Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences Commons™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 331 - 360 of 63893

Full-Text Articles in Computer Sciences

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, …

Go to article

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 …

Go to article

Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter Aug 2026

Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter

Discovery Day - Daytona Beach

Lightweight UAV-to-UAV Detection and Tracking for Advanced Air Mobility Applications addresses the significant challenge of reliable UAV-to-UAV detection on resource-constrained platforms, particularly within Advanced Air Mobility (AAM) environments where dense, low-altitude airspace requires robust detect-and-avoid capabilities. This work presents the development and experimental evaluation of a lightweight detection and tracking framework for autonomous detect-and-avoid applications. The approach is designed to support real-time onboard operation in multi-vehicle environments characteristic of emerging AAM systems. The proposed framework integrates optical and LiDAR sensing with a low-complexity machine learning decision-support layer that reduces false detections without replacing the underlying control-oriented detection pipeline. This design …

Go to article

Ai-Driven Predictive Analysis Of Airline Profitability Under Macroeconomic And Sustainable Aviation Fuels, Shivika Singh Aug 2026

Ai-Driven Predictive Analysis Of Airline Profitability Under Macroeconomic And Sustainable Aviation Fuels, Shivika Singh

Discovery Day - Daytona Beach

This study presents an AI-enhanced predictive model to assess airline profitability under the combined influence of macroeconomic trends and the adoption of sustainable aviation fuel (SAF). By including economic indicators such as GDP growth, inflation rates, and fuel price volatility with airline operational data, including ticket prices and fuel costs, the model simulates profitability across multiple carriers. Scenario-based analyses, encompassing optimistic, moderate, and pessimistic projections, illustrate different financial sensitivities between low-cost and legacy airlines.

Go to article

Determinants And Invertibility In Finite Modular Systems, Osasu Omobude Aug 2026

Determinants And Invertibility In Finite Modular Systems, Osasu Omobude

Discovery Day - Daytona Beach

This project investigates determinants and matrix invertibility in finite modular systems, focusing on matrices over Zn. Using the Hill cipher as context, it examines the algebraic conditions under which a matrix is invertible in modular arithmetic. In particular, the project studies how the determinant determines invertibility, showing that a matrix over Zn is invertible if and only if its determinant is coprime with n.   The project further compares invertibility over the real numbers with invertibility over modular systems, highlighting the distinction between prime moduli Zp and composite moduli. In the prime case, matrices behave similarly to those over fields, where …

Go to article

Designing Process-Focused Feedback For College Writers Using Genai, Beata Blood, Maissane Aik, Zoey Zaldivar Aug 2026

Designing Process-Focused Feedback For College Writers Using Genai, Beata Blood, Maissane Aik, Zoey Zaldivar

Discovery Day - Daytona Beach

As generative AI tools like ChatGPT become more common in higher education, writing instructors face the challenge of guiding students toward effective and ethical use, particularly in asynchronous environments where immediate feedback is limited. This presentation reports on an exploratory study that addresses this challenge by shifting attention from AI’s outputs to students’ moment-by-moment writing processes. Grounded in applied linguistics approaches to writing research and process-tracing methods, the project employed case studies with both expert and novice users of GenAI. Expert participants, including academics and industry professionals, completed writing tasks while integrating AI into their workflows. Their sessions were recorded …

Go to article

Small Uas Detection: Threat Intelligence & Risk Management Project, Tyler Johnson Aug 2026

Small Uas Detection: Threat Intelligence & Risk Management Project, Tyler Johnson

Discovery Day - Daytona Beach

The TRANSPORTATION SECURITY ADMINISTRATION / FEDERAL AIR MARSHAL SUAS DETECTION: THREAT INTELLIGENCE & RISK MANAGEMENT PROJECT addresses the emerging safety and security challenges posed by the rapid growth of small Unmanned Aircraft Systems (sUAS) in complex airspace environments. This study analyzed 92 days of sensor-captured Remote Identification (RID) data collected near Fort Lauderdale-Hollywood International Airport (FLL) to assess operational behaviors, aviation risk, and ground risk associated with drone activity. The primary objective of this research is to identify patterns of unauthorized or hazardous sUAS operations to enhance situational awareness and inform actionable risk-mitigation strategies. The analysis identified 335 flights from …

Go to article

How Ai Influences The Design Process Of Unmanned Underwater Vehicles’ (Uuvs) 3d Sonar System, Eden Tsouklaris, Abriella Smith, Brianna Broderick, Carissa Aumack, Victoria Cornaro Aug 2026

How Ai Influences The Design Process Of Unmanned Underwater Vehicles’ (Uuvs) 3d Sonar System, Eden Tsouklaris, Abriella Smith, Brianna Broderick, Carissa Aumack, Victoria Cornaro

Discovery Day - Daytona Beach

With the exponential growth of Artificial Intelligence (AI), user interface (UI) designers have explored using AI to shorten design time. This study assessed the effectiveness of UIs designed with AI programs versus manual methods for an Unmanned Underwater Vehicle (UUV) control system. Participants were tasked with designing an interface that would allow submarine operators to monitor and coordinate three UUVs repairing a severed underwater communication cable at a depth of 2,000 meters. The scenario presented several operational challenges (zero visibility, sonar-only perception, data latency, and potential system degradation), requiring participants' designs to maintain spatial awareness and support remote repair tasks. …

Go to article

High Tempo Air Operations, Joseph Lipson, Brennan Flanagan, Trevor Sterbens, Brandon Godfrey, Jeremiah Sepich Aug 2026

High Tempo Air Operations, Joseph Lipson, Brennan Flanagan, Trevor Sterbens, Brandon Godfrey, Jeremiah Sepich

Discovery Day - Daytona Beach

Aircraft carrier flight decks are one of the most dangerous work environments in the world, where dozens of aircraft must be moved, fueled, and armed within strict time limits. Currently, Flight Deck Handling Officers track aircraft positions using a physical board with wooden pucks that can be knocked out of place or become outdated during fast-moving operations. This study looks at whether using AI tools helps people design a better digital version of this tracking system. Participants with little design experience were randomly selected and then randomly assigned to one of two groups — one that could use AI tools …

Go to article

Humans Vs. Ai: Comparing Approaches To Disaster Response Interface Design, Kelly Nguyen, Olivia Hartmann, Kailey Hrbek, Madeline Nees, Gabrielle Roth, Emily Silliman Aug 2026

Humans Vs. Ai: Comparing Approaches To Disaster Response Interface Design, Kelly Nguyen, Olivia Hartmann, Kailey Hrbek, Madeline Nees, Gabrielle Roth, Emily Silliman

Discovery Day - Daytona Beach

Amphibious emergency support operations involve rapidly changing information, high stress, and significant cognitive demands, which can make decision-making and situation awareness more difficult for operators. When interfaces are poorly designed, they can contribute to issues such as alarm flooding, confusion from incomplete information, and delayed responses, all of which increase operational risk during time-critical disaster situations. This study explores whether using generative AI to assist with interface design will improve performance (output quality and effort) and usability compared to a manual sketch mock-up. Participants were asked to design a dashboard interface to support disaster relief operations following a Category 5 …

Go to article

Evaluating The Impact Of Ai-Assisted Tools On Novice Interface Design For Combat Search And Rescue Operations, Louis Pandolfo, Kaylee H. Akerlund, Cassidi Ellison, Sierra Martinez Aug 2026

Evaluating The Impact Of Ai-Assisted Tools On Novice Interface Design For Combat Search And Rescue Operations, Louis Pandolfo, Kaylee H. Akerlund, Cassidi Ellison, Sierra Martinez

Discovery Day - Daytona Beach

Combat Search and Rescue (CSAR) operations are specialized military missions with the goal of rescuing personnel from hostile territory, often involving helicopters and elite teams tasked with locating and stabilizing survivors. It is imperative to a mission's success that any interface used by rescuers is efficient and usable, as they work under high risk, high stress, and time limited conditions. This study examined how access to artificial intelligence (AI) design tools influence novice interface design under a time constraint. Participants completed an interface design exercise based on a simulated U.S. Navy maritime disaster and CSAR mission. The overall aim of …

Go to article

Myoelectric Transradial Prosthesis Motor Control With Temporal Convolutional Neural Network Signal Processing, Carolyn Ascha Richardson, Katherine Clark, Francis Genco, Hope Lea, Tobiah Rosser Aug 2026

Myoelectric Transradial Prosthesis Motor Control With Temporal Convolutional Neural Network Signal Processing, Carolyn Ascha Richardson, Katherine Clark, Francis Genco, Hope Lea, Tobiah Rosser

Discovery Day - Daytona Beach

Transradial (below-the-elbow) amputees account for more than half of all upper limb amputations. Myoelectric prosthetic arms, which use electromyography (EMG) sensors on the surface of the forearm to convert electrical signals from residual limb muscles and mimic hand movement, are popular options for these amputees. However, these prostheses are limited in residual muscle detection and movement accuracy. The objective of this project is to affordably manufacture an externally-powered transradial prosthesis prototype through EMG time-versus-voltage readings collected with six Delsys Trigno Avanti and eight Thalmic MYO EMG sensor channels placed along the extensor digitorum, extensor carpi radialis, extensor carpi ulnaris, flexor …

Go to article

From Code To Cube: Interactive Fluid Simulation With Real Time Motion Control, Dominic Ziccardi, Carter Groezinger Aug 2026

From Code To Cube: Interactive Fluid Simulation With Real Time Motion Control, Dominic Ziccardi, Carter Groezinger

Discovery Day - Daytona Beach

This research project explores the use of FluidX3D, an open-source lattice Boltzmann method (LBM) solver, to simulate fluid behavior within a three-dimensional cube container. The system supports both standard water models and rheoscopic fluid visualization, allowing detailed observation of complex flow dynamics in real time. The simulation accurately represents fluid motion, gravity-driven behavior, and rotational response within a bounded cubic domain. The longterm objective is to extend this digital simulation into a physical installation consisting of six synchronized square displays arranged to form a cube. This configuration will create a volumetric illusion of fluid occupying a tangible, handheld structure. An …

Go to article

Navigating Enhanced Exploration Assistance (Nexa), Azhari Abbas, Caleb Fakunle, Ryan Powell, Donovan Livingston Aug 2026

Navigating Enhanced Exploration Assistance (Nexa), Azhari Abbas, Caleb Fakunle, Ryan Powell, Donovan Livingston

Discovery Day - Daytona Beach

NEXA is an artificial intelligence software platform developed to enhance residential security and property monitoring through seamless integration with autonomous drone systems. This research application of advanced AI in surveillance aims to create a standalone solution capable of real-time threat detection and intelligent alert management. By processing visual and sensory data, NEXA facilitates autonomous drone operation with minimal human intervention. Secure communication channels ensure that instant alerts are delivered to property owners and, potentially, law enforcement, improving response times in security incidents, search-and-rescue operations, and perimeter surveillance. Additionally, NEXA is capable of interfacing with commercially available drone platforms and presents …

Go to article

An Evaluation Of Machine Learning Models' Efficacy In Determining Uav Spoofing Attacks, Nicolas Machado, Jaxon Selzer Aug 2026

An Evaluation Of Machine Learning Models' Efficacy In Determining Uav Spoofing Attacks, Nicolas Machado, Jaxon Selzer

Discovery Day - Daytona Beach

An Evaluation of Machine Learning Models' Efficacy in Determining UAV Spoofing Attacks - The rapid integration of Unmanned Aerial Vehicles (UAVs) into urban airspace has introduced significant cybersecurity concerns, particularly due to vulnerabilities in Automatic Dependent Surveillance–Broadcast (ADS-B), which lacks authentication and encryption. This project addresses the problem of detecting spoofing and data manipulation attacks that can compromise UAV safety and mission reliability. The objective of this work is to evaluate the effectiveness of machine learning–based anomaly detection, specifically Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks, as protocol-agnostic solutions for identifying anomalous UAV behavior. To achieve this, …

Go to article

Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk Aug 2026

Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk

Discovery Day - Daytona Beach

HELIO: Heliophysics Enhanced Learning for Intelligent Orbits   Satellite constellations operating in near-Earth space are increasingly vulnerable to space weather disturbances, such as solar flares, coronal mass ejections (CMEs), and high-speed solar wind streams, which degrade communications, destabilize attitude control, and accelerate orbital decay. These disturbances directly threaten mission continuity, constellation availability, and space asset survivability. Current protective approaches rely primarily on ground-based alerts and lack integration with broader space domain awareness, which results in programmed reactive protocols that are often initiated too late to prevent performance degradation and asset loss. The HELIO project addresses this gap by turning space-weather forecasts …

Go to article

Interplanetary Trajectory Optimization With Reinforcement Learning, Shiloh Cuffe Aug 2026

Interplanetary Trajectory Optimization With Reinforcement Learning, Shiloh Cuffe

Discovery Day - Daytona Beach

This project investigates the application of reinforcement learning (RL) to optimize low-thrust interplanetary trajectory design, focusing on the Earth-Venus transfer leg of the BepiColombo mission. Traditional trajectory optimization methods, such as patched conics and genetic algorithms, often require simplifying assumptions or complex optimization schemes. This work formulates the trajectory design problem as an optimal control problem (OCP) within a Markov Decision Process (MDP) framework, enabling an RL agent to learn efficient transfer strategies under realistic spacecraft constraints. The objective is to develop an autonomous guidance approach capable of replicating or improving upon established mission designs. The spacecraft is modeled as …

Go to article

Generalized Cloud-Based Compressible Aerodynamics Calculator And Simulation Web App, Massimo Mansueto, Liam Griesacker, Andres Torres-Figueroa Aug 2026

Generalized Cloud-Based Compressible Aerodynamics Calculator And Simulation Web App, Massimo Mansueto, Liam Griesacker, Andres Torres-Figueroa

Discovery Day - Daytona Beach

The Generalized Cloud-Based Compressible Aerodynamics Calculator and Simulation Web App focuses on the development of a tool to support the analysis, visualization, and teaching of compressible aerodynamics. In the case of most undergraduate aerospace engineering courses, students rely on static equations, charts, and manual calculations, which can make it difficult to conceptualize complex flow phenomena such as shock waves, expansion fans, and nozzle flow. The purpose of this project is to create an accessible platform that integrates a compressible flow calculator, nozzle sizing tool, and interactive simulations into a single educational resource. The application is implemented using modern web development …

Go to article

Feasibility Of High-Throughput Onboard Ai For Mars Rovers Under Solar Constraints, Aashman Gupta Aug 2026

Feasibility Of High-Throughput Onboard Ai For Mars Rovers Under Solar Constraints, Aashman Gupta

Discovery Day - Daytona Beach

This project evaluates the feasibility of sustained onboard AI autonomy for a solar-powered Mars rover by directly linking solar energy availability to achievable compute performance. While Mars solar irradiance and edge computing performance have been studied independently, no unified framework currently couples surface power generation to autonomy throughput in an experimentally validated manner. The project will begin with a simulation of solar power generation for a 1 m² rover-mounted array across a Martian sol, accounting for seasonal variation, dust opacity, and array configuration (fixed versus sun-tracking). The resulting power profile will then be coupled to representative compute platforms running autonomy …

Go to article

An Energy-Aware Meta-Learning Framework For Real-Time Lunar Rover Localization Via Adaptive Algorithm Selection, Jose Demedeiros, Garrett Seyler Aug 2026

An Energy-Aware Meta-Learning Framework For Real-Time Lunar Rover Localization Via Adaptive Algorithm Selection, Jose Demedeiros, Garrett Seyler

Discovery Day - Daytona Beach

This work proposes an energy-aware meta-learning framework that selects the single most suitable localization algorithm for a lunar rover, per scene, using only monocular imagery and orbital maps. The goal is to achieve sub-meter accuracy while minimizing onboard compute and energy consumption. We assemble a suite of seven lunar-relevant algorithms spanning relative and absolute localization, including monocular ORB-SLAM3, LuVo homography-based visual odometry, Censible cross-view matching with orbital imagery, crater-based methods (LunarNav and ShadowNav), monocular horizon navigation with a DEM, and DROID-SLAM. Relative methods provide incremental motion updates, while absolute methods deliver global pose fixes; an Extended Kalman Filter fuses these …

Go to article

A Qualitative Analysis Of Human-Ai Interaction Through Animated Shapes, Kavya Dipen Shah, Angel Hinojosa, Caroline Deck Aug 2026

A Qualitative Analysis Of Human-Ai Interaction Through Animated Shapes, Kavya Dipen Shah, Angel Hinojosa, Caroline Deck

Discovery Day - Daytona Beach

As technology becomes more advanced, it is important to understand how people perceive the intentions and abilities of machines. This project, conducted in the InTeRACT Lab, explores how we attribute humanlike qualities to different types of agents, ranging from animals to robots. The study analyzes data from an experiment where participants watched animations of moving triangles. Although the videos were identical, participants were told the shapes represented either humans, robots, dogs, or inanimate objects. While previous math-based data showed that these labels changed how people felt, those structured scales didn't allow for a natural, unbiased explanation of what people actually …

Go to article

A System Safety Approach To Assuring Artificial Intelligence Enabled Functions In Civil Aviation, Evan Bear, Quinn Galen Aug 2026

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 …

Go to article

A Hybrid Llm-Srgm Framework For Ai-Enabled Reliability Assessment In Safety-Critical Software Systems, Caleb Stone, Shrenik Jadhav Aug 2026

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 …

Go to article

Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson Aug 2026

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 …

Go to article

Social Attributions Of Moving Shapes: Comparing Qualitative Analyses Of Humans Vs. Ai, Angel Hinojosa Aug 2026

Social Attributions Of Moving Shapes: Comparing Qualitative Analyses Of Humans Vs. Ai, Angel Hinojosa

Discovery Day - Daytona Beach

As technology becomes more intelligent, the relationship between humans and machines is rapidly shifting. Whether a machine is perceived as a capable partner or a source of wariness often depends on the intentions and abilities, we attribute to it. My research in the InTeRACT Lab seeks to empirically assess these perceptions by comparing how we view different nonhuman agents, ranging from animals to robots.   This study analyzes qualitative data from a task where participants viewed animations of moving triangles. While the videos remained the same, participants were told the shapes represented either humans, robots, dogs, or inanimate shapes. Previous quantitative …

Go to article

A Survey On Machine Learning Applications For Operating System Fingerprinting, Siri Siqveland Aug 2026

A Survey On Machine Learning Applications For Operating System Fingerprinting, Siri Siqveland

Discovery Day - Daytona Beach

In the modern age of computers and interconnected networks, cybersecurity and cyber-attackers are evolving in tandem to exploit each other’s vulnerabilities. One technique used by both parties is Operating System Fingerprinting (OSF): with the knowledge of what Operating System a target system is running, innate vulnerabilities can be identified and patched or exploited. Historically, OSF utilizes two main methods: passive and active—the former trades accuracy with undetectability while the latter is generally more detectable but more accurate. However, recent work has combined OSF with Machine Learning (ML) to improve accurate identification. The work presented here is a survey for the …

Go to article

Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods Aug 2026

Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods

Discovery Day - Daytona Beach

Phaëthon System is the project name for the Search and Rescue Drone Initiative. This initiative will improve the current search and rescue drone industry by introducing new techniques to get through dense forest canopies and other places where an overhead view is not useful. The Phaëthon System uses a swarm of drones that can penetrate under the tree canopy to map and search with the utmost efficiency and safety for rescuers. A command drone is launched to survey the overall search area, and set up a communications and data link. The next component is then released, which is a swarm …

Go to article

Stress-Triggered Automation Reliance, Jazmin Elek Aug 2026

Stress-Triggered Automation Reliance, Jazmin Elek

Discovery Day - Daytona Beach

Automation is widely used in complex systems and includes any process that replaces human motor, sensory, or cognitive functions with machines or computers (Norman, 1996). As automation becomes more common, understanding how humans trust and interact with these systems is critical. Trust can be measured by whether users override automation or blindly follow its prompts (Norman, 1996).   Artificial intelligence (AI) introduces additional complexity by enabling systems to learn patterns from data it generates. AI performs tasks with the ability to learn from experience (NASA, 2024). AI builds internal databases that can mimic human-like responses (Norman, 1996). However, AI systems can …

Go to article

Modeling Doppler-Shifted Solar Spectra From Simulated Asteroidal Dust Populations Using Orbital Evolution Codes, Skylar G. Butler, Jarrett Dieterle Aug 2026

Modeling Doppler-Shifted Solar Spectra From Simulated Asteroidal Dust Populations Using Orbital Evolution Codes, Skylar G. Butler, Jarrett Dieterle

Discovery Day - Daytona Beach

We investigate how orbital properties of interplanetary dust particles produce Doppler-shifted solar absorption lines using synthetic spectra generated from particle outputs of a numerical orbital evolution code. The code is based on the Ipatov dynamical model, written in Fortran and using the SWIFT integration package to track the evolution of dust particles originating from asteroid and comet populations. The program reads input files containing particle orbital elements and heliocentric positions, along with planetary parameters and integration settings, and computes the time evolution of particle trajectories under gravitational perturbations. The resulting particle states are then used to generate synthetic spectra by …

Go to article

Dcat - Distributed Computing And Analysis Tool, Asher Zwickel, Jacob Burdge Aug 2026

Dcat - Distributed Computing And Analysis Tool, Asher Zwickel, Jacob Burdge

Discovery Day - Daytona Beach

This project uses distributed computing to process and analyze large datasets related to cyber breaches and attacks. Its main goal is to find patterns between initial cyber incidents and what happens next. It looks at whether responses tend to escalate, calm down, or stay about the same over time. Understanding this helps explain how digital conflicts develop and whether they follow predictable paths. The project was built as part of university research and runs on custom software across a cluster of 17 Chromebooks. While the system can study many topics, it is currently focused on cyber activity. The software uses …

Go to article

First Prev Next Last