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  • Open Access

    ARTICLE

    An Open and Adaptable Approach to Vulnerability Risk Scoring

    Harri Renney1,*, Isaac V Chenchiah2, Maxim Nethercott1, Rohini Paligadu1, James Lang1

    Journal of Cyber Security, Vol.7, pp. 221-238, 2025, DOI:10.32604/jcs.2025.064958 - 14 July 2025

    Abstract In recent years, the field of cybersecurity has expanded to encompass a deeper understanding of best practices, user behaviour, and the tactics, motivations, and targets of threat actors. At the same time, there is growing interest in how cyber data analytics can support informed decision-making at senior levels. Despite the broader advancements, the field still lacks a robust scientific foundation for accurately calculating cyber vulnerability risk. Consequently, vulnerabilities in hardware and software systems often remain unaddressed for extended periods, undermining the effectiveness of risk mitigation efforts. This paper seeks to address the gap in vulnerability… More >

  • Open Access

    REVIEW

    Contemporary Management of Failing Modified Fontan after the Total Cavopulmonary Connection

    Honghao Fu#, Zhangwei Wang#, Shoujun Li*

    Congenital Heart Disease, Vol.20, No.3, pp. 287-303, 2025, DOI:10.32604/chd.2025.067619 - 11 July 2025

    Abstract Congenital heart disease (CHD) stands as the most common cardiovascular disorder among children, exerting a profound impact on the growth, development, and quality of life of the affected pediatric population. The modified Fontan procedure, the total cavopulmonary connection (TCPC), has become a pivotal palliative or definitive surgical method for treating complex CHD cases, including single ventricle and tricuspid valve atresia. Through staged surgical processes, this technique directly diverts vena cava blood into the pulmonary artery, thus improving the patient’s oxygenation status. Despite the initial success of the Fontan circulation in providing a means for survival More > Graphic Abstract

    Contemporary Management of Failing Modified Fontan after the Total Cavopulmonary Connection

  • Open Access

    ARTICLE

    Deep Q-Learning Driven Protocol for Enhanced Border Surveillance with Extended Wireless Sensor Network Lifespan

    Nimisha Rajput1,#, Amit Kumar1, Raghavendra Pal1,#, Nishu Gupta2,*, Mikko Uitto2, Jukka Mäkelä2

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3839-3859, 2025, DOI:10.32604/cmes.2025.065903 - 30 June 2025

    Abstract Wireless Sensor Networks (WSNs) play a critical role in automated border surveillance systems, where continuous monitoring is essential. However, limited energy resources in sensor nodes lead to frequent network failures and reduced coverage over time. To address this issue, this paper presents an innovative energy-efficient protocol based on deep Q-learning (DQN), specifically developed to prolong the operational lifespan of WSNs used in border surveillance. By harnessing the adaptive power of DQN, the proposed protocol dynamically adjusts node activity and communication patterns. This approach ensures optimal energy usage while maintaining high coverage, connectivity, and data accuracy. More >

  • Open Access

    ARTICLE

    The Blockchain Neural Network Superior to Deep Learning for Improving the Trust of Supply Chain

    Hsiao-Chun Han, Der-Chen Huang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3921-3941, 2025, DOI:10.32604/cmes.2025.065627 - 30 June 2025

    Abstract With the increasing importance of supply chain transparency, blockchain-based data has emerged as a valuable and verifiable source for analyzing procurement transaction risks. This study extends the mathematical model and proof of ‘the Overall Performance Characteristics of the Supply Chain’ to encompass multiple variables within blockchain data. Utilizing graph theory, the model is further developed into a single-layer neural network, which serves as the foundation for constructing two multi-layer deep learning neural network models, Feedforward Neural Network (abbreviated as FNN) and Deep Clustering Network (abbreviated as DCN). Furthermore, this study retrieves corporate data from the… More > Graphic Abstract

    The Blockchain Neural Network Superior to Deep Learning for Improving the Trust of Supply Chain

  • Open Access

    ARTICLE

    Machine Learning-Optimized Energy Management for Resilient Residential Microgrids with Dynamic Electric Vehicle Integration

    Mohammed Moawad Alenazi*

    Journal on Artificial Intelligence, Vol.7, pp. 143-176, 2025, DOI:10.32604/jai.2025.066067 - 27 June 2025

    Abstract This paper presents a novel machine learning (ML) enhanced energy management framework for residential microgrids. It dynamically integrates solar photovoltaics (PV), wind turbines, lithium-ion battery energy storage systems (BESS), and bidirectional electric vehicle (EV) charging. The proposed architecture addresses the limitations of traditional rule-based controls by incorporating ConvLSTM for real-time forecasting, a Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning agent for optimal BESS scheduling, and federated learning for EV charging prediction—ensuring both privacy and efficiency. Simulated in a high-fidelity MATLAB/Simulink environment, the system achieves 98.7% solar/wind forecast accuracy and 98.2% Maximum Power Point… More >

  • Open Access

    ARTICLE

    Design and Optimization of Converging-Diverging Liquid Cooling Channels for Enhanced Thermal Management in Lithium-ion Battery Packs

    Tianjiao Zhang*, Yibo Xu, Long Li, Kequn Li, Hua Zhang

    Frontiers in Heat and Mass Transfer, Vol.23, No.3, pp. 819-832, 2025, DOI:10.32604/fhmt.2025.064287 - 30 June 2025

    Abstract Power batteries serve as key components of new energy vehicles and are distinguished by their large capacity, long lifespan, high energy density, and stable operation. The strict temperature demands of power battery packs necessitate the development of highly efficient thermal management systems. In this study, a converging-diverging liquid cooling channel featuring a wave shaped structure was designed and analyzed for 18,650-type lithium-ion batteries. To investigate the design methodology for flow channel structure, a thermal model for the heat generation rate of the 18,650-type battery was developed. A comparative analysis of four geometrical configurations of converging-diverging… More >

  • Open Access

    ARTICLE

    Basic psychological needs satisfaction mediation of the relationship between kindergarten error management climate and creative teaching

    Jing Wang1, Ping Li2,*

    Journal of Psychology in Africa, Vol.35, No.2, pp. 167-172, 2025, DOI:10.32604/jpa.2025.065788 - 30 June 2025

    Abstract The present study aimed to examine the association between kindergarten error management climate and creative teaching and the mediating role of basic psychological needs satisfaction. A sample of 561 Chinese kindergarten teachers (females = 98%, Mage = 34.32, SD = 1.25) completed self-reported questionnaires on their work error management atmosphere, basic psychological needs satisfaction, and innovative teaching. The results structural equation modelling path analysis showed that high kindergarten error management climate was associated with higher innovative teaching. Moreover, the need for competence, but not the need for relatedness accounted for kindergarten error management atmosphere related to More >

  • Open Access

    ARTICLE

    Security-Constrained Optimal Power Flow in Renewable Energy-Based Microgrids Using Line Outage Distribution Factor for Contingency Management

    Luki Septya Mahendra1, Rezi Delfianti2,*, Karimatun Nisa1, Sutedjo1, Bima Mustaqim3, Catur Harsito4, Rafiel Carino Syahroni5

    Energy Engineering, Vol.122, No.7, pp. 2695-2717, 2025, DOI:10.32604/ee.2025.063807 - 27 June 2025

    Abstract Ensuring the reliability of power systems in microgrids is critical, particularly under contingency conditions that can disrupt power flow and system stability. This study investigates the application of Security-Constrained Optimal Power Flow (SCOPF) using the Line Outage Distribution Factor (LODF) to enhance resilience in a renewable energy-integrated microgrid. The research examines a 30-bus system with 14 generators and an 8669 MW load demand, optimizing both single-objective and multi-objective scenarios. The single-objective optimization achieves a total generation cost of $47,738, while the multi-objective approach reduces costs to $47,614 and minimizes battery power output to 165.02 kW.… More >

  • Open Access

    EDITORIAL COMMENT

    The unsuspected nonpalpable testicular mass detected by ultrasound: a management problem – Page 1764

    Canadian Journal of Urology, Vol.32, No.2, pp. 1767-1767, 2025

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Deep Learning-Based Glass Detection for Smart Glass Manufacturing Processes

    Seungmin Lee1, Beomseong Kim2, Heesung Lee3,*

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1397-1415, 2025, DOI:10.32604/cmc.2025.066152 - 09 June 2025

    Abstract This study proposes an advanced vision-based technology for detecting glass products and identifying defects in a smart glass factory production environment. Leveraging artificial intelligence (AI) and computer vision, the research aims to automate glass detection processes and maximize production efficiency. The primary focus is on developing a precise glass detection and quality management system tailored to smart manufacturing environments. The proposed system utilizes the various YOLO (You Only Look Once) models for glass detection, comparing their performance to identify the most effective architecture. Input images are preprocessed using a Gaussian Mixture Model (GMM) to remove… More >

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