Nanjiang Zhong^*, Xinchen Jiang, Yuan Yao

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4741-4757, 2025, DOI:10.32604/cmc.2025.059536 - 06 March 2025

Abstract The proliferation of rumors on social media has caused serious harm to society. Although previous research has attempted to use deep learning methods for rumor detection, they did not simultaneously consider the two key features of temporal and spatial domains. More importantly, these methods struggle to automatically generate convincing explanations for the detection results, which is crucial for preventing the further spread of rumors. To address these limitations, this paper proposes a novel method that integrates both temporal and spatial features while leveraging Large Language Models (LLMs) to automatically generate explanations for the detection results.… More >

Wu-Jiu Sun¹, Xiao Fan Liu^1,2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4117-4136, 2025, DOI:10.32604/cmc.2025.059528 - 06 March 2025

Abstract Predicting information dissemination on social media, specifically users’ reposting behavior, is crucial for applications such as advertising campaigns. Conventional methods use deep neural networks to make predictions based on features related to user topic interests and social preferences. However, these models frequently fail to account for the difficulties arising from limited training data and model size, which restrict their capacity to learn and capture the intricate patterns within microblogging data. To overcome this limitation, we introduce a novel model Adapt pre-trained Large Language model for Reposting Prediction (ALL-RP), which incorporates two key steps: (1)… More >

Yanjiao Wang, Zewei Nan^*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4709-4740, 2025, DOI:10.32604/cmc.2025.058894 - 06 March 2025

Abstract Cyclic-system-based optimization (CSBO) is an innovative metaheuristic algorithm (MHA) that draws inspiration from the workings of the human blood circulatory system. However, CSBO still faces challenges in solving complex optimization problems, including limited convergence speed and a propensity to get trapped in local optima. To improve the performance of CSBO further, this paper proposes improved cyclic-system-based optimization (ICSBO). First, in venous blood circulation, an adaptive parameter that changes with evolution is introduced to improve the balance between convergence and diversity in this stage and enhance the exploration of search space. Second, the simplex method strategy… More >

Haydar Abdulameer Marhoon^1,2,*, Rafid Sagban^3,4, Atheer Y. Oudah^1,5, Saadaldeen Rashid Ahmed^6,7

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4181-4218, 2025, DOI:10.32604/cmc.2025.058822 - 06 March 2025

Abstract In order to address the critical security challenges inherent to Wireless Sensor Networks (WSNs), this paper presents a groundbreaking barrier-based machine learning technique. Vital applications like military operations, healthcare monitoring, and environmental surveillance increasingly deploy WSNs, recognizing the critical importance of effective intrusion detection in protecting sensitive data and maintaining operational integrity. The proposed method innovatively partitions the network into logical segments or virtual barriers, allowing for targeted monitoring and data collection that aligns with specific traffic patterns. This approach not only improves the diversit. There are more types of data in the training set,… More >

Feng Wei^*, Zhao Chen, Yin Wang, Dongqing Liu, Xun Zhang, Zhao Zhou

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5325-5341, 2025, DOI:10.32604/cmc.2025.058802 - 06 March 2025

Abstract The integration of artificial intelligence (AI) with advanced power technologies is transforming energy system management, particularly through real-time data monitoring and intelligent decision-making driven by Artificial Intelligence Generated Content (AIGC). However, the openness of power system channels and the resource-constrained nature of power sensors have led to new challenges for the secure transmission of power data and decision instructions. Although traditional public key cryptographic primitives can offer high security, the substantial key management and computational overhead associated with these primitives make them unsuitable for power systems. To ensure the real-time and security of power data… More >

Shitharth Selvarajan^1,2,3,*, 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 >

Zhengrong Shi^1,3, Hai Hong¹, Yanming Shen^2,*, Jingyong Cai^1,*

Energy Engineering, Vol.122, No.3, pp. 885-903, 2025, DOI:10.32604/ee.2025.061976 - 07 March 2025

Abstract Phase Change Material (PCM)-based cold energy storage system (CESS) can effectively utilize the peak and valley power resources to reduce the excessive dependence on the power grid. In this study, a PCM-based CESS was designed for cold storage applications. The optimal number of PCM plates was determined through numerical simulations to meet the required cold storage temperature and control time. Additionally, the air temperature field, flow field, and melting characteristics of the PCM plates during the cooling release process were analyzed. The effects of plate positioning and thickness on the cooling release performance were further… More >

Xincong Shi^1,2, Yuze Ji^3,*, Xinrui Wang³, Ruimin Tian³, Chao Zhang²

Energy Engineering, Vol.122, No.3, pp. 1199-1220, 2025, DOI:10.32604/ee.2025.061586 - 07 March 2025

Abstract With the development of integrated power and gas distribution systems (IPGS) incorporating renewable energy sources (RESs), coordinating the restoration processes of the power distribution system (PS) and the gas distribution system (GS) by utilizing the benefits of RESs enhances service restoration. In this context, this paper proposes a coordinated service restoration framework that considers the uncertainty in RESs and the bi-directional restoration interactions between the PS and GS. Additionally, a coordinated service restoration model is developed considering the two systems’ interdependency and the GS’s dynamic characteristics. The objective is to maximize the system resilience index… More >

Jian Gao¹, Hongliang Hao², Caifeng Wen^1,*, Yongsheng Wang³, Zhanhua Han⁴, Edwin E. Nykilla², Yuwen Zhang²

Energy Engineering, Vol.122, No.3, pp. 1175-1198, 2025, DOI:10.32604/ee.2025.061083 - 07 March 2025

Abstract Power quality is a crucial area of research in contemporary power systems, particularly given the rapid proliferation of intermittent renewable energy sources such as wind power. This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra, PSD, and random signal power spectra. The relationship was derived, validated through experiments and simulations, and subsequently applied to multi-objective optimization. Various optimization algorithms were compared to achieve optimal system power quality. The findings revealed that the relationships between power quality indices and PSD were influenced by variations in More >

Giovanni Miracco^1,*, Francesco Nicoletti¹, Vittorio Ferraro², Dimitrios Kaliakatsos¹

Energy Engineering, Vol.122, No.3, pp. 861-883, 2025, DOI:10.32604/ee.2025.060750 - 07 March 2025

Abstract Indoor air quality (IAQ) is often overlooked, yet a poorly maintained environment can lead to significant health issues and reduced concentration and productivity in work or educational settings. This study presents an innovative control system for mechanical ventilation specifically designed for university classrooms, with the dual goal of enhancing IAQ and increasing energy efficiency. Two classrooms with distinct construction characteristics were analyzed: one with exterior walls and windows, and the other completely underground. For each classroom, a model was developed using DesignBuilder software, which was calibrated with experimental data regarding CO₂ concentration, temperature, and relative… More >