Digital Commons Network^™

Base Running: A Lost Art In Baseball, Ethan York

Departmental Honors & Graduate Capstone Projects

In an era of baseball dominated by home runs and launch angles, the subtle art of baserunning is often overlooked, despite its measurable impact on winning games. Baserunning Runs (BsR) addresses this gap by quantifying the number of runs a player contributes through performance on the basepaths, capturing value beyond traditional metrics like stolen bases. This study constructs multiple regression models that predict BsR for Major League Baseball (MLB) players based on baserunning-related statistics. The primary objective is to examine the association between BsR and key predictors, including stolen bases (SB), extra bases taken (EB), and sprint speed (SS), while …

Uav Blast Load Characterization For Structural Design, Jalee Grace Spain

Civil Engineering Undergraduate Honors Theses

As the use of drones, or UAVs, increases, so does the risk of collision with infrastructure. When drones collide with a building, an impact or blast load is applied. Using current literature and structural analysis, a load case can be defined for a blast load induced by a drone.

Exploring Urban School Counselors' Lived Experiences Engaging As Advocacy Leaders And Change Agents To Empower And Support Black And Brown Students, Linda M. ColóN

Theses, Dissertations and Culminating Projects

To make a difference in Black and Brown students' educational experiences, school counselor advocacy is crucial. A qualitative phenomenological study was conducted to explore the practices urban school counselors incorporate to engage as social justice leaders, advocates, and change agents to empower and support Black and Brown students. The goal was to identify practices urban school counselors utilized to create greater equity for Black and Brown students. Also, from school counselors’ lived experiences, the goal was to learn how they engaged key-school stakeholders in advocacy. In addition, the hope was to bring to the forefront how the intersecting cultural identities …

The Cobalt Curse: Cobalt’S Role And Risks, Marley Jackowitz

Student Theses 2015-Present

This paper examines the hidden environmental, geopolitical, economic, and social costs of the cobalt supply chain. Fueled by the demand for battery technology and electric vehicles, cobalt has become an essential element to the green energy transition. With the largest share of global cobalt deposits, the Democratic Republic of the Congo bears a disproportionate share of the industry’s harms. Cobalt mining in the DRC is marked by environmentally degrading practices and inhumane working conditions, compromising Congolese health, safety, and well-being. Chapter 1 discusses the environmental impacts of DRC cobalt mining and its adverse effects on public health. Environmentally degrading mining …

Strengthening Cyber Resilience In Critical Infrastructure: Lessons From Major Attack Case Studies, Jodi Barnes

Data Science Undergraduate Honors Theses

This comparative case study research paper analyzes the Colonial Pipeline attack, the Oldsmar Water Treatment Plant attack, and related case studies to identify past and current gaps in cyber resilience in critical infrastructure.  It provides insights into the importance of cybersecurity and opportunities to enhance protection in an increasingly digital world.  Findings include unsecure practices, limited communication between sectors, outdated technology, and weaknesses in security processes and employee training. These vulnerabilities are interconnected and are largely driven by limited funding within critical infrastructure systems, which restricts the ability to address them effectively.

Reimagining Less-Than-Truckload Pricing Development In Competitive Bid Environments With Artificial Intelligence, Lawson C. Levin

Data Science Undergraduate Honors Theses

This undergraduate thesis explores how data analytics and engineering judgment are used to support pricing decisions in the less-than-truckload (LTL) freight market. It’s based on an internship with ArcBest Corporation. It explains the company’s background, its role in the LTL market, and the responsibilities of a Pricing and Supply Chain Engineer within the Yield department.

Most of the internship was spent evaluating requests for proposals (RFPs), in which a negotiating third party provides a customer’s shipment data that must be cleaned, analyzed, and translated into a comprehensive pricing offer. Using the Data Science Analytics Process as a framework, this thesis …

Prescribing Company Action Through Machine Learning And Ai, Breck T. Husong

Data Science Undergraduate Honors Theses

The purpose of this research is to implement an OpenAI Reinforced Learning prescription-giving model for improving sales on a week-by-week basis. The data used comes from a segment of High Impact Analytics’s sales data that has been anonymized for proprietary reasons. The features among the data include inventory numbers, shipments in transit, total quantity and dollars of products sold each week for the past 2 years, all aggregated at the store-item-week level. In order to build this model, Tigramite, a causal discovery model combined with prediction models XGBoost, Linear Regression, Ridge Regression, Lasso Regression, Scikit-learn’s MLP, and Keras’s Neural Model …

A Comparative Machine Learning Framework For Identifying Ai-Generated Versus Real Celebrity Faces, Sidney Gehring

Data Science Undergraduate Honors Theses

The rapid advancements in the world of generative artificial intelligence has enabled the creation of highly realistic fictitious facial images, raising concerns about authenticity and bias in computer vision systems. This study investigates the capabilities of machine learning models to distinguish between real and artificially generated facial images across gender and race focusing on celebrity imagery. Four datasets were used against the classification model, each trained on images of a single celebrity within distinct demographic groups: White women, White men, Black women, and Black men. For each group, real images are paired with AI-generated counterparts designed to closely replicate the …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Developing Tracking Compliance Standards For Inbound Freight: A Data-Driven Industry Application At O’Reilly Automotive, Jackson Endacott

Data Science Undergraduate Honors Theses

Visibility of inbound freight is critical for managing operational efficiency, yet many organizations lack standardized compliance metrics for third-party carriers to uphold, preventing them from utilizing tracking data to make data-driven decisions. During a summer internship with the Transportation Department at O’Reilly Automotive, data inconsistencies were addressed in the Transportation Management System (TMS), and that data was utilized to create tracking compliance standards for third-party carriers. Data populated from various sources within O’Reilly’s TMS was cleaned, validated, and utilized to create a Tracking Scorecard that evaluates message transmission rates, timeliness, and errors. This tool provides actionable insights to improve tracking …

Exergames And Motivation To Exercise, Nathaniel Clark

Theses & ETDs

Physical inactivity is a significant public health concern, and motivation has been identified as a key barrier to regular exercise. This thesis investigates exergames, video games that require physical activity to play, as a means of increasing exercise motivation and physical activity. Chapter 1 describes the Exertron 5000, a custom exergame system developed in Godot, a free and open source node and scene-based game engine. The system uses a lightweight wearable interface to track physical activity to control the game. Movement data is processed through a multi-stage filtering and smoothing pipeline to extract pedaling speed. The exergame is an asteroids-like …

The Moral Influences On Non-Denominational Christian Students’ College Major Decision And Future Career Outlook, Makayla Frame

Honors Projects

This is an undergraduate research project for the Honors College. A qualitative research project in the form of case studies was conducted on the influence of Non-Denominational Christian morals and values on how college students decide college major and future career. Non-Denomination students in particular were chosen for this study because of the recent rise in popularity of the Non-Denominational belief in the US, especially among young adults.

The study outlines previous research on the Christian religion, the history of Non-Denominationality, and how typical college students decide their major. The conclusions of the study are that Non-Denominational Christian college students …

Supremacy Politics: The Coding Of Power In Artificial Intelligence (Ai), Dana G. Jones

North Carolina Civil Rights Law Review

No abstract provided.

Pyspqr: A Python Package For Density Estimation Using Deep Learning, Cameron Eddy, Reetam Majumder

Electrical Engineering and Computer Science Undergraduate Honors Theses

Splines are used for representing complex functions. In statistics, splines can be used for distributional shapes that are difficult to model by traditional parametric approaches. Ramsay (1) uses M-Spline bases to estimate continuous distributions. Semi-Parametric Quantile Regression (SPQR), developed by Xu and Reich (2), models conditional distributions where a neural network is used to estimate the basis function weights that depend on covariates. (3) implements a package for SPQR in R. We build on this by implementing a version of SPQR in Python with PyTorch. By using PyTorch, we can use more sophisticated deep learning architectures than those available in …

Towards Multi-Hop Retrieval Using Bipartite Question-Oriented Graphs, Micah Mccollum

Electrical Engineering and Computer Science Undergraduate Honors Theses

Accurately answering multi-hop questions requires full retrieval of multiple, interdependent passages and is a long-standing problem in the area of natural language question answering (QA). While retrieval-augmented generation (RAG) helps address single-hop questions, many retrievers presently focus on semantic similarity in a dense vector space, which is insufficient for handling multi-hop questions specifically. To ameliorate this, we propose constructing a bipartite question- oriented graph composed of hypothetically generated questions connected to passages at index time. The construction of the graph is guided by a large language model (LLM) to prioritize the formation of edges that signal whether a question can …

Evaluating The Use Of Extended Reality Technology To Improve Marching Band Conducting Patterns, Nathan R. Fuhrman

Electrical Engineering and Computer Science Undergraduate Honors Theses

Conducting pattern consistency is an essential skill for marching band drum

majors, yet developing this consistency through individual practice remains diffi-

cult without real-time feedback. This thesis investigates if the use of extended

reality technologies can be used to enhance the conducting skills of novice drum

majors. Using the Meta Quest 3’s passthrough capability, the system overlays vi-

sual feedback elements — including a 3D pattern guide, path visualization, tempo

cues, and a real-time score — onto the user’s physical environment. A within-

subjects study with seven participants evaluated eight combinations of three binary

feedback variables: pattern guide visibility, tempo …

​Autonomous Agentic Orchestration For Physics-Aware Scientific Discovery: An Integrative Multimodal Framework For 2d Material Characterization​, Sankalp Pandey

Electrical Engineering and Computer Science Undergraduate Honors Theses

The advancement of next-generation semiconductor and quantum technologies relies on the scalability of the fabrication of two-dimensional (2D) van der Waals heterostructures. However, this process is severely bottlenecked by characterization workflows. Optical microscopy provides high-throughput imaging of 2D material flakes, but lacks the explicit physical priors required for the discernment of sub-nanometer thickness variations, such as distinguishing monolayers from bilayers. The use of computer vision models to automate the localization and characterization process of the flakes was proposed. As a part of this effort, we develop QuantumFlake, an open-source framework to streamline the integration and deployment of computer vision models …

Software Integration In Personal Healthcare Devices And The Patient User Experience, Yassine Chahid, Patrick Slattery

Publications and Research

This study examines the current landscape and future direction of medical device hardware and software integration, focusing on how each contributes to patient care. It begins by analyzing hardware focused medical devices, such as implantable tools patients may rely on to assist with their condition, alongside diagnostic and monitoring equipment used to treat conditions in a variety of medical areas (e.g. cardiovascular conditions). It then evaluates how software is currently integrated through embedded systems, data processing, and user interfaces that support real time monitoring and clinical decision making, and how this impacts quality of care for the patient whilst minimizing …

Implementation Of A Local Llm Serving System For Agentic Ai, Zhiheng Ni

All Theses

This thesis presents a system that allows large AI models to run directly on personal devices instead of relying on cloud servers. Recent advances in artificial intelligence, especially large language models (LLMs), have made it possible to build powerful applications such as chatbots, coding assistants, and intelligent agents. However, most of these systems run in the cloud, which raises concerns about privacy, latency, and cost.

To address these issues, this work develops a local AI serving system that runs efficiently on a specialized hardware component called a Neural Processing Unit (NPU). The system provides a unified interface that supports multiple …

Exploring Alternative Curriculum Implementation In Special Education Settings, Amber R. Wilson

Dissertations

The purpose of this qualitative case study was to understand teachers’ perceptions of implementing an alternative curriculum in their self-contained special education settings and grade levels, as well as their perceptions of the training and ongoing support provided for its implementation. This study used a case study research design. Findings revealed that the participants experienced several challenges related to training, ongoing support, and curriculum implementation, including issues aligning the alternative curriculum with state standards and assessments. This study is significant because alternative curriculum implementation is under-researched in the United States, and the international literature on this topic is limited.

Secondary Teachers’ Perceptions On The Wida Framework To Support Academic Literacy In Multilingual Learners, Laura G. Faris

Dissertations

The purpose of this study was to determine teachers’ perceptions of benefits and barriers to using the WIDA Framework to support academic literacy in multilingual learners (MLs).  Content-area teachers of MLs who continue to learn English are teaching academic literacy through complex linguistic structures for students to both comprehend and produce informative textual structures which occur in secondary textual reading and written assessments in the literature and historical content areas. Qualitative methods including reflective journal entries, semi-structured teacher interviews, and classroom observations were used to collect data on teachers’ perceptions of the effectiveness of using the WIDA Framework to better …

Teaching Legal Thinking In The Age Of Ai: Reimagining Legal Education Through Cognitive Science And Deliberate Practice, Joan R. M. Bullock

University of Baltimore Law Review

No abstract provided.

Course Insight Portfolio: Math 1060 Calculus Of One Variable I, Minh Ha, Dinaniaina Florence Rafidimanantsoa, Preston Sessoms, Rishabh Shukla

Publications

The following portfolio is a representation of the course MATH 1060, Calculus I, taught at Clemson University. The contents can be broken down into 3 major components.

• The first being an analysis of the students who may typically be in the course, the prerequisites required to take the course, and what paths students have after completing the course. This analysis is based upon the course curriculum at Clemson, and as a result will likely not align with that of other universities

. • The second major component is a map of the concepts discussed in MATH 1060 as well …

Course Insight Portfolio Math 1040: Precalculus And Introductory Differential Calculus, Jessica Ayers, Morgan Hayes, Meghan Kerrick, Uthman Rasaq, Drishty Singh

Publications

This portfolio includes four primary elements. First is a document titled “Where did they come from? Where are they going?” that provides a description of the types of students who are likely to take the course, followed by the “Course Concept Map” that visually depicts the flow of topics and possible misconceptions in MATH 1040. Additionally, the “Misconceptions Overlay” document lists articles that offer interesting discussion and further insight into the ideas students may bring to MATH 1040 or develop throughout the course. Two lesson plans are included that cover “Continuity and Introduction to Classifying Discontinuities” as well as an …

Course Insight Portfolio: Math 1080, A Gentle Introduction To Infinite Series, Igor Luis Aureliano, Leyanis Falcon Hernandez, Ross George, Fnu Monika

Publications

This lesson aims to introduce the concept of an infinite series through geometric representations and partial sums to help students develop an intuitive understanding of convergence. A common misconception students may have when first encountering infinite series is the belief that “a sum of infinitely many things must be infinite”. Through the study of a convergent geometric series, students will investigate how the limit of partial sums can produce a finite value, thereby addressing this misconception and developing a more accurate understanding of infinite series.

Comparative Risk Metrics For U.S. Commercial Aviation, Mihhail Berezovski

BCAAS Reports

No abstract provided.

Multi-Population Sufficient Dimension Reduction, Xuerong Meggie Wen, Yuexiao Dong, Li Xing Zhu

Mathematics and Statistics Faculty Research & Creative Works

A novel dimension-reduction method is introduced for multi-population data. The approach conducts a joint analysis that exploits information shared across populations while accommodating population-specific effects. Unlike partial dimension reduction methods, which identify related directions across all populations, or conditional analyses conducted independently within each population, the proposed two-step procedure leverages cross-population information to enhance estimation accuracy. The methodology is demonstrated through simulations and two real-data applications.

Shooting For The Stars: Stem Outreach Strategies Between 2nd And 7th Grade, Paige Miller

Chemical Engineering Undergraduate Honors Theses

Engineering and planetary science outreach programs are increasingly important as industries and research organizations face growing demand for STEM professionals. Despite the importance of these fields, many students receive little exposure to engineering careers during their early educational experiences. This honors thesis examines the effectiveness of interactive STEM outreach presentations designed for elementary and middle school students. Specifically, this study evaluates outreach activities centered on chemical engineering applications and the NASA M2M CO₂ regeneration project for Martian environments.

Two student age groups participated in this study: 2nd grade students at Butterfield Elementary School and 7th grade students at Woodland Junior …

Modeling Hot Jupiter Atmospheres For The Classification Of Low Abundance Molecules, Mika Brown

Physics Undergraduate Honors Theses

Transmission spectroscopy is a powerful method for studying exoplanet atmospheres. With the recent launch of the James Webb Space Telescope (JWST), several molecules have been successfully detected in hot Jupiter atmospheres at an unprecedented level of precision with transmission spectroscopy. To better understand current detection capabilities and limitations, this project used machine learning techniques to determine which molecules are currently identifiable at the spectral resolution and wavelength range of JWST’s NIRSpec instrument in PRISM mode. A large synthetic dataset of transmission spectra was first generated using the petitRADTRANS radiative transfer Python package. The resulting spectra were then used to train …

From Merchant Poetry To Digital Scholarship: The Influences Of Contemporary Mapping Traditions On La Sfera, Nicholas Pagliocca

Theses & ETDs

No abstract provided.