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Atmospheric Gas Dynamics Of Mars: A Multi-Sensor Remote Sensing Approach For Fine Vertical, Global, And Event-Driven Analysis, Frányerson R. López Ochoa Aug 2026

Atmospheric Gas Dynamics Of Mars: A Multi-Sensor Remote Sensing Approach For Fine Vertical, Global, And Event-Driven Analysis, Frányerson R. López Ochoa

Discovery Day - Daytona Beach

To provide precise vertical resolution and worldwide coverage across all seasons and altitudes, this study integrated nadir, limb, occultation, and general circulation model (GCM) measurements in a thorough remote sensing examination of the Martian atmosphere. The study examined the density and temperature structures of major atmospheric gases, mainly carbon dioxide (CO₂), molecular nitrogen (N₂), and argon (Ar), using mission datasets from the Mars Reconnaissance Orbiter (MRO), Mars Express (MEX), and the ExoMars Trace Gas Orbiter (TGO). It also assessed retrieval uncertainties resulting from dust, ice clouds, and sensor limitations. The study concluded that, though valuable, single-geometry observation techniques are unable …

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Optimization Of Co₂ Removal In Carbon Dioxide Removal Assembly (Cdra) Using Nonlinear Equilibrium Modeling And Zeolite-Based Adsorption Simulation, Frányerson R. López Ochoa Aug 2026

Optimization Of Co₂ Removal In Carbon Dioxide Removal Assembly (Cdra) Using Nonlinear Equilibrium Modeling And Zeolite-Based Adsorption Simulation, Frányerson R. López Ochoa

Discovery Day - Daytona Beach

This study follows a quantitative, non-experimental, existing-data design to examine the optimization of carbon dioxide removal in spacecraft’s Carbon Dioxide Removal Assembly (CDRA) through the integration of nonlinear isotherm modeling and process-level cycle simulation. Existing carbon dioxide adsorption equilibrium data from multiple zeolite sorbents, including Grace Davison Grade (544 13X, 522 5A, and 514 4A), Honeywell UOP (APG-III, LiLSX VSA-10), and BASF 13X, is analyzed to determine which adsorption models best represent carbon dioxide loading behavior and how these models can be used to reduce energy consumption in spacecraft regeneration processes. The study fitted eight nonlinear isotherm models – Langmuir, …

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Enhancing Fibre–Matrix Interface Properties In Cfrps Using Cohesive Zone Modelling, Arjun Myadam, Alexander Skoppe Aug 2026

Enhancing Fibre–Matrix Interface Properties In Cfrps Using Cohesive Zone Modelling, Arjun Myadam, Alexander Skoppe

Discovery Day - Daytona Beach

Carbon fibre reinforced polymers (CFRPs) are extensively used in aerospace, automotive, and structural applications owing to their high specific strength, stiffness, and design flexibility. The mechanical performance of these composites is critically governed by the fibre–matrix interface, which controls stress transfer and directly influences damage initiation, crack propagation, and fracture behaviour. The interface strength is quantified through the interfacial shear strength (IFSS) and fracture energy, both serving as key indicators of composite integrity. Nanoscale fibre surface modifications are widely employed to enhance interfacial bonding and can also impart multifunctionality, such as capacitive properties, magnetic behaviour, and piezoelectricity. For instance, nanoscale …

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Artificial Intelligence (Ai) In Mental Health: Perceptions Of Ai Therapists, Ulker Yusupova Aug 2026

Artificial Intelligence (Ai) In Mental Health: Perceptions Of Ai Therapists, Ulker Yusupova

Discovery Day - Daytona Beach

This study explores how people perceive Artificial Intelligence (AI) therapists compared to human therapists, focusing on differences in empathy, effectiveness, and competence. As AI tools like ChatGPT and mental health chatbots become more commonly used for emotional support, it is important to understand how users evaluate them in comparison to human professionals. To begin addressing this, in the first part of the study, participants reviewed therapist-client conversation transcripts and identified whether they believed the therapist was human or AI-generated, helping us validate the materials for the main study. Notably, initial findings suggest that participants frequently relied more on surface-level language …

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N31 Multi-Sensor Data Fusion For Enhanced Cislunar Space Domain Awareness Using Radar And Optical Observations, Lucas Bottero Aug 2026

N31 Multi-Sensor Data Fusion For Enhanced Cislunar Space Domain Awareness Using Radar And Optical Observations, Lucas Bottero

Discovery Day - Daytona Beach

MULTI-SENSOR DATA FUSION FOR ENHANCED CISLUNAR SPACE DOMAIN AWARENESS USING RADAR AND OPTICAL OBSERVATIONS   As operations extend into cislunar space, maintaining Space Domain Awareness (SDA) becomes increasingly challenging due to the vast distances, sparse infrastructure, and complex gravitational dynamics between Earth and the Moon. Radar and optical sensors are the primary modalities used for space surveillance, each with its strengths and limitations. Radar offers continuous observation capabilities regardless of lighting conditions but is limited by power and range at cislunar distances. Optical sensors provide high angular precision but depend on favorable illumination and line-of-sight geometry. However, there has been limited …

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Modeling A Spaceborne Passive Radar Architecture For Tracking Resident Space Objects Using Ground-Based Signals Of Opportunity, Chinmay Gaikwad Aug 2026

Modeling A Spaceborne Passive Radar Architecture For Tracking Resident Space Objects Using Ground-Based Signals Of Opportunity, Chinmay Gaikwad

Discovery Day - Daytona Beach

Modeling a Spaceborne Passive Radar Architecture for Tracking Resident Space Objects Using Ground-Based Signals of Opportunity Due to an increase in manned and unmanned space activities, there is an increase in demand for resilient space operations. This project investigates passive-radar architecture for space domain awareness in which satellites in a low-Earth-orbit mega-constellation are adapted as distributed sensing platforms for tracking debris and other non-cooperative resident space objects. The motivation is to overcome the coverage, cost, and scalability limits of conventional active or ground-based systems by using lightweight passive receivers that exploit ground-based illuminators of opportunity. In this concept, the receivers …

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The Effects Of Acute Dietary Nitrate Supplementation On The Inspiratory Muscle Metaboreflex In Young Healthy Adults, Sabrina Ehrenfort, Riley Dienna, Ben Kerns, Hannah Lyons, Rachel Phillips Aug 2026

The Effects Of Acute Dietary Nitrate Supplementation On The Inspiratory Muscle Metaboreflex In Young Healthy Adults, Sabrina Ehrenfort, Riley Dienna, Ben Kerns, Hannah Lyons, Rachel Phillips

Discovery Day - Daytona Beach

Increased work of breathing (Wb) triggers the inspiratory muscle metaboreflex, which elevates systemic blood pressure in response to diaphragmatic fatigue. To counteract this, dietary nitrate could act as a source of nitric oxide, which is known to improve muscle power and efficiency (Jones et al., 2018). This study examines the hypothesis that acute nitrate supplementation would attenuate this response. Utilizing the KH2 device from PowerBreathe, 20 healthy participants (mean age: 21.1 ± 2.5 years; range: 18–30 years) underwent a resistive breathing task (RBT) for a total of three minutes at 60% of their maximal inspiratory pressure (MIP). All 20 participants …

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Using Sysml Models To Verify System Design And Identify Discrepancies In A Satellite System, Noah Fulton Aug 2026

Using Sysml Models To Verify System Design And Identify Discrepancies In A Satellite System, Noah Fulton

Discovery Day - Daytona Beach

This study investigates the use of Systems Modeling Language (SysML) to verify subsystem design consistency and identify integration discrepancies in a multidisciplinary satellite program. Project COMET, an Embry-Riddle effort under the University Nanosatellite Program (UNP), consists of six subsystems but lacks a centralized system model. This leads to inconsistencies between subsystem inputs, outputs, and interface definitions. Typically, SysML models are created early in the system design cycle; However, this study will evaluate how creating system models post preliminary design review (PDR) can assist a project by verifying subsystem integration or by identifying discrepancies between independently developed subsystems. This study will …

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Environmental Ethics Of Plastics And Microplastics Manufacturing: Balancing Industrial Production And Ecological Responsibility, Arindam Gupta Aug 2026

Environmental Ethics Of Plastics And Microplastics Manufacturing: Balancing Industrial Production And Ecological Responsibility, Arindam Gupta

Discovery Day - Daytona Beach

The global production of plastics has increased dramatically over the past several decades, providing substantial economic and societal benefits while simultaneously generating complex environmental and ethical challenges. A growing body of research has identified microplastics—plastic particles smaller than 5 millimeters—as persistent pollutants that accumulate in aquatic ecosystems, soil systems, and the atmosphere. These particles originate both from the degradation of larger plastic products and from direct industrial production processes used in plastics manufacturing. The ethical implications of plastics and microplastics production raise important questions about environmental responsibility, regulatory oversight, and the balance between economic development and ecological sustainability. This project …

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Spatial Dynamics Of Lead Waste: An Esda Approach To U.S. Interstate Transfers, Santiago Acuna Gonzalez Aug 2026

Spatial Dynamics Of Lead Waste: An Esda Approach To U.S. Interstate Transfers, Santiago Acuna Gonzalez

Discovery Day - Daytona Beach

Spatial Dynamics of Lead Waste: An ESDA Approach to U.S. Interstate Transfers   This research applied a novel Exploratory Spatial Data Analysis (ESDA) methodology to analyze interstate movements (n= 446) of lead (Pb; CAS 7339-92-1) among facilities that transported more than 1,000 lbs offsite across the United States, using the Environmental Protection Agency’s (EPA) 2024 Toxic Release Inventory (TRI). Using QGIS, the analysis produced three geospatial products by integrating TRI Form R Schedule 3A with coordinates from the EPA Facility Registry Service (FRS) to populate offsite locations. First, a state-level net-flow choropleth distinguished exporting from importing states. Second, an export-focused map …

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Environmental Ethics And Impact Of Artificial Intelligence Data Centers, Jacky Yang Aug 2026

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, …

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Is It Safe To Speak Up? A Theoretical Examination Of The Measurement Of Psychological Safety, Carissa Aumack Aug 2026

Is It Safe To Speak Up? A Theoretical Examination Of The Measurement Of Psychological Safety, Carissa Aumack

Discovery Day - Daytona Beach

When working with teams, certain factors will dictate whether they function well or not, with one such factor being psychological safety. Psychological safety (PS) is determined by a shared belief that, within the team, it is safe to take interpersonal risks (Edmonson, 1999). This definition does not entirely encapsulate the concept of PS, as it focuses on the concept as a team-based belief and does not consider how individual beliefs of PS can differ from the collective. A cursory literature review was conducted (8 articles related to PS), and based on the findings, a nomological network (i.e., a representation of …

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Quantitative Analysis Of A Single Operator’S Flight Behavior In Simulation, Zackrey Schraeder Aug 2026

Quantitative Analysis Of A Single Operator’S Flight Behavior In Simulation, Zackrey Schraeder

Discovery Day - Daytona Beach

Uncrewed Aircraft Systems (UAS), or more commonly known as drones, have become increasingly used for a variety of applications, and more research has emerged studying the human-machine interaction and pilot performance metrics. Current research focuses on desired behaviors or aggregated pilot data which does not provide a holistic picture of an individual pilot’s flight behaviors, which are shaped by their own experience, preferences, and risk tolerance. The study investigates whether an individual pilot’s flight behaviors can be considered a pattern or if there is enough flight-to-flight variability to consider the behaviors inconsistent. A series of 20 flights were conducted in …

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Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder Aug 2026

Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder

Discovery Day - Daytona Beach

Modernization of Deicing Operations Utilizing Uncrewed Aircraft Systems   The use of Uncrewed Aircraft Systems (UAS), commonly known as drones, has become more apparent in everyday life within the United States (US). The Airport Cooperative Research Program (ACRP) has provided an opportunity to utilize drones to improve quality of life and operational efficiency at airports across the US. Students from Embry-Riddle Aeronautical University under the callsign Team Frostbite, consists of Hunter Lisle, Zakrey Schraeder, and Christopher Sidor. The team provides a potential solution utilizing UAS to measure the efficiency of deicing applications at Patrick Leahy Burlington International Airport (BTV) in Burlington, …

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Assessing Attachment To Ai: Understanding The Theoretical Correlations And Consequences, Brianna Broderick Aug 2026

Assessing Attachment To Ai: Understanding The Theoretical Correlations And Consequences, Brianna Broderick

Discovery Day - Daytona Beach

Current research on Artificial Intelligence (AI) focuses on its capabilities and our understanding of it as an instrumental tool (i.e., utility completing tasks). However, as its ability to replicate natural language improves through both text and voice, an ever-growing number of users have turned to AI for emotional companionship. Concern grows as prior research on technology dependency suggests AI bonding may lead to less interaction with others and, in extreme circumstances, has already led to cases of suicide and divorce. Kasturiaratna & Hartanto (2025) developed the AI Attachment (AIA) scale, consisting of three factors, which include: emotional closeness (i.e., personal …

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Quantifying Grain Size In Scanning Electron Microscopy Images, Katherine Hoffsetz Aug 2026

Quantifying Grain Size In Scanning Electron Microscopy Images, Katherine Hoffsetz

Discovery Day - Daytona Beach

This project explores advanced image analysis techniques to assess the microstructure of highly strained austenitic stainless steel. Utilizing Python imaging libraries such as scikit-image and OpenCV, we aim to extract precise measurements for grain size from scanning electron microscopy (SEM) images. These metrics will be examined against the computed grain sizes of the sample from electron backscatter diffraction measurements. By automating the extraction of grain size measurements from SEM images, this study contributes to steamlining the quality assurance/ quality control of industrially processed materials.

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Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth Aug 2026

Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth

Discovery Day - Daytona Beach

Understanding the complex causal relationships underlying aviation accidents is critical for improving safety and preventing future incidents. However, much of this information exists in unstructured narrative reports, making large-scale analysis difficult. This project aims to automatically extract and model causal chains from National Transportation Safety Board (NTSB) accident narratives using a combination of traditional natural language processing (NLP) techniques, transformer-based architectures, and graph-based knowledge representation. Traditional NLP methods, including named entity recognition, dependency parsing, and rule-based pattern matching, will be used to identify structured cause–effect relationships. These approaches will be compared with transformer-based models, including a lightweight encoder for classification …

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Numerical Modeling Of A Secondary Breakup In The Veritas Asteroid Family, Jarrett Dieterle Aug 2026

Numerical Modeling Of A Secondary Breakup In The Veritas Asteroid Family, Jarrett Dieterle

Discovery Day - Daytona Beach

The Veritas asteroid family, located in the outer main belt, is believed to have formed from the catastrophic breakup of a parent body approximately 8.3 million years ago (e.g., Nesvorný et al., 2003). Larger fragments remained in the main belt, while smaller particles evolved inward under radiation forces, forming a toroidal dust structure observable in infrared data as paired bands. Previous studies (e.g., Dermott et al., 2001) have shown that these bands can be linked to their parent families and modeled from their initial disruptions. We propose that the 10° dust bands associated with Veritas may record evidence of a …

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Exploring Generation Z Pilots' Approach To Training Automation: An Interview Study, Mary Bender Aug 2026

Exploring Generation Z Pilots' Approach To Training Automation: An Interview Study, Mary Bender

Discovery Day - Daytona Beach

Introduction. Today's pilots learn to fly on aircraft with sophisticated automated systems, such as the G1000. Although automation can reduce workload, over-relying on this technology can lead to decreased situational awareness, complacency, and a loss in manual flying skills (Parasuraman, 2000; Parasuraman et al., 2000; Parasuraman & Wickens, 2017; Taylor et al., 2020). Instructor pilots, in turn, are faced with the challenge of teaching students how to leverage a system that can affect their performance, both positively and negatively. The purpose of this study was to explore the strategies and challenges that instructor pilots face when training students on automation. …

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High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin Aug 2026

High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin

Discovery Day - Daytona Beach

Site exploration requires in-situ resource utilization when the physical properties of resources are unknown. Therefore, a generalizable object manipulation method is crucial for extraterrestrial environments. Existing studies develop reinforcement learning policies that enable interaction with objects, in which quadruped robots learn to reach commanded goals with one foot while balancing with the remaining legs. However, in these studies, goal-oriented task execution relies on high-level trajectories provided by human experts, which limits autonomous robotic operations. In this study, we propose a hierarchical DRL in which a high-level pedipulation policy outputs commands for a low-level reach policy, enabling autonomous, smooth and affordable …

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Ai Race Between The Us And China, Kennedy Lyon-Lindersmith Aug 2026

Ai Race Between The Us And China, Kennedy Lyon-Lindersmith

Discovery Day - Daytona Beach

Technological leadership in AI and semiconductor manufacturing are both directly linked with military power and geopolitical influence. At the same time, the U.S. and China are currently defining the future of conflict in the cyber domain and are in strategic competition as China attempts to displace the U.S. as a global leader in AI. These factors contribute to an important national security threat that the U.S. is facing right now: An AI race between the U.S. and China, specifically regarding military cyber operations. This paper discusses some of the implications of a digital battlefield and analyzes international laws, international institutions, …

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Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes, Paulo Carreon Aug 2026

Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes, Paulo Carreon

Discovery Day - Daytona Beach

Quantitative Assessment of Cybersecurity Risk Variability Across Transportation Modes examines how cybersecurity risks differ across major transportation sectors and addresses the lack of a structured, cross modal analysis in existing transportation cybersecurity research. As transportation systems increasingly rely on digital infrastructure, communication networks, operational technologies, and interconnected platforms, they become more exposed to cyber threats that can affect safety, mobility, operations, and public trust. Despite the growing importance of this issue, there is still limited research that quantitatively compares how cyber risks vary across transportation modes such as road and intelligent transportation systems, aviation, rail and transit, and maritime systems. …

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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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