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Unboxing Accessibility: Evaluating the Out-of-Box Experience of the Playstation Access™ Controller
Get PDFMany video gamers with mobility disabilities face significant barriers when using video game controllers, creating a demand for assistive technology within the gaming industry. The PlayStation Access™ Controller (PAC) is an adaptive gaming device designed to improve accessibility for individuals with disabilities through customizable controls. Due to the diverse experiences people with disabilities face, it is important to evaluate a variety of users, from no mobility impairment experiences to caregivers, and those experiencing a mobility disability, to ensure that a range of groups have the ability to set-up and use the PAC. A key aspect of this Out-of-Box Experience (OOBE) process encompasses initial interactions with the product, from unboxing to first-time use. This study evaluates the OOBE of the PAC for individuals with various disability and gaming experiences. Initial findings suggest that while the PAC\u27s packaging is intuitive and customizable, challenges exist regarding the complexity and length of setup, controller size, and button symbol recognition. The aim is to identify design strengths that can inform future assistive technologies while also addressing potential areas for improvement to enhance accessibility and ease of use
Multi-Modal Aerial Object Detection for Enhanced Airport Safety
Get PDFThe rise of small unmanned aerial systems (sUAS) near airports presents growing safety risks, including mid-air collisions, operational disruptions, and security threats. Current detection systems, such as radar and optical tracking, struggle to reliably identify and classify aerial — particularly non-cooperative drones — under variable operational conditions.
This research proposes a multi-modal aerial object detection system that combines six sensor modalities to enable real-time surveillance. By integrating sensor fusion and machine learning (ML), the system aims to improve detection and classification accuracy, reduce false positives, and support Real-time Decision-making for airport safety personnel. The research aims to evaluate system performance under varied weather and lighting conditions and develop a scalable framework for enhanced Situational Awareness in airport operations
Class Activity, Understanding and Applying Tolerances
Get PDFThis assignment is designed to help EGR120 – Graphical Communication students understand, interpret, and apply dimensional tolerances in engineering drawings. It is structured into four main parts: Pre-assessment, AI-supported learning, application and calculation, and final reflection. In the Pre-assessment, students begin by reflecting on their initial understanding of dimensional tolerances and how parts fit together, which promotes critical thinking and activates prior knowledge. The AI-supported learning phase involves using tools like CoPilot or ChatGPT to explore and clarify key concepts such as tolerance, types of fit between mating components, nominal values, and real-world examples. This fosters responsible AI use as a learning support tool. The application and calculation phase combines both AI and non-AI tasks, where students create their own mechanical part fit scenario, assign appropriate tolerances, perform detailed calculations, and use AI to confirm their fit type, later verifying the AI’s output against a provided technical chart. The final reflection phase requires students to consider what they learned, the role AI played in their understanding, and how this knowledge applies to real engineering contexts.
This assignment supports students in developing technical, conceptual, and digital literacy skills. It enables them to interpret mechanical drawings with tolerance, distinguish between types of fit (clearance, interference, transition), and perform relevant calculations. Conceptually, they recognize the functional importance of dimensional accuracy and the role of tolerances in assembly and performance. Furthermore, it encourages digital literacy by practicing responsible and critical use of AI tools to support learning rather than replace it. To replicate this activity, educators should emphasize when students should use or avoid AI to encourage authentic reflection and calculation. Class time should be allocated to allow thoughtful completion of each step, and instructors should actively engage with students to prompt deeper thinking during the activity. Visual aids or physical models can help ground abstract concepts, while creativity should be encouraged during the mechanical part fit scenario task. Collaboration among peers is also recommended, especially for the later stages, and sharing anonymized student reflections can spark discussion and enhance learning
Kinship Infrastructure Design: Evaluating Diversity and Resilience in Emergency Response Systems Through Agent-Based Modeling
No full textTraditional infrastructure systems are often designed for predictable scenarios, making them vulnerable to disruption when real-world conditions change unexpectedly. This research addresses that limitation by introducing Kinship Infrastructure Design (KID), a bioinspired framework based on the kinship coefficient (Φ). Adapted from studies of genetic relatedness in eusocial insects, the kinship coefficient (Φ) measures similarity and diversity among system components by calculating the degree to which their functional traits—encoded as a synthetic genome—match. This research investigates whether a system design can achieve a “Goldilocks Zone” of functional diversity where systems achieve optimal adaptability and coordination under uncertainty.
Rather than relying on predicting exactly how the system might fail, KID uses kinship coefficients as a design tool to guide early resource allocation decisions in the early design stage. This approach allows systems to remain flexible and effective even under uncertain disaster scenarios. The framework is evaluated using two constructive simulations implemented with agent-based modeling.
The first case study applies KID to a simulated wildfire response scenario, and models firefighting agents such as helicopters, firetrucks, bulldozers, and construction crews. These are encoded with traits like speed and suppression capability to calculate kinship coefficients for different configurations.
The second case study applies KID to a simulated COVID-19 scenario, involving agents like delivery drivers, doctors, nurses, IT personnel, and households. Each is defined by attributes such as response time, capacity, and service reliability. This case investigates how kinship-guided configurations maintain critical services during a public health crisis.
Across both case studies, the highest performance occurred within the mid-range kinship coefficients (Φ ≈ 0.50–0.75). In this region, the wildfire system achieved its peak with 83.6 percent of forest saved, while the pandemic-response system reached its maximum with 92 percent of daily service demand met, demonstrating a shared “Goldilocks Zone” where diversity and cohesion are optimally balanced.
By applying kinship-based principles across different infrastructure design challenges, this research aims to demonstrate KID’s potential as a versatile and scalable method for designing resilient infrastructure systems in uncertain environments
Considerations of Undrained Behavior of Compacted Clay Embankments Under Extreme Wetting-Drying Cycles
No full textMany geotechnical analyses, including slope stability, involve unsaturated soils or soils in thevadose zone. Undrained loading happens when the increase in driving forces occurs quicker thanthe ability of the soil to dissipate its pore-water pressure (PWP). During undrained loading forcompacted clay embankments, in which the material is typically unsaturated, it has beenestablished that the increase in shear strength caused by an increase in confining pressure is largerthan the reduction in shear strength due to a decrease in matric suction. This concept is not wellestablished in engineering practice because the conventional understanding is that the strength ofunsaturated soils is larger than that of saturated soils due to suction. Air compresses under theapplication of total stress loading, even in undrained conditions, which leads to an increase in thedegree of saturation because of a decrease in the void ratio, and hence, the decrease in matricsuction. On the other hand, infiltration and evaporation of water create downward and upward flowwithin the embankment, respectively; this flow affects the distribution of PWP. In addition, thelevel of drying, i.e., how low the moisture content is of the soil during a drying cycle, affects thevolumetric change during the following wetting cycles. This paper explores the above processesand their effect on the estimation of the undrained shear strength of compacted clay embankmentsunder the expected climate change and extreme cycles of wetting and drying. An unsaturatedtriaxial testing program is proposed to further confirm the above
Insights on AI-supported Uncrewed and Autonomous Systems Education
No full textArtificial Intelligence (AI) related technology is reshaping the educational experience in programs focused on uncrewed and autonomous systems, aviation, robotics, and aerospace, with growing implications for workforce readiness and cross-sector innovation. Early survey data, capturing student, educator, and employer perspectives, reveals that AI-supported tools are notably changing student engagement, communication, and skills development. Initial indications underscores the importance of AI proficiency and technological familiarity in hiring and workforce development, particularly in technical and operational roles. Key areas of focus include the use of AI to strengthen outreach and interactivity; enrich instruction through intelligent simulations; inform curricular improvements using data analytics; and prepare students for careers across the operational ecosystem. Backed by real-world examples from schools, industry, and government, the findings once fully captured and analyzed are expected to show how AI-supported education can help align academic training with the evolving skill demands of emerging technologies across sectors
High-Fidelity Modeling of eVTOL Rotor Unsteady Aerodynamic and Aeroacoustic Response to Time-Harmonic Gust
No full textThe rapid emergence of Urban Air Mobility (UAM) demands accurate prediction and mitigation of noise generated by electric vertical take-off and landing (eVTOL) aircraft operating in complex urban environments. Among the various noise sources, the aerodynamic and acoustic response of rotors to unsteady inflow represents a major uncertainty in community-noise assessment and certification. This thesis investigates the aerodynamic and aeroacoustic behavior of a representative eVTOL rotor subjected to time-harmonic inflow disturbances, providing a detailed numerical framework to quantify how periodic gusts influence rotor performance, unsteady loading, and sound radiation.
The study employs a three-stage computational methodology using the open-source solver \textit{OpenFOAM v2412} coupled with the \textit{PSU-WOPWOP} acoustic post-processor. First, a baseline rotor simulation is conducted under uniform inflow to validate the computational model against experimental data from the Virginia Tech full-scale acoustic measurements of the Joby Aviation 2017 prototype rotor. The comparison of thrust, torque, and sound pressure levels demonstrates close agreement, confirming the accuracy of the selected Spalart--Allmaras Delayed Detached Eddy Simulation (SA-DDES) turbulence model. Second, a time-harmonic gust generator is implemented via a localized momentum-source formulation to create convected inflow disturbances with controlled amplitude and frequency, verified to maintain phase and amplitude coherence during propagation. Finally, gust--rotor interaction cases are performed for two inflow amplitudes, representing 10\% and 30\% perturbations of the mean velocity.
Results show that while mean thrust and torque remain nearly constant across gust intensities, the unsteady load fluctuations increase in thrust and torque, producing distinct spectral sidebands at the blade-passing frequency. Acoustic analysis reveals modest amplification of tonal components at the BPF, accompanied by slight attenuation of low-frequency radiation. The developed framework contributes to the broader goal of establishing predictive tools for urban aeroacoustic certification and noise-sensitive vehicle design
Elephant in the Classroom: How Ethical AI Can Improve Student Success
No full textThe integration of artificial intelligence (AI) into teaching and learning in higher education without compromising academic integrity is a pressing issue. To make the benefits of generative AI (GenAI) available to students while upholding principles of ethics and academic honesty, the authors implemented an ethical use of AI policy in their Introduction to Research Methods at Embry-Riddle University. The authors hypothesized and found that allowing ethical utilization of AI would lead to higher student engagement and academic success. These findings offer valuable insights for higher education programs and educators, particularly in security studies
Panel #8: Aviation Cybersecurity Regulations and Standards
No full textPanel #8: Aviation Cybersecurity Regulations and Standards
Focuses on evolving aviation cybersecurity regulatory frameworks, standards and certification requirements, with insights from industry leaders.
Moderator: Sanjay Bajekal (Collins Aerospace)
Panelists:
• Douglas Britton (RunSafe) • Glenn Burnett (Bell) • Don Christie (Honeywell) • Jens Hennig (GAMA) • Stefan Schwindt (GE Aerospace