Digital Commons Network^™

Grm-022 Exploring Coronavirus 2019 Datasets With Convolutional Neural Networks, Ryan Deem, Sandeep Kumar Vupputuri, Tyler Hood, Droan Patel, Stephen Jacobs

C-Day Computing Showcase

Over the past several decades, the healthcare sector has increased its data creation velocity at an astonishing rate. More doctors and patients have access to real-time imaging technology, which leads to earlier detection and diagnosis for a variety of diseases. In this project, we will explore several datasets that were gathered by various health organizations during the Coronavirus 2019 (COVID-19) pandemic. We will leverage big data analytics techniques and neural network modeling to gain deeper insights into the differentiated diagnosis of COVID-19.

Grm-041 Ai-Driven Analysis Of Openalg Curriculum: Mapping Ai Competencies Across Georgia’S Higher Education Landscape, Michelle Ilechukwu, Iveren Leghemo, Timothy Ngeny

C-Day Computing Showcase

This project investigates the presence of artificial intelligence (AI) competencies across Georgia’s higher education curriculum using university course catalogs as the primary data source, supplemented by OpenALG materials. We applied large language models, including OpenAI’s ChatGPT and embedding APIs, to analyze over 34,000 courses summarizing content, classifying AI relevance, and mapping to global frameworks (AI4K12 and UNESCO). Techniques such as topic clustering, semantic similarity analysis, and geographic distribution mapping were used to uncover patterns in AI integration. Findings reveal that AI content is concentrated in computing disciplines and research universities, with limited coverage in community colleges, MSIs, and non-technical fields. …

Grm-043 Performance Assessment Of Deepseek Versus Bard And Chatgpt In Detecting Alzheimer’S Dementia, Muhammad Awais Arshad

C-Day Computing Showcase

Alzheimer’s disease is a growing public health issue due to its progressive nature and increasing prevalence. Large language models (LLMs) offer promising avenues for non-invasive cognitive assessment through natural language understanding. In this study, we evaluate DeepSeek’s general-purpose model V3 and reasoning-enhanced R1 variant—for identifying Alzheimer’s dementia (AD) and Cognitively Normal (CN) individuals using transcripts derived from spontaneous speech. Two baseline prompting strategies (zero-shot, chain-of-thought ) were applied to both model types and an additional query (self-consistency prompting) was applied to assess better predictions. Accuracy was the primary performance metric. When positively identifying AD, the general-purpose DeepSeek V3 model produced …

Grm-080 Leveraging Data Science For Resilience: Improving Trauma-Informed Care Practice For Adverse Childhood Experience With Ai & Data Science Application, Mohmmad Arif Shaik

C-Day Computing Showcase

Adverse Childhood Experiences (ACEs) have long-lasting effects on physical health, mental well-being, education, and socioeconomic outcomes. Resilient Georgia (RG), a statewide initiative, seeks to address ACEs through trauma-informed care and data-driven strategies. However, challenges in data collection, analysis, and tracking hinder the effectiveness of these efforts. This study explores the role of data science and interactive visualization tools in improving outcomes for individuals and communities affected by ACEs. A key focus of this research is the development of a data science management application designed to enhance data collection and facilitate real-time decision-making. The application features interactive dashboards that allow stakeholders …

Grm-093 Advances In Non-Invasive Glucose Sensing: A Comprehensive In Vitro Analysis, El Arbi Belfarsi, Henry Flores

C-Day Computing Showcase

This study explores non-invasive glucose sensing using infrared (IR) imaging and electrical measurements in an in-vitro setup. Glucose samples (70–200 mg/dL) were prepared by diluting concentrated solutions (700–2000 mg/dL) 1:10 in synthetic blood concentrate, with 2 mg/dL increments. A custom 3D-printed black cuvette holder ensured consistent alignment of components, including either an IR camera or a 1550 nm photodiode, light sources (850 nm LED/laser, 808 nm, 650 nm, or 1600 nm), and a 3 mm skin-mimicking silicone layer. A Region Based Convolutional Neural Network (RCNN) trained on IR images achieved the lowest RMSE of 10.98 mg/dL at 850 nm LED. …

Uc-019 Gwinnett County Public Schools - Data Masking Tool, Emmett Peters, Diego Frausto Ramirez, Abhay Tompkins Silas Talele, Jesus Trejo-Tamayo

C-Day Computing Showcase

In today’s data-driven world, organizations handle vast amounts of sensitive information, including personally identifiable information (PII), health records, and financial data. For institutions like schools, this data often includes sensitive details about students, parents, and staff, making data protection not just important, but critical. With increasing privacy regulations such as GDPR and HIPAA, organizations must implement robust measures to protect this information while still enabling its use for legitimate purposes like testing, analytics, and development. Our web-based data masking tool addresses this need by allowing organizations to protect sensitive data without compromising its usability. By applying dynamic masking rules to …

Uc-125 Database Masking Tool - Project 04 - Team 1, Lleyton Callison, Josh Tettey-Enyo, Reda Salimi, Stephen Sigmon, Alec Quillen

C-Day Computing Showcase

The Database Masking Tool for Gwinnett County Public Schools secures sensitive data while preserving its analytical utility. Developed alongside an in-depth research paper, this web-based solution enables real-time masking of information in SQL Server and MySQL databases. Utilizing automated field recognition, it applies three masking techniques—Faker-based masking, hash masking, and pseudonymization through generalized masking—to protect personally identifiable information. Key features include an intuitive interface for configuring masking rules, real-time data previews, and an export function for generating masked datasets in multiple formats. Built with a React-Flask stack and containerized for consistency, the system supports compliance with GDPR, HIPAA, and FERPA. …

Ur-115 Mobinav: Accessible Campus Navigation, Eric Legostaev, Damien Castro, Dom Evans

C-Day Computing Showcase

MobiNav addresses the gap in campus navigation by providing personalized route planning for individuals with diverse mobility requirements. The system uses dual-layer routing (Google Maps API and custom OSRM routing), real-time obstacle reporting, and detailed accessibility feature mapping. It creates custom routes considering wheelchair access, elevation changes, building entrances, and temporary obstacles. Initially scoped for Kennesaw State University's Marietta campus, it is designed for scalability to other locations.

Gc-039 Clinicpix: Secure Medical Image Sharing Web Application, Michael Harris, Selorm Kumi, Zhi Ern Tan, James Hodgson

C-Day Computing Showcase

ClinicPix is a cloud-based system designed to streamline the management of medical images such as X-rays and MRIs. It offers healthcare providers and patients a secure, intuitive interface to upload, view, and share medical images across institutions and devices. The platform ensures full compliance with HIPAA through robust security measures, including role-based access control, end-to-end encryption, and comprehensive audit trails. Its scalable architecture supports growing data needs while maintaining high performance and reliability. By enhancing accessibility and safeguarding sensitive health information, the platform aims to improve clinical workflows, patient engagement, and collaborative care.

Gc-089 Safecircle:​ Ai And Micro-Radar-Based Remote Monitoring For Patients With Ad/Adrd​, Awan-Ur Rahman, Shakib Quddus, Soarov Chakra Borty

C-Day Computing Showcase

Alzheimer's disease and related dementias (AD/ADRD) is an irreversible and degenerative neurological condition 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.

Grm-038 Optimizing Prompts For Alzheimer's Speech Classification Using Llm, Imaan Shahid

C-Day Computing Showcase

Large Language Models (LLMs) are widely used in Alzheimer's disease research to classify speech patterns. However, there is no standardized framework to ensure the reliability of prompts used in these classifications. This study investigates the sensitivity of Alzheimer’s disease classification prompts to small variations and finds that these prompts are indeed sensitive, leading to inconsistencies in model performance. To address this, we implement an automatic prompt optimization framework to refine the base prompt. Experimental results demonstrate that the optimized prompt improves classification accuracy by 12.83% compared to the baseline, underscoring the significance of systematic prompt engineering in enhancing the reliability …

Grm-042 Ihelp: A Care Partner Activation Program Mhealth System For Ad/Adrd Caregivers, Trisha Bhowmick

C-Day Computing Showcase

The iHelpCare platform is designed to offer a seamless and supportive experience for patients and caregivers through a clear and user-friendly interface. Users begin at the login page, where they can either sign in or create a new account. Once logged in, the home page provides access to essential services such as a 24/7 helpline, emergency visit coordination, emergency support, and a service directory. It also includes engagement tools like discussion forums, learning modules, and resource materials, along with community-focused features such as events, activities, and support groups. The personalized dashboard allows users to monitor health conditions, review patient history, …

Grp-087 Empowering Alzheimer’S Caregivers: Designing Explainable And Personalized Ai For Mental Health Support​, Syeda Umme Salma, Chandra Rekha Renduchintala, Isa Siddique

C-Day Computing Showcase

This study presents the design of an AI-powered caregiver support app aimed at personalized mental health and burden management for individuals caring for Alzheimer’s patients. The design is grounded in insights drawn from a comprehensive analysis of 28 recent studies on AI-driven mental health interventions. These findings informed the implementation of key features, including machine learning models such as Random Forest, clustering, and supervised learning to create adaptive care plans tailored to patient and caregiver profiles. The system dynamically adjusts task schedules based on engagement data and provides interpretable recommendations through SHAP. With built-in emotional check-ins, mood tracking, and caregiver-centric …

Ur-099 Empowering Mental Wellness: A Comprehensive Study And Design Of A Predictive System For Early Mental Health Intervention​, Anh Duong

C-Day Computing Showcase

Mental health is an essential part of living a balanced and fulfilling life, but it is often overlooked compared to physical health. While physical health is important for performing daily activities, mental health plays a crucial role in how we manage stress, build connections, and make decisions. Previous research studies have shown that nearly 60 million Americans experienced a mental illness in 2024, yet there were only 340 people for every one mental health provider in the U.S. Furthermore, young adults aged 18–25—who are the most digitally connected generation—suffer from the highest rates of severe mental illness yet are the …

Ur-112 Monarch: A Privacy-Focused Nlp Model For Emotional Pattern Detection, Tyler Clanton, Derick Burbano-Ramon

C-Day Computing Showcase

Introducing: Monarch — a privacy-focused deep learning model that interprets emotional patterns in text. Monarch is trained on large, lexicon-based datasets and uses fine-tuned NLP models (BERT) to identify patterns associated with sadness, worry, anger, and distress. It runs entirely offline with no data collection, making it ideal for private use. Monarch evaluates text and returns clear, readable probability scores across emotional categories, giving users insight into emotional trends. Monarch is interpretive, not diagnostic, displaying results based on scientifically backed linguistic patterns. Its potential use in schools could help flag early signs of distress, giving educators a chance to support …

Ai Assistance In Legal Analysis: An Empirical Study, Johnathan H. Choi, Daniel Schwarcz

Journal of Legal Education

No abstract provided.

Numerical Analysis Of The Seir Model, Abigail R. Beckelhimer

Departmental Honors & Graduate Capstone Projects

Epidemiological models delineate the spread of diseases within a population. In this research project, the Susceptible-Exposed-Infected-Recovered (SEIR) Model was examined numerically for comparison between several methods. Approximations were obtained through Euler’s Method, Taylor’s Method, Runge-Kutta Methods, and Multi-step Methods. Hypothetical situations with parameter alterations were considered in order to better understand the effects the parameters have on the model. The goal of this project was to portray the usefulness of numerical approximations for predicting the behavior of the SEIR model and thus the course of a pandemic.

Health Risk Assessment Of Heavy Metal(Loid)S Intake From Beverages In The United States, Hannah T.V. Stoner, Tewodros Rango Godebo, Pornpimol Kodsup Taylor

School of Public Health Faculty Publications

Heavy metals in beverages can pose health risks in an exposure-dependent manner, however, few studies in the United States have evaluated their metal content and health risks. This study determined the concentrations of eight metal(loid)s, As, Al, Cd, Cr, Mn, Ni, Pb, and Zn, in 60 beverages via inductively coupled plasma[sbnd]mass spectrometry (ICPMS). The highest median concentrations (µg/kg) were found in mixed fruit juices for Ni (45.7), Cr (14.8), and As (4.5); tea for Mn (5,300), Al (730), and Pb (1.4); and plant-based milk for Zn (835) and Cd (1.1). Chronic daily intake (CDI) across age groups was calculated using …

Preservation And Integrity Of Laboratory Solutions: Understanding The Impact Of Storage Practices On Chemical Stability And Experimental Accuracy, Azza Al Jahdhami

Honors Theses

Chemical storage methods represent a key matter ignored within labs, educational sites, workplaces, and even households. Many people, including various students and instructors within the chemistry field, are unaware of the proper methods for storing and disposing of common chemicals. This study aims to understand the effects of storage practices on chemical stability and experimental accuracy, dealing with the following questions: What kind of effects result from improper chemical disposal? How can improper storage affect the overall chemical effectiveness? Why is sink disposal of many solutions discouraged, and why is waste container disposal always necessary?

Through a literature review, this …

The National Cybersecurity Teaching Coalition: Expanding Cybersecurity Education Opportunities, Paul Wagner, Melissa Dark, Robert Honomichl, Filipo Sharevski, Sandra Leiterman

Journal of Cybersecurity Education, Research and Practice

The increasing prevalence of cybersecurity threats and the shortage of qualified professionals necessitate innovative solutions for cybersecurity education at all levels. Despite the expansion of post-secondary cybersecurity programs, employer dissatisfaction with graduates and a lack of standardized introductory curricula highlights the need for structured secondary education pathways. The National Cybersecurity Teaching Coalition (NCTC) and its National Cybersecurity Teaching Academy (NCTA) address this gap by equipping high school educators with the necessary knowledge and credentials to teach cybersecurity effectively. NCTA offers an 18-credit cybersecurity graduate certificate program to ensure teachers are competent and confident to develop and teach cybersecurity curriculum with …

Ai-Based Detection Of Optical Microscopic Images Of Pseudomonas Aeruginosa In Planktonic And Biofilm States, Bidisha Roy Sengupta, Esther Mallet, Angel Torres, Ravyn Solis

Faculty Publications

No abstract provided.

Re: Approval Letter For The Draft Final Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Phase Iii Quality Assurance Project Plan (Qapp) (Dated February 27, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

04.14.2025 Ored Connect, Liz Williamson

ORED Newsletter

Updated CITI Training Courses

Science Celebration

IHL Prepayment Approval

Re: Approval Letter For The Draft Final Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Quality Assurance Project Plan (Qapp) For Microbial Analysis And Biotreatability Study (Dated February 27, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Final Silver Bow Creek Conservation Area Repository Data Gap Data Summary Report (Dated April 4, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Ai & Xr Explorations To Support Social Interactions: Speculative Design For Ubiquitous Workplace Space By And For Neurodivergent Employees, Dominique Michaud, Alejandro Reyes, Jonathan Proulx Guimond, Fafadzi Akpene Agbe, Valérie Payen, Diane Gabrielle Tremblay, Marie Claude Leblanc, Claude Vincent, Geoffreyjen Edwards, Caroline Brassard, Marie Helene Parizeau, Valéry Psyche, Martin Caouette, James Hutson, Piper Hutson, Julie Ruel, Julien Voisin, Jocelyne Kiss

Faculty Scholarship

This study explores the potential of interdisciplinary theories and advanced technologies, such as augmented realities and artificial intelligence, to address the socio-professional integration challenges faced by neurodivergent individuals, particularly those on the autism spectrum. It investigates the design of personalized, functional spaces that integrate interconnected living environments and intelligent systems tailored to support communication needs. Using speculative design methodology, the research adopts an experiential framework to examine alternative solutions, starting with a central hypothesis and testing it through debates with researchers, experts, neurodivergent individuals, and knowledge users. The premise is rooted in the recognition that neurodivergent individuals encounter significant barriers …

Integrating Ai-Driven Neurofeedback With Brain-Computer Interfaces: A Paradigm For Effortless Learning And Workforce Transformation, James Hutson

Faculty Scholarship

This editorial discusses the merging of AI-driven neurofeedback with brain-computer interfaces (BCIs) to create a new model for effortless, unconscious learning. By interpreting and reinforcing specific neural patterns, these technologies can enable users to acquire skills without traditional instruction, making them especially valuable in fast-evolving industries. They also offer powerful tools for individuals with physical impairments by enabling control through thought alone. However, the author emphasizes the importance of ethical oversight, particularly around cognitive autonomy, data privacy, and consent. As the field matures, ongoing research and regulation will be essential to ensure responsible development and widespread, beneficial use.

The Effect Of Soil Conditioner And Growth Booster On The Agronomic Characters And Number Of Nodules Of Black Soybean, Tien Turmuktini, I Putu Rahmat Santoso, Lia Amalia, Nunung Sondari, Elly Roosma Ria, Yenny Muliani, Endang Kantikowati, Tualar Simarmata

Jurnal Kultivasi

Soil Conditioner & Growth Booster (SCGB) is a potion that was made to be used as a soil conditioner and plant growth promoter. SCGB is made from organic matter, biological fertilizers, soil ameliorants, and microelements. This research aims to determine the best dosage of SCGB on the agronomic characters, effective nodules, and black soybean variety ‘Detam-1’ yield. This research was conducted in the experimental field of the Faculty of Agriculture, Winaya Mukti University, Sumedang, Indonesia. This experiment used a simple randomized block design (RBD) with six treatments (0, 3, 6, 9, 12, 15 kg/ha) and repeated 4 times. The observation …

Assessing Readiness For Transformation From Rule-Based To Ai-Based Chatbot In Uae Healthcare: A Case Study Of A Rehabilitation Hospital In Abu Dhabi, Mubarak Alketbi

Thesis/ Dissertation Defenses

This research investigates the readiness of UAE healthcare institutions to transition from rule-based chatbot systems to AI-powered alternatives, focusing on a rehabilitation hospital in Abu Dhabi. Through a structured quantitative study involving 96 healthcare professionals, the research explores technology acceptance, service quality, usability, and implementation readiness. Findings highlight strong correlations between perceived usefulness and behavioral intention to adopt AI, emphasizing the importance of integration, staff training, and service reliability. The study proposes a practical implementation framework for healthcare transformation, offering insights for institutions seeking to improve operational efficiency through AI integration.

Butte Priority Soils Operable Unit Draft Final 2023 Reclamation Improvement Sites Sampling: Bres No. 84 – Mandan Park Site Evaluation Summary Report, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.