Physical Sciences and Mathematics Commons^™

2026 April - Tennessee Climate Snapshot, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Chopchop: The Digital Cookbook, Dominc Mcdevitt, Shane Misley, Katie Cerda, Kobie Henson, Adolfo Duran

Presentations - 2026

Problem With traditional recipe organization methods,

● Recipes are scattered across paper, PDFs, Word docs, and notes

● Paper recipes can be lost, damaged, or left at home

● Digital recipes are difficult to edit, store, and organize

● Manually typing or updating recipes is time-consuming

● Sharing recipes is inconvenient and often confusing

● Limited or inconsistent cloud access reduces accessibility

● Formatting is messy and inconsistent across platforms

● No simple, centralized system for managing recipes

Budgeting Apps, Financial Literacy, And Financial Control, Max Masabo, Abdullah Mohammad Mahi

Presentations - 2026

Our paper shows the real hidden connections between budgeting app usage and financial wellbeing of U.S Households

Match-A-Fit, Adan Diaz De Leon, Juan Marco Saca Dada, Brianna Mendoza, Arsalan Kataneh, Theophile Nsabimana, Pedro Jacobo

Presentations - 2026

Welcome to Match-a-Fit! Match-a-Fit is an iOS application that allows the user to create a digital closet by uploading images of their clothing items. With AI, the program can generate outfits based on the digital closet, the time, and the occasion. Match-a-Fit’s purpose is designed to help users who struggle to get ready, run out of time, or can’t decide on an outfit, by easily generating outfit options based on the occasion.

Comparative Analysis Of Mlp And Cnn Models For Cardiac Arrhythmia Classification, Veltman Okey-Ejowhor, Vahid Emamian

Posters - 2026

Electrocardiogram (ECG) is a record of the electric activity of the heart over time. ECG analysis plays a pivotal role in diagnosing critical heart conditions. Significant developments have been made in the realm of deep learning and applied artificial intelligence. These deep learning models have been utilized heavily because of their ability to analyze deep morphological features of each signal. The model architecture used in this study is a convolutional neural network (CNN) combined with a multi-layered perceptron (MLP). The MLP acts as an input filter that classifies normal heartbeat signals from abnormal. The CNN is the second filter in …

The Willow Who Kept The Secrets Of The Heart, Ana Suarez

Speak for the Trees!

This digital museum exhibit features the climate change fairy tale The Willow Who Kept the Secrets of the Heart, presented as a written narrative and recorded reading that explores the symbolic relationship between the Weeping Willow, water, and ecological care in the face of climate change. It also includes an infographic highlighting the Weeping Willow’s habitat, characteristics, and environmental challenges in Texas, along with a curator’s talk and curator’s board. The exhibit features an artifact entry using a half-filled vial of water to represent climate instability and the often-overlooked resources that sustain life, as well as a persuasive essay, …

Maddenlite, Sergio Pena

Posters - 2026

Sports simulations often rely on opaque, proprietary algorithms (like EA's Madden NFL). MaddenLite bridges the gap between sports analytics and interactive gaming by utilizing historical NFL Play-by-Play (PBP) data to drive a transparent, mathematically accurate simulation engine. The goal was to create a lightweight, UI-driven desktop application where users can simulate cross-era matchups (e.g., 2007 Patriots vs. 2025 Chiefs), manipulate rosters, and simulate entire seasons complete with official NFL tiebreaker protocols.

Foxbuddy, Luis Eduardo Garza Jr.

Posters - 2026

Emergency preparedness remains a significant challenge for individuals due to disorganized resource management and lack of accessible guidance. Additionally, cybersecurity risks during emergencies are often overlooked, leaving individuals vulnerable to digital threats such as phishing, scams, and data exposure. FoxBuddy provides a centralized, user-friendly platform that enhances both physical preparedness and cybersecurity awareness.

Using Ai-Based Predictive Scheduling To Improve Patient Flow And Reduce Wait Times In Healthcare Clinics, Oscar Martinez

Posters - 2026

• Healthcare systems face increasing challenges in patient access and wait times
• Average wait times for specialist care continue to rise, creating:
  • Delays in treatment
  • Reduced patient satisfaction
  • Increased system inefficiencies (Sanford, 2025)
• A major contributor is operational bottlenecks, defined as:
  • Points of congestion that slow or disrupt service flow
• Hospitals typically operate under process layouts, which:
  • Handle diverse patient needs
  • Reduce specialization efficiency
• Contributing factors to bottlenecks:
  • Physician shortages and burnout
  • Administrative burden
  • Inefficient scheduling systems (Moura & Pinho, 2025)
• AI offers potential solutions through:
  • Predictive scheduling
  • Automation of administrative processes
  • Data-driven optimization of patient flow

Optimizing Retail Grocery Inventory Using Ai And Large Language Models: Evidence On Forecast Accuracy, Waste Reduction, And Cost Efficiency, Robert Miller, Stephen Garcia, Brandon Ermis

Posters - 2026

Aim: To evaluate how AI and LLMs improve forecasting accuracy, reduce waste, and enhance inventory decision-making

Synthesis And Characterization Of Metal Complexes Of Oxindole-Based Β-Lactams, Kenya Rosas, Erick Morales Orrante, Carlos Sifuentes, Alexsei Nazarov

Posters - 2026

• β-lactams are essential structural components of many antibiotics and widely studied due to their biological importance and synthetic versatility.
• The Ugi reaction is a multicomponent reaction, involving a primary amine, carboxylic acid, isocyanide, and an aldehyde or a ketone, that rapidly generates α-acetamido carboxamide derivatives (Ugi adducts).
• The synthesis and characterization of four oxindole-based β-lactam derivatives:
  • 1-Benzyl-N-(tert-butyl)-2-oxo-3-(2-oxoazetidin-1-yl)indoline-3-carboxamide (4a).
  • N-(tert-butyl)-2-oxo-3-(2-oxoazetidin-1-yl)-1-phenylindol-3-carboxamide (4ab).
  • N-(tert-Butyl)-2-oxo-3-(2-oxoazetidin-1-yl)indoline-3-carboxamide (4d).
  • N-(tert-butyl)-1-methyl-2-oxo-3-(2-oxoazetidin-1-yl)indol-3-carboxamide (4e).
• The coordination of the four Ugi adducts with Cu (II) and Ni (II) at different pH points to enhance their stability and improve biological activity.

Agglomeration Of Particles Streaming Down A Zigzag, Juan Llamas

Posters - 2026

Zigzags or “letdown ladders” limit the flow speed of dry grains as they flow downward by gravity when loading silos, ships, barges, railcars, or trucks.

• Reduce cracking and shattering of grains.

• Increase grain shelf life.

• Increase grain resale value. • Increase ability of grain to germinate.

• Reduce generation of grain dust, an explosion and environmental hazard.

How can we design a zigzag that we know will not plug?

Beyond Technology Acceptance: Ai Adoption In The United States And Korean Accounting Firms, Madeline Ortega, Brenda Vazquez Saavedra

Posters - 2026

A comparison of AI adoption between the United States and South Korea

A View Under The Hood: Duquesne Kline's Law And Computing Program, Wesley M. Oliver, Katherine L.W. Norton, Martin Mckown, David Horrigan

West Virginia Law Review

No abstract provided.

Fear In The Forecast: Do You Believe The Government Controls The Weather?, Gabriella Bartsch

Honors Papers and Posters

Weather manipulation by the government is among the most widely believed conspiracy theories in America, with over 49 percent of Americans subscribing to this belief. As belief in weather-related conspiracies continues to gain traction, understanding the political and social factors that drive these beliefs becomes increasingly essential. In this study, data from the Chapman Survey of American Fears, a representative national sample of U.S. adults, as well as a qualitative content analysis of X/Twitter posts from 2020 to 2026, are used. This research examines how political partisanship and conspiratorial predisposition are reflected in media consumption and levels of institutional trust, …

Ecovoltaic Solar Energy Development Creates Novel Microclimate, Temperature, And Soil Moisture Patterns Under Solar Panels In A Warm Desert, Juan Pinos, Seth M. Munson, Claire C. Karban, Matthew D. Petrie

Life Sciences Faculty Research

Background As solar energy development expands in desert regions, new installation practices and solar technologies seek to balance ecosystem conservation and energy generation (ecovoltaics). The Gemini Solar Project, a large ecovoltaic facility located in the northeastern Mojave Desert, employed low impact installation methods to reduce disturbance of the desert ecosystem within arrays of bifacial panels mounted on solar tracking systems. We evaluated microclimate and environmental conditions across five locations: four within-facility microsites (underneath solar panels, east and west panel driplines, and interspaces between panel rows) and one in the undisturbed desert outside the facility. Results Under panel microsites experienced lower …

Deep Learning-Based Automated Pneumonia Detection From Chest X-Rays: A Comparative Study Of Custom Cnn And Transfer Learning Architectures, Ahmed Sajim

Honors Theses

Pneumonia is a leading global cause of mortality, claiming approximately 2.5 million lives an-nually and placing exceptional diagnostic pressure on radiologists in resource-limited settings. Manual interpretation of chest X-ray (CXR) images is time-consuming, subject to inter-observer variability, and limited by radiologist availability. This thesis presents a systematic investiga-tion into deep learning-based automated pneumonia detection comparing five convolutional neural network (CNN) architectures: a custom-designed 2D CNN and four pretrained transfer learning models—ResNet, DenseNet, MobileNet, and VGG19.

A targeted data augmentation pipeline addresses the severe class imbalance in the Kag-gle Chest X-Ray Pneumonia dataset, expanding the Normal class from 1,583 to 9,495 …

Taphonomy And Fossil Record Of Eufistulana Mumia In The Owl Creek Formation Of The Mississippi Embayment, Riley Rilette

Honors Theses

This study examines the taphonomy and preservation of Eufistulana mumia, a boring bivalve, within the Owl Creek Formation of northeastern Mississippi. The formation was deposited in a shallow marine environment of Maastrichtian age within the Mississippi Embayment. A total of 66 specimens were collected from exposures within the formation and analyzed to evaluate morphometric variation and orientation patterns. Field measurements of trend and plunge of each specimen were recorded in situ using a geological compass, and specimens were later prepared and measured in the laboratory with digital calipers. Morphometric results show consistent tube morphology, with basal widths larger than distal …

Algorithm Performance In The Search For Hamiltonian Cycles, Chance Davis

Honors Theses

The Hamiltonian cycle problem is ubiquitous in both computer science and graph theory: Given a connected graph, a solution would either confirm the existence of a cycle which visits each vertex only once or its nonexistence. The importance of this problem, as well as its difficulty, is described in the Clay Mathematics Institute’s Millenium Prize Problems and Karp’s 21 NP-complete problems. Despite its “hardness,” solutions to the Hamiltonian cycle problem are desired in logistics, electronic circuit design, and network routing, among other fields. In this work, we benchmark a promising exhaustive enumeration algorithm on various graphs, including ones derived from …

Ai-Assisted 3d Pre-Visualization: Streamlining Animatics For Filmmakers, Nishit Thapa

Honors Theses

Pre-visualization is a core part of film pre-production. Creators use it to test blocking, lighting, camera movement, and spatial relationships before committing to a shot. Despite this, three-dimensional pre-visualization remains out of reach for many entry-level filmmakers, as the software is expensive and takes substantial time to learn.

Recent AI developments have produced generative systems capable of creating highly re-alistic imagery and video from text prompts. These systems open new possibilities for visual sto-rytelling but are not built for the iterative, hands-on process that pre-visualization requires, where creators must adjust scene parameters, camera logic, and spatial configurations throughout.

This thesis …

Evaluating Predictive Structure In Penny Stocks Using Machine Learning And Statistical Methods, Susom Hait

Honors Theses

Market prediction attempts have primarily focused on large-cap stocks due to their stability and market consistency. As such, studies that use time-series techniques to predict large-cap stocks have produced consistent results. Despite the success of large-cap predictions, penny stocks have remained unexplored in modern academia due to their high volatility, low liquidity, and structural instability. Regardless, unexplored market potential and technological advancements underscore the need for preliminary research into penny stock forecasting. This study aims to determine whether meaningful predictive structures exist in time-series penny stock data. This study utilizes an incremental approach. Various penny stocks were selected, pooled, and …

Multi-Jurisdictional Hazard Mitigation Plan For Landslides For The Kentucky River Area Development District, Kentucky, Hudson J. Koch, Matt M. Crawford, Jason M. Dortch

Contract Reports--KGS

Landslides are a widespread and complex geologic hazard that affects people and infrastructure. The Kentucky River Area Development District, Kentucky, sustains relatively high landslide activity that impacts several municipalities in eastern Kentucky. This hazard mitigation planning project outlines landslide hazard and risk assessments for the Kentucky River Area Development District, with information needed for each community in the region to develop mitigation strategies that will support infrastructure and development needs, land-use planning, situational awareness, and response and recovery actions for the communities.

Factors Associated With Lapses In Care Among People Living With Hiv In South Carolina, Xueying Yang Ph.D., Fanghui Shi, Shujie Chen, Gavi Samuel, Bankole Olatosi Ph.D., Sharon Weissman, Xiaoming Li Ph.D., Jiajia Zhang Ph.D.

Faculty Publications

Utilizing statewide electronic health records (EHR) data, this study aims to assess the factors determining the occurrence of lapses in HIV care among people with HIV (PWH) in South Carolina (SC). All adult (≥ 18 years old) PWH who were diagnosed with HIV between 2006 and 2018 with at least two HIV care encounters and at least 1-year follow-up record were included in the analysis. The outcome, a lapse in care, was defined as a repeated measure of HIV care encounter that occurs over a year following the previous visit. Generalized Estimation Equation models were employed. The study cohort had …

Fingerprinting Voice Commands Of Vpn-Protected Smart Speakers, Xiaoguang Guo, Keyang Yu, Qi Li, Dong Chen

Computer Science Faculty Research and Publications

Extensive recent research has shown that it is surprisingly easy to infer Amazon Alexa voice commands over their network traffic data. To prevent these traffic analytics (TA)-based inference attacks, smart home owners are considering deploying virtual private networks (VPNs) to safeguard their smart speakers. In this work, we design a new machine learning-powered attack framework—VoiceAttack that could still accurately fingerprint voice commands on VPN-encrypted voice speaker network traffic. We evaluate VoiceAttack under 5 different real-world settings using Amazon Alexa and Google Home. Our results show that VoiceAttack could correctly infer voice command sentences with a Matthews Correlation Coefficient (MCC) of …

Research Ethics: When Ethics And Legal Rules Collide: Breaking Terms Of Service To Collect Data, Michael Zimmer, Casey Fiesler, Jessica Vitak

Computer Science Faculty Research and Publications

In many ethics classes, one of the early lessons is distinguishing between ethics and law. Ethics are the moral principles that guide decisions based on values, commitments, and purposes. Laws, by contrast, are formal rules enforced by social institutions to regulate behavior. Ethics and law frequently overlap: most people recognize that stealing is (almost always) ethically wrong, and it is also illegal. There are, of course, exceptions often discussed in ethics courses, such as the classic dilemma of stealing for a morally compelling purpose (e.g., to feed the poor).

Federated Retrieval-Augmented Generation For Cybersecurity In Resource-Constrained Iot And Edge Environments: A Deployment-Oriented Scoping Review, Hangyu He, Yuan, Kai Wu, Wei Ni

Research outputs 2022 to 2026

Cybersecurity operations in IoT and edge environments require fast, evidence-grounded decisions under strict resource and trust constraints. While large language models can support triage and incident analysis, their parametric knowledge may be outdated and prone to hallucination. Retrieval-augmented generation (RAG) improves grounding by conditioning responses on retrieved evidence, but also introduces new risks such as knowledge-base poisoning, indirect prompt injection, and embedding leakage. Federated learning enables collaborative adaptation without centralizing sensitive data, motivating federated RAG (FedRAG) architectures for distributed cybersecurity deployments. This study presents a deployment-oriented scoping review of FedRAG for cybersecurity. The review follows PRISMA-ScR reporting guidance and synthesizes …

Ai Models As Cultural Beings: Investigating Ai Cultural Biases And The Impact Of Cultural Alignment On Human-Ai Creative Collaboration, Choon Ngee Tan, Meng Han, Roy Y. J. Chua, Chi-Ying Cheng

Research Collection Lee Kong Chian School Of Business

Existing research on AI cultural biases predominantly focuses on Western models, overlooking critical gaps in non-Western models. We conduct a comparative analysis of AI models – ChatGPT (U.S. developed) and ErnieBot (China developed) – from different cultures to investigate how corresponding cultural biases manifest in their outputs. Additionally, we examine how cultural alignment between human users and AI models impacts their collaborative creative performance and the underlying psychological mechanisms. In Study 1, multi-choice prompt with zero-shot technique was used to evaluate cultural biases in four widely used AI models – ChatGPT-3.5/4, ErnieBot-3.5/4 – comparing their responses to established cultural psychometric …

Fluid-Mediated Particle Transport: Revisiting Snowstorm Simulations In 2d With An Updated Pressure Calculation Algorithm, E. Maldonado, Michael W. Roth

The Compass: Earth Science Journal of Sigma Gamma Epsilon

We develop and present computer simulations of snowfall and snowfall management near buildings using deflection fins. Our approach first entails a numerical solution to the Navier – Stokes fluid dynamics equations in order to determine wind velocity profiles with and without deflection fins. Subsequent to finding the velocity field, snow particles are introduced and are subject to Newton’s Laws in order to allow transport, sticking to surfaces, landing and ultimately accumulation. We revisit previous work, presenting and discussing program construction and validation, along with cursory systematic studies of varying geometrical parameters in the simulation. The utility of the simulations is …

Sigma Gamma Epsilon Student Research Poster Session, Geological Society Of America Annual Meeting 2025, San Antonio, Texas, Usa, Scott R. Beason, Lee S. Potter

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Society of Sigma Gamma Epsilon (SGE) sponsors a poster session at every annual meeting of the Geological Society of America. The 37th SGE undergraduate research poster session took place during the 2025 Geological Society of America Annual Meeting (GSA Connects) in San Antonio, Texas, USA, on Monday, October 20, 2025. Fifty-seven (57) posters were presented in Exhibit Hall 1 at the Henry B. Gonzalez Convention Center between 8:30 AM and 5:30 PM at the poster session, with authors present between 9:00 AM and 11:00 AM. Titles, authors (italics for the presenting author), affiliations, and abstracts for each poster are …

Experimental And Computational Investigations Of Li-Ion And Na-Ion Battery Cathode Materials, Shintaro Inaba , ‘26

Senior Theses, Projects, and Awards

Batteries allow storage of chemical energy and controlled conversion of energy as electricity. Known to mankind since the eighteenth century, batteries have been vital in manufacturing, service industry, and use of portable electronics and electric vehicles. These systems utilize rechargeable batteries, where redox reactions are practically reversible. Lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs) are two rechargeable systems that are widely explored in the field of electrochemistry and electrical engineering due to their abundance of materials, relative safety, energy density and power density. Discovery and optimization of those battery materials are crucial in improving their performance and accelerating commercialization. In …