Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (216)
  • Open Access

    ARTICLE

    Data Aggregation Point Placement and Subnetwork Optimization for Smart Grids

    Tien-Wen Sung1, Wei Li1, Chao-Yang Lee2,*, Yuzhen Chen1, Qingjun Fang1

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 407-434, 2025, DOI:10.32604/cmc.2025.061694 - 26 March 2025

    Abstract To transmit customer power data collected by smart meters (SMs) to utility companies, data must first be transmitted to the corresponding data aggregation point (DAP) of the SM. The number of DAPs installed and the installation location greatly impact the whole network. For the traditional DAP placement algorithm, the number of DAPs must be set in advance, but determining the best number of DAPs is difficult, which undoubtedly reduces the overall performance of the network. Moreover, the excessive gap between the loads of different DAPs is also an important factor affecting the quality of the… More >

  • Open Access

    ARTICLE

    Smart Grid Security Framework for Data Transmissions with Adaptive Practices Using Machine Learning Algorithm

    Shitharth Selvarajan1,2,3,*, Hariprasath Manoharan4, Taher Al-Shehari5, Hussain Alsalman6, Taha Alfakih7

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4339-4369, 2025, DOI:10.32604/cmc.2025.056100 - 06 March 2025

    Abstract This research presents an analysis of smart grid units to enhance connected units’ security during data transmissions. The major advantage of the proposed method is that the system model encompasses multiple aspects such as network flow monitoring, data expansion, control association, throughput, and losses. In addition, all the above-mentioned aspects are carried out with neural networks and adaptive optimizations to enhance the operation of smart grid networks. Moreover, the quantitative analysis of the optimization algorithm is discussed concerning two case studies, thereby achieving early convergence at reduced complexities. The suggested method ensures that each communication More >

  • Open Access

    REVIEW

    Optimal Location of Renewable Energy Generators in Transmission and Distribution System of Deregulated Power Sector: A Review

    Digambar Singh1, Najat Elgeberi2, Mohammad Aljaidi3,*, Ramesh Kumar4,5, Rabia Emhamed Al Mamlook6, Manish Kumar Singla4,7,8,*

    Energy Engineering, Vol.122, No.3, pp. 823-859, 2025, DOI:10.32604/ee.2025.059309 - 07 March 2025

    Abstract The literature on multi-attribute optimization for renewable energy source (RES) placement in deregulated power markets is extensive and diverse in methodology. This study focuses on the most relevant publications directly addressing the research problem at hand. Similarly, while the body of work on optimal location and sizing of renewable energy generators (REGs) in balanced distribution systems is substantial, only the most pertinent sources are cited, aligning closely with the study’s objective function. A comprehensive literature review reveals several key research areas: RES integration, RES-related optimization techniques, strategic placement of wind and solar generation, and RES… More >

  • Open Access

    ARTICLE

    Bayesian Stochastic INLA Application to the SIR-SI Model for Investigating Dengue Transmission Dynamics

    Mukhsar1,*, Andi Tenriawaru2, Gusti Ngurah Adhi Wibawa1, Bahriddin Abapihi1, Sitti Wirdhana Ahmad3, I Putu Sudayasa4

    Intelligent Automation & Soft Computing, Vol.40, pp. 177-193, 2025, DOI:10.32604/iasc.2025.058884 - 24 February 2025

    Abstract Despite extensive prevention efforts and research, dengue hemorrhagic fever (DHF) remains a major public health challenge, particularly in tropical regions, with significant social, economic, and health consequences. Statistical models are crucial in studying infectious DHF by providing a structured framework to analyze transmission dynamics between humans (hosts) and mosquitoes (vectors). Depending on the disease characteristics, different stochastic compartmental models can be employed. This research applies Bayesian Integrated Nested Laplace Approximation (INLA) to the SIR-SI model for DHF data. The method delivers accurate parameter estimates, improved computational efficiency, and effective integration with early warning systems. The… More >

  • Open Access

    ARTICLE

    Vector Extraction from Design Drawings for Intelligent 3D Modeling of Transmission Towers

    Ziqiang Tang1, Chao Han1, Hongwu Li1, Zhou Fan1, Ke Sun1, Yuntian Huang1, Yuhang Chen2, Chenxing Wang2,*

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2813-2829, 2025, DOI:10.32604/cmc.2024.059094 - 17 February 2025

    Abstract Accurate vector extraction from design drawings is required first to automatically create 3D models from pixel-level engineering design drawings. However, this task faces the challenges of complicated design shapes as well as cumbersome and cluttered annotations on drawings, which interfere with the vector extraction heavily. In this article, the transmission tower containing the most complex structure is taken as the research object, and a semantic segmentation network is constructed to first segment the shape masks from the pixel-level drawings. Preprocessing and postprocessing are also proposed to ensure the stability and accuracy of the shape mask… More >

  • Open Access

    ARTICLE

    Efficient Data Aggregation and Message Transmission for Information Processing Model in the CPS-WSN

    Chao-Hsien Hsieh1, Qingqing Yang2,*, Dehong Kong2, Fengya Xu2, Hongmei Wang2

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2869-2891, 2025, DOI:10.32604/cmc.2024.058122 - 17 February 2025

    Abstract The Cyber-Physical Systems (CPS) supported by Wireless Sensor Networks (WSN) helps factories collect data and achieve seamless communication between physical and virtual components. Sensor nodes are energy-constrained devices. Their energy consumption is typically correlated with the amount of data collection. The purpose of data aggregation is to reduce data transmission, lower energy consumption, and reduce network congestion. For large-scale WSN, data aggregation can greatly improve network efficiency. However, as many heterogeneous data is poured into a specific area at the same time, it sometimes causes data loss and then results in incompleteness and irregularity of… More >

  • Open Access

    ARTICLE

    A Dynamic Prediction Approach for Wire Icing Thickness under Extreme Weather Conditions Based on WGAN-GP-RTabNet

    Mingguan Zhao1,2,*, Xinsheng Dong1,2, Yang Yang1,2, Meng Li1,2, Hongxia Wang1,2, Shuyang Ma1,2, Rui Zhu3, Xiaojing Zhu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2091-2109, 2025, DOI:10.32604/cmes.2025.059169 - 27 January 2025

    Abstract Ice cover on transmission lines is a significant issue that affects the safe operation of the power system. Accurate calculation of the thickness of wire icing can effectively prevent economic losses caused by ice disasters and reduce the impact of power outages on residents. However, under extreme weather conditions, strong instantaneous wind can cause tension sensors to fail, resulting in significant errors in the calculation of icing thickness in traditional mechanics-based models. In this paper, we propose a dynamic prediction model of wire icing thickness that can adapt to extreme weather environments. The model expands… More >

  • Open Access

    COMMENTARY

    Biological processes involved in mechanical force transmission in connective tissue: Linking bridges for new therapeutic applications in the rehabilitative field

    AUGUSTO FUSCO1, STEFANO BONOMI2,*, LUCA PADUA1,2

    BIOCELL, Vol.49, No.1, pp. 1-5, 2025, DOI:10.32604/biocell.2024.058418 - 24 January 2025

    Abstract Connective tissue is a dynamic structure that reacts to environmental cues to maintain homeostasis, including mechanical properties. Mechanical load influences extracellular matrix (ECM)—cell interactions and modulates cellular behavior. Mechano-regulation processes involve matrix modification and cell activation to preserve tissue function. The ECM remodeling is crucial for force transmission. Cytoskeleton components are involved in force sensing and transmission, affecting cellular adhesion, motility, and gene expression. Proper mechanical loading helps to maintain tissue health, while imbalances may lead to pathological processes. Active and passive movement, including manual mobilization, improves connective tissue elasticity, promotes ECM-cell homeostasis, and More > Graphic Abstract

    Biological processes involved in mechanical force transmission in connective tissue: Linking bridges for new therapeutic applications in the rehabilitative field

  • Open Access

    ARTICLE

    Innovative Lightweight Encryption Schemes Leveraging Chaotic Systems for Secure Data Transmission

    Haider H. Al-Mahmood1,*, Saad N. Alsaad2

    Intelligent Automation & Soft Computing, Vol.40, pp. 53-74, 2025, DOI:10.32604/iasc.2024.059691 - 10 January 2025

    Abstract In secure communications, lightweight encryption has become crucial, particularly for resource-constrained applications such as embedded devices, wireless sensor networks, and the Internet of Things (IoT). As these systems proliferate, cryptographic approaches that provide robust security while minimizing computing overhead, energy consumption, and memory usage are becoming increasingly essential. This study examines lightweight encryption techniques utilizing chaotic maps to ensure secure data transmission. Two algorithms are proposed, both employing the Logistic map; the first approach utilizes two logistic chaotic maps, while the second algorithm employs a single logistic chaotic map. Algorithm 1, including a two-stage mechanism… More >

  • Open Access

    ARTICLE

    GFRF R-CNN: Object Detection Algorithm for Transmission Lines

    Xunguang Yan1,2, Wenrui Wang1, Fanglin Lu1, Hongyong Fan3, Bo Wu1, Jianfeng Yu1,*

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1439-1458, 2025, DOI:10.32604/cmc.2024.057797 - 03 January 2025

    Abstract To maintain the reliability of power systems, routine inspections using drones equipped with advanced object detection algorithms are essential for preempting power-related issues. The increasing resolution of drone-captured images has posed a challenge for traditional target detection methods, especially in identifying small objects in high-resolution images. This study presents an enhanced object detection algorithm based on the Faster Region-based Convolutional Neural Network (Faster R-CNN) framework, specifically tailored for detecting small-scale electrical components like insulators, shock hammers, and screws in transmission line. The algorithm features an improved backbone network for Faster R-CNN, which significantly boosts the More >

Displaying 1-10 on page 1 of 216. Per Page