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Uc-138-166 The Allies Connect Platform: Improving Access To Community Resources Through Technology​ ​, Sarah Holland, Neha Anand, Aldrick Andoh, Yacine Diop, Alex Rogers Apr 2026

Uc-138-166 The Allies Connect Platform: Improving Access To Community Resources Through Technology​ ​, Sarah Holland, Neha Anand, Aldrick Andoh, Yacine Diop, Alex Rogers

C-Day Computing Showcase

Finding help shouldn’t be difficult, but for many people, it is. Important information about food, shelter, and local support is often scattered across different websites, social media pages, and documents, making it hard to find what’s needed, especially in urgent situations. The Allies Connect platform was created to bring that information into one place. It is a centralized, mobile-friendly platform that allows users to: • Search for resources • Register for events • Connect with nonprofits At the same time, the platform also provides organizations with simple tools to keep their information accurate and up to date. By focusing on …

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Uc-143-178 Georgia Laws Of Life Crm Implemenetation, Nicholas Sternon, Josh Flores, Jessica Scales, Opurbo Bhuiyan, Shiv Patel Apr 2026

Uc-143-178 Georgia Laws Of Life Crm Implemenetation, Nicholas Sternon, Josh Flores, Jessica Scales, Opurbo Bhuiyan, Shiv Patel

C-Day Computing Showcase

This project focuses on implementing a Customer Relationship Management (CRM) system for Georgia Laws of Life using the Little Green Light (LGL) platform. The organization previously relied on spreadsheets, which caused issues such as duplicate records, inefficient reporting, and difficulty managing relationships. To address this, the team analyzed existing workflows and developed a structured data model. The system was configured, and sample data including constituents, donations, schools, and contracts was successfully imported to validate the design. The results show that the CRM system improves data organization, enhances relationship tracking, and provides a more efficient and scalable solution for managing organizational …

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Uc-162-194 Smart Soil Analyzer, Samuel Florez Garcia, Edward Johnson, Aaron Gamino, Tassha Burton, Wyatt Kinney Apr 2026

Uc-162-194 Smart Soil Analyzer, Samuel Florez Garcia, Edward Johnson, Aaron Gamino, Tassha Burton, Wyatt Kinney

C-Day Computing Showcase

The Smart Soil Analyzer is a machine learning-based application designed to maximize agricultural efficiency and sustainability. Our team developed a predictive system using a K-Nearest Neighbors (KNN) classifier trained on a comprehensive crop recommendation dataset. The tool allows users to input key environmental and soil metrics, including Nitrogen (N), Phosphorus (P), Potassium (K), temperature, humidity, pH levels, and rainfall. By processing these variables, the model accurately predicts the most suitable crop for the specific land conditions. This solution provides farmers with data-driven insights to optimize yields, reduce fertilizer waste, and combat soil degradation through precise crop matching.

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Uc-164-215 Hootnest: Ai-Powered Ksu Student Assistant, Tabitha Washington, Aspen Steele Apr 2026

Uc-164-215 Hootnest: Ai-Powered Ksu Student Assistant, Tabitha Washington, Aspen Steele

C-Day Computing Showcase

HootNest helps prospective Kennesaw State students get clear, reliable answers about college life. It is designed for students who may not have easy access to counselors, mentors, or campus visits. The chatbot allows students to ask the chatbot anything they need to know.

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Ur-133-165 Quantum Machine Learning For Science And Engineering, Barclay Barnes, Anna Zharikov, Meriem Hamzi Apr 2026

Ur-133-165 Quantum Machine Learning For Science And Engineering, Barclay Barnes, Anna Zharikov, Meriem Hamzi

C-Day Computing Showcase

Quantum machine learning (QML) has emerged as a promising method for overcoming the computational limitations of classical machine learning when analyzing large and complex data sets. This project investigates the application of QML algorithms to real-world science and engineering problems, with a focus on civil and environmental engineering datasets. We develop and evaluate a Python-based system, implemented in Google Colab, that integrates multiple quantum computing frameworks, including PennyLane, TensorFlow Quantum, and Qiskit, to implement and compare several QML models against their classical counterparts. The proposed system explores a range of algorithms such as Quantum Neural Networks, Quantum Support Vector Machines, …

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Ur-171-118 Aidflow: A Predictive Financial Aid Transparency System For Students, Chaathurya Nakkana Apr 2026

Ur-171-118 Aidflow: A Predictive Financial Aid Transparency System For Students, Chaathurya Nakkana

C-Day Computing Showcase

Students frequently experience delays and confusion regarding financial aid refunds due to unclear system statuses and lack of communication. This project introduces AidFlow, a predictive financial aid transparency system that translates complex financial data into clear explanations, predicts refund timelines, and provides actionable guidance. A rule-based model and system pipeline were developed to simulate real-world scenarios and improve student understanding and decision-making.

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Ex-116-209 The Understudy – A 2.5d Turn-Based Story Game​, Ara Randolph, Rin Egl, Cayden Herrington, Jonah Swerdlow, Carter Griffin, Amaya Cruz Apr 2026

Ex-116-209 The Understudy – A 2.5d Turn-Based Story Game​, Ara Randolph, Rin Egl, Cayden Herrington, Jonah Swerdlow, Carter Griffin, Amaya Cruz

C-Day Computing Showcase

“The Understudy” is a whimsy-filled 2.5D turn-based theatrical adventure where you play as the last-minute understudy, who has been suddenly thrust into the spotlight after the lead mysteriously vanishes right before showtime. Armed with nothing but masks (comedic, dramatic, and tragic) and a script you definitely didn’t not rehearse enough, you fight your way through a cast of dramatic acting troupe members, ranging from a painfully shy tree to a snarky jester ex to a pompous king who’s very sure you don’t belong on his stage. Swap masks to change your combat style, solve dialogue puzzles, and prove that even …

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Gc-119-134 Pipeline For Vr Embodied Lecture Authoring And Ai Gesture Refinement, Rishi Kiran Aiyatham Prabakar Apr 2026

Gc-119-134 Pipeline For Vr Embodied Lecture Authoring And Ai Gesture Refinement, Rishi Kiran Aiyatham Prabakar

C-Day Computing Showcase

While Virtual Reality (VR) offers immersive educational opportunities, its pedagogical success relies heavily on a genuine sense of "instructor presence". This project presents a hybrid pipeline that automatically refines presenter 3D avatar gestures using semantic AI. Our non-VR recording system captures high-fidelity facial tracking and MediaPipe for upper-body pose estimation via standard RGB video. For emotion recognition, a local Large Language Model analyzes audio transcripts to generate a timestamped emphasis track. This semantic engine, intelligently exaggerating gestures during critical lecture moments. The captured motion and AI-enhanced gestures are synthesized and replayed on a virtual lecturer within an VR environment for …

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Gc-126-148 Allies Connect- Georgia's Nonprofit And Volunteer Coordination Platform, Molly Calhoun, Takeshia Banks, David Castro, Ryan Hanrahan, Tarik Davis Apr 2026

Gc-126-148 Allies Connect- Georgia's Nonprofit And Volunteer Coordination Platform, Molly Calhoun, Takeshia Banks, David Castro, Ryan Hanrahan, Tarik Davis

C-Day Computing Showcase

Georgia's nonprofit services face an issue of discoverability. While many nonprofits have the resources to help their community members succeed, they have trouble actually connecting to members of the community that need their support. Connecting with these resources is challenging for community members because their avenues of communication are spread across the internet. Some have their own websites, some have a Facebook page where they post events, some rely on word of mouth and fliers, and others rely on phone chains to keep their community members informed. This means that community members seeking support need to be able to access …

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Gc-130-160 C-Day Explorer: A Domain-Aware Platform For Discovering And Extending Ksu Student Projects, Rohan Jonnalagadda, Sanketh Chapaneri Apr 2026

Gc-130-160 C-Day Explorer: A Domain-Aware Platform For Discovering And Extending Ksu Student Projects, Rohan Jonnalagadda, Sanketh Chapaneri

C-Day Computing Showcase

C-Day showcases some of the strongest computing projects at KSU, but once each event ends, past work becomes scattered across semester pages, posters, PDFs, and videos, making it difficult to see long-term trends or build on prior ideas. C-Day Explorer addresses this gap with a centralized, domain-aware web platform that aggregates project records from 21 semesters of C-Day archives, KSU Digital Commons, winner pages, and YouTube presentation videos. The system organizes 1,286 projects into 11 computing domains with high abstract coverage, poster and video links, and similarity-based connections that help users quickly find related work and promising directions for extension. …

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Grm-083-218 Wise: Whitebox Importance-Based Subnetwork Extraction And The Privacy-Preserving Properties Of Model Compression, Mason Pederson Apr 2026

Grm-083-218 Wise: Whitebox Importance-Based Subnetwork Extraction And The Privacy-Preserving Properties Of Model Compression, Mason Pederson

C-Day Computing Showcase

WISE (Whitebox Importance-based Subnetwork Extraction) is a structured compression algorithm which extracts task-specific subnetworks by instrumenting a pretrained networks with learned gates on transformer components and optimizing on task loss and L0 sparsity regularization. WISE maintains high task performance at high sparsity levels (81-88% accuracy at 85%) where other SOTA methods collapse to near random chance. We present the first evaluation of model compression along privacy dimensions: attribute inference resistance, training data memorization, and extraction attack vulnerability. Structured compression via learned gates produces subnetworks with favorable privacy-utility balance without any explicit privacy mechanism. WISE masks also transfer to fresh models …

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Grm-153-198 Safecircle: Ai And Micro-Radar-Based Remote Monitoring For Patients With Ad/Adrd, Awan-Ur- Rahman, Soarov Borty, Gowtham Ankolu Apr 2026

Grm-153-198 Safecircle: Ai And Micro-Radar-Based Remote Monitoring For Patients With Ad/Adrd, Awan-Ur- Rahman, Soarov Borty, Gowtham Ankolu

C-Day Computing Showcase

Alzheimer's disease and related dementias (AD/ADRD) are irreversible and degenerative neurological conditions that severely impacts neurons, resulting in cognitive decline and memory loss. This study explores a mHealth system, including a SafeCircle iOS prototype, a novel solution that combines artificial intelligence with cutting-edge micro-radar technology. The platform offers a variety of features, including management of patient and caregiver profiles, real-time alerts in case of emergencies, emergency contact lists, one-touch SOS support, sharing of live locations, and recording of unusual events in video. It is a responsive and reliable care assistant that optimizes patient safety while reducing caregiver burden.

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Grm-156-153 Finding Top-K Assignments For Multi-Hypothesis Tracking, Tyler Hood, Rakshak Gurung Apr 2026

Grm-156-153 Finding Top-K Assignments For Multi-Hypothesis Tracking, Tyler Hood, Rakshak Gurung

C-Day Computing Showcase

Multi-Hypothesis Tracking (MHT) is a framework for solving the data association problem in multi-target tracking by maintaining multiple possible assignments between observations and targets over time. Rather than committing to a single solution, MHT explores a set of competing hypotheses, allowing it to handle noise, missed detections, and ambiguous measurements. In practical systems such as radar, LiDAR, and vision-based tracking, MHT is commonly implemented using algorithms like Murty’s algorithm to generate multiple high-quality assignment solutions from the Hungarian algorithm. In this work, we instead propose an assignment-tree-based approach, where hypotheses are incrementally constructed and prioritized using a structured search strategy. …

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Grm-157-180 Precision Engineering: Using Ai To Design Nanoparticles That Target Malignant Cells, Rakshak Gurung, Nino Tkabladze Apr 2026

Grm-157-180 Precision Engineering: Using Ai To Design Nanoparticles That Target Malignant Cells, Rakshak Gurung, Nino Tkabladze

C-Day Computing Showcase

The challenge of predicting nanoparticle distribution remain a significant hurdle in nanomedicine. This research presents a computational framework for the inverse design of nanoparticles, utilizing ML models to optimize drug delivery systems for tumor targeting. By analyzing the relationship between nanoparticle compositions and biological accumulation, the model identifies optimal configurations to maximize therapeutic efficacy. The results demonstrate that AI-driven inverse design can significantly streamline the development of precision nanocarriers, reducing the need for exhaustive experimental trials.

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Maximizing Uinta Basin Oil Well Yield Through Geochemical Fingerprinting Of Produced Water, Troy W. Day Apr 2026

Maximizing Uinta Basin Oil Well Yield Through Geochemical Fingerprinting Of Produced Water, Troy W. Day

Theses and Dissertations

The Uinta Basin is an unconventional oil play that has, since 2017, annually increased hydrocarbon extraction through modern drilling and fracing techniques with increased frac loading. The primary production target is the Uteland Butte Member of the Green River Formation, which consists of interbedded limestones, dolostones, and thick, organic-rich mudstones. Along with increased hydrocarbon production, volumes of produced water from the Uteland Butte Member have also risen. Water is co-produced with hydrocarbons and is an undesirable byproduct of hydrocarbon extraction. Large frac operations now consistently have highly variable percentages of recovered water volume relative to oil. This increase in water …

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The Euler Characteristic, Cara Admiraal Apr 2026

The Euler Characteristic, Cara Admiraal

SPARK Symposium Presentations

The Euler characteristic is an example of a topological invariant most famously Leonard Euler proved that for any convex polyhedron with $v$ vertices, $f$ faces, and $e$ edges, $v-e+f=2$. In this presentation, we will extend his ideas to define the Euler characteristic for surfaces.

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Temperature-Induced Uncertainty In Fixed-Context Retrieval-Augmented Generation, Steven Zeng, Murat Kuzlu Apr 2026

Temperature-Induced Uncertainty In Fixed-Context Retrieval-Augmented Generation, Steven Zeng, Murat Kuzlu

Cybersecurity Undergraduate Research Showcase

This study examines how decoding temperature affects output uncertainty in a fixed-context retrieval-augmented generation (RAG) system. We define uncertainty as the semantic dispersion among repeated answers under the same fixed retrieved context, with greater dispersion interpreted as higher uncertainty. To isolate this answer-generation variability from retrieval drift, each question was paired with a fixed retrieved context, and repeated generations differed only in temperature. The experiment used nine questions drawn from a machine-learning textbook corpus, with three questions each at easy, moderate, and hard difficulty. Each question was evaluated at five temperatures (0.0, 0.25, 0.5, 0.75, and 1.0) over 30 iterations, …

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Massively Parallel Kalman Filtering: Scaling State Estimation Via Cuda Kernels, Joseph Campione, Peter Chim, Hannah Depuydt, William Johnston, Jackson Phillips, Brian White Apr 2026

Massively Parallel Kalman Filtering: Scaling State Estimation Via Cuda Kernels, Joseph Campione, Peter Chim, Hannah Depuydt, William Johnston, Jackson Phillips, Brian White

Mathematics & Computer Science Student Scholarship

This project addresses the challenge of state estimation in real-world conditions by fusing data from multiple sensors using the Kalman Filter. To ensure numerical stability, we use the Joseph Form covariance update, which guarantees valid results but introduces significant computational overhead due to its complexity. To overcome this limitation, we implement a parallelized solution using custom CUDA kernels on a GPU, distributing matrix operations across thousands of threads rather than relying on sequential CPU execution. Through systematic benchmarking across matrix sizes ranging from 4×4 to 4096×4096, we identify a crossover region where GPU performance surpasses CPU efficiency. This work shows …

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Developing Physics And Computing Identities In A Computationally Integrated Physics Course, Elizabeth Hallock Apr 2026

Developing Physics And Computing Identities In A Computationally Integrated Physics Course, Elizabeth Hallock

Engineering & Physics Student Scholarship

No abstract provided.

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Creating A Random Number Generator Harnessing: Lava Lamps As A Source Of Randomness, Rachel Barter, Nicolas Guerra, Sarah O'Connor Apr 2026

Creating A Random Number Generator Harnessing: Lava Lamps As A Source Of Randomness, Rachel Barter, Nicolas Guerra, Sarah O'Connor

Mathematics & Computer Science Student Scholarship

No abstract provided.

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Investigating The Substrate Specificity Of Azo Bond Reduction In The Human Gut Microbiome, Najoude Claude, Annick Kenfack, Glorimar De Los Santos, Madeline Bormes Apr 2026

Investigating The Substrate Specificity Of Azo Bond Reduction In The Human Gut Microbiome, Najoude Claude, Annick Kenfack, Glorimar De Los Santos, Madeline Bormes

Chemistry & Biochemistry Student Scholarship

The bacteria of the human gut microbiome can metabolize drugs, often causing unintended side effects. The uniqueness and variability of each individual’s microbial composition, coupled with our limited understanding of specific enzyme functions, make the metabolic outcomes of these therapeutics difficult. Azoreductase enzymes are of particular interest due to their ability to reduce azo bonds, which are often found in drugs and food dyes. Azo dyes can also be reduced nonenzymatically by hydrogen sulfide, a bacterial metabolite produced during sulfate and cysteine metabolism. The goal of this study is to examine the specificity and relative kinetics of both enzymatic and …

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A Computational Approach To Periodic Orbits Of State-Dependent Delay Differential Equations, Noah Corbett Apr 2026

A Computational Approach To Periodic Orbits Of State-Dependent Delay Differential Equations, Noah Corbett

Electronic Theses and Dissertations

The field of delay differential equations (DDEs) concerns the study of systems whose evolution depends on certain past states of the system. Of particular interest are the state-dependent DDEs, whose delay terms are non-constant and depend on the current state itself. In this thesis, we provide rigorous solution-finding techniques for a certain class of one-dimensional state-dependent DDEs, as well as a state-dependent delayed Van der Pol equation. This technique is inspired by the classical Picard-Lindelof theorem and is successful in proving the existence and uniqueness of orbits in such systems under certain reasonable restrictions. We then employ the Lagrange-Chebyshev interpolating …

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Probing The Disequilibrium Chemistry Of Two Late T-Dwarfs Using Planetary Intensity Code For Atmospheric Scattering, Crystal-Lynn Jacqueline Bartier Apr 2026

Probing The Disequilibrium Chemistry Of Two Late T-Dwarfs Using Planetary Intensity Code For Atmospheric Scattering, Crystal-Lynn Jacqueline Bartier

Theses and Dissertations

We have performed a detailed analysis of the atmospheric properties of two late-T type brown dwarfs, 2MASSI J0415195-093506 and 2MASS J05591914-140448. For each brown dwarfs, we combined the spectra of each brown dwarf from the ground at 1-2.5 µm, AKARI at 2.5-5 µm, and from the Spitzer Space Telescope at 5-15 µm. For this project, we are particularly interested in probing the extent of vertical mixing. For this analysis, we used the Planetary Intensity Code for Atmospheric Scattering (PICASO), which is a code that creates a radiative transfer model for a given set of atmospheric parameters. With PICASO we find …

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Re: Approval Letter For The 2023 Butte Priority Soils Operable Unit (Bpsou) Stormwater Evaluation And Maintenance Report (Dated April 8, 2026), Emma Rott Apr 2026

Re: Approval Letter For The 2023 Butte Priority Soils Operable Unit (Bpsou) Stormwater Evaluation And Maintenance Report (Dated April 8, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Re: Conditional Approval Letter For Diggings East 95 % Remedial Design Package Submittal (Dated March 25, 2006), The Silver Bow Creek Conservation Area (Sbcca) – 95 Percent Programmatic Technical Specifications Submittal (Dated March 25, 2026), The Butte Priority Soils Operable Unit (Bpsou) Sbcca Operations And Maintenance (O&M) Plan (Dated March 24, 2026), And The Sbcca Final Principles For A Greener Cleanup Report (Dated February 4, 2026), Emma Rott Apr 2026

Re: Conditional Approval Letter For Diggings East 95 % Remedial Design Package Submittal (Dated March 25, 2006), The Silver Bow Creek Conservation Area (Sbcca) – 95 Percent Programmatic Technical Specifications Submittal (Dated March 25, 2026), The Butte Priority Soils Operable Unit (Bpsou) Sbcca Operations And Maintenance (O&M) Plan (Dated March 24, 2026), And The Sbcca Final Principles For A Greener Cleanup Report (Dated February 4, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Patient-Level Breast Cancer Classification From Multi-View Mammography With Side-Specific Evidence For Interpretability, Bushra Intakhab Apr 2026

Patient-Level Breast Cancer Classification From Multi-View Mammography With Side-Specific Evidence For Interpretability, Bushra Intakhab

Electronic Theses and Dissertations

Breast cancer remains one of the leading causes of cancer-related death among women. Early detection through screening mammography is therefore very important. However, mammogram interpretation can be difficult because abnormalities may be subtle and spread across different views. The increasing workload of radiologists can also affect timely analysis. Artificial intelligence (AI) has been widely explored to support mammography interpretation by improving speed and consistency. However, many existing AI methods focus on patch-level or image-level analysis rather than the full patient exam. This limits their ability to capture the complete clinical picture, since important information is distributed across multiple views. In …

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Spot Scanning Proton Beams Characterization Via Plastic Scintillator Detector, Saad Bin Saeed Ahmed Apr 2026

Spot Scanning Proton Beams Characterization Via Plastic Scintillator Detector, Saad Bin Saeed Ahmed

Electronic Theses and Dissertations

In spot scanning proton therapy, the machine steers magnetically a narrow pencil beam across the target volume, delivering highly conformal dose distributions layer by layer. As beam size is very small, this introduces a dosimetry problem. The beam is dynamic and the dose gradients are steep — conditions that push conventional ionization chambers beyond their reliable operating range. Plastic scintillation detectors offer a potential solution. Their sub-millimeter active volumes avoid the volume-averaging effects over larger chambers, and their very high temporal resolution making real-time monitoring feasible. This thesis characterizes the Blue Physics plastic scintillation detector in spot scanning proton fields …

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Re: Approval Letter For The 2022 Butte Priority Soils Operable Unit (Bpsou) Stormwater Evaluation And Maintenance Report (Dated April 8, 2026), Emma Rott Apr 2026

Re: Approval Letter For The 2022 Butte Priority Soils Operable Unit (Bpsou) Stormwater Evaluation And Maintenance Report (Dated April 8, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Re: Approval Letter For The 2024 Butte Priority Soils Operable Unit (Bpsou) Stormwater Evaluation And Maintenance Report (Dated April 8, 2026), Emma Rott Apr 2026

Re: Approval Letter For The 2024 Butte Priority Soils Operable Unit (Bpsou) Stormwater Evaluation And Maintenance Report (Dated April 8, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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The Item Response Warehouse: What It Is, How To Use It, And Targets For Potential Improvements, Savira D. Nadela, Hansol Lee, Nishka Jain, Ayaan Gupta, Xingyi Zhang, Benjamin W. Domingue Apr 2026

The Item Response Warehouse: What It Is, How To Use It, And Targets For Potential Improvements, Savira D. Nadela, Hansol Lee, Nishka Jain, Ayaan Gupta, Xingyi Zhang, Benjamin W. Domingue

Chinese/English Journal of Educational Measurement and Evaluation | 教育测量与评估双语期刊

The Item Response Warehouse (IRW) is a repository of harmonized item response datasets designed to support secondary analysis and methodological research in psychological and educational measurement. This paper serves as a practical guide for researchers interested in using the IRW. We describe the structure of IRW datasets and the quantitative and qualitative metadata available for dataset selection, and we demonstrate how researchers can navigate the IRW website to explore and compare available tables. We further show how the IRW R and Python packages can be used to filter datasets programmatically, download response-level data, and generate standardized citations for reproducible research …

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