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  • Open Access

    ARTICLE

    Real-Time Fault Detection and Isolation in Power Systems for Improved Digital Grid Stability Using an Intelligent Neuro-Fuzzy Logic

    Zuhaib Nishtar1,*, Fangzong Wang1, Fawwad Hassan Jaskani2, Hussain Afzaal3

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2919-2956, 2025, DOI:10.32604/cmes.2025.065098 - 30 June 2025

    Abstract This research aims to address the challenges of fault detection and isolation (FDI) in digital grids, focusing on improving the reliability and stability of power systems. Traditional fault detection techniques, such as rule-based fuzzy systems and conventional FDI methods, often struggle with the dynamic nature of modern grids, resulting in delays and inaccuracies in fault classification. To overcome these limitations, this study introduces a Hybrid Neuro-Fuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic. The model’s performance was evaluated through extensive simulations on the… More >

  • Open Access

    ARTICLE

    Does artificial intelligence (AI) anxiety increase employees’ deviant behavior toward the organization? The role of emotional exhaustion and leadership support

    Chengcheng Sha, Lin Wang, Xiaolei Pan*

    Journal of Psychology in Africa, Vol.35, No.2, pp. 207-214, 2025, DOI:10.32604/jpa.2025.065761 - 30 June 2025

    Abstract This study investigated the relationship between AI anxiety and deviant behavior, as well as the roles of emotional exhaustion and leader support in this context. The sample comprised 381 Chinese e-commerce employees (72.7% female, age range 21–36 years). The results of the Process model analysis indicate that AI anxiety significantly is associated with higher deviant behaviour. Emotional exhaustion partially mediates this relationship between AI anxiety and employee deviant behavior exacerbating deviant behaviour. Leader support moderates the AI anxiety effect on emotional exhaustion such that when leader support is low. AI anxiety is associated with higher 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 >

  • Open Access

    REVIEW

    Survey on AI-Enabled Resource Management for 6G Heterogeneous Networks: Recent Research, Challenges, and Future Trends

    Hayder Faeq Alhashimi1, Mhd Nour Hindia1, Kaharudin Dimyati1,*, Effariza Binti Hanafi1, Feras Zen Alden2, Faizan Qamar3, Quang Ngoc Nguyen4,5,*

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3585-3622, 2025, DOI:10.32604/cmc.2025.062867 - 19 May 2025

    Abstract The forthcoming 6G wireless networks have great potential for establishing AI-based networks that can enhance end-to-end connection and manage massive data of real-time networks. Artificial Intelligence (AI) advancements have contributed to the development of several innovative technologies by providing sophisticated specific AI mathematical models such as machine learning models, deep learning models, and hybrid models. Furthermore, intelligent resource management allows for self-configuration and autonomous decision-making capabilities of AI methods, which in turn improves the performance of 6G networks. Hence, 6G networks rely substantially on AI methods to manage resources. This paper comprehensively surveys the recent… More >

  • Open Access

    ARTICLE

    A Novel Proactive AI-Based Agents Framework for an IoE-Based Smart Things Monitoring System with Applications for Smart Vehicles

    Meng-Hua Yen1,*, Nilamadhab Mishra2,*, Win-Jet Luo3, Chu-En Lin1

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1839-1855, 2025, DOI:10.32604/cmc.2025.060903 - 17 February 2025

    Abstract The Internet of Everything (IoE) coupled with Proactive Artificial Intelligence (AI)-Based Learning Agents (PLAs) through a cloud processing system is an idea that connects all computing resources to the Internet, making it possible for these devices to communicate with one another. Technologies featured in the IoE include embedding, networking, and sensing devices. To achieve the intended results of the IoE and ease life for everyone involved, sensing devices and monitoring systems are linked together. The IoE is used in several contexts, including intelligent cars’ protection, navigation, security, and fuel efficiency. The Smart Things Monitoring System… More >

  • Open Access

    ARTICLE

    Enhancing User Experience in AI-Powered Human-Computer Communication with Vocal Emotions Identification Using a Novel Deep Learning Method

    Ahmed Alhussen1, Arshiya Sajid Ansari2,*, Mohammad Sajid Mohammadi3

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2909-2929, 2025, DOI:10.32604/cmc.2024.059382 - 17 February 2025

    Abstract Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing details about the speaker’s goals and desires, as well as their internal condition. Certain vocal characteristics reveal the speaker’s mood, intention, and motivation, while word study assists the speaker’s demand to be understood. Voice emotion recognition has become an essential component of modern HCC networks. Integrating findings from the various disciplines involved in identifying vocal emotions is also challenging. Many sound analysis techniques were developed in the… More >

  • Open Access

    ARTICLE

    Revolutionizing Automotive Security: Connected Vehicle Security Blockchain Solutions for Enhancing Physical Flow in the Automotive Supply Chain

    Khadija El Fellah1,*, Ikram El Azami2,*, Adil El Makrani2, Habiba Bouijij3, Oussama El Azzouzy4

    Computer Systems Science and Engineering, Vol.49, pp. 99-122, 2025, DOI:10.32604/csse.2024.057754 - 03 January 2025

    Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >

  • Open Access

    ARTICLE

    Deep learning identification of novel autophagic protein-protein interactions and experimental validation of Beclin 2-Ubiquilin 1 axis in triple-negative breast cancer

    XIANG LI1,#, WENKE JIN2,#, LIFENG WU2, HUAN WANG1, XIN XIE1, WEI HUANG1,*, BO LIU2,*

    Oncology Research, Vol.33, No.1, pp. 67-81, 2025, DOI:10.32604/or.2024.055921 - 20 December 2024

    Abstract Background: Triple-negative breast cancer (TNBC), characterized by its lack of traditional hormone receptors and HER2, presents a significant challenge in oncology due to its poor response to conventional therapies. Autophagy is an important process for maintaining cellular homeostasis, and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors. In contrast to targeting protein activity, intervention with protein-protein interaction (PPI) can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways. Methods: Here, we employed Naive Bayes, Decision Tree, and k-Nearest Neighbors to elucidate the complex PPI… More >

  • Open Access

    REVIEW

    Navigating IoT Security: Insights into Architecture, Key Security Features, Attacks, Current Challenges and AI-Driven Solutions Shaping the Future of Connectivity

    Ali Hassan1, N. Nizam-Uddin2, Asim Quddus3, Syed Rizwan Hassan4, Ateeq Ur Rehman5,*, Salil Bharany6

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3499-3559, 2024, DOI:10.32604/cmc.2024.057877 - 19 December 2024

    Abstract Enhancing the interconnection of devices and systems, the Internet of Things (IoT) is a paradigm-shifting technology. IoT security concerns are still a substantial concern despite its extraordinary advantages. This paper offers an extensive review of IoT security, emphasizing the technology’s architecture, important security elements, and common attacks. It highlights how important artificial intelligence (AI) is to bolstering IoT security, especially when it comes to addressing risks at different IoT architecture layers. We systematically examined current mitigation strategies and their effectiveness, highlighting contemporary challenges with practical solutions and case studies from a range of industries, such More >

  • Open Access

    REVIEW

    AI-Driven Learning Management Systems: Modern Developments, Challenges and Future Trends during the Age of ChatGPT

    Sameer Qazi1,*, Muhammad Bilal Kadri2, Muhammad Naveed1,*, Bilal A. Khawaja3, Sohaib Zia Khan4, Muhammad Mansoor Alam5,6,7, Mazliham Mohd Su’ud6

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3289-3314, 2024, DOI:10.32604/cmc.2024.048893 - 15 August 2024

    Abstract COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus. The foremost and most prime sector among those affected were schools, colleges, and universities. The education system of entire nations had shifted to online education during this time. Many shortcomings of Learning Management Systems (LMSs) were detected to support education in an online mode that spawned the research in Artificial Intelligence (AI) based tools that are being developed by the research community to improve the effectiveness of LMSs. This paper presents a detailed survey of the different enhancements to LMSs, which… More >

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