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123 articles for “risk management”
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The Heat of Competition: Assessing Climate Vulnerabilities and Adaptive Governance in Endurance, Winter, and Youth Sports
Abstract: Background: Climate change is fundamentally reshaping the environmental parameters of global sport, posing unprecedented risks to athlete health, safety, and performance. As rising temperatures, frequent extreme heat events, and deteriorating air quality become the new normal, athletic environments from community fields to elite international arenas face an existential threat. Purpose: This study provides an interdisciplinary synthesis of the multifaceted impacts of climate change on athletes, integrating evidence from sports medicine, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 9–17 Read article
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Integrating Atmospheric Science: Understanding Greenhouse Gases, Aerosols, and Air Quality Dynamics
Abstract: Atmospheric science investigates the Earth’s atmospheric systems to understand their composition, dynamics, and the implications for climate, weather, and air quality. This review explores five primary areas within the field: atmospheric composition, atmospheric modeling, remote sensing, air pollution, and boundary layer dynamics, highlighting critical challenges and advancements. Rising levels of greenhouse gases (GHGs), including carbon dioxide and methane, continue to drive global warming, while feedback mechanisms—like cloud interactions and surface …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 32–35 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article