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Articles 8521 - 8550 of 291657

Full-Text Articles in Physical Sciences and Mathematics

Uc-0250 Tortured Artist, Caitlin Tigani, Ben Scholl, Anaiya Tucker, Adam Tucker Nov 2025

Uc-0250 Tortured Artist, Caitlin Tigani, Ben Scholl, Anaiya Tucker, Adam Tucker

C-Day Computing Showcase

You are a photographer that wants to move, so you take pictures of your house to give to your real- estate agent. However, as you are developing the photos you hear a noise that makes you turn on the lights, ruining your photos. Now you must retake the photos before morning, but something around the house has changed. Rooms are no longer in the right place, items are moved around, doors are locked, and an entity is watching you. Will you find the secrets within the puzzles or be left tortured?

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Uc-0224 Loving Arms: Website Audit & Redesign, Marcus Harrison, Chris Stropoli, Katherine Gibson, Vaughn Berger, Jesus Flores Valdez Nov 2025

Uc-0224 Loving Arms: Website Audit & Redesign, Marcus Harrison, Chris Stropoli, Katherine Gibson, Vaughn Berger, Jesus Flores Valdez

C-Day Computing Showcase

Our team’s project aims to enhance the Loving Arms Cancer Outreach website, making it more accessible and user-friendly for all visitors. Loving Arms is a nonprofit supporting individuals and families affected by cancer, and their website plays a key role in sharing information, connecting people to support programs, and reaching those in need. To achieve this, we first audited the current site to identify areas of confusion or outdated content, and we are currently in the process of providing a redesigned website. These updates are intended to improve the visitor experience while giving staff a reliable, easy-to-use platform that better …

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Uc-1149 Ai Systems For A Stealth Videogame​, Lukas Ehler, Evan Weir, Javier Corona Nov 2025

Uc-1149 Ai Systems For A Stealth Videogame​, Lukas Ehler, Evan Weir, Javier Corona

C-Day Computing Showcase

Shmovement Games 3/5 has been making progress towards creating a videogame that leverages multiple types of AI systems working in unison with one-another. This will be a game in which the player sneaks around enemies while trying to grab objects marked as the player's primary objective. This is a project for our CGDD 4242 AI class in which we are implementing a single agent, multi-agent, and advanced multi-agent system into one game.

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Uc-1166 Southern Bathtub Race: A Video Game Revival, Caroline Roberson, Jes Crouch, Treonna Gardner, Jose Landaverde, Jake Lashley Nov 2025

Uc-1166 Southern Bathtub Race: A Video Game Revival, Caroline Roberson, Jes Crouch, Treonna Gardner, Jose Landaverde, Jake Lashley

C-Day Computing Showcase

Southern Bathtub Race is a video game commemorating the annual SPSU Bathtub Races held from 1968 - 1991. The player controls a bathtub racer from a 1st-person perspective as they compete against the computer to navigate a racetrack modeled after the SPSU campus of 1991. The environmental assets and textures were created with traditional acrylic painting. The game is intended to replicate the races and student spirit on the SPSU campus for both SPSU alumni and KSU students.

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Uc-1175 Admissions Assistant - Ai Chatbot, Chelsea Oduro, Jeffery Bond, Tanner Morgan, Allen Scott, Joy Parks Nov 2025

Uc-1175 Admissions Assistant - Ai Chatbot, Chelsea Oduro, Jeffery Bond, Tanner Morgan, Allen Scott, Joy Parks

C-Day Computing Showcase

The Kennesaw State University (KSU) Graduate Admissions website contains extensive information on programs, application processes, deadlines, and eligibility requirements. However, its dense structure can make it difficult for prospective students to quickly locate specific details. This often leads to repeated inquiries from admissions staff, increasing their workload and delaying responses to more complex applicant needs. This project addresses those challenges by introducing a chatbot capable of retrieving and presenting the website information in a more intuitive, conversational format, improving user satisfaction and reducing workflow overhead for admissions staff.

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Uc-1232 Stronghold, Caitlin Tigani, Adam Tucker, Camden Lloyd, Dale Balsor Nov 2025

Uc-1232 Stronghold, Caitlin Tigani, Adam Tucker, Camden Lloyd, Dale Balsor

C-Day Computing Showcase

Our goal for this game is to create a game using both a single agent and multi agent AIs. In our game you can either play against the current AI or train the AI up as it fights against another AI. The training will use genetic AI. So whichever AI wins that row will be the one that move on. The loser will have their weights adjusted. This means the more that you train the Stronghold AI the harder the AI will be to fight against. The final game mode available is being able to play against another.

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Uc-1234 Fundoria, Connor Stabler, Dameon Jones, Rafay Hassan, Michael Liu, Brenden Horne Nov 2025

Uc-1234 Fundoria, Connor Stabler, Dameon Jones, Rafay Hassan, Michael Liu, Brenden Horne

C-Day Computing Showcase

Fundoria is an educational technology project designed to transform financial literacy and career readiness for elementary and middle-grade students. The platform combines interactive gameplay, AI-driven personalized learning, and real-world job simulations to teach essential financial concepts in an engaging, age-appropriate way. Students explore budgeting, saving, banking, and career skills through guided missions that adapt to their learning styles. Fundoria also provides teachers and schools with standards-aligned activities, classroom resources, and assessment tools that connect academic content to practical, everyday decisions. By blending gamification with evidence-based instruction, Fundoria empowers students to build confidence, develop responsible financial habits, and prepare for future …

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Uc-1240 Project Ibis, Isaac Alderman, Braden Mizell, Collin Sutton Nov 2025

Uc-1240 Project Ibis, Isaac Alderman, Braden Mizell, Collin Sutton

C-Day Computing Showcase

Project Ibis (working title) is a first person, narrative heavy, puzzle-lite RPG that follows the story of a renaissance era plague doctor and their attempt to alter the minds of three subjects; a gardener, a street urchin, and a priest. The game’s narrative is set in historically accurate 1637 Florence, Italy, in the wake of the Great Plague of Milan, and draws heavily from renaissance culture. Each subject being treated is a complex person with personal conflicts and issues; our focus is on tackling mental and emotional health through empathy and nuance rather than diagnosis. Different aspects of each subject’s …

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Uc-1257 Integrating A Pressure Profiling Dock Into An Open-Source Digital Art Framework, Luke Miller, Noah Enyart, Jonah Smith, Jaeden Jones Nov 2025

Uc-1257 Integrating A Pressure Profiling Dock Into An Open-Source Digital Art Framework, Luke Miller, Noah Enyart, Jonah Smith, Jaeden Jones

C-Day Computing Showcase

The effectiveness and expressiveness of digital drawing are heavily dependent on an artist’s control over their medium; pen pressure dynamics, which enables fine-tuned variation in line weight and opacity. While the use of this tool improves an artist's control, the open-source editor GIMP currently offers only limited means to visualize or adjust these pressure behaviors in real time. GIMP does support pressure-based input, however, it lacks a dedicated interface for configuring a personalized pressure profile, creating a barrier for users seeking precision comparable to commercial tools. This project addresses that gap by designing and implementing a Stylus Pressure Profiling Dock …

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Uc-1260 Digital Micromouse Maze Simulation, Chase Bell Nov 2025

Uc-1260 Digital Micromouse Maze Simulation, Chase Bell

C-Day Computing Showcase

We construct a digital simulation of the Micromouse competition and analyze popular algorithms for searching (A*, Dijkstra’s, and Flood-fill). From our analyses, we design an algorithm with the goal of achieving the shortest possible run time to the end of the maze.

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Uc-1262 Georgia Watch - Georgia Hospital Accountability Score, Robert Straiton, Patrick Cox, Constant Nortey, Sankalp Amaravadi, Kahmin Keller Nov 2025

Uc-1262 Georgia Watch - Georgia Hospital Accountability Score, Robert Straiton, Patrick Cox, Constant Nortey, Sankalp Amaravadi, Kahmin Keller

C-Day Computing Showcase

Georgia Watch and the members of this team have partnered to change how Georgia residents understand their healthcare by providing a source of objective metrics which affect their care. This project represents the quintessential React Project produced with the purpose of a reactive interface for the end user, built for maintainability for any subsequent developers. The hospital data is maintained in JSON format for its ease of parsing and adjustment pending any changes. The interactive map was developed through the MAPBOX library, and the team is maintaining a deployment via an independent repository with necessary control over the website.

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Uc-1268 Falling Debris, Julian Duarte, Adam Martin, Rylan Collins, Hugh Haggard, Chance Boecker Nov 2025

Uc-1268 Falling Debris, Julian Duarte, Adam Martin, Rylan Collins, Hugh Haggard, Chance Boecker

C-Day Computing Showcase

Falling Debris is a student-developed party 2D platformer game in which players have to survive falling blocks by grappling upward to outlive the others. The game is played in rounds, and between them, players can purchase items to improve their odds of survival.

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Uc-1269 Website Makeover - Loving Arms Cancer Outreach, Yuliana Pacheco, Alicia Cook, Taylor Tompkins, Schuyler Bridges, Dalton Roberts Nov 2025

Uc-1269 Website Makeover - Loving Arms Cancer Outreach, Yuliana Pacheco, Alicia Cook, Taylor Tompkins, Schuyler Bridges, Dalton Roberts

C-Day Computing Showcase

Loving Arms Cancer Outreach (LACO) provides financial, emotional, and community support to individuals affected by cancer, making an accessible and reliable website essential to its mission. Our team conducted a quality assurance audit using tools such as Google Lighthouse and axe DevTools, identifying issues with accessibility, navigation, readability, and mobile responsiveness. Using these findings, we redesigned key sections of the site, improved layouts and forms, and recommended updated plugins to enhance usability and long-term performance. We also developed a Website Architecture and Maintenance Guide to support sustainability. This project establishes the foundation for a modern, user-friendly website that strengthens LACO’s …

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Uc-1274 Cloud-Native Ci/Cd Pipeline, Enitan Meduteni, Rami Elmostafa, Matt Crowley, Kade Fleming, Cecily Graffree Nov 2025

Uc-1274 Cloud-Native Ci/Cd Pipeline, Enitan Meduteni, Rami Elmostafa, Matt Crowley, Kade Fleming, Cecily Graffree

C-Day Computing Showcase

This project documents a 12-week capstone implementing a cloud-native CI/CD pipeline using industry-standard DevOps tools. The system integrates Jenkins for continuous integration, Kubernetes for container orchestration, GitOps (ArgoCD) for automated deployments, DevSecOps practices including RBAC and vulnerability scanning, and comprehensive monitoring using Prometheus and Grafana. Mentored by Sudheer Amgothu, Principal Cloud Operations Engineer.

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Gc-0241 Using Dog Breed Classification Uncertainty Estimation To Inform Mixed Breed Ancestry​, Brandon Mackey, Maryam Koya, Theodore King, Scott Hutchison Nov 2025

Gc-0241 Using Dog Breed Classification Uncertainty Estimation To Inform Mixed Breed Ancestry​, Brandon Mackey, Maryam Koya, Theodore King, Scott Hutchison

C-Day Computing Showcase

This study investigates whether Monte Carlo uncertainty estimation and probability distributions can be used to identify ancestral composition of mixed-breed dogs. A dataset containing images of purebred dogs was used to train a Monte Carlo Dropout model. The trained model will next be tested on images of mixed breed dogs. Our hypothesis is that the model can be used to provide informative probability distribution for breed ancestry classification, offering a potentially valuable tool for analyzing the genetics of dogs.

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Gc-1144 Meetless: The Operating System For Business In The Ai Age, An Pham Nov 2025

Gc-1144 Meetless: The Operating System For Business In The Ai Age, An Pham

C-Day Computing Showcase

Meetless functions as an OS for modern organizations: a secure, multi-agent runtime that turns scattered inputs (docs, emails, tickets, chats) into asynchronous, outcome-driven discussions with decisions, owners, and due dates—so teams ship without meetings. System architecture (OS metaphor).- Kernel (Orchestrator): schedules “processes” across specialized agents using routing policies, guardrails, and retry semantics. - Process I/O: unified connectors for Google/Microsoft suites, Slack, Jira/Linear, and web sources, normalized into a document graph with vector embeddings. - Memory & FS: temporal knowledge graph (Neo4j) + document store (PostgreSQL) + vector index (Weaviate) with time-aware retrieval. - Syscalls/APIs: /discussions.create, /decisions.propose, /actions.sync, /summaries.latest; all idempotent …

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Gc-1147 Enhancing Mass Casualty Triage Training Through Human–Ai Collaboration In Virtual Reality (Vr), Rishi Kiran Aiyatham Prabakar Nov 2025

Gc-1147 Enhancing Mass Casualty Triage Training Through Human–Ai Collaboration In Virtual Reality (Vr), Rishi Kiran Aiyatham Prabakar

C-Day Computing Showcase

Mass casualty triage requires quick, accurate decisions under pressure. Live training is costly and time-intensive. Virtual Reality (VR) trainings approach has shown comparable learning effectiveness compared to live trainings, motivating the use of VR simulations. This study explores how collaboration with an AI robot partner can enhance the triage training effectiveness. The Findings will contribute in understanding how human-AI collaboration enhances trainings.

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Gc-1162 Present Panic Game, Adetunji Adegeye, Kendrick Bryant, Catherine Ayeronwi Nov 2025

Gc-1162 Present Panic Game, Adetunji Adegeye, Kendrick Bryant, Catherine Ayeronwi

C-Day Computing Showcase

Present Panic is a festive top-down 2D arcade game where players control an elf inside Santa’s workshop and must collect presents while avoiding Christmas-themed enemies. During Sprint 2 in our SWE class, our team transitioned from a functional prototype to a fully developed Beta, expanding assets, implementing UI systems, building levels, and integrating polished game mechanics following the MDA framework. We developed new artwork, sound effects, animations, and user interface elements including a main menu, HUD, pause menu, and scene transitions. A survey and both manual and automated testing were prepared to gather user feedback. This Beta version forms the …

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Grm-0216 Towards Analyzing The Bridge Dataset With Quantum Machine Learning, Gayathri Kolavennu Nov 2025

Grm-0216 Towards Analyzing The Bridge Dataset With Quantum Machine Learning, Gayathri Kolavennu

C-Day Computing Showcase

This research presents a comparative evaluation of classical and quantum machine learning models applied to the Bridge dataset. Classical algorithms like Support Vector Machine, Random Forest, and Neural Networks are benchmarked against Quantum SVM, Quantum Random Forest, and Quantum Neural Networks using identical preprocessing and training conditions. Results indicate a consistent quantum advantage, with quantum models achieving higher accuracy, stronger nonlinear feature separation, and improved minority-class detection. QSVM and QNN exhibit the most significant performance gains. Although quantum models require greater computational resources, the findings underscore the emerging effectiveness of quantum-enhanced learning for structural classification tasks in the NISQ era.

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Grm-1145 Autumn Lite Llm, Michael Knighten Nov 2025

Grm-1145 Autumn Lite Llm, Michael Knighten

C-Day Computing Showcase

Autumn Lite is an inspectable, small-footprint language modeling pipeline for reproducible experimentation and practical integration into video-game non-player character (NPC) systems. It comprises four components: (1) a regex-aware tokenizer/normalizer for vocabulary construction and mixed prose–code handling; (2) a classical evaluation track that reports perplexity to quantify predictive quality; (3) a compact neural language model (decoder-only Transformer) targeted at low latency and controllable outputs; and (4) a lightweight sentiment classifier (logistic regression) that assigns positive/neutral/negative tags to steer text-to-speech (TTS) prosody during NPC dialogue. By combining transparent preprocessing with baseline metrics and a small, deployable decoder, Autumn Lite aims to deliver …

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Grm-1245 A Synthetic Data Engine For Explainable Injection-Area Perception, Yukang Shen Nov 2025

Grm-1245 A Synthetic Data Engine For Explainable Injection-Area Perception, Yukang Shen

C-Day Computing Showcase

Vision-Language-Action (VLA) systems are beginning to support everyday clinical workflows. Deltoid intramuscular injection is a representative task, but progress is limited by data scarcity, privacy constraints, and the cost of expert annotation. Recent text-to-image (T2I) models make large-scale data synthesis possible, yet ensuring anatomical correctness, diversity, and label quality remains difficult. To address this gap, we propose a Synthetic Data Engine tailored for medical perception, integrating cold-start filtering, controlled T2I generation, CLIP-based quality checks, and iterative segmentation training. We further introduce an anthropometry-grounded formulation of injection safety that produces interpretable safe-zone guidance. Experiments show that synthetic data can effectively bootstrap …

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Grm-1252 How Humans Perceive Mobile Robots: Anxiety, Environment, And Behavior Analysis, Rohan Jonnalagadda, Reed Tumlin, Roderick Powell Nov 2025

Grm-1252 How Humans Perceive Mobile Robots: Anxiety, Environment, And Behavior Analysis, Rohan Jonnalagadda, Reed Tumlin, Roderick Powell

C-Day Computing Showcase

We conducted 6,400 physics-based simulations to examine how environmental and behavioral factors shape human anxiety during interactions with mobile robots. The model incorporated robot behavior, environmental density, visibility, indoor/outdoor settings, and human age. Anxiety was driven primarily by context: levels were highest indoors, during daytime, and in sparse environments, while nighttime and outdoor interactions consistently reduced anxiety. Robot behavior produced smaller effects, with erratic and non-avoidance strategies yielding slightly higher responses. Older adults showed marginally greater anxiety across all conditions. These findings suggest that environmental design and deployment context matter more than avoidance strategy, offering guidance for improving the safety …

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Grm-20169 Proxy Recognition And Inclusive Scoring Method (Prism): Evaluating Context-Dependent Bias In Large Language Models For Resume Screening, Crystal Tubbs, Destiny Raburnel Nov 2025

Grm-20169 Proxy Recognition And Inclusive Scoring Method (Prism): Evaluating Context-Dependent Bias In Large Language Models For Resume Screening, Crystal Tubbs, Destiny Raburnel

C-Day Computing Showcase

AI-driven hiring tools are reshaping recruitment but often mirror biases in their training data. PRISM examines how large language models express or reduce demographic bias during resume evaluation and how linguistic context within prompts shapes these outcomes. Using a controlled dataset of 324 synthetic resumes with racially neutral surnames, differing only by first name as the demographic proxy, we compared GPT 3.5 turbo with a Sentence BERT similarity model. Under neutral prompts, no stable bias was observed across demographic groups, yet contextual shifts in the prompt changed how the model responded to proxy cues. These findings show that LLM bias …

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Grm-20188 Intelligent Book Recommendation And Rating Prediction System, Destiny Raburnel Nov 2025

Grm-20188 Intelligent Book Recommendation And Rating Prediction System, Destiny Raburnel

C-Day Computing Showcase

When selecting a book, readers often rely on surface level information such as the title, author, synopsis, and keywords to determine whether a story matches their interests. These features contain important cues related to genre, tone, and narrative elements that help set expectations before reading. The Intelligent Book Recommendation and Rating Prediction System works to automate this process by using natural language processing and machine learning techniques. It takes in readers’ personalized reading data such as book titles, author, subjects, synopsis, and personal ratings to learn semantic patterns using TF-IDF vectorization. A supervised Linear Regression model was then trained to …

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Gc-0157 Ai Graduate Admissions Assistant, Katherine Hyatt, Ginger Wright, Pablo Edgar, Oluwatosin Akinwusi, Alan Johnson Nov 2025

Gc-0157 Ai Graduate Admissions Assistant, Katherine Hyatt, Ginger Wright, Pablo Edgar, Oluwatosin Akinwusi, Alan Johnson

C-Day Computing Showcase

Project Overview: Create a "Proof of Concept" for an AI Graduate Admissions Assistant chatbot that will: • Autonomously reference KSU website information in real-time • Direct users efficiently to specific, relevant content • Reduce questions for admissions personnel • Self-update its knowledge base when website content changes •Provide accurate, instant responses to common admissions questions and allow for response correction in an admin dashboard

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Gc-0270 Oncoboost - Hydration Monitoring Application, Blossom Madubike, Aafra Alam, Damola Ojo Nov 2025

Gc-0270 Oncoboost - Hydration Monitoring Application, Blossom Madubike, Aafra Alam, Damola Ojo

C-Day Computing Showcase

Dehydration is a common and preventable complication for oncology patients, especially those undergoing chemotherapy and radiation. Side effects such as nausea, fatigue, and loss of appetite make it difficult for patients to maintain adequate fluid intake, contributing to avoidable discomfort and potential treatment disruptions. This capstone project presents Onco-Boost, a mobile hydration monitoring application designed to help adult oncology patients track daily fluid intake, recognize their intake patterns, and stay engaged in daily self-care between clinic visits. Built with React Native and Expo, and backed by Firebase for authentication and cloud data storage. Onco-Boost translates clinical hydration guidance and research …

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Gc-1146 Student Engagement Portal: Enhancing Student Success Through Milestone Tracking, Antonio Brewer, Taylor Bolinger, Tyler Dawkins, Ricartho Franck, Moises Valles Nov 2025

Gc-1146 Student Engagement Portal: Enhancing Student Success Through Milestone Tracking, Antonio Brewer, Taylor Bolinger, Tyler Dawkins, Ricartho Franck, Moises Valles

C-Day Computing Showcase

The Student Engagement Portal, also known as the Milestone Map, is a platform developed to help students within KSU’s College of Computing and Software Engineering monitor their academic and professional growth. The system enables students to log milestones, check in at events, and view progress toward personal and departmental goals. Built with a full-stack architecture using NestJS, React, and MongoDB, the portal also includes an administrative dashboard for event management and analytics. The project demonstrates how progress tracking and clear visualization of achievements can improve communication, organization, and engagement between students and the college.

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Gc-1198 Onboarding Tool For New Smartphone Users, Namita Velagapudi, Bhagya Surekha Dasari, Yaswanth Maddineni, Rohith Venkata Sai Chekka, Balachandar Pinninti Nov 2025

Gc-1198 Onboarding Tool For New Smartphone Users, Namita Velagapudi, Bhagya Surekha Dasari, Yaswanth Maddineni, Rohith Venkata Sai Chekka, Balachandar Pinninti

C-Day Computing Showcase

The Smartphone Onboarding Tool is an interactive web platform created to help seniors and new smartphone users become comfortable with mobile technology. It offers a realistic, simulated smartphone interface, guided walkthroughs, and an easy-to-use design that builds confidence in performing everyday tasks. Caregivers can monitor user progress, while learners can practice safely without affecting an actual device. The solution is developed with a React frontend, a Node.js/Express backend, and an SQLite database, all built with a strong focus on mobile-first accessibility.

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Gc-1215 Clinicalrag: A Scalable Benchmark Of Privacy, Relevance, And Speed In Semantic Retrieval For Clinical Transcriptions​ ​, Pradyumna Kumar, Sai Sruti Dandibhatla, Srinivasan Subramanian, Purna Chandu Anukula, Pranitha Athukuri Nov 2025

Gc-1215 Clinicalrag: A Scalable Benchmark Of Privacy, Relevance, And Speed In Semantic Retrieval For Clinical Transcriptions​ ​, Pradyumna Kumar, Sai Sruti Dandibhatla, Srinivasan Subramanian, Purna Chandu Anukula, Pranitha Athukuri

C-Day Computing Showcase

Traditional keyword search struggles with the scale, complexity, and contextual depth of clinical data. This project develops and evaluates semantic search systems that better understand medical language, enabling physicians and researchers to retrieve contextually relevant information through a Retrieval Augmented Generation (RAG) framework. We integrate privacy-preserving methods, including differential privacy and homomorphic encryption to protect sensitive clinical transcriptions. For improved speed and accuracy, we enhance the baseline RAG architecture with Hierarchical Navigable Small World (HNSW) indexing and Maximal Marginal Relevance (MMR) based reranking. To ensure scalability, clinical documents are ingested using PySpark and stored in a vector database optimized for …

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Gc-1233 An Ai-Powered Convolutional Neural Network System For Multi-Class Image Classification Of Rice Plant Leaf Diseases, Akshay Krishna Varma Buddharaju, Siri Yellu, Pranay Kumar Peddi Nov 2025

Gc-1233 An Ai-Powered Convolutional Neural Network System For Multi-Class Image Classification Of Rice Plant Leaf Diseases, Akshay Krishna Varma Buddharaju, Siri Yellu, Pranay Kumar Peddi

C-Day Computing Showcase

This project focuses on building an intelligent system that can automatically identify common diseases found on rice leaves by analyzing simple images. Using a deep convolutional neural network, the model learns to recognize visual patterns associated with three major diseases: Bacterial Blight, Brown Spot, and Leaf Smut. These diseases often show subtle differences in color, texture, and leaf damage, and the model is trained to distinguish them accurately. The goal of this work is to show how artificial intelligence can support modern agriculture by helping farmers detect problems early, even without expert knowledge. By processing images through careful preprocessing, augmentation, …

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