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26 articles for “AI Threat Detection”
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Unmasking Human Metapneumovirus: The Emerging Threat to Vulnerable Populations
Abstract: Human Metapneumovirus (HMPV) is a contagious respiratory virus that commonly spreads among individuals. It can cause serious infections, especially in high-risk groups like infants, older adults, and individuals with weakened immune systems.It is a major contributor to acute respiratory illnesses. Since its discovery in 2001, HMPV has been identified as a common cause of both upper and lower respiratory tract illnesses, with clinical presentations ranging from mild symptoms to severe …
Published in International Journal of Virus Studies · Vol. 2, Issue 1, 2025 · pp. 16–24 Read article
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Intrusion Eye Detector
Abstract: Uncertainty about security risks and illegal access are becoming more prevalent in a variety of settings, such as private homes, business buildings, and critical government buildings. Conventional security systems, which may not offer real-time warnings or prompt reactions, frequently rely on passive monitoring, including CCTV cameras and motion sensors. Artificial intelligence (AI) and computer vision-based intelligent systems are becoming more and more popular as a means of improving security and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 28–32 Read article
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Emerging Threats in Wireless Network Security: A Contemporary Analysis
Abstract: A crucial component of the architecture of contemporary information technology is wireless network security, as wireless communications .Given the continued importance of wireless communication in today's information technology architecture, wireless network security Since wireless communication is becoming more and more essential to our everyday lives, wireless network security is an essential component of today's information technology infrastructure. An overview of the main ideas, problems, and solutions for protecting wireless networks …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 2, 2023 · pp. 1–9 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article