fang-Yie Leu3, Wen-Cheng Jiang2, Shih-Ting Tseng2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2779-2794, 2024, DOI:10.32604/cmes.2024.052124

    Abstract Various mobile devices and applications are now used in daily life. These devices require high-speed data processing, low energy consumption, low communication latency, and secure data transmission, especially in 5G and 6G mobile networks. High-security cryptography guarantees that essential data can be transmitted securely; however, it increases energy consumption and reduces data processing speed. Therefore, this study proposes a low-energy data encryption (LEDE) algorithm based on the Advanced Encryption Standard (AES) for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things (IoT) devices. In the proposed LEDE algorithm, the system time More >

  • Open Access


    A Data Intrusion Tolerance Model Based on an Improved Evolutionary Game Theory for the Energy Internet

    Song Deng1,*, Yiming Yuan2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3679-3697, 2024, DOI:10.32604/cmc.2024.052008

    Abstract Malicious attacks against data are unavoidable in the interconnected, open and shared Energy Internet (EI), Intrusion tolerant techniques are critical to the data security of EI. Existing intrusion tolerant techniques suffered from problems such as low adaptability, policy lag, and difficulty in determining the degree of tolerance. To address these issues, we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas: 1) it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights; and 2) it combines a tournament competition More >

  • Open Access


    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


    Exploring Multi-Task Learning for Forecasting Energy-Cost Resource Allocation in IoT-Cloud Systems

    Mohammad Aldossary1,*, Hatem A. Alharbi2, Nasir Ayub3

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4603-4620, 2024, DOI:10.32604/cmc.2024.050862

    Abstract Cloud computing has become increasingly popular due to its capacity to perform computations without relying on physical infrastructure, thereby revolutionizing computer processes. However, the rising energy consumption in cloud centers poses a significant challenge, especially with the escalating energy costs. This paper tackles this issue by introducing efficient solutions for data placement and node management, with a clear emphasis on the crucial role of the Internet of Things (IoT) throughout the research process. The IoT assumes a pivotal role in this study by actively collecting real-time data from various sensors strategically positioned in and around… More >

  • Open Access


    Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

    Imtiaz Ahmad1, Tariq Hussain2, Babar Shah3, Altaf Hussain4, Iqtidar Ali1, Farman Ali5,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3585-3629, 2024, DOI:10.32604/cmc.2024.050596

    Abstract Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost. One of them is a sensor network with embedded sensors working as the primary nodes, termed Wireless Sensor Networks (WSNs), in which numerous sensors are connected to at least one Base Station (BS). These sensors gather information from the environment and transmit it to a BS or gathering location. WSNs have several challenges, including throughput, energy usage, and network lifetime concerns. Different strategies have been applied to get over these… More >

  • Open Access


    Maximizing Resource Efficiency in Cloud Data Centers through Knowledge-Based Flower Pollination Algorithm (KB-FPA)

    Nidhika Chauhan1, Navneet Kaur2, Kamaljit Singh Saini3, Sahil Verma3, Kavita3, Ruba Abu Khurma4,5, Pedro A. Castillo6,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3757-3782, 2024, DOI:10.32604/cmc.2024.046516

    Abstract Cloud computing is a dynamic and rapidly evolving field, where the demand for resources fluctuates continuously. This paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing environments. The motivation stems from the pressing issue of accommodating fluctuating levels of user demand efficiently. By adhering to the proposed resource allocation method, we aim to achieve a substantial reduction in energy consumption. This reduction hinges on the precise and efficient allocation of resources to the tasks that require those most, aligning with the broader goal of… More >

  • Open Access


    Smart Micro Grid Energy System Management Based on Optimum Running Cost for Rural Communities in Rwanda

    Fabien Mukundufite1,*, Jean Marie Vianney Bikorimana1, Alexander Kyaruzi Lugatona2

    Energy Engineering, Vol.121, No.7, pp. 1805-1821, 2024, DOI:10.32604/ee.2024.051398

    Abstract The governmental electric utility and the private sector are joining hands to meet the target of electrifying all households by 2024. However, the aforementioned goal is challenged by households that are scattered in remote areas. So far, Solar Home Systems (SHS) have mostly been applied to increase electricity access in rural areas. SHSs have continuous constraints to meet electricity demands and cannot run income-generating activities. The current research presents the feasibility study of electrifying Remera village with the smart microgrid as a case study. The renewable energy resources available in Remera are the key sources… More >

  • Open Access


    Fault Diagnosis Method of Energy Storage Unit of Circuit Breakers Based on EWT-ISSA-BP

    Tengfei Li1, Wenhui Zhang1, Ke Mi1, Qingming Lin1, Shuangwei Zhao2,*, Jiayi Song2

    Energy Engineering, Vol.121, No.7, pp. 1991-2007, 2024, DOI:10.32604/ee.2024.049460

    Abstract Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers (LVCBs). A fault diagnosis algorithm based on an improved Sparrow Search Algorithm (ISSA) optimized Backpropagation Neural Network (BPNN) is proposed to improve the operational safety of LVCB. Taking the 1.5kV/4000A/75kA LVCB as an example. According to the current operating characteristics of the energy storage motor, fault characteristics are extracted based on Empirical Wavelet Transform (EWT). Traditional BPNN has problems such as difficulty adjusting network weights and thresholds, being sensitive to initial weights, and quickly falling into More >

  • Open Access


    Knowledge Mapping of Hybrid Solar PV and Wind Energy Standalone Systems: A Bibliometric Analysis

    Quan Zhou*, Haiyang Li

    Energy Engineering, Vol.121, No.7, pp. 1781-1803, 2024, DOI:10.32604/ee.2024.049387

    Abstract Renewable energy is becoming more attractive as traditional fossil fuels are rapidly depleted and expensive, and their use would release pollutants. Power systems that use both wind and solar energy are more reliable and efficient than those that utilize only one energy. Hybrid renewable energy systems (HRES) are viable for remote areas operating in standalone mode. This paper aims to present the state-of-the-art research on off-grid solar-wind hybrid energy systems over the last two decades. More than 1500 published articles extracted from the Web of Science are analyzed by bibliometric methods and processed by CiteSpace… More >

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