Digital Commons Network^™

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 …

Effects Of Thermal Interface Materials On Thermal Conductivity Measurement Using A Modified Astm D5470 Thermal Resistance Tester, Chinmaya Joshi

Mechanical Engineering Undergraduate Honors Theses

In this paper, we have investigated the effect of thermal interface materials (TIMs) on the accuracy and uncertainty of thermal conductivity measurements. A modified ASTM D5470 thermal resistance tester (TRT) is developed to measure the out-of-plane thermal conductivity of pyrolytic graphite (PG) and grade 2 titanium (TiG2) with and without TIMs. Compared to the ASTM D5470 standard, this modified design uses three thermocouples per side to support regressive analysis and explores the use of TIMs.s Nine PG samples and four TiG2 samples of varying thickness have been tested to obtain thermal resistance as a function of sample thickness. The steady-state …

Investigation Into The Microbiome Of Blow Fly Eggs Using Microseqtm Id, Samantha S. Davis, Drusilla Sheridan, Jennifer Rosati

Undergraduate Research

There is little published research characterizing the microbiome associated with blow fly eggs and how they may affect the colonization behaviors of certain blow fly species. Once deposited, blow fly eggs are rapidly introduced to a diverse range of microorganisms, which can vary depending on the species of blow fly, the environment, and the decomposition stage of the substrate (Junqueira et al., 2017). Since blow flies are among the first insects to colonize decomposing remains, the microbial communities present on their eggs could serve as key indicators of the decomposition stage at the time of egg-laying, thus providing a potential …

Deleting Values May Either Increase Or Decrease Variance, David L. Farnsworth

Articles

The impact upon variance when a value is deleted is addressed. It is shown that the cutoff for the deleted value yielding an increase or a decrease in variance is approximately one standard deviation from the mean for a univariate random variable with equally distributed probability on a finite set of elements and for a univariate set of observations. The influence of truncation of the domain for such a discrete random variable and for observations is considered.

Comparative Analysis Of The Community Reinvestment Act And The B Impact Assessment, Ella G. Claborn

Finance Undergraduate Honors Theses

This thesis presents a comparative analysis of the Community Reinvestment (CRA) and the B Corp Certification through the B-Impact Assessment (BIA). The CRA was enacted in 1977 and is a mandatory regulatory measure aimed at addressing discriminatory lending practices and encouraging equitable credit distribution in underserved communities. In contrast, the BIA is a voluntary assessment developed by the nonprofit B Lab to evaluate a company’s social, environmental and governance practices, which lead to B Corp Certification. This analysis explores the historical background, mission, methodology, success metrics and financial costs associated with each framework. Ultimately, this thesis highlights how both models, …

Minimizing Uncovered Triples: An Integer Programming Approach To College Football Conference Scheduling, Caleb Mallett

Industrial Engineering Undergraduate Honors Theses

Collegiate football teams often compete in groups of 8-20 teams known as conferences. One such conference, the Atlantic Coastal Conference (ACC), added three new schools for the 2024-25 season, bringing their total to 17 teams. Currently, each ACC team plays eight games against others within the ACC. At the season’s conclusion, the two ACC teams with the best intraconference record compete in a conference championship game. With 17 total teams each playing eight games, the ACC could have a three-way tie for the best record where none of top the three teams play one another. To avoid this situation, we …

Earthscape Ai Dataset V1.1, Matthew Massey, Abdullah-Al-Zubaer Imran

Research Data--KGS

EarthScape v1.1 Dataset Download Links:

esv1p1_smokeset.zip (197 MB)

esv1p1_splits.zip (2.5 MB)

esv1p1_usa_ky_data.zip (1 MB)

esv1p1_usa_ky_hardin_howevalley.zip (26.3 GB)

esv1p1_usa_ky_hardin_sonora.zip (26.3 GB)

esv1p1_usa_ky_warren.zip (166 GB)

Surficial geologic mapping is essential for understanding Earth surface processes and supporting applications in engineering, hazard assessment, and resource management. However, traditional mapping approaches are labor-intensive, limiting spatial coverage and introducing subjectivity. To address these challenges, we introduce EarthScape, a multimodal, AI-ready geospatial dataset designed for surficial geologic mapping and Earth surface analysis. EarthScape integrates high-resolution aerial RGB and near-infrared (NIR) imagery, digital elevation models (DEM), multi-scale terrain features derived from DEMs, and hydrologic and infrastructure vector …

The Impact Of Irrigation On Agricultural Land Values In The United States Southeast And An Analysis Of Farmland Prices In South Carolina, Christopher L. Thomas

All Theses

Land is a key component of the agriculture industry in the United States. According to the United States Department of Agriculture, farm real estate (land and buildings) accounted for 82.8% of total US farm sector assets in 2022, consequently making land the largest source of wealth in a farmer’s investment portfolio and the primary source of collateral used for farm operating loans. The Southeastern region of the United States has seen rapid farmland appreciation and intense population growth in recent years. This research investigates the rising farmland prices across the Southeast from both a regional and state-level perspective. Chapter Two …

Modeling Dna Repair In Escherichia Coli Using A Boolean And Stochastic Framework, Gabrianne Ivey

All Theses

DNA can be damaged through both internal and external sources. Therefore, cells have created methods to repair DNA damage. In Escherichia coli, the system responsible for DNA repair is termed the SOS response. This system consists of more than 50 genes and contains three main repair pathways: nucleotide excision repair, translesion synthesis, and homologous recombination. The response is initiated when DNA lesions result in the accumulation of single-stranded DNA (ssDNA). The protein RecA is activated by binding to ssDNA and is then denoted RecA*. RecA* assists in the auto-cleavage of LexA which is the primary repressor protein involved in …

Performance Of Inline Compression With Software Caching For Reducing The Memory Footprint In Pysdc, Emily Lattanzio

All Theses

The volume of data required for High Performance Computing (HPC) applications is growing faster than the memory storage available to store the required data, leading to performance bottlenecks in transferring data. Whether sending data from main memory to computation nodes or between parallel processes during runtime, the more data there is to send, the longer it will take to for that data to be sent from one location to the next. Hence the need for inline data compression, which reduces the amount of allocated memory needed by storing the largest data structures in a compressed format and decompressing/recompressing single variables …

Fit To Stay: Understanding The Impact Of Person-Group Fit On Transfer Intentions In College Sports, Marlee Johnson

All Theses

NCAA policy changes in 2021 regarding student-athlete transfer and external compensation have brought attention to the issue of turnover in college sports. Organizational psychologists have been studying turnover intentions and psychological antecedents of turnover intentions for years; however, little is known about the psychological variables that lead student-athletes to develop transfer intentions. The aim of this study was to explore the influence of both perceived supplementary and complementary person-group (PG) fit on student-athletes’ transfer intentions. It also examined affective commitment as a mediator between supplementary PG fit and intention to transfer and perceived team performance as a moderator in the …

Evaluation Of Pre-Trained Vision Language Models In Challenging Contexts, Kankan Zhou

Dissertations and Theses Collection (Open Access)

The rapid advancement and proliferation of pre-trained vision-language models (VLMs) have heralded a new era in the realm of artificial intelligence (AI), opening up unprecedented opportunities and challenges alike. This dissertation sets forth on an ambitious and comprehensive journey to critically evaluate the performance and limitations of pre-trained VLMs, particularly in complex and challenging contexts that test the bounds of their capabilities. Our focus is twofold: to rigorously assess the extent of bias embedded in these models, and to meticulously scrutinize their reasoning abilities, highlighting parallels and disparities between machine and human cognition.

We initiate our exploration with a targeted …

Path Tracing And Physically-Based Rendering With Directx Raytracing, Jiabin Wang

Programming Theses and Dissertations

This artifact is designed to simulate global illumination by using DirectX raytracing pipeline. Physically-based Rendering (PBR) and path tracing were integrated to achieve photo realistic rendering effect.

Full-Stack Web Applications: Industry Standard Frameworks, Libraries & Technologies, Yassine Chahid, Patrick Slattery

Publications and Research

This research explores emerging full-stack web development technologies across front-end, back-end, and DevSecOps domains. It evaluates modern tools including Django, React, and TypeScript—focusing on their key features such as compile-time error checking—through to the development of a web application. By examining documentation for the frameworks Node.js, Next.js, Tailwind CSS, and others, along with the deployment tools Docker and Git for version/release control, the study analyzes how these innovations speed up development, improve existing practices, and have often replaced older technologies. Cloud solutions for tasks such as authentication and deployment will also be evaluated, along with various web-application technology stacks and …

Design And Analysis Of An Isolated Resonant Pulsed Dc-Dc Buck-Boost Converter, Edgar Arturo Mora Tena

Master's Theses

This thesis entails the design, modeling, simulation, construction, and analysis of a new isolated DC-DC buck-boost converter with Zero-Current-Switching (ZCS) operation, continuous input current, and a low-side switch to simplify driving requirements. The proposed converter was designed to regulate a 5V output from an input range of 15V-18V, at a rated output power of 20W, and a switching frequency range of 90kHz-500kHz. Software simulations are performed to develop a mathematical model that describes the converter’s modes of operation, as well as the current and voltage waveforms of the resonant power components. Results from hardware experimentation confirm that the converter effectively …

Impacts Of Temperature Acclimation On Swimming Performance And Metabolic Dynamics Of The Amargosa River Pupfish, Cyprinodon Nevadensis Amargosae, Teresa E. Guerre

Master's Theses

Climate change is leading to warmer atmospheric temperatures in many regions of the world, which in turn is raising the temperatures of aquatic habitats and simultaneously shifting the frequency and severity of extreme precipitation events. In fishes, metabolic demands are higher under warmer conditions, while dissolved oxygen levels typically decline in warmer water. This mismatch may limit the ability of fishes to cope with high water flow events like floods that can occur following extreme rainfall. A few species of pupfishes (genus Cyprinodon) in the Death Valley region of California and Nevada, USA, occupy stream or river habitats with …

Maternal Occupational Exposure To Noise, Kristen W. Van Buren, Carissa M. Rocheleau, I. Chen Chen, Wayne T. Sanderson, Leslie A. Macdonald, Elizabeth A. Masterson, Eirini Nestoridi, Elizabeth C. Ailes

Epidemiology and Environmental Health Faculty Publications

Objectives We investigated associations between occupational noise and gestational diabetes mellitus, pregnancy-related hypertension (including pre-eclampsia/eclampsia), preterm birth and small for gestational age (SGA) infants. Methods Data were analysed for 7889 singleton, live-born infants without major birth defects or chromosomal disorders and their mothers from the National Birth Defects Prevention Study from 1997 to 2011. Typical maternal occupational noise exposure in all jobs held from 1 month prior to conception through the end of pregnancy was estimated by expert rater and categorised as quiet (<60 A-weighted decibels (dBA)), low (60-75 dBA), moderate (76-84 dBA) or loud (>85 dBA). Multiple logistic regression was used to estimate associations (adjusted ORs and 95% CIs) between …

Development Of Novel Pharmaceutical For Optimization Of Opioid Overdose Treatment, Larae Kram

Celebrating Scholarship and Creativity Day (2018-)

Although opioids are highly effective drugs for pain management, their overuse and addictive nature has caused an opioid epidemic, resulting in many cases of opioid addiction and overdose. There are two current opioid overdose drugs that are FDA approved: naloxone and nalmefene. These drugs have a higher affinity to the active binding pocket on the opioid receptor than opioids do and displace the opioids, preventing any further binding of the opioid and halting the opioid’s effects. However, naloxone is not active long enough to outlast the duration of the opioid and nalmefene causes severe withdrawal symptoms. The development of more …

Performance Optimization Of A 1:10 Scale Radio-Controlled Car Through Aerodynamic And Mechanical Enhancements, George Kerner

Celebrating Scholarship and Creativity Day (2018-)

Changes in the performance of a 1/10 scale radio-controlled car due to various mechanical and aerodynamic modifications were investigated. The car’s mechanical performance was evaluated by measuring lap times on custom figure-eight and oval tracks to assess handling. A straight 60-foot track was used to measure acceleration times. Mechanical modifications included a low-center-of-gravity chassis, a higher power motor, and wider street tires to optimize suspension, drivetrain, and grip. Aerodynamic enhancements included the integration of front and rear spoilers, a diffuser, and an undertray all designed using Autodesk Fusion. All aerodynamic components were 3D printed and mounted to the vehicle for …

Applause, Anonymous

Touche Ross Publications

No abstract provided.

Exploring Teachers' Experiences Developing Adaptive Learning Systems With High-Stakes Testing Requirements: A Transcendental Phenomenological Study, Brian J. Le Fevre

Doctoral Dissertations and Projects

The theory that guided this study was Bandura’s self-efficacy theory, which was utilized to relate to teachers’ beliefs about engaging in behaviors influenced by high-stakes testing. A transcendental methodology was used for the study design as the study aimed to explore teachers’ shared experiences while bracketing my previous experiences. The sample population consisted of second- to sixth-grade teachers who instructed subjects who were assessed by high-stakes testing in the Southeastern United States. Data was collected using interviews, focus groups, and journal prompt responses. Following data collection, the data was coded and analyzed to develop the essence of the shared experiences …

Resonating Patterns: Adaptive Resonance Theory And Self-Organizing Maps, Meeti Dixit

Theses

Adaptive Resonance Theory (ART) represents a powerful neural network architecture designed to address the stability-plasticity dilemma. Its primary objective is to enable rapid learning without compromising retention. ART embodies characteristics of self-organization and self-stabilization, distinguishing it from traditional neural networks. Unlike error-based learning prevalent in conventional models, ART employs competitive learning mechanisms. One of the distinguishing features of ART is its involvement in hypothesis testing, a departure from the approach of deep learning. This capability allows ART to learn dynamically in real-time environments. Over time, various ART models have emerged that cater to different types of data, such as binary …

Predicting Student Dropout Risk Using Machine Learning, Fatma Alameri

Theses

Student dropout remains a persistent challenge in higher education, undermining institutional performance, reducing workforce preparedness, and limiting students’ academic and economic opportunities. Accurately identifying students at risk of attrition is complex, due to the interplay of academic, financial, and behavioral factors. This thesis addresses this challenge by applying a combined machine learning framework—integrating both unsupervised and supervised techniques—to predict student dropout using structured, first-year academic and financial data. The study utilizes a comprehensive dataset of 4,424 undergraduate student records from a European higher education institution, covering ten academic years and comprising 35 variables related to academic performance, enrollment behavior, and …

Investigating Elementary Preservice Teachers' Struggles In Mathematics Problem Solving And The Use Of Scaffolds For Supporting Them, Frank Forte

Theses, Dissertations and Culminating Projects

Mathematical problem solving is a topic that has seen an increased focus in recent years, highlighted by its inclusion as the first Standard for Mathematical Practice in the Common Core State Standards for Mathematics (CCSSM). However, elementary preservice teachers (PSTs) often struggle when solving problems that are nonroutine and require higher cognitive demand. Many have little experience solving this type of problem and show an increased level of anxiety around problem solving, which impacts the way they engage their students with problem solving. To support PSTs to become better problem solvers, it is important to provide opportunities for PSTs to …

Hybrid Fea And Meta-Modeling For De Optimization Of A Highly Saturated Spoke Ipm, Oluwaseun A. Badewa, Marcelo Silva, Rosemary E. Alden, Pedram Asef, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper introduces a novel approach for high performance electric motor design that combines machine learning (ML)-based meta-modeling with a differential evolution (DE) optimization algorithm. The method leverages finite element analysis (FEA) results to train the ML meta-model, enabling efficient design optimization for high-power density cored machines, such as spoke interior permanent magnet motors (IPM), which exhibit complex nonlinearities and saturation effects. This hybrid ML-DE framework seeks to provide an alternative for physics-based electric motor design and optimization, offering significant reductions in computational effort while maintaining accuracy. The meta-model’s accuracy in capturing the nonlinear relationships between design parameters, core losses, …

Does Universal Screening Increase The Proportion Of Culturally, Linguistically, And Economically Diverse Students In Gifted Education?, Leona Alexander

Dissertations

The purpose of this quantitative study was to examine the impact of implementing a universal cognitive screening tool on the proportional representation of culturally, linguistically, and economically diverse (CLED) first-grade students in Gifted and Talented Education (GATE) programs. This study employed a comparative interrupted time series design utilizing a difference-in-differences (DiD) regression model along with additional statistical analyses (two-proportions z-tests and Mann-Whitney U tests) due to limitations in the sample sizes.

Participants included first-grade students (N=425) from two demographically and socioeconomically similar districts in a Rocky Mountain region. One district implemented the universal screener (intervention group n=368), and the other …

Temporal Dynamics In Spatial Random Field Theory: A Methodological Advance In Fmri Data Analysis, Theophilus Barnabas Kobina Acquah

Dissertations

Functional magnetic resonance imaging (fMRI) is a noninvasive tool for studying neural correlates of cognition by measuring task-evoked brain activity. Accurate interpretation of fMRI data depends on modeling the hemodynamic response (HR), which varies across brain regions and conditions. Brain plasticity adds complexity as functional changes during development and aging affect cognition, emotion, and behavior. BOLD signals display complex temporal dynamics influenced by both neural and physiological factors, challenging conventional models. This highlights the need for adaptive frameworks that account for temporal dependencies and spatial heterogeneity in neural activity detection. This current study enhances fMRI data analysis by integrating temporal …

Monitoring The Qosh Tepa Canal Project: A Geospatial Timeline Of Taliban Water Diversion, Enerel L. Crosslin

Honors Thesis

The World Food Program states that “acute malnutrition in Afghanistan is above emergency thresholds in 25 out of 34 provinces and is expected to worsen”. Aiming to support agriculture, the Taliban began to build the 285 km “Qosh Tepa Canal” to divert 17% of the Amu Darya, which supports the livelihoods of millions of people in downstream Uzbekistan and Turkmenistan. The World Bank estimated that roughly 2.4 million Central Asians could become climate refugees by 2050. Our objectives are to create a timeline of satellite imagery of the canal’s construction. Our research questions are (1) Can we characterize water diversion …

On 2-Superirreducible Polynomials Over Finite Fields, J. W. Bober, L. Du, D. Fretwell, G. S. Kopp, T. D. Wooley

Faculty Publications

We investigate k-superirreducible polynomials, by which we mean irreducible polynomials that remain irreducible under any polynomial substitution of positive degree at most k. Let F be a finite field of characteristic p. We show that no 2-superirreducible polynomials exist in F[t] when p=2 and that no such polynomials of odd degree exist when p is odd. We address the remaining case in which p is odd and the polynomials have even degree by giving an explicit formula for the number of monic 2-superirreducible polynomials having even degree d. This formula is analogous to that given by Gauss for the number …