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  • Open Access

    ARTICLE

    Optimizing AES S-Box Implementation: A SAT-Based Approach with Tower Field Representations

    Jingya Feng1, Ying Zhao2,*, Tao Ye1, Wei Feng3,*

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1491-1507, 2025, DOI:10.32604/cmc.2025.059882 - 26 March 2025

    Abstract The efficient implementation of the Advanced Encryption Standard (AES) is crucial for network data security. This paper presents novel hardware implementations of the AES S-box, a core component, using tower field representations and Boolean Satisfiability (SAT) solvers. Our research makes several significant contributions to the field. Firstly, we have optimized the GF() inversion, achieving a remarkable 31.35% area reduction (15.33 GE) compared to the best known implementations. Secondly, we have enhanced multiplication implementations for transformation matrices using a SAT-method based on local solutions. This approach has yielded notable improvements, such as a 22.22% reduction in More >

  • Open Access

    ARTICLE

    MACLSTM: A Weather Attributes Enabled Recurrent Approach to Appliance-Level Energy Consumption Forecasting

    Ruoxin Li1,*, Shaoxiong Wu1, Fengping Deng1, Zhongli Tian1, Hua Cai1, Xiang Li1, Xu Xu1, Qi Liu2,3

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2969-2984, 2025, DOI:10.32604/cmc.2025.060230 - 17 February 2025

    Abstract Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and… More >

  • Open Access

    ARTICLE

    Analysis of Renewable Energy Absorption and Economic Feasibility in Multi-Energy Complementary Systems under Spot Market Conditions

    Xiuyun Wang, Zipeng Zhang, Chuang Liu*, Guoliang Bian

    Energy Engineering, Vol.122, No.2, pp. 577-619, 2025, DOI:10.32604/ee.2024.056748 - 31 January 2025

    Abstract As the power system transitions to a new green and low-carbon paradigm, the penetration of renewable energy in China’s power system is gradually increasing. However, the variability and uncertainty of renewable energy output limit its profitability in the electricity market and hinder its market-based integration. This paper first constructs a wind-solar-thermal multi-energy complementary system, analyzes its external game relationships, and develops a bi-level market optimization model. Then, it considers the contribution levels of internal participants to establish a comprehensive internal distribution evaluation index system. Finally, simulation studies using the IEEE 30-bus system demonstrate that the More >

  • Open Access

    ARTICLE

    Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

    Altaf Hussain1, Shuaiyong Li2, Tariq Hussain3, Razaz Waheeb Attar4, Farman Ali5,*, Ahmed Alhomoud6, Babar Shah7

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2357-2394, 2024, DOI:10.32604/cmc.2024.056694 - 18 November 2024

    Abstract Ad hoc networks offer promising applications due to their ease of use, installation, and deployment, as they do not require a centralized control entity. In these networks, nodes function as senders, receivers, and routers. One such network is the Flying Ad hoc Network (FANET), where nodes operate in three dimensions (3D) using Unmanned Aerial Vehicles (UAVs) that are remotely controlled. With the integration of the Internet of Things (IoT), these nodes form an IoT-enabled network called the Internet of UAVs (IoU). However, the airborne nodes in FANET consume high energy due to their payloads and… More >

  • Open Access

    ARTICLE

    Numerical Simulation of Heat Transfer Process and Heat Loss Analysis in Siemens CVD Reduction Furnaces

    Kunrong Shen*, Wanchun Jin, Jin Wang

    Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1361-1379, 2024, DOI:10.32604/fhmt.2024.057372 - 30 October 2024

    Abstract The modified Siemens method is the dominant process for the production of polysilicon, yet it is characterised by high energy consumption. Two models of laboratory-grade Siemens reduction furnace and 12 pairs of rods industrial-grade Siemens chemical vapor deposition (CVD) reduction furnace were established, and the effects of factors such as the diameter of silicon rods, the surface temperature of silicon rods, the air inlet velocity and temperature on the heat transfer process inside the reduction furnace were investigated by numerical simulation. The results show that the convective and radiant heat losses in the furnace increased… More >

  • Open Access

    ARTICLE

    A Novel Bi-Level VSC-DC Transmission Expansion Planning Method of VSC-DC for Power System Flexibility and Stability Enhancement

    Weigang Jin1, Lei Chen2,*, Shencong Zheng2, Yuqi Jiang2, Yifei Li2, Hongkun Chen2

    Energy Engineering, Vol.121, No.11, pp. 3161-3179, 2024, DOI:10.32604/ee.2024.054068 - 21 October 2024

    Abstract Investigating flexibility and stability boosting transmission expansion planning (TEP) methods can increase the renewable energy (RE) consumption of the power systems. In this study, we propose a bi-level TEP method for voltage-source-converter-based direct current (VSC-DC), focusing on flexibility and stability enhancement. First, we established the TEP framework of VSC-DC, by introducing the evaluation indices to quantify the power system flexibility and stability. Subsequently, we propose a bi-level VSC-DC TEP model: the upper-level model acquires the optimal VSC-DC planning scheme by using the improved moth flame optimization (IMFO) algorithm, and the lower-level model evaluates the flexibility More >

  • Open Access

    ARTICLE

    A Two-Layer Optimal Scheduling Strategy for Rural Microgrids Accounting for Flexible Loads

    Guo Zhao1,2, Chi Zhang1,2,*, Qiyuan Ren1,2

    Energy Engineering, Vol.121, No.11, pp. 3355-3379, 2024, DOI:10.32604/ee.2024.053130 - 21 October 2024

    Abstract In the context of China’s “double carbon” goals and rural revitalization strategy, the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids. Considering the operational characteristics of rural microgrids and their impact on users, this paper establishes a two-layer scheduling model incorporating flexible loads. The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid, while the lower-layer aims to minimize the total electricity cost for rural users. An Improved Adaptive Genetic Algorithm (IAGA) is proposed to solve the model. Results show that the two-layer scheduling model with More >

  • Open Access

    ARTICLE

    A Lightweight Intrusion Detection System Using Convolutional Neural Network and Long Short-Term Memory in Fog Computing

    Hawazen Alzahrani1, Tarek Sheltami1, Abdulaziz Barnawi2, Muhammad Imam2,*, Ansar Yaser3

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4703-4728, 2024, DOI:10.32604/cmc.2024.054203 - 12 September 2024

    Abstract The Internet of Things (IoT) links various devices to digital services and significantly improves the quality of our lives. However, as IoT connectivity is growing rapidly, so do the risks of network vulnerabilities and threats. Many interesting Intrusion Detection Systems (IDSs) are presented based on machine learning (ML) techniques to overcome this problem. Given the resource limitations of fog computing environments, a lightweight IDS is essential. This paper introduces a hybrid deep learning (DL) method that combines convolutional neural networks (CNN) and long short-term memory (LSTM) to build an energy-aware, anomaly-based IDS. We test this… More >

  • Open Access

    ARTICLE

    Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

    Juan Li1, Tingting Xu1,*, Yi Gu2, Chuang Liu1, Guiping Zhou2, Guoliang Bian1

    Energy Engineering, Vol.121, No.10, pp. 2777-2795, 2024, DOI:10.32604/ee.2024.052331 - 11 September 2024

    Abstract In fossil energy pollution is serious and the “double carbon” goal is being promoted, as a symbol of fresh energy in the electrical system, solar and wind power have an increasing installed capacity, only conventional units obviously can not solve the new energy as the main body of the scheduling problem. To enhance the system scheduling ability, based on the participation of thermal power units, incorporate the high energy-carrying load of electro-melting magnesium into the regulation object, and consider the effects on the wind unpredictability of the power. Firstly, the operating characteristics of high energy… More >

  • Open Access

    ARTICLE

    eQUEST Based Building Energy Modeling Analysis for Energy Efficiency of Buildings

    Saroj Lamichhane1, Roseline Mostafa2, Bhaskaran Gopalakrishnan2,*, Dayakar G. Devaru3

    Energy Engineering, Vol.121, No.10, pp. 2743-2767, 2024, DOI:10.32604/ee.2024.051035 - 11 September 2024

    Abstract Building energy performance is a function of numerous building parameters. In this study, sensitivity analysis on twenty parameters is performed to determine the top three parameters that have the most significant impact on the energy performance of buildings. Actual data from two fully operational commercial buildings were collected and used to develop a building energy model in the Quick Energy Simulation Tool (eQUEST). The model is calibrated using the Normalized Mean Bias Error (NMBE) and Coefficient of Variation of Root Mean Square Error (CV(RMSE)) method. The model satisfies the NMBE and CV(RMSE) criteria set by… More > Graphic Abstract

    eQUEST Based Building Energy Modeling Analysis for Energy Efficiency of Buildings

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