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  • Open Access

    ARTICLE

    Enhancing the Efficiency of Multi-Electrolyzer Clusters with Lye Mixer: Topology Design and Control Strategy

    Mingxuan Chen1, Jun Jia2, Baoping Zhang1, Leiyan Han3, Mengbo Ji3,4, Zhangtao Yu1, Dongfang Li1, Wenyong Wang1, Hongjing Jia1, Huachi Xu2,*

    Energy Engineering, Vol.121, No.10, pp. 3055-3074, 2024, DOI:10.32604/ee.2024.051524 - 11 September 2024

    Abstract The rise in hydrogen production powered by renewable energy is driving the field toward the adoption of systems comprising multiple alkaline water electrolyzers. These setups present various operational modes: independent operation and multi-electrolyzer parallelization, each with distinct advantages and challenges. This study introduces an innovative configuration that incorporates a mutual lye mixer among electrolyzers, establishing a weakly coupled system that combines the advantages of two modes. This approach enables efficient heat utilization for faster hot-startup and maintains heat conservation post-lye interconnection, while preserving the option for independent operation after decoupling. A specialized thermal exchange model… More >

  • Open Access

    ARTICLE

    Bio-Inspired Intelligent Routing in WSN: Integrating Mayfly Optimization and Enhanced Ant Colony Optimization for Energy-Efficient Cluster Formation and Maintenance

    V. G. Saranya*, S. Karthik

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 127-150, 2024, DOI:10.32604/cmes.2024.053825 - 20 August 2024

    Abstract Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to… More >

  • Open Access

    ARTICLE

    Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

    Jiaxin Qiao1, Yuchen Hao2, Yingqi Liao3, Fang Liang3, Jing Bian1,*

    Energy Engineering, Vol.121, No.9, pp. 2655-2680, 2024, DOI:10.32604/ee.2024.049509 - 19 August 2024

    Abstract The massive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations. To accurately assess the flexible regulation capabilities of distribution stations, a multi-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics, considering different geographical locations, coverage areas, and response capabilities. Firstly, the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed, and a resource regulation capability model is established to quantify the adjustable range of different regulation resources. On… More >

  • Open Access

    ARTICLE

    Analysis of Electricity Consumption Pattern Clustering and Electricity Consumption Behavior

    Liang Zhu1, Junyang Liu1, Chen Hu1, Yanli Zhi2, Yupeng Liu3,*

    Energy Engineering, Vol.121, No.9, pp. 2639-2653, 2024, DOI:10.32604/ee.2024.041441 - 19 August 2024

    Abstract Studying user electricity consumption behavior is crucial for understanding their power usage patterns. However, the traditional clustering methods fail to identify emerging types of electricity consumption behavior. To address this issue, this paper introduces a statistical analysis of clusters and evaluates the set of indicators for power usage patterns. The fuzzy C-means clustering algorithm is then used to analyze 6 months of electricity consumption data in 2017 from energy storage equipment, agricultural drainage irrigation, port shore power, and electric vehicles. Finally, the proposed method is validated through experiments, where the Davies-Bouldin index and profile coefficient More >

  • Open Access

    ARTICLE

    A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

    Hina Gul1, Sana Ullah1, Ki-Il Kim2,*, Farman Ali3

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1831-1850, 2024, DOI:10.32604/cmc.2024.052841 - 15 August 2024

    Abstract The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications, such as remote health monitoring, industrial monitoring, transportation, and smart agriculture. Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes. This paper presents a traffic-aware, cluster-based, and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks. The proposed protocol divides the network into clusters where optimal cluster heads are selected among super… More >

  • Open Access

    ARTICLE

    A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters

    Zhongshang Chen, Ji Feng*, Fapeng Cai, Degang Yang

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2031-2048, 2024, DOI:10.32604/cmc.2024.052114 - 15 August 2024

    Abstract In clustering algorithms, the selection of neighbors significantly affects the quality of the final clustering results. While various neighbor relationships exist, such as K-nearest neighbors, natural neighbors, and shared neighbors, most neighbor relationships can only handle single structural relationships, and the identification accuracy is low for datasets with multiple structures. In life, people’s first instinct for complex things is to divide them into multiple parts to complete. Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures. Taking inspiration from this, we propose a novel neighbor method: Shared Natural Neighbors (SNaN). More >

  • Open Access

    ARTICLE

    Research on Site Planning of Mobile Communication Network

    Jiahan He1, Guangjun Liang1,2,3,*, Meng Li4, Kefan Yao1, Bixia Wang1, Lu Li5

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3243-3261, 2024, DOI:10.32604/cmc.2024.051710 - 15 August 2024

    Abstract In this paper, considering the cost of base station, coverage, call quality, and other practical factors, a multi-objective optimal site planning scheme is proposed. Firstly, based on practical needs, mathematical modeling methods were used to establish mathematical expressions for the three sub-objectives of cost objectives, coverage objectives, and quality objectives. Then, a multi-objective optimization model was established by combining threshold and traffic volume constraints. In order to reduce the time complexity of optimization, a non-dominated sorting genetic algorithm (NSGA) is used to solve the multi-objective optimization problem of site planning. Finally, a strategy for clustering… More >

  • Open Access

    ARTICLE

    Genetic Variability and Phenotypic Correlations Study among Grain Quality Traits and Mineral Elements Concentrations in Colored and Non-Colored Rice (Oryza sativa L.)

    Adel A. Rezk1,2,*, Mohamed M. El-Malky3, Heba I. Mohamed4,*, Hossam S. El-Beltagi1,5

    Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1733-1748, 2024, DOI:10.32604/phyton.2024.052739 - 30 July 2024

    Abstract Twenty-four rice genotypes were examined to assess genetic variability, heritability, and correlations for seven-grain quality traits, eight nutritional elements, and protein. ANOVA revealed significant differences for the quality traits studied. For every trait under study, the phenotypic coefficient of variation was higher than the correspondence genotypic coefficient of variation. Heritability in a broad sense varied from 29.75% for grain length to 98.31% for the elongation trait. Hulling percentage recovery had a highly significant positive correlation with milling and head rice percentage. Consequently, milling percentage had a highly positive correlation with head rice percentage. In amylose… More >

  • Open Access

    ARTICLE

    Efficient Clustering Network Based on Matrix Factorization

    Jieren Cheng1,3, Jimei Li1,3,*, Faqiang Zeng1,3, Zhicong Tao1,3, Yue Yang2,3

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 281-298, 2024, DOI:10.32604/cmc.2024.051816 - 18 July 2024

    Abstract Contrastive learning is a significant research direction in the field of deep learning. However, existing data augmentation methods often lead to issues such as semantic drift in generated views while the complexity of model pre-training limits further improvement in the performance of existing methods. To address these challenges, we propose the Efficient Clustering Network based on Matrix Factorization (ECN-MF). Specifically, we design a batched low-rank Singular Value Decomposition (SVD) algorithm for data augmentation to eliminate redundant information and uncover major patterns of variation and key information in the data. Additionally, we design a Mutual Information-Enhanced More >

  • Open Access

    ARTICLE

    Advancements in Remote Sensing Image Dehazing: Introducing URA-Net with Multi-Scale Dense Feature Fusion Clusters and Gated Jump Connection

    Hongchi Liu1, Xing Deng1,*, Haijian Shao1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2397-2424, 2024, DOI:10.32604/cmes.2024.049737 - 08 July 2024

    Abstract The degradation of optical remote sensing images due to atmospheric haze poses a significant obstacle, profoundly impeding their effective utilization across various domains. Dehazing methodologies have emerged as pivotal components of image preprocessing, fostering an improvement in the quality of remote sensing imagery. This enhancement renders remote sensing data more indispensable, thereby enhancing the accuracy of target identification. Conventional defogging techniques based on simplistic atmospheric degradation models have proven inadequate for mitigating non-uniform haze within remotely sensed images. In response to this challenge, a novel UNet Residual Attention Network (URA-Net) is proposed. This paradigmatic approach… More > Graphic Abstract

    Advancements in Remote Sensing Image Dehazing: Introducing URA-Net with Multi-Scale Dense Feature Fusion Clusters and Gated Jump Connection

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