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Small Unmanned Aerial Systems-Assisted Airport Obstruction And Perimeter Inspections, Christopher Candler, Christopher M. Saylor, Marcus Thompson, Tejash Zala Aug 2026

Small Unmanned Aerial Systems-Assisted Airport Obstruction And Perimeter Inspections, Christopher Candler, Christopher M. Saylor, Marcus Thompson, Tejash Zala

Discovery Day - Daytona Beach

Airports are required to maintain obstruction-free airspace surfaces under 14 CFR Part 77; however, vegetation and perimeter obstruction management is often conducted through periodic ground inspections and contractor-led surveys that provide only snapshot conditions. These approaches may delay detection of encroachments into approach, transitional, horizontal, or primary surfaces, increasing the risk of operational impacts and reactive mitigation. This study proposes an FAA-aligned framework integrating small unmanned aircraft systems (sUAS) into obstruction monitoring workflows through recurring, repeatable perimeter inspections. High-resolution optical and LiDAR sensors, combined with RTK/PPK-enabled GNSS correction, generate centimeter-level geospatial datasets that are processed into canopy height models. These …

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Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning, Bill Deng Pan, Yupeng Yang Aug 2026

Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning, Bill Deng Pan, Yupeng Yang

Discovery Day - Daytona Beach

Runway incursions remain one of the most persistent safety challenges in modern aviation operations, often resulting from complex interactions among human, environmental, and operational factors. While existing Safety Management System (SMS) frameworks emphasize monitoring the frequency of incursions, they provide limited predictive capability regarding event severity. This ongoing study seeks to address that gap by applying a novel tabular-to-image deep-learning approach to improve the accuracy and interpretability of runway-incursion severity prediction models. Data for this study will be drawn from the Federal Aviation Administration (FAA) Runway Safety Statistics and National Transportation Safety Board (NTSB) accident databases. The methodology will involve …

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Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions, Bill Deng Pan Aug 2026

Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions, Bill Deng Pan

Discovery Day - Daytona Beach

The effective implementation of Safety Management Systems (SMS) at airports depends not only on compliance with regulatory requirements but also on the presence of a strong and measurable safety culture. While the Federal Aviation Administration (FAA)’s increasing emphasis on SMS has accelerated adoption across certificated airports, many airport operators, often coming from operational, engineering, or business backgrounds, lack practical methods to assess safety culture in a structured and actionable manner. Existing guidance highlights the importance of safety culture and safety climate. However, limited research exists on how airport stakeholders perceive and experience safety culture within the airport operating environment. This …

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Geometry-Conditioned Adversarial Defense For Sar Automatic Target Recognition Via Regime-Specialist Classification Heads, Skyler Fabre Aug 2026

Geometry-Conditioned Adversarial Defense For Sar Automatic Target Recognition Via Regime-Specialist Classification Heads, Skyler Fabre

Discovery Day - Daytona Beach

This project, titled Geometry-Conditioned Adversarial Defense for SAR Automatic Target Recognition via Regime-Specialist Classification Heads, addresses the critical vulnerability of deep neural networks deployed in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems to adversarial perturbations. This is where imperceptible pixel-level modifications cause confident misclassification, posing serious risks in defense and aerospace applications. The objective is to develop and evaluate RegimeResNet, a geometry-conditioned classification architecture that exploits sensor metadata unique to SAR collection systems. Rather than treating all images uniformly, RegimeResNet partitions the SAR capture space into nine geometric regimes defined by depression angle and target azimuth angle extracted …

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Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison Aug 2026

Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison

Discovery Day - Daytona Beach

Aviation accidents are rarely the result of a single failure but rather from a complex causal chain of latent failures. While traditional data mining models often predict incident occurrence, they frequently overlook the sequential mechanics defined by known accident causation theoretical frameworks like the Swiss Cheese Model and the FAA's HFACS. This project addresses the need for interpretable, reliable, multi-stage forecasting by proposing a Sequential Causal Architecture that transforms theoretical causation models into a structured Directed Acyclic Graph (DAG) for multimodal accident causation chain prediction. Data from the NTSB and DOT is used and connected together in a meaningful way …

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Energy-Aware Bimodal Contact Detection For Leg Odometry, Emre Girgin Aug 2026

Energy-Aware Bimodal Contact Detection For Leg Odometry, Emre Girgin

Discovery Day - Daytona Beach

Autonomous exploration of extraterrestrial environments using legged robots requires robust GNSS-free 3D state estimation. Standard leg odometry relies on Zero-Velocity Updates (ZUPT), which assume a grounded foot remains completely stationary. This assumption consistently fails on deformable granular terrain due to unobservable slippage, rapidly degrading state estimation. To mitigate this critical failure mode, we propose a dual contact-detection framework designed to robustly gate an Error-State Extended Kalman Filter (ESEKF) tracking pose, velocity, and IMU biases.   The architecture isolates physical load and kinematics by modeling contact detection as two independent parallel Hidden Markov Models (HMMs). The Load HMM processes Ground Reaction Forces, …

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Heuristic Trafficability Assessment For Autonomous Lunar Surface Operations Using Orbital Data Products, Leia Spaniak Aug 2026

Heuristic Trafficability Assessment For Autonomous Lunar Surface Operations Using Orbital Data Products, Leia Spaniak

Discovery Day - Daytona Beach

This study seeks to map the surface of the Moon by developing a new orbital dataset composed of layers that inform trafficability. The project supports the objectives of the Artemis Program by focusing operations on the Lunar South Pole, where terrain conditions remain difficult to assess over broad areas. With future validation anticipated through cone penetrometer testing, the study examines what orbital data layers can reveal about bearing capacity through estimated internal friction angle, density, and cohesion. The research evaluates the feasibility of this methodology by comparing the mapping strategy to data obtained during the Apollo 15, 16, and 17 …

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Assured Learning For Intelligent Dynamic Systems: A Metacognitive Framework, Rocio Jado Puente, Michael Budihartono, Eduar Cabrera Gaspar Aug 2026

Assured Learning For Intelligent Dynamic Systems: A Metacognitive Framework, Rocio Jado Puente, Michael Budihartono, Eduar Cabrera Gaspar

Discovery Day - Daytona Beach

Assured Learning for Intelligent Dynamic Systems: A Metacognitive Framework   Advanced Air Mobility systems, including electric vertical takeoff and landing (eVTOL) aircraft and autonomous drone platforms, require increasingly high levels of autonomy and safety. Meeting these demands calls for intelligent systems that can adapt in real time to uncertainty and changing environmental conditions. However, traditional certification methods are not well suited to rigorously measure or quantitatively verify the performance of online learning components because of their non-deterministic behavior.   This work introduces a novel runtime safety assurance method based on a metacognitive architecture (MCA) that supervises and regulates learning-enabled components. The approach …

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Motivational Outsourcing: Ai, Self-Determination, And The Changing Nature Of Adult Learning, Zoe Spanos Aug 2026

Motivational Outsourcing: Ai, Self-Determination, And The Changing Nature Of Adult Learning, Zoe Spanos

Discovery Day - Daytona Beach

Artificial intelligence (AI) is increasingly embedded into adult learning and higher education, serving not only as a support tool for cognitive aid but also as a system that can shape how learners regulate their motivation and engagement. This presentation examines how the use of AI in adult learning contexts may support or undermine self-determined motivation, drawing from Self-Determination Theory (SDT). It is a conceptual paper that draws on existing literature and theoretical analysis, examining AI reliance from minimal use to full automation across SDT's three basic psychological needs: autonomy, competence, and relatedness. Motivation is essential for learning, but the quality …

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Learning Motion Primitive Selection And Environment Abstraction, Edison Alberto Martinez Samaniego, Natalie Alexander, Kaelyn Weddle Aug 2026

Learning Motion Primitive Selection And Environment Abstraction, Edison Alberto Martinez Samaniego, Natalie Alexander, Kaelyn Weddle

Discovery Day - Daytona Beach

Learning Motion Primitive Selection and Environment Abstraction Advanced Air Mobility (AAM) is emerging as a transformative solution for short and medium range transportation; however, it introduces an operational model that differs significantly from conventional aviation. AAM vehicles are expected to operate closer to populated areas, with increased autonomy, in dense urban and suburban environments. These settings present constrained maneuvering conditions which highlights the importance of maintaining safe operation under degraded flight conditions. Abnormal conditions may endanger onboard passengers, people on the ground, and surrounding infrastructure, making rapid detection and mitigation essential to prevent loss of control. Recent research has explored …

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Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac, Jadia Renee Ewing, Alexander Van Baelan, Conrad Prisby, Rafal P. Smietana Aug 2026

Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac, Jadia Renee Ewing, Alexander Van Baelan, Conrad Prisby, Rafal P. Smietana

Discovery Day - Daytona Beach

Air traffic congestion is an increasingly important factor in aviation safety as global flight activity continues to grow. This project investigates whether higher traffic density is associated with an increased risk of aviation incidents and identifies key contributing factors. Using publicly available flight (ADS-B) and incident (NTSB) data, we apply several machine learning models to analyze traffic patterns and predict risk. We begin with logistic regression to evaluate the relationship between density and incident probability, followed by decision trees to extract interpretable rules describing high-risk conditions. K-nearest neighbors (KNN) is used to examine similarity in traffic patterns among incident flights, …

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Impact Of Stress & Fatigue On Cardiovascular Function In Young Pilots: A Thematic Review, Swarna Manoj Aug 2026

Impact Of Stress & Fatigue On Cardiovascular Function In Young Pilots: A Thematic Review, Swarna Manoj

Discovery Day - Daytona Beach

Impact of Stress & Fatigue on Cardiovascular Function in Young Pilots: A Thematic Review   Authors: Swarna Manoj, Scott Ferguson   Keywords: pilot, stress, fatigue, heart rate variability (HRV), cardiovascular disease (CVD) Aviation is expanding globally and young pilots are the major workforce, yet FAA protocols require mandatory ECG only from age 35, with annual cardiac screening after age 40. Over the past five years, a pattern of sudden cardiac arrests in pilots particularly aged 30-40 has urged safety concerns. Despite the existing literature examining fatigue, burnout, stress, sleep hygiene and circadian disruption, only few studies systematically examine how these factors impact …

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A Sustainability Index For Airlines: A Kpi-Based Framework For Benchmarking Environmental Performance, Craig Dedrick Aug 2026

A Sustainability Index For Airlines: A Kpi-Based Framework For Benchmarking Environmental Performance, Craig Dedrick

Discovery Day - Daytona Beach

The aviation industry faces increasing pressure to reduce its environmental impact, yet standardized methods for evaluating airline sustainability performance remain limited. This study proposes a structured sustainability index designed to benchmark airline environmental strategies using fourteen key performance indicators (KPIs) derived from publicly disclosed corporate sustainability and annual reports. To improve analytical clarity, the KPIs are organized into seven conceptual clusters capturing distinct dimensions of environmental performance: strategic governance and commitment, operational and fleet efficiency, the sustainable aviation fuel (SAF) ecosystem, emissions reduction and climate mitigation outcomes, carbon management and neutralization, energy transition and electrification, and environmental pollution and resource …

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Agar-Natural Polymer Composites For Packaging Applications, Alaa Alnatsheh Aug 2026

Agar-Natural Polymer Composites For Packaging Applications, Alaa Alnatsheh

Discovery Day - Daytona Beach

Global plastic production reached 359 million metric tons in 2018, with packaging accounting for about 31% of total use and expected to continue increasing toward 2060. Recycling remains limited, with approximately 66% of recyclable packaging in the United States not being recycled. These challenges have increased interest in biodegradable materials derived from renewable sources. Agar, a polysaccharide extracted from red seaweed, has strong film-forming ability but shows limitations such as low mechanical strength and high water sensitivity. This study investigates agar-based bioplastic films using three formulation approaches: agar-starch (binary), agar-starch-chitosan (ternary), and agar with nanocellulose (nano-enhanced). Films were prepared using …

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Why Are Motorcyclist Fatalities Increasing?, Caroline Deck, Ana Cruz Beltrami, Riley Curran, Crystal Cutler Aug 2026

Why Are Motorcyclist Fatalities Increasing?, Caroline Deck, Ana Cruz Beltrami, Riley Curran, Crystal Cutler

Discovery Day - Daytona Beach

According to the National Highway Traffic Safety Administration, from 2019 to 2023 there was a 26% increase of motorcycle crash deaths. In 2023, motorcycle crashes accounted for 15.5% of all crash fatalities in the United States, despite accounting for 3% of registered vehicles. This literature review investigates the contributing factors to the increasing motorcycle fatality rates. In this review, rider characteristics, vehicle factors, roadway environments, and policy are examined for contributions to increased risk. Previous literature has primarily focused on behavioral and demographic factors when investigating this problem. However, evidence suggests that the conditions affecting crash severity and survivability have …

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The Regeneratively Cooled Engine Development (R.E.D.) Project, Joseph Traverso, Sharjeel Malik, Ford Catlin Aug 2026

The Regeneratively Cooled Engine Development (R.E.D.) Project, Joseph Traverso, Sharjeel Malik, Ford Catlin

Discovery Day - Daytona Beach

The Experimental Rocket Propulsion Lab (ERPL) is a student-run organization dedicated to designing, building, and testing experimental rocket engines. With ERPL transitioning toward flight vehicles, developing engines with longer burn times is critical to future club success. One limitation to burn time is an engine’s ability to withstand extreme combustion temperatures, typically in excess of 5000 F. ERPL engines have found success with passive cooling techniques such as ablative, heatsink, and film cooling, but these techniques aren’t suitable for extended burn times. Therefore, ERPL has created the Regeneratively cooled Engine Development (R.E.D) project, with the objective to design, analyze, and …

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Is Lane Splitting/Lane Filtering Safe Or Dangerous?, Anastacio Doucas Nolas, Sierra Juliano, Shawn De La Osa, Kimberly R. Williamson Aug 2026

Is Lane Splitting/Lane Filtering Safe Or Dangerous?, Anastacio Doucas Nolas, Sierra Juliano, Shawn De La Osa, Kimberly R. Williamson

Discovery Day - Daytona Beach

This course-based research project examines whether lane splitting and lane filtering are inherently dangerous or whether their safety depends on human factors and traffic conditions. Using published crash, behavioral, and policy literature, the project compares how these motorcycle maneuvers affect riders and other road users across different roadway environments. The analysis distinguishes lane splitting, which occurs between moving lanes of traffic, from lane filtering, which typically occurs at low speeds in stopped or slow traffic queues. Findings suggest that safety cannot be explained by the maneuver alone. Instead, outcomes are shaped by speed differential, driver perception failures, rider workload, intersection …

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Advancing Aircraft Maintenance - Smart Mechanic Glasses Proposal, Diego Cordero-Rios, Ilan Soler, Ryan Mercer, Addison Groce, Ruipeng Zhao, Zimo Yang Aug 2026

Advancing Aircraft Maintenance - Smart Mechanic Glasses Proposal, Diego Cordero-Rios, Ilan Soler, Ryan Mercer, Addison Groce, Ruipeng Zhao, Zimo Yang

Discovery Day - Daytona Beach

Commercial aircraft maintenance is increasingly challenged by aging fleets, expanding use of composite materials, labor shortages, and rising expectations for reliability, safety, and cost-effectiveness. Modern aircraft systems demand that maintenance technicians interpret large amounts of technical data to detect complex and hidden defects while navigating limited visibility, distractions, outdated manuals, and inconsistent flows between teams. Traditionally, technicians rely on printed manuals, tablets, or laptops, which increase cognitive load and interrupt task execution, ultimately decreasing productivity, especially in confined physical spaces. Meanwhile, the use of advanced materials, such as composites, creates inspection and repair demands that are more labor-intensive and time-consuming; …

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3d Printing In Construction: Technology And Digital Innovation, Zachary Braunstein, Tyler Fritsch, Leah Oberkehr, Ethan Arvidson Aug 2026

3d Printing In Construction: Technology And Digital Innovation, Zachary Braunstein, Tyler Fritsch, Leah Oberkehr, Ethan Arvidson

Discovery Day - Daytona Beach

The study of 3D Printing in Construction: Technology and Digital Innovation examines the growing role of additive manufacturing in transforming traditional construction practices. This literature review explores the evolution of construction 3D printing from early conceptual research on contour crafting to modern automated construction systems that integrate robotics with digital design technologies such as Building Information Modeling. The review highlights practical applications including the design and testing of a 3D printed concrete pedestrian bridge and the increasing use of 3D concrete printing in residential construction to reduce labor demands and project timelines. It also discusses advancements in printable materials, including …

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Low-Rank Spectral Analysis For The Reddening Of The Seven Sisters Star Cluster, Eric Rodarte, Angelina Scalice, Madison Warner, Kevin Numbe Aug 2026

Low-Rank Spectral Analysis For The Reddening Of The Seven Sisters Star Cluster, Eric Rodarte, Angelina Scalice, Madison Warner, Kevin Numbe

Discovery Day - Daytona Beach

The Pleiades, also known as the Seven Sisters, is a stunning star cluster located approximately 440 light-years from Earth. This vibrant assemblage of hot blue stars in the Taurus constellation can be admired with the naked eye or through binoculars during early autumn. In this presentation, we utilize spectral theory to measure the reddening in the Pleiades star cluster. To evaluate the impact of interstellar dust on reddening, we employ principal component analysis (PCA) on a matrix representing color indices from various photometric bands linked to the cluster’s photometric data. This dataset was obtained from VIZIER. Our PCA analysis of …

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Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez Aug 2026

Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez

Discovery Day - Daytona Beach

The proposed work seeks to improve the fundamental understanding of the properties concerning 3-D printing filaments that have potential to be used for lunar applications. The associated properties in focus for the proposed study, vibration and thermal-vacuum-resistance, are fundamental aspects of spaceflight and are critical to mission success for objectives associated with the environmental factors in space. The successful outcome of the proposed work will answer questions relating to the feasibility of micro carbon fiber filled nylon 3-D printing filaments such as Markforged’s Onyx® for application for projects in the Space Technologies Laboratory, including for the development of structures relating …

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A Comparative Classical And Data-Driven Facial Analysis Of Wide-Field-Of-View Lens Captures, Andrew Murphy, Giovanni C. Decapua, Anthony M. Cafiso, Max E. Raabe, Kaden E. Van Leuven Aug 2026

A Comparative Classical And Data-Driven Facial Analysis Of Wide-Field-Of-View Lens Captures, Andrew Murphy, Giovanni C. Decapua, Anthony M. Cafiso, Max E. Raabe, Kaden E. Van Leuven

Discovery Day - Daytona Beach

WFOV lenses are becoming popular in facial recognition due to the fact that they enhance subject coverage and improve the chances of detecting target faces. However, wide-angle optics introduce nonlinear distortion around the image periphery, which degrades the performance of recognition pipelines. In this poster presentation, we use WFOV lens captures to analyze facial recognition using classical low-complexity algorithms based on the discrete Fourier transform (DFT), discrete cosine transform (DCT), principal component analysis (PCA), and data-driven learning with convolutional neural networks. Finally, we present computational efficiency, compression, accuracy, and precision of recognizing distorted images with qualitative and quantitative measures.

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Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy Aug 2026

Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy

Discovery Day - Daytona Beach

The Circular Restricted Three-Body Problem (CR3BP) is renowned for its intricate and chaotic dynamics, leaving it without a closed-form solution. In this poster, we introduce an innovative approach to determine spacecraft trajectories within the CR3BP framework using matrix factorization techniques. We formulate a matrix equation where the right-hand side vector is constructed from the spacecraft's position and velocity data, while the coefficient matrix is derived from the spacecraft's temporal data. Subsequently, we apply several matrix decomposition techniques, including modified Gram-Schmidt, the Householder technique, and Givens Rotation, to analyze the coefficient matrix and derive the spacecraft trajectories. Finally, we evaluate the …

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Hydroquad - A Drone Quadruped Hybrid, Haitish Gandhi, Dheer Chhabria Aug 2026

Hydroquad - A Drone Quadruped Hybrid, Haitish Gandhi, Dheer Chhabria

Discovery Day - Daytona Beach

The HyDroQuad is a hybrid robotic system designed to navigate environments where traditional robots face limitations. By combining a quadrupedal walking mechanism with an aerial drone, the platform is able to walk efficiently on stable terrain and transition to flight when encountering obstacles such as rocks, gaps, or steep slopes. This adaptability makes it a strong candidate for future planetary exploration, where terrain is often uneven and unpredictable. This work focuses on developing and evaluating a functional prototype of the system. A fully integrated platform, HDQ-MK1, was designed and constructed by combining a lightweight multirotor drone with a compact quadruped …

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A Myoelectric Prosthesis Utilizing A Convolutional Neural Network And Signal Processing, Hope Lea, Katherine Clark, Francis Genco, Carolyn Ascha Richardson, Tobiah Rosser Aug 2026

A Myoelectric Prosthesis Utilizing A Convolutional Neural Network And Signal Processing, Hope Lea, Katherine Clark, Francis Genco, Carolyn Ascha Richardson, Tobiah Rosser

Discovery Day - Daytona Beach

A Myoelectric Prosthesis Utilizing A Convolutional Neural Network and Signal Processing   Commercially available myoelectric prostheses for transradial amputees utilize electromyography (EMG) sensors to observe electrical signals from superficial muscle contractions and control robotic fingers, yet often have flaws regarding adaptability and dexterity. These devices require users to learn awkward muscle patterns, as the EMG placement and gesture recognition does not consider how humans would normally think about moving their hand. Additionally, the number of available gestures is more limited, as the devices are threshold-based and do not sample enough muscles. This work seeks to address these issues by creating a …

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Earthquake-Resistant Design And Base Isolation Techniques, Christian George, Jacob Sweeten, Gabriela Cotto, Savion Stewart Aug 2026

Earthquake-Resistant Design And Base Isolation Techniques, Christian George, Jacob Sweeten, Gabriela Cotto, Savion Stewart

Discovery Day - Daytona Beach

Earthquake-resistant design has become a critical feature in construction near active fault lines, where seismic activity is most frequent and potentially destructive. In recent years, technological advancements have significantly improved methods for protecting buildings from earthquake damage. Among these innovations, base isolation systems have appeared as one of the most effective solutions. By decoupling a building from ground motion, base isolators reduce the transmission of seismic forces, helping to prevent structural damage and support building stability during earthquakes. In addition to improving safety, base isolation systems can also reduce long-term costs associated with earthquake-related repairs and maintenance. Base-isolated structures are …

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Hurricane-Resilient Construction Practices In The Southeastern United States, Eleanor Hopkins, Jonathan Gildersleeve, Kieran Hemminger, Remingtin Rodriguez Aug 2026

Hurricane-Resilient Construction Practices In The Southeastern United States, Eleanor Hopkins, Jonathan Gildersleeve, Kieran Hemminger, Remingtin Rodriguez

Discovery Day - Daytona Beach

Hurricanes pose a significant threat to infrastructure and communities across the southeastern United States, causing billions of dollars in structural damage each year. High wind speeds, storm surge, and wind-driven rain frequently lead to roof failures, structural collapse, and severe interior water damage. As coastal populations continue to grow, improving the resilience of buildings in hurricane-prone regions has become a critical engineering and planning challenge. This literature review examines hurricane-resilient construction practices and evaluates strategies that improve structural performance during extreme weather events. Key areas of focus include continuous load path structural systems, reinforced roof-to-wall connections, elevated foundations to mitigate …

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Plastic Roads And Waste Utilization In Pavements: Recycling Plastic Waste Into Durable Road Construction, Hunter Smith, Caden Hoffer, Robert Kincart, Winston De Feria Weber Aug 2026

Plastic Roads And Waste Utilization In Pavements: Recycling Plastic Waste Into Durable Road Construction, Hunter Smith, Caden Hoffer, Robert Kincart, Winston De Feria Weber

Discovery Day - Daytona Beach

Plastic waste production continues to increase worldwide, creating significant environmental and waste management challenges. With over 350 million tons of plastic waste generated annually, researchers and engineers are exploring innovative methods to reuse materials in sustainable construction practices. To reduce construction waste and make productive use of recycled materials, engineers are investigating utilization applications for plastic waste in pavement systems. This project examines the use of recycled plastic as a modifier in asphalt pavement mixtures to improve road performance while addressing environmental concerns. The objective of this work is to evaluate how incorporating recycled plastics into asphalt mixtures can enhance …

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Results And Implications For Space Weather Forecasting Of Periodic Mesoscale Solar Wind Structures Responsible For Radiation Belt Particle Loss, Grace Gratton Aug 2026

Results And Implications For Space Weather Forecasting Of Periodic Mesoscale Solar Wind Structures Responsible For Radiation Belt Particle Loss, Grace Gratton

Discovery Day - Daytona Beach

Highly dynamic and structured mesoscale solar wind continually buffets Earth's magnetosphere, the moon, and Mars. These mesoscale structures cause several significant risks to spacecraft and astronauts, including driving radiation belt depletion and amplifying the hazards of CMEs and SIRs through upstream solar wind preconditioning. Characterizing the solar origins and solar wind properties of geoeffective mesoscale structures is essential for eventually forecasting their arrival and space weather impact at various satellites. In this interdisciplinary work, we leverage modeling and data analysis to characterize a series of events observed by the Balloon Array for Radiation-belt Relativistic Electron Losses (BARREL) instrument – in …

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Analyzing Fungal Growth Dynamics Under Different Environmental Conditions Using A Lotka–Volterra Competition System, Maria Ordonez, Fabrio Araujo Aug 2026

Analyzing Fungal Growth Dynamics Under Different Environmental Conditions Using A Lotka–Volterra Competition System, Maria Ordonez, Fabrio Araujo

Discovery Day - Daytona Beach

Fungi play a critical role in ecosystems as decomposers that recycle nutrients and maintain environmental balance. Their populations are influenced by multiple environmental factors such as temperature, humidity, nutrient availability, and interactions with other organisms. In this project, the Lotka–Volterra model is used to analyze how competing fungal species interact and how these interactions influence population dynamics over time. By modeling two fungal populations competing for the same limited resources, the equations illustrate how environmental conditions and competition coefficients determine whether one species dominates; both species coexist, or one species becomes extinct. The model provides insight into how changes in …

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