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Abstract The rising complexity of urban areas, along with growing public safety needs, has made intelligent video surveillance systems more essential. The current surveillance systems that rely on human observation and p...

Abstract The deep reinforcement learning techniques offers a novel approach to real-time control for hybrid power flow controllers. This paper introduces a bus voltage optimization adjustment strategy, utilizing a Markov...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

Abstract This model is highly helpful in thermal management and complex energy systems, particularly where precise control over heat and mass transfer is required. Solarized nanofluids can be used to improve heat absorpt...

Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...

Abstract Occupational Health and Safety (OHS), which holds substantial importance due to its profound human implications and far-reaching economic consequences, requires effective management to minimize workplace acciden...

Abstract Wearable sensor–based human activity recognition (HAR) is central to smart sport and health-monitoring applications, yet existing deep learning models often rely on ad hoc multimodal fusion and offer limited i...

Abstract Breast cancer is still the most significant contributor to morbidity and mortality among women in China. Despite advances in imaging and molecular testing, few reliable biomarkers exist for early detection and d...

Abstract Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems have significantly advanced data modelling capabilities and improved opportunities for extracting knowledge from vast and heterogeneo...