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Articles 1 - 7 of 7
Full-Text Articles in Risk Analysis
Environmental Ethics And Impact Of Artificial Intelligence Data Centers, Jacky Yang
Environmental Ethics And Impact Of Artificial Intelligence Data Centers, Jacky Yang
Discovery Day - Daytona Beach
Data centers, including artificial intelligence (AI) facilities, serve as the backbone for many modern digital services and products. With the rapid digitization of society, the expansion of these centers in the United States has accelerated significantly. From an anthropocentric and utilitarian perspective, they provide economic benefits, supporting employment and generating public revenue. However, they can also create a significant amount of environmental and societal challenges. From an ecocentric and environmental justice perspective, AI data centers has contributed to increased competition for the limited resources, such as water, electricity, and land and has been linked to rising utility costs, noise pollution, …
An Innovative Approach To Real-Time Noise Monitoring And Detection In Airport Ramp Operations, Grace Hamilton, Nicole E. Egan, Anderson Peralta, Deyaneira Rodriguez, Maria G. Valentinez
An Innovative Approach To Real-Time Noise Monitoring And Detection In Airport Ramp Operations, Grace Hamilton, Nicole E. Egan, Anderson Peralta, Deyaneira Rodriguez, Maria G. Valentinez
Discovery Day - Daytona Beach
Airport ramp personnel are routinely exposed to hazardous noise levels exceeding occupational safety thresholds, increasing the risk of permanent hearing loss, degraded communication, and operational incidents. Traditional ramp noise management relies primarily on periodic monitoring and personnel protective equipment (PPE), which limits real-time hazard recognition and a proactive risk mitigation strategy. The purpose of this study is to evaluate the safety and financial effectiveness of implementing a real-time noise monitoring and detection system within airport ramp operations in alignment with Safety Management System (SMS) principles. A literature review, Preliminary Hazard Analysis (PHA), and financial cost-benefit analysis were conducted to compare …
A System Safety Approach To Assuring Artificial Intelligence Enabled Functions In Civil Aviation, Evan Bear, Quinn Galen
A System Safety Approach To Assuring Artificial Intelligence Enabled Functions In Civil Aviation, Evan Bear, Quinn Galen
Discovery Day - Daytona Beach
Artificial intelligence and machine learning techniques are increasingly proposed for use in safety-critical civil aviation functions including perception decision support and pilot assistance. Existing aviation safety and certification standards such as ARP4754A and DO-178C were developed under assumptions of determinism explicit requirements and complete behavioral specification which do not directly apply to learning-enabled systems. This mismatch has created uncertainty regarding how artificial intelligence enabled avionics can be safely assured and certified. This paper presents a system safety approach for assuring artificial intelligence enabled functions within existing aviation certification frameworks. In this approach safety assurance is based on explicitly identifying the …
A Hybrid Llm-Srgm Framework For Ai-Enabled Reliability Assessment In Safety-Critical Software Systems, Caleb Stone, Shrenik Jadhav
A Hybrid Llm-Srgm Framework For Ai-Enabled Reliability Assessment In Safety-Critical Software Systems, Caleb Stone, Shrenik Jadhav
Discovery Day - Daytona Beach
Ensuring the reliability of software intensive and safety critical systems is a persistent challenge across aerospace, defense, transportation, and other mis- sion focused domains. Traditional software relia- bility growth models (SRGM) provide useful quanti- tative insight into defect discovery trends, but they rely mostly only on numerical failure data and do not use the rich contextual information contained in test logs, anomaly reports, and engineering notes. This paper presents a hybrid framework that com- bines semantic features extracted by a large lan- guage model (LLM) with a non-homogeneous Pois- son process (NHPP) based software reliability growth model. The LLM analyzes …
Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson
Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson
Discovery Day - Daytona Beach
Title: Dual-Perspective Risk Analysis for Human-LLM Decision Comparison in UAV Swarm Navigation Unmanned aerial vehicle (UAV) swarms operating in low-altitude wireless network environments encounter localized disruptions that degrade positioning and navigation metrics. These disruptions are modeled as geographic failure zones with defined boundaries. A UAV discovers a zone by entering it and observing degraded performance on its onboard systems. This work assumes that affected UAVs can autonomously retreat to safety using onboard sensors and focuses on the subsequent rerouting decision. Once recovered, the system generates candidate repositioning points surrounding the vehicle, each scored using Conditional Value-at-Risk (CVaR). A human operator …
An Exploration Into Aviation Safety & Security In Nigeria, Hana Marz, Nicholas Degarmo, Kathrine Lopez, Michael Chrisman
An Exploration Into Aviation Safety & Security In Nigeria, Hana Marz, Nicholas Degarmo, Kathrine Lopez, Michael Chrisman
Discovery Day - Daytona Beach
Aviation safety and security standards are fundamental for enabling the reliability and sustainability of aviation operations. Aviation safety and security are influenced by organizational and institutional standards, as well as the application of human factors principles. This paper aims to explore the regional variances of aviation safety and security culture within Nigeria. Nigeria has taken steps to align with international aviation standards, offering insight into how the region shapes its regulatory environment, organizational culture, and how cultural factors affect safety and security practices. However, Nigeria continues to face challenges such as inconsistent regulatory enforcement and limited safety reporting, which impact …
Bridging The Gap: Cybersecurity And Occupational Safety Frameworks In Ai Data Centers, Athena Leader
Bridging The Gap: Cybersecurity And Occupational Safety Frameworks In Ai Data Centers, Athena Leader
Discovery Day - Daytona Beach
Bridging the Gap: Cybersecurity and Occupational Safety Frameworks in AI Data Centers As artificial intelligence infrastructure expands, AI data centers represent a critical and underexamined convergence of cybersecurity and occupational safety risk. Existing frameworks such as NIST, OSHA, and ISO standards were largely developed in isolation, leaving significant gaps in how organizations manage risks that are simultaneously digital and physical in nature. This study investigates the gaps and overlaps between cybersecurity and occupational safety frameworks as they apply specifically to AI data center environments. Drawing on a targeted literature review of established regulatory and standards-based frameworks, this research identifies where …