Physical Sciences and Mathematics Commons^™

Near-Earth Object (Neo) Surveyor Development: Challenges And Opportunities In Support Of Planetary Defense, G. Loftus, B. Carlsen, P. Scott, S. Backlund, L. Reinhart, T. Martin, T. Hoenes, R. Burgon, S. Ashby, J. Peterson, B. Lamborn, J. Bowman

Space Dynamics Laboratory Publications

The Near-Earth Object (NEO) Surveyor mission is a key element in our future planetary defense portfolio, which will survey our solar system in the infrared to discover and characterize asteroids and comets.

The mission is designed to detect, track, and characterize small bodies throughout our solar system. By United States Congress mandate, NASA must discover more than 90% of all asteroids and comets that are larger than 140 meters in diameter and could potentially impact Earth. NEO Surveyor will provide critical decision support for stakeholders who must assess the risks of NEO impacts to Earth and identify potential mitigation strategies. …

Assessment Of H2s-Induced Cracking Susceptibility In Steam Line Pipes And Weld Zones During Geothermal Well Construction, Riene Kaelamanda Pragitta, Yudha Pratesa

Journal of Materials Exploration and Findings

The susceptibility of steam line pipes, especially in the HAZ (heat-affected zone) and weldment areas, to hydrogen sulfide in the geothermal industry is crucial to understand from the early stages, particularly during construction. The combination of tensile stress from residual stresses after welding and metallurgical phase transformation makes the joint areas vulnerable to sulfide stress cracking. This condition becomes even more extreme when the equipment operates during the well stimulation phase. This research assesses the severity of H₂S-induced cracking using NACE MR0175 and ISO 15156-1 standards, focusing on the effects of pH and partial pressure of H₂S (p_{H₂S …}

Fossil Leaf Cuticle: Best Practices For Preparation And Paleo-Co2 Analysis, Xiaoqing Zhang, Dana L. Royer, Carina E. Colombi, Juan Martin Drovandi, Jennifer C. Mcelwain, Gaëtan Guignard, Qin Leng, Barry H. Lomax, Nathan D. Sheldon, Rebekah A. Stein, Garland R. Upchurch, Yongdong Wang, Hong Yang, Richard S. Barclay, Ying Cui, Wolfram Kürschner, Joseph N. Milligan, Isabel Montañez, Jon D. Richey, Tammo Reichgelt, Gongle Shi, Selena Y. Smith, Margret Steinthorsdottir

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Leaf cuticle is the waxy envelope that protects leaves from desiccation, UV damage, and abrasion. The cuticle encodes information about a plant's chemistry and leaf epidermal and stomatal cell morphology. Fossil leaf cuticle has been used to determine taxonomic affinities for almost two centuries and recognized in recent decades for its value in reconstructing paleoenvironments and paleoclimates, especially atmospheric CO2. Fossil leaf cuticle preparation techniques are typically reported as single workflows tied to individual studies, starting with finding fossils in the field through the steps of preparing cuticle for chemical and morphological analysis, including decisions about type of microscopy and …

Wildfires Impact On Water Treatment, Alli Willmarth, Matthew Jorgenson, Kyle Shimabuku

CURCI Student Research

Study Objective: Determine the effectiveness of using powder activated carbon to remove wildfire dissolved organic matter (DOM).

Usage Of Natural Language Processing And Deep-Learning Techniques On Thematic Apperception Tests To Predict Big Five Personality Traits, Blayten Jones

Electrical Engineering and Computer Science Undergraduate Honors Theses

The usage of personality as a method of behavioral prediction and outcomes of success has grown considerably over the last few decades. This project explores predicting user personality profiles via the Big Five personality index through the integration of advanced natural language processing techniques as well as neural networks. Using a dataset provided by Dr. James W. Pennebaker, participants analyze an image—formally referred to as a thematic apperception test—and write a thorough paragraph describing the details. This free-form text, along with their personality test results, is captured in a structured dataset. Many deep-learning and machine learning models have been used …

A Novel Approach To Attention-Based Models In Image Completion: Weighted Spatial-Attention Using Radial Distance, Tyler D. Kuper

Electrical Engineering and Computer Science Undergraduate Honors Theses

Humans infer missing visual information by focusing on spatial relationships in the context of their surroundings. Machine learning aims to replicate this skill through image completion, a fundamental task in current computer vision research. While advances in self-attention layers have recently enhanced generative machine learning models for text, these mechanisms still currently lack the capability to handle sparse image completion efficiently. We introduce a distance-based attention mechanism that uses radial-based weights to efficiently reconstruct an image. We compare this attention mechanism with self-attention and a fully connected network on an image completion task using the MNIST dataset. Our results show …

Fairness In Recommender Systems: Balancing Bias In Academic Paper Selection, Zachary Bergin

Electrical Engineering and Computer Science Undergraduate Honors Theses

Bias in academic paper selection remains a consistent issue, even within processes designed to promote fairness, such as double-blind peer review, bias stays persistent. In this paper we investigate demographic bias while particularly focusing on racial bias in the process of selecting academic papers and explore the impact of fairness aware recommender systems on the demographic parity. To build an effective system our focus is on the Special Interest Group on Computer Human Interaction (SIGCHI) a pillar in the community, we develop a neural network-based recommender system that uses real demographic data collected by other systems withing the context of …

Leveraging P4 Programmable Switches For Resilient Operation And Design Of Phasor Measurement Unit Networks, Eva Casto

Electrical Engineering and Computer Science Undergraduate Honors Theses

The power grid utilizes a device called the phasor measurement unit (PMU), allowing power system administrators to remotely monitor and manage the state of the grid in Wide Area Monitoring Systems (WAMS). The advantages of PMUs – such as fine-grained, time-synchronized measurements and efficient, decentralized monitoring – are what make them key devices in the power grid. However, PMU technology also comes with new threats of the digital age, like malfunctions and cyberattacks, which can result in missing and faulty measurements that compromise power grid observability. P4 programmable networks can be used to detect faulty PMU data in a decentralized, …

An Introductory-Level Undergraduate Cs Course That Introduces Parallel Computing, Tia Newhall, Kevin C. Webb, Vasanta Chaganti, Andrew Danner

Computer Science Faculty Works

We present the curricular design, pedagogy, and goals of an introductory-level course on computer systems that introduces parallel and distributed computing (PDC) to students who have only a CS1 background. With the ubiquity of multicore processors, cloud computing, and hardware accelerators, PDC topics have become fundamental knowledge areas in the undergraduate CS curriculum. As a result, it is increasingly important for students to learn a common core of introductory parallel and distributed computing topics and to develop parallel thinking skills early in their CS studies. Our introductory-level course focuses on three main curricular goals: 1) understanding how a computer runs …

Diversity-Augmented Training For Generalizable Ai Agents, Wenjun Li

Dissertations and Theses Collection (Open Access)

Deep Reinforcement Learning (RL) has achieved remarkable success over the past decade, from superhuman performance in video games to real-world applications like robotics. However, RL models often lack generalization, making them unreliable when deployed in unfamiliar scenarios. For example, robots must adapt to varying terrains with different slopes and obstacles, yet standard RL training does not explicitly promote such adaptability. While various methods have been proposed to enhance RL robustness, achieving reliable generalization remains an open challenge.

This dissertation focuses on improving the generalization capability of agents in three major settings: infinite horizon RL agents, finite horizon RL agents, and …

2025 May - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

For May 2025, the main weather/climate stories were the continued pattern of severe weather impacting Tennessee as well as Chattanooga recording their wettest May in the 147-year weather history of the city. Starting with the record rainfall in Chattanooga, the Chattanooga airport weather station recorded a total of 12.02-inches of rainfall over May 2025, 8.08-inches above normal and 0.02-inches above the previous record wettest May in 1929. Many other areas of East Tennessee and the Cumberland Plateau also had well above normal rainfall this month, but they were emerging out of a drought from last fall and winter …

Statistical Designs For Learning User Preference And Experience, William S. Fisher

All Dissertations

For any organization, designing a new product or planning the features of a new service is a complex decision-making process which depends on understanding its users' preferences and the experiences they have with prototypes of the new product or service. Design of experiments (DOE) offers a framework to aid in the modeling and collection of data to learn user preferences and experiences to facilitate this decision-making process. Questions such as ``which of our newly proposed products is preferred most by our customers" and ``which version of our new service results in the highest monthly revenue" can be readily addressed by …

From The University To The Universe: Byu’S West Mountain Observatory, Amber Zendejas, Dan Broadbent

BYU West Mountain Observatory Project

Brigham Young University’s West Mountain Observatory (WMO) is a research facility that offers primarily undergraduate students valuable mentoring and hands-on learning opportunities. Established in 1981, the observatory was built in response to increasing light pollution in Provo, Utah, which began affecting research at the Orson Pratt Observatory (OPO) atop the Eyring Science Center on the BYU main campus. Before WMO was created, OPO served as the primary observatory for astronomical research at BYU. Construction plans for a new observatory began in the late 1970s, as university planners and astronomers sought a location with minimal light pollution, favorable elevation, relatively easy …

Understanding University-Level Food Recovery Programs’ Approaches To Minimizing Food Waste While Combating Food Insecurity In The United States, Ella F. Flesher

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Food is wasted every day at each level of the food system from production to consumption. This surplus has significant negative impacts on the environment after food is sent to the landfill and allowed to rot. However, some surplus food can be repurposed and diverted from the landfill. This study served as an initial investigation to explore multiple food waste diversion programs and analyze their structure, best practices, and methods to divert leftover food. This study specifically aimed to compare and contrast food recovery programs by interviewing participants from three food recovery programs from different university institutions. With the key …

Land8fire: A Complete Study On Wildfire Segmentation Through Comprehensive Review, Human-Annotated Multispectral Dataset, And Extensive Benchmarking, Anh Tran

Data Science Undergraduate Honors Theses

Early and accurate wildfire detection is critical for minimizing environmental damage and ensuring a timely response. However, existing satellite-based wildfire datasets suffer from limitations such as coarse ground truth, poor spectral coverage, and class imbalance, which hinder progress in developing robust segmentation models. In this paper, we introduce Land8Fire, a new large-scale wildfire segmentation dataset composed of over 20,000 multispectral image patches derived from Landsat 8 and manually annotated for high-quality fire masks. Building on the ActiveFire dataset, Land8Fire improves ground truth reliability and offers predefined splits for consistent benchmarking. We evaluate a range of state-of-the-art convolutional and transformer-based models, …

Design, Testing, And Characterization Of A Dc-Discharge Miniature Gridded Ion Thruster, Ishaan Mishra

Senior Project - Physics and Optical Engineering

Gridded Ion Thrusters are a satellite propulsion system that generate a Low- Temperature Plasma and electrostatically accelerates the ions to produce thrust at a high specific impulse. This work presents the design, testing, and initial characterization of a 3- cm diameter DC-discharge ring-cusp Gridded Ion Thruster that utilizes Argon as a propellant. The test infrastructure including vacuum chamber, propellant feed system, and power supplies are detailed, and operation of the ion thruster described. The material selections and design details have been presented, along with characterization based on steady-state propellant and power inputs described. In addition, a Heaterless Hollow Cathode design …

Accelerating Knowledge Graph And Ontology Engineering With Large Language Models, Cogan Shimizu, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Large Language Models bear the promise of significant acceleration of key Knowledge Graph and Ontology Engineering tasks, including ontology modeling, extension, modification, population, alignment, as well as entity disambiguation. We lay out LLM-based Knowledge Graph and Ontology Engineering as a new and coming area of research, and argue that modular approaches to ontologies will be of central importance.

Education In The Era Of Neurosymbolic Ai, Chris Davis Jaldi, Eleni Ilkou, Noah Schroeder, Cogan Shimizu

Computer Science and Engineering Faculty Publications

Education is poised for a transformative shift with the advent of neurosymbolic artificial intelligence (NAI), which will redefine how we support deeply adaptive and personalized learning experiences. The integration of Knowledge Graphs (KGs) with Large Language Models (LLMs), a significant and popular form of NAI, presents a promising avenue for advancing personalized instruction via neurosymbolic educational agents. By leveraging structured knowledge, these agents can provide individualized learning experiences that align with specific learner preferences and desired learning paths, while also mitigating biases inherent in traditional AI systems. NAI-powered education systems will be capable of interpreting complex human concepts and contexts …

Optimal Experimental Plan For Multi-Level Stress Testing Under Progressively Hybrid Censoring, David Kojo Amakye

Open Access Theses & Dissertations

Reliability analysis is essential for understanding how products perform over time, particularly in environments where failure data is limited or costly to obtain. One effective approach is multi-level stress testing, where test units are subjected to varying levels of stress to accelerate failures and extract more information within constrained timeframes. This study presents a novel optimization-based framework for designing life-testing experiments under progressively Type-II hybrid censoring, assuming Weibull lifetime distributions. Leveraging a Variable Neighborhood Search (VNS) algorithm, we determine efficient allocations of test units and censoring parameters across multiple stress levels to enhance the precision of estimates of the model …

Electrodeposition Of Gallium Nitride_Unraveling The Role Of Precursors, Deposition Conditions, And Substrate Effects For Semiconductor Applications, Mauricio Azier Leyva Aranzabal

Open Access Theses & Dissertations

Gallium nitride (GaN) is a wide-bandgap semiconductor noted for its remarkable optoelectronic and structural characteristics, rendering it a potential material for high-power, high-frequency, and optoelectronic device applications. This dissertation investigates the electrochemical synthesis of GaN thin films by potentiostatic and galvanostatic electrodeposition techniques using aqueous solutions of gallium nitrate (Ga(NO3)3), ammonium nitrate (NH4NO3), and auxiliary agents like potassium nitrate and urea. The main aim is to examine the essential elements affecting nitrogen incorporation and film shape while assessing electrochemical performance on various conductive substrates.A thorough investigation was performed to evaluate the impacts of electrodeposition duration, electrolyte pH, precursor molar concentrations, …

A Study Of End-Cut Preference In Tree-Based Modeling, Xiangya Wang

Open Access Theses & Dissertations

Decision trees, particularly those built using the Classification and Regression Trees (CART) algorithm, are widely used for their interpretability and flexibility. However, the greedy nature of the CART splitting procedure gives rise to the end-cut preference (ECP) phenomenon, wherein split points near the extremes of predictor ranges are favored. This study offers a comprehensive investigation of ECP, exploring its theoretical underpinnings, practical manifestations, and implications for both single decision trees and ensemble methods such as Random Forests. Through theoretical analysis and simulation studies, we examine how ECP affects tree structure, variable selection, and predictive accuracy across tree-structured, linear, and nonlinear …

Navigating The Challenges Of Coccidioides Surveillance: Insights From The Environment Of El Paso County, Texas, Tanzir Hossain

Open Access Theses & Dissertations

Coccidioidomycosis, or Valley fever, is a fungal infection resulting from the inhalation of spores from the Coccidioides species (C. immitis and C. posadasii), native to arid areas of the Western Hemisphere. Coccidioidomycosis presents considerable health hazards and can be fatal. It affects between 206,000 and 360,000 individuals annually, leading to 700 to 1,100 fatalities in the United States alone. In response to these issues, extensive research has concentrated on therapeutic goals for this infectious disease. Nonetheless, more limited research has focused on the environmental detection of its causative fungi, which is crucial for forecasting treatment needs and formulating preventive strategies. …

Artificial Intelligence In Modern Game Development, Karan Raval

ART 108: Introduction to Games Studies

Artificial intelligence has transformed the landscape of game development in ways early pioneers could only imagine. In my project I explore four major phases of AI evolution: classical AI methods, the rise of machine learning, the advent of transformer architectures, and a spirited debate about whether transformers truly think. To illustrate these shifts I use examples like MYCIN, which helped doctors decide treatments, and Deep Blue, which beat a world chess champion. You’ve probably lost track of time exploring an open world that adapts to your choices, right? That sense of immersion is powered by AI behind the scenes. From …

2025 May 1 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Silver Nanoparticles In Ammonia Sensing And Photovoltaics, Madhuka Liyanage

All Dissertations

Nanocomposite films (NCF) containing silver nanoparticles (AgNPs), separated by thin layers of silica/poly-4-vinylpyridine/polyvinylpyrrolidone, were fabricated via drop casting, spin coating, dip coating on glass substrate and drop casting on nylon filter membranes. The more uniform films were produced by drop casting on nylon filter membranes due to their solvent wicking properties. The films demonstrate electrical conductivity that varies in response to moist ammonia and water vapors. The changes in conductivity are attributed to hydrogen bonding between ammonia and water molecules with the silica/polymer layers, as well as the direct adsorption of ammonia onto the silver surface. Notably, NCFs with polyvinylpyrrolidone …

Growth, Cladding, And Characterization Of Single Crystal Optical Fiber: The Next Evolution In Directed Energy Systems, Allen Benton

All Dissertations

High-power fiber lasers are steadily increasing in maximum power and rapidly approaching theoretical maximum power output from a single fiber aperture. The low thermal conductivity of silica fibers is an inherent limitation to the dissipation of heat from the fiber core, and the buildup of heat within the laser gain media is the principal driver of transverse mode instability within fiber systems. This limitation necessitates the exploration of alternate fiber host materials. Due to their high thermal conductivity, excellent transmission range, ability to host most of the optically active rare earth ions, and success as bulk laser materials, single-crystalline YAG …

Qualitative And Quantitative Analysis Of New Psychoactive Substances And Related Metabolites Using Liquid Chromatography-Ion Mobility-Mass Spectrometry (Lc-Im-Ms), Ralph Aderorho

All Dissertations

The increasing prevalence of novel psychoactive substances (NPS) in illicit drug markets has posed significant challenges for forensic and clinical toxicology, primarily due to the structural similarity and diversity among these compounds. This dissertation investigates the application of advanced liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS/MS) techniques, using the high-resolution Structures for Lossless Ion Manipulations (SLIM) platform and the drift tube ion mobility spectrometry (DT-IMS), for the qualitative and quantitative analysis of various types of synthetic opioids, synthetic cannabinoids, psychedelics and xylazine. By combining IMS separations with mass spectrometry and targeted chemical derivatization, this work enhances the ability to distinguish and characterize …

The Evolution Of Nanoparticles In Nanoparticle Doped Optical Fibers, Mary Cahoon

All Dissertations

Optical fiber and fiber laser technologies based on silica glass are critical to many technologies today. One method to improve the optical performance of laser fibers is engineer the local environment around the active elements in the glass. To that end, this Dissertation focused on the fabrication and characterization of fibers made with nanoparticles incorporated into the glass to control the local composition. First, the nanoparticle composition and structure was analyzed as it evolved from from the initially-synthesized form to incorporation into the dense aluminum-silicate glass. The aluminum oxide in the glass was found to be important not only to …

Robust And Efficient Solvers For Physics-Based Pde’S, Elizabeth Hawkins

All Dissertations

This work was partially supported by the U.S. Department of Energy under award DE- SC0025292, by NSF grant DMS 2152623, and by NSF grant DMS 2011490.

This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Mathematical Multifaceted Integrated Capability Centers (MMICCs) program, under Field Work Proposal 22-025291 (Multifaceted Math- ematics for Predictive Digital Twins (M2dt)), Field Work Proposal 23-020467, and Computing and Information Sciences (CIS) investment area in the Laboratory Directed Research and Development program at Sandia National Laboratories. This written work is authored by an employee …

Decision Space Decomposition For Multiobjective Programs, Emma Soriano

All Dissertations

Being inspired by the parametric decomposition theorem for multiobjective optimization problems (MOPs) of Cuenca and Miguel (2017), and by the block- coordinate descent for single objective optimization problems, we present a decom- position theorem for computing the set of minimal elements of a partially ordered set. This set is decomposed into subsets whose minimal elements are used to retrieve the overall minimal elements. We apply this approach to strictly convex MOPs de- composing their decision space into lines. The line decomposition benefits from the fact that a multiobjective line search problem is equivalent to solving a collection of single objective …