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  • Open Access

    REVIEW

    AI-Powered Digital Twin Frameworks for Smart Grid Optimization and Real-Time Energy Management in Smart Buildings: A Survey

    Saeed Asadi1, Hajar Kazemi Naeini1, Delaram Hassanlou2, Abolhassan Pishahang3, Saeid Aghasoleymani Najafabadi4, Abbas Sharifi5, Mohsen Ahmadi6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1259-1301, 2025, DOI:10.32604/cmes.2025.070528 - 26 November 2025

    Abstract The growing energy demand of buildings, driven by rapid urbanization, poses significant challenges for sustainable urban development. As buildings account for over 40% of global energy consumption, innovative solutions are needed to improve efficiency, resilience, and environmental performance. This paper reviews the integration of Digital Twin (DT) technologies and Machine Learning (ML) for optimizing energy management in smart buildings connected to smart grids. A key enabler of this integration is the Internet of Things (IoT), which provides the sensor networks and real-time data streams that fee/d DT–ML frameworks, enabling accurate monitoring, forecasting, and adaptive control.… More >

  • Open Access

    ARTICLE

    Performance Boundaries of Air- and Ground-Coupled GPR for Void Detection in Multilayer Reinforced HSR Tunnel Linings: Simulation and Field Validation

    Yang Lei1,*, Bo Jiang1, Yucai Zhao2, Gaofeng Fu3, Falin Qi1, Tian Tian1, Qiankuan Feng1, Qiming Qu1

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1657-1679, 2025, DOI:10.32604/sdhm.2025.069415 - 17 November 2025

    Abstract Detecting internal defects, particularly voids behind linings, is critical for ensuring the structural integrity of aging high-speed rail (HSR) tunnel networks. While ground-penetrating radar (GPR) is widely employed, systematic quantification of performance boundaries for air-coupled (A-CGPR) and ground-coupled (G-CGPR) systems within the complex electromagnetic environment of multilayer reinforced HSR tunnels remains limited. This study establishes physics-based quantitative performance limits for A-CGPR and G-CGPR through rigorously validated GPRMax finite-difference time-domain (FDTD) simulations and comprehensive field validation over a 300 m operational HSR tunnel section. Key performance metrics were quantified as functions of: (a) detection distance (A-CGPR:… More >

  • Open Access

    PROCEEDINGS

    Simulation Analysis of in-Situ TiC Generation by Laser Cladding and Study on Mechanical Properties of Enhanced Coatings

    Xiaoxiao Li, Xiujiang Shi*, Yusheng Jian, Yaqi Yang, Bailing Guan, Zehong Cai

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-1, 2025, DOI:10.32604/icces.2025.011099

    Abstract Based on COMSOL simulation software, the planar Gaussian heat source model was used to simulate and analyze the surface reinforced nickel-based coating on H13 steel, and the optimal process parameters were obtained. Secondly, TiC reinforced nickel base coating was prepared in situ on H13 steel surface by laser cladding technology. The morphology, phase composition, microhardness and friction and wear properties of matrix, single coating and gradient coating were compared by scanning electron microscopy, X-ray diffractometer, microhardness tester and universal friction and wear machine. Finally, the bionic gradient TiC reinforced nickel base coating was prepared on… More >

  • Open Access

    ARTICLE

    Hybrid Meta-Heuristic Feature Selection Model for Network Traffic-Based Intrusion Detection in AIoT

    Seungyeon Baek1,#, Jueun Jeon2,#, Byeonghui Jeong1, Young-Sik Jeong1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 1213-1236, 2025, DOI:10.32604/cmes.2025.070679 - 30 October 2025

    Abstract With the advent of the sixth-generation wireless technology, the importance of using artificial intelligence of things (AIoT) devices is increasing to enhance efficiency. As massive volumes of data are collected and stored in these AIoT environments, each device becomes a potential attack target, leading to increased security vulnerabilities. Therefore, intrusion detection studies have been conducted to detect malicious network traffic. However, existing studies have been biased toward conducting in-depth analyses of individual packets to improve accuracy or applying flow-based statistical information to ensure real-time performance. Effectively responding to complex and multifaceted threats in large-scale AIoT… More >

  • Open Access

    ARTICLE

    A Qualitative Analysis of Emotions among Rescue and Recovery Workers Responding to the Oklahoma City Bombing

    E. Whitney Pollio1,*, David E. Pollio2, Carol S. North3,4

    International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1483-1495, 2025, DOI:10.32604/ijmhp.2025.067755 - 31 October 2025

    Abstract Objectives: At the time of the bombing of the federal building in Oklahoma City, Oklahoma (OKC), it was the deadliest terrorist attack in the United States of America. Available research on this incident, and in general, has been quantitative, using deductive methods. The purpose of the current study was to systematically examine professional disaster response workers’ emotions elicited spontaneously and in detail as they were experienced over time after a major disaster. This qualitative study will add to existing knowledge of psychopathology and the psychosocial effects of disasters on professional responders, which have not been… More >

  • Open Access

    ARTICLE

    Colored Tubes and Chlorella Vulgaris Bioinput Improve Growth and Quality of Hancornia speciosa Seedlings

    Giovana Pinheiro Viana da Silva1, Edilson Costa1,*, Paulo Henrique Rosa Melo1, Fernanda Pacheco de Almeida Prado Bortolheiro1, Thaise Dantas2, Flávio Ferreira da Silva Binotti1, Carlos Eduardo da Silva Oliveira1, Abimael Gomes da Silva1

    Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3109-3123, 2025, DOI:10.32604/phyton.2025.070221 - 29 October 2025

    Abstract Hancornia speciosa ‘Gomes’, commonly known as mangabeira, is a fruit-bearing tree native to Brazil that plays a crucial role in sustaining its native biome, restoring degraded areas, and improving the socio-environmental conditions of these regions. The use of colored materials and bioinputs can help improve the quality of seedling production of Hancornia speciosa. This study aimed to evaluate the use of colored seedling tubes and a Chlorella vulgaris-based bioinput in developing Hancornia speciosa seedlings. The experiment was conducted at the Mato Grosso do Sul State University (UEMS), in Cassilândia, MS, using a completely randomized design in a 5 ×… More >

  • Open Access

    ARTICLE

    Peltier Water Cooling System with Solar Energy and IoT Technology Demonstration Set

    Prasongsuk Songsree*, Chaiyapon Thongchaisuratkrul*

    Energy Engineering, Vol.122, No.11, pp. 4541-4559, 2025, DOI:10.32604/ee.2025.068448 - 27 October 2025

    Abstract The purpose of this research is to design and develop a demonstration Set of a water cooling system using a Peltier with solar energy and technology, and IoT (Internet of Things), and test and measure the performance of the Peltier Plate Water Cooling System Demonstration Set under different environmental conditions. To be used as a model for clean energy systems and experimental learning materials. The prototype system consists of a 100-W solar panel, a 12 V 20 Ah battery, a Peltier plate, a DS18B20 sensor, and a NodeMCU microcontroller. The system performance is determined by… More >

  • Open Access

    REVIEW

    Integrating AI, Blockchain, and Edge Computing for Zero-Trust IoT Security: A Comprehensive Review of Advanced Cybersecurity Framework

    Inam Ullah Khan1, Fida Muhammad Khan1,*, Zeeshan Ali Haider1, Fahad Alturise2,*

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4307-4344, 2025, DOI:10.32604/cmc.2025.070189 - 23 October 2025

    Abstract The rapid expansion of the Internet of Things (IoT) has introduced significant security challenges due to the scale, complexity, and heterogeneity of interconnected devices. The current traditional centralized security models are deemed irrelevant in dealing with these threats, especially in decentralized applications where the IoT devices may at times operate on minimal resources. The emergence of new technologies, including Artificial Intelligence (AI), blockchain, edge computing, and Zero-Trust-Architecture (ZTA), is offering potential solutions as it helps with additional threat detection, data integrity, and system resilience in real-time. AI offers sophisticated anomaly detection and prediction analytics, and… More >

  • Open Access

    REVIEW

    Federated Learning in Convergence ICT: A Systematic Review on Recent Advancements, Challenges, and Future Directions

    Imran Ahmed1,#, Misbah Ahmad2,3,#, Gwanggil Jeon4,5,*

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4237-4273, 2025, DOI:10.32604/cmc.2025.068319 - 23 October 2025

    Abstract The rapid convergence of Information and Communication Technologies (ICT), driven by advancements in 5G/6G networks, cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT), is reshaping modern digital ecosystems. As massive, distributed data streams are generated across edge devices and network layers, there is a growing need for intelligent, privacy-preserving AI solutions that can operate efficiently at the network edge. Federated Learning (FL) enables decentralized model training without transferring sensitive data, addressing key challenges around privacy, bandwidth, and latency. Despite its benefits in enhancing efficiency, real-time analytics, and regulatory compliance, FL adoption faces… More >

  • Open Access

    ARTICLE

    Transfer Learning-Based Approach with an Ensemble Classifier for Detecting Keylogging Attack on the Internet of Things

    Yahya Alhaj Maz1, Mohammed Anbar1, Selvakumar Manickam1,*, Mosleh M. Abualhaj2, Sultan Ahmed Almalki3, Basim Ahmad Alabsi4

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5287-5307, 2025, DOI:10.32604/cmc.2025.068257 - 23 October 2025

    Abstract The Internet of Things (IoT) is an innovation that combines imagined space with the actual world on a single platform. Because of the recent rapid rise of IoT devices, there has been a lack of standards, leading to a massive increase in unprotected devices connecting to networks. Consequently, cyberattacks on IoT are becoming more common, particularly keylogging attacks, which are often caused by security vulnerabilities on IoT networks. This research focuses on the role of transfer learning and ensemble classifiers in enhancing the detection of keylogging attacks within small, imbalanced IoT datasets. The authors propose… More >

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