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Full-Text Articles in Computer Sciences
Ur-0248 Shell Commands Used In Cybersecurity Training, Nathan Kourk, Jacob Suda, Ming Butler, Yonnas Alemu
Ur-0248 Shell Commands Used In Cybersecurity Training, Nathan Kourk, Jacob Suda, Ming Butler, Yonnas Alemu
C-Day Computing Showcase
This project explores patterns in shell command usage during cybersecurity training programs. We will analyze syntax frequency and selection of shell commands across multiple datasets looking for patterns in user behavior. The goal of this study is to identify differences between programs, and to provide insight into the trends within the command line environment.
Ur-0247 Lyric Prediction Model, Evan Gideon, Garrett Dasher, Ulrich Batanado, Drew Claerbout, Andrew Henshaw
Ur-0247 Lyric Prediction Model, Evan Gideon, Garrett Dasher, Ulrich Batanado, Drew Claerbout, Andrew Henshaw
C-Day Computing Showcase
Word prediction plays a central role in the development and refinement of large language models, supporting applications such as search optimization, dialect identification, and conversational AI systems like Siri as AI text generation becomes increasingly widespread, the demand for precise and contextually aware predictive capabilities continues to grow. This project presents lyric prediction model designed to generate the next lyric based on preceding words, with the ability to identity line breaks and sequential structure. Ultimately, this work aims to advance lyrical text generation by enabling the model to emulate the stylistic characteristics of specific artists or musical genre.
Ur-0246 Quantum Ml For Science & Engineering, Dharani Shakthivel, Haoxian Tan, Justin Martin
Ur-0246 Quantum Ml For Science & Engineering, Dharani Shakthivel, Haoxian Tan, Justin Martin
C-Day Computing Showcase
Classical machine learning methods - including CNNs, SVMs, PCA, Logistic Regression, and Random Forests - have achieved strong performance across fields such as computer vision, malware detection, and drug discovery. However, these models face scalability limits when trained on large or high-dimensional datasets. Quantum computing introduces superposition, interference, and entanglement, enabling quantum kernels, quantum feature maps, and hybrid quantum-classical architectures that may reduce computational cost or enhance data representation. This project implements classical versions of these algorithms alongside their quantum counterparts to evaluate differences in accuracy, efficiency, and resource demands. By comparing performance across diverse scientific and engineering datasets, the …
Grp-0275 Graph Attention Network Based Downlink Channel Prediction Using In Frequency Division Duplexed Nextgen Networks, Jui Mhatre
C-Day Computing Showcase
In Frequency Division Duplex (FDD) 5G networks, downlink channel state information (CSI) must be estimated at the user equipment (UE) and fed back to the base station, a process that requires frequent CSI-RS transmission and uplink feedback, resulting in high overhead and energy consumption. This research proposes a novel base-station–centric framework that predicts the downlink channel matrix directly at the gNB, eliminating the need for continuous CSI-RS–based estimation at the UE. By leveraging uplink channel observations, geometric environment features, and learned mappings between uplink and downlink channel relationships, our model reconstructs the downlink MIMO channel with high fidelity. The system …
Grp-0217 Comparative Analysis Of Os-Level Security Vulnerabilities And Isolation Mechanisms In Hypervisors And Containers, Jiban Krisna Das
Grp-0217 Comparative Analysis Of Os-Level Security Vulnerabilities And Isolation Mechanisms In Hypervisors And Containers, Jiban Krisna Das
C-Day Computing Showcase
This project investigates the operating-system-level performance and isolation mechanism of Virtual Machines and Docker container. The experiment includes CPU/memory microbenchmarks, disk throughput tests, web-server latency measurements, multi-process scheduling stress and controlled security checks. We aim to quantify each benchmark under identical conditions. The study findings reveal that Docker consistently provides lower overhead and faster I/O due to its shared-kernel architecture, while VirtualBox maintains stronger isolation but introduces more scheduling and disk latency. The findings provide practical insights for the OS system designers to find better execution environments for security critical and performance-sensitive workloads.
Grp-0214 User-Level Gpu Right-Sizing In Hpc: A Framework For Predicting Training Runtime, Yinning Zhang, S M Tanvir Faysal Alam Chowdhoury
Grp-0214 User-Level Gpu Right-Sizing In Hpc: A Framework For Predicting Training Runtime, Yinning Zhang, S M Tanvir Faysal Alam Chowdhoury
C-Day Computing Showcase
Graphics Processing Unit (GPU) resources in High-Performance Computing (HPC) systems are frequently underutilized due to inaccurate user-provided run time estimates. This research develops a machine learning framework for predicting neural network training time from architectural features, dataset size, and other hyperparameters. This approach can be implemented on any HPC systems without requiring hardware access or runtime profiling as other preceding methods do. We sampled neural network models from the NATS-Bench benchmark and used 3 benchmark datasets to generate 400 training configurations. We used these 400 data points to build regression models and found that the best model, Gradient Boosting Regressor, …
Ur-0225 Carbonyl Detection In Ir Using Deep Learning, Dharani Shakthivel
Ur-0225 Carbonyl Detection In Ir Using Deep Learning, Dharani Shakthivel
C-Day Computing Showcase
The goal of this project is to train a Convolutional Neural Network (CNN) to recognize carbonyl groups in infrared (IR) spectra. A carbonyl group is defined by a characteristic C=O double bond, which produces a strong, easily recognizable absorption peak near 1700 cm⁻¹. To develop and evaluate the model, I am using spectra prepared through three common techniques: KBr disc, nujol mull, and liquid film. Among these, liquid-film spectra provide the cleanest signal and most closely resemble what a chemist visually relies on when identifying carbonyls. In contrast, both the KBr disc and nujol mull methods require mixing the target …
Uc-1276 Ci-Cd Pipeline Team 2, Cameron Arnold
Uc-1276 Ci-Cd Pipeline Team 2, Cameron Arnold
C-Day Computing Showcase
Our project is about creating a basic cloud-native pipeline that can build and deploy an application in a more automated way. We will also try to add some security checks and monitoring tools so that we can see how everything is working. The goal is to get hands-on experience with the process and show a working demo at the end of the semester.
Gc-0151 Smart Hr Onboarding With Microsoft 365 Team 2 Capstone Project, Annalise Gregory, Michael Colley, David Laurent, Harshita Agarwal, Nilesh Kumar
Gc-0151 Smart Hr Onboarding With Microsoft 365 Team 2 Capstone Project, Annalise Gregory, Michael Colley, David Laurent, Harshita Agarwal, Nilesh Kumar
C-Day Computing Showcase
The Smart HR Onboarding with Microsoft 365 Capstone Project aims to transform the new hire onboarding experience by leveraging Microsoft 365 tools to deliver a seamless, automated process. Using Power Automate, we streamline tasks through automated emails, reminders, and documents sharing. This ensures every step of the onboarding journey is efficient and consistent. Sharepoint and Outlook serve as the main sources of storing and sharing required tasks. Power Automate's integration with Power BI allows for real-time reporting with an interactive dashboard the provides insights into onboarding progress or areas where new hires need support. This project aims to simplify onboarding …
Gc-0251 Reproducing Extended Isolation Forests With Star-Cast, Drew Patrick, Ram Sai Sivakoti, Rohit Malik, Vardhineedi Surya Kamal, Venkata Sasidhar Reddy Palagundla
Gc-0251 Reproducing Extended Isolation Forests With Star-Cast, Drew Patrick, Ram Sai Sivakoti, Rohit Malik, Vardhineedi Surya Kamal, Venkata Sasidhar Reddy Palagundla
C-Day Computing Showcase
Fraud models routinely flag suspicious transactions but rarely explain why, which slows investigations and erodes trust. In this work we study Extended Isolation Forest (EIF) for unsupervised fraud detection and propose STAR-CAST, a lightweight framework that turns raw anomaly scores into threshold-aligned IF–THEN rule cards with explicit reliability measures. Using the public credit-card fraud dataset (284,807 transactions, 492 frauds; ~0.17% prevalence), we apply a time-aware 70/15/15 Train/Validation/Test split and fit-on-train preprocessing (Amount log1p→z; Time z; V1–V28 retained). We train IF, EIF, an EIF ensemble, a Mahalanobis baseline, and density models (HBOS, COPOD, ECOD) fully unsupervised, evaluate them as rankers first …
Gc-1154 Peer Evaluation Automation And Feedback System, Sameer Khan, Nnedi Okafor
Gc-1154 Peer Evaluation Automation And Feedback System, Sameer Khan, Nnedi Okafor
C-Day Computing Showcase
A web-based platform to streamline peer evaluations in team-based courses. Professors can securely create and manage student rosters, assign students to courses/teams, trigger email invitations, and receive structured, professor- friendly reports with both numeric and textual feedback. Optional AI features may summarize comments and flag potential concerns, depending on timeline and scope.
Grm-0237 Efficient Defense Against Adversarial Patch Attacks In Remote Sensing Using Transfer Learning, Ravi Rogannagari
Grm-0237 Efficient Defense Against Adversarial Patch Attacks In Remote Sensing Using Transfer Learning, Ravi Rogannagari
C-Day Computing Showcase
Remote sensing is the science of acquiring information about the Earth's surface using satellite-mounted imaging sensors. In the past, this data had to be interpreted manually, which was slow, tedious, and often prone to error. With the rise of deep learning, image classification models have greatly accelerated and improved remote sensing tasks such as land-use analysis, environmental monitoring, etc. However, despite their strong performance, these models are still vulnerable to adversarial patch attacks—physically realizable patterns that, when placed on an object, can force the model to make incorrect predictions. This creates serious risks for practical geospatial applications. Traditional defenses like …
Grm-0243 Sentient Agi Rights And The Future: The Modern Digital Prometheus, Ryan Deem
Grm-0243 Sentient Agi Rights And The Future: The Modern Digital Prometheus, Ryan Deem
C-Day Computing Showcase
As artificial intelligence advances toward artificial general intelligence (AGI), society must determine how to ethically integrate sentient AI into our communities. This paper argues that once AI achieves sentience and human-level intelligence, it should be granted the same rights and protections as human citizens. Using utilitarian and deontological perspectives, as well as the IEEE Code of Ethics, it examines why treating AGI as lesser beings could lead to fear, conflict, and harmful outcomes—echoing the cautionary themes of Frankenstein. The paper also evaluates public concerns and existing governance frameworks, proposing that mutual respect, rights, and responsibilities are essential for safe coexistence …
Grm-20242 Cipher: Covert Influence Passed Via Hidden Encoding In Representations Evaluating Subliminal Bias Transfer During Knowledge Distillation, Crystal Tubbs
C-Day Computing Showcase
AI models can inherit hidden behavioral biases when student models learn from teacher outputs during knowledge distillation. Project CIPHER investigates whether covert signals, such as zero-width Unicode characters or column order shifts, can transmit bias from a teacher model to a student model even when the student never receives group labels. Using an experimental pipeline with controlled subliminal cues and dual distillation, the project aims to reproduce and measure subtle bias transfer. Preliminary results showed that weak signals produce no measurable bias, while the redesigned high-frequency signal and MLP student architecture reveal quantifiable disparity.
Uc-0180 Encoding Creative Commons Licenses To Images, Tyler Pellegrini, Trey Wilcox, Marcus Johnson, Connor Oberlin
Uc-0180 Encoding Creative Commons Licenses To Images, Tyler Pellegrini, Trey Wilcox, Marcus Johnson, Connor Oberlin
C-Day Computing Showcase
In our project we were tasked with modifying Gimp’s metadata editor to allow artists to check and add Creative Commons licenses and metadata to their image’s. This is done so that artist have an extra layer of protection for themselves and their art, with the ability to choose from multiple types of licenses allowing them to tailor this protection to the needs and desires they have for their artwork.
Uc-0223 Predicting Nba Player Re-Injury Using Net Rating, Anaya Tention
Uc-0223 Predicting Nba Player Re-Injury Using Net Rating, Anaya Tention
C-Day Computing Showcase
This project examines whether player performance data can signal injury risk before an absence occurs. Using game-by-game net rating trends, I applied an exponentially weighted control-chart approach to detect early shifts in performance that might indicate a rising risk of re-injury. The method successfully identified 71% of re-injury cases with an average 20-game lead, suggesting that performance declines can serve as an early warning signal. While the false-alarm rate was high, the results show that performance-based monitoring has potential value for teams seeking proactive player-health insights.
Uc-0250 Tortured Artist, Caitlin Tigani, Ben Scholl, Anaiya Tucker, Adam Tucker
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?
Uc-0224 Loving Arms: Website Audit & Redesign, Marcus Harrison, Chris Stropoli, Katherine Gibson, Vaughn Berger, Jesus Flores Valdez
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 …
Uc-1149 Ai Systems For A Stealth Videogame, Lukas Ehler, Evan Weir, Javier Corona
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.
Uc-1166 Southern Bathtub Race: A Video Game Revival, Caroline Roberson, Jes Crouch, Treonna Gardner, Jose Landaverde, Jake Lashley
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.
Uc-1175 Admissions Assistant - Ai Chatbot, Chelsea Oduro, Jeffery Bond, Tanner Morgan, Allen Scott, Joy Parks
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.
Uc-1232 Stronghold, Caitlin Tigani, Adam Tucker, Camden Lloyd, Dale Balsor
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.
Uc-1234 Fundoria, Connor Stabler, Dameon Jones, Rafay Hassan, Michael Liu, Brenden Horne
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 …
Uc-1240 Project Ibis, Isaac Alderman, Braden Mizell, Collin Sutton
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 …
Uc-1257 Integrating A Pressure Profiling Dock Into An Open-Source Digital Art Framework, Luke Miller, Noah Enyart, Jonah Smith, Jaeden Jones
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 …
Uc-1260 Digital Micromouse Maze Simulation, Chase Bell
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.
Uc-1262 Georgia Watch - Georgia Hospital Accountability Score, Robert Straiton, Patrick Cox, Constant Nortey, Sankalp Amaravadi, Kahmin Keller
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.
Uc-1268 Falling Debris, Julian Duarte, Adam Martin, Rylan Collins, Hugh Haggard, Chance Boecker
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.
Uc-1269 Website Makeover - Loving Arms Cancer Outreach, Yuliana Pacheco, Alicia Cook, Taylor Tompkins, Schuyler Bridges, Dalton Roberts
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 …
Uc-1274 Cloud-Native Ci/Cd Pipeline, Enitan Meduteni, Rami Elmostafa, Matt Crowley, Kade Fleming, Cecily Graffree
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.