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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 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 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 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 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 Individualized educational management cannot be avoided in meeting various learner needs in cases where teaching strategies are changed in line with the performance trends and preferences of students. Reinforcem...

Abstract The increase in vehicle ownership and urban population puts a strain on roads and increases traffic congestion within developed and developing nations. Congestion affects an individual’s time and increases an ...

Abstract Matching college students with appropriate innovative training projects is a challenging task that often relies on static assignment techniques, which overlook individual interests, skills, and learning styles. ...

Abstract This study examined whether defensive pessimism-related processes influence university students’ approaches to learning, psychological well-being, and academic performance indirectly through academic procrasti...