Digital Commons Network^™

Ai In Consideration Of Her: Accounting For Gendered Workplace Dynamics In The Design And Evaluation Of Human-Centered Ai Integration In Everyday Workplaces, Kelsea S. Schulenberg

All Dissertations

Rapid advancements in the technical capabilities and availability of generative Artificial Intelligence (AI) systems, such as OpenAI's ChatGPT, have drawn widespread attention to the opportunities and challenges associated with AI integration into everyday workplaces (i.e., office-type work). Following calls for organizations to consider the ethical and workplace-specific impacts of generative AI's use before integrating it into the workplace, this dissertation addresses three critical gaps in Human-Centered Computing (HCC) and AI workplace integration research. First, this dissertation unpacks the underdeveloped links between women's representation - or lack thereof - in AI-related fields and how their experiences with gendered workplace dynamics in …

Surface Reaction And Transportation Of Radium-226 In Marine Systems, Jiusi Wang

All Dissertations

Historical uses of radium (Ra)-containing self-luminous paint, such as on gauges and dials in naval ships, have led to the potential for such paint, and thus Ra, to be released into the marine environment. Radium-226 (²²⁶Ra) behavior in marine systems is not fully described in the literature, presenting a knowledge gap in the process of evaluating potential ecological impact of Ra in marine systems. This study explores various mechanisms contributing to Ra environmental transport in marine systems on a laboratory scale, including leaching, sorption, and diffusion. ²²⁶Ra leaching from watch hand dials containing radioactive luminous paint is …

Hydrodynamics Of Perforated Heave Plates, Muhammad Usman

All Dissertations

Ocean waves are a clean and renewable energy source that can help reduce dependence on fossil fuels and combat climate change. To capture this energy, researchers have developed devices known as wave energy converters (WECs). One common type, called a two-body point absorber WEC, uses a buoy floating on the ocean surface connected to a submerged reaction plate, known as the heave plate, which lies underwater. The relative up-and-down motion between the buoy and the heave plate, driven by ocean waves, generates usable power via a power take-off (PTO) system. Traditionally, these submerged heave plates are solid structures. However, this …

Opposed-Piston Two Stroke Engine As A High Power Density Solution In Heavy Duty Applications: An Experimental Evaluation With Diesel And Ethanol, Ankur Bhatt

All Dissertations

With an increasing demand to reduce greenhouse gas (GHG) emissions, the conventional powertrain technology is at a saturation point. There is reinvigorated research interest in alternative powertrain designs that offer potentially higher efficiencies and lower engine-out emissions compared to conventional powertrains. The opposed piston two-stroke (OP2S) engine is one such alternative engine architecture that has demonstrated a reduction in engine-out emissions and increased efficiency compared to conventional four-stroke diesel engines. Like any two-stroke engine, the scavenging process and the composition of the internal residuals are predominantly governed by the pressure differential between the intake and the exhaust ports. Without dedicated …

Reverse (Bio)Engineering: A Machine Learning Approach To Optimize Baseball Pitcher Health And Performance, Robert C. Moore

All Dissertations

Ball tracking systems are becoming ubiquitous in sport, creating an unprecedented opportunity for big data applications to optimize human health and performance. These applications are especially common in baseball, a sport known for analyzing ball flight data to quantify performance. Analysts routinely use ball flight data to identify the attributes of top performing pitchers, finding that the best pitchers throw with optimal combinations of release speed and spin to precise locations. However, for certain pitchers, the throwing motion required to produce optimal ball flight places exceedingly high biomechanical load on the elbow, and consequently injury rates continue to rise. This …

Legitimacy, Learning, And Launch: Exploring Relationships, Community, And Connection In An Undergraduate Research Experience, Randi J. Sims

All Dissertations

Undergraduate research experiences (UREs) are critically important methods for integrating undergraduate students into legitimate scientific practices. While widely celebrated for producing positive outcomes such as increased self-efficacy, research skills, and STEM retention, less is known about the processes through which undergraduate mentees become integrated members of their research groups and the broader scientific community. This dissertation presents findings from both a systematic literature review and a quantitative ethnographic study of a biological sciences URE at a southeastern R1 predominantly white institution (PWI). Grounded in communities of practice and legitimate peripheral participation frameworks, this study explores how undergraduate researchers build relationships, …

Contributions To Statistical Modeling And Estimation Of Rainfall Intensity–Duration–Frequency Curves, Jiyun Huang

All Dissertations

Extreme rainfall can cause flooding, damage infrastructure, and create serious risks for communities. Engineers use Intensity-Duration-Frequency (IDF) curves to estimate precipitation extremes over different lengths of time, such as one hour or one day, and the average time one would expect wait for one of these events to occur. Several approaches exist for estimating IDF curves, but no single approach is known to be best in all cases. In this dissertation, I study statistical methods that aim to improve IDF curve estimation. I use the Canadian Regional Climate Model (CanRCM4) Large Ensemble, which contains 35 independent climate simulations. These simulations …

Leveled Homomorphic Encryption Schemes: Noise And Precision Control, Kyle Yates

All Dissertations

Homomorphic encryption allows for computations on encrypted data without exposing the underlying plaintext, enabling secure and private data processing in various applications such as cloud computing and machine learning. In this thesis, we conduct a comprehensive worst-case noise analysis for three prominent leveled homomorphic encryption schemes: Brakerski-Gentry-Vaikuntanathan (BGV), Brakerski-Fan-Vercauteren (BFV), and Cheon-Kim-Kim-Song (CKKS). We propose modifications to these schemes and their residue number system (RNS) variants, ensuring fresh encryption noise falls under a constant bound. For BFV and BGV, we design and prove parameter conditions which guarantee certain homomorphic circuit evaluations return ciphertexts containing noise within a fixed bound. For …

Hybrid Learning For Rough Terrain Navigation Of Actively Articulated Wheeled Vehicles, Dhruv Mehta

All Dissertations

Conventional wheeled ground vehicles have been used for rough terrain navigation in the recent years. They consist of a chassis connected to wheels through passive, semi-active, or active suspension systems. However, their fixed configurations limit mobility and maneuverability, constraining their ability to autonomously navigate diverse and rough terrains. Autonomous Ground Vehicles (AGVs) face significant challenges in this regard, including varying terrain roughness, soil hardness, and obstacle crossing.

To address these limitations, Actively Articulated Wheeled Vehicle (AAWV) architectures have recently emerged, offering real-time geometric adaptability. AAWVs have chassis and wheels connected via articulated serial or parallel linkages. However, increased articulation introduces …

Data-Driven Discovery Of Finite-Dimensional Koopman Operator For Modeling And Control Of Uncrewed Ground Vehicles, Ajinkya Joglekar

All Dissertations

This dissertation advances data-driven modeling and adaptive control techniques for Uncrewed Ground Vehicles (UGVs), with a focus on autonomy in mission-critical and safety sensitive environments. UGVs are deployed across a wide spectrum of domains, from structured manufacturing shop floors to unstructured off-road terrains, including planetary exploration, precision agriculture, and disaster response. These platforms, operating in dull, dirty, and dangerous conditions, demand autonomy that is both adaptable and robust. While traditional model-based control methods offer interpretability and robustness, they struggle with unmodeled dynamics, parameter variations, and integration of high-dimensional sensing. Conversely, modern machine learning approaches can directly exploit sensory data but …

Digital Reflections: Evaluating Body Dissatisfaction In Xr Through Eye- And Body-Tracked Virtual Humans, Deyrel Diaz

All Dissertations

In an era where digital and physical realities increasingly intertwine, the perception of body image is undergoing a significant transformation. Traditional understandings of body dissatisfaction, long studied in relation to psychological distress and eating disorders, are now being reshaped by technologies such as Virtual Reality (VR), Augmented Reality (AR), and Artificially Intelligent (AI)- generated media. These technologies have introduced novel ways of experiencing and interacting with the human form, raising critical questions about their impact on self-perception and internalization of beauty standards.

As virtual representations become more prevalent in entertainment, social media, and interactive platforms, it is becoming more crucial …

Cosmic Duets: A Search For Binary Supermassive Black Holes In Merging Galaxies, Sagar Adhikari

All Dissertations

Galaxies are vast cosmic islands of stars, dust, and gas. They come in various shapes and sizes. They might look static for the timescales we are used to, but they are dynamic and collisional systems that can merge with other galaxies to make bigger galaxies. Most galaxies, including the Milky Way, host a central supermassive black hole (SMBH) with a mass greater than a million (sometimes a billion) times the mass of the Sun. When galaxies merge, their SMBHs form a binary system before ultimately merging. These cosmic duets are of great interest to astronomers and astrophysicists as they are …

On Variations Of Isolation In Graphs, Geoffrey Boyer

All Dissertations

In 2015, Caro and Hansberg introduced a wonderful and natural generalization of the well-studied parameter of domination in graphs. For a graph $G$ and a family of graphs $\FF$, they define $S$ to be an $\FF$-isolating set if $G-N[S]$ contains no member of $\FF$ as a subgraph. The case where $\FF=\{K_1\}$ coincides with domination. The case where $\FF=\{K_2\}$ is now simply referred to as an isolating set. We strengthen known results about the isolation number of a graph, and explore variations of the parameter including the independent and total versions.

In particular for connected graphs of order $n$, a bound …

Closing The Achievement Gap: School Counselors’ Role In Enhancing College And Career Access For First-Generation Students, Conswyla J. Decoteau

All Dissertations

Professional school counselors play a vital role in supporting each student's academic, experiential, and personal growth, especially in preparing them for success in post-secondary education. Due to social, academic, and financial disadvantages, first-generation students face significant obstacles. Given that inequities persist despite efforts to improve access to higher education, this problem is important to address. To close the academic gap that first-generation students face, effective counseling programs that are sensitive to cultural differences are necessary. In order to better understand how school counselors in rural high schools may help first-generation students close the gap in access to college and careers, …

First Principles Calculation Of Electron-Phonon Coupling In Nonequilibrium Quantum Materials, Chendi Xie

All Dissertations

This dissertation combines first-principles computation and light-induced nonequilibrium analysis to understand and control electron–phonon coupling (EPC) and emergent many-body phenomena in quantum materials, in both equilibrium and nonequilibrium states.

Chapters 1 and 2 build the theoretical and computational foundation, beginning with electron and phonon self-energies, linewidths, and perturbation theory for EPC, followed by density functional theory (DFT) and density functional perturbation theory (DFPT), which serve as the first-principles workhorses used throughout. Chapter 3 reviews Bardeen-Cooper-Schrieffer (BCS) and Migdal-Eliashberg theory, including the BCS gap - transition temperature (T_c) relation and the strong-coupling generalization, and delineates the practical validity bound …

Accident Data Analytics And Ai-Based Auditory Enhancement For Highway Construction Safety, Thinh Nguyen

All Dissertations

This research develops data-driven and AI-enhanced approaches to improve worker safety in highway construction environments. The study integrates advanced analytics and auditory signal enhancement to identify high-risk worker behaviors and improve real-time safety warnings. The work consists of three core studies. The first study applies Sequential Pattern Mining and Social Network Analysis to more than 1,000 construction accident reports to identify high-risk worker actions and their hidden sequential relationships with accident types and consequences. These insights reveal sector-specific risk patterns, supporting the creation of targeted, data-informed safety interventions. The second study introduces an AI-based auditory enhancement model built on a …

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

All Dissertations

The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, …

Enhancing Teacher Planning Practices To Improve Teacher Self-Efficacy Through Professional Learning Communities, Philip L. Price

All Dissertations

This improvement science dissertation investigated the impact of implementing Professional Learning Communities (PLC) on teacher self-efficacy at Parkway Elementary, a Title I school serving a diverse student population with historically lower academic performance. The study addressed the problem of low teacher self-efficacy, a critical factor influencing Tier 1 instructional quality and student outcomes. Utilizing the Plan-Do-Study-Act cycle, this research tested the theory that adopting a four-question framework within weekly collaborative grade-level meetings would measurably increase teacher self-efficacy. Seven teachers participated in the research, with data collected through the Teacher Sense of Efficacy Scale, semi-structured interviews, and PLC observations. Quantitative findings …

Flexible Spatial Priors In Bayesian Neuroimaging: Gmrf, Nngp, And Deep Gmrf, Boyoung Hur

All Dissertations

Structural neuroimaging is essential for understanding neurological disorders such as Alzheimer’s disease, enabling accurate delineation of brain regions through image segmentation. Among various segmentation methods, multi-atlas-based approaches like label fusion have become leading techniques. In statistics, Bayesian hierarchical models for label fusion are increasingly favored for their ability to incorporate uncertainty and prior knowledge. Also, a key challenge in modeling neuroimaging data is spatial dependence among image voxels, making the choice of spatial prior critical—particularly in high-resolution settings where segmentation accuracy and computational efficiency are both essential.

This dissertation proposes fully Bayesian spatial hierarchical models that explore two flex- ible …

Developing American Indian/Alaska Native Children As Leaders In The Climate Movement, Joseph Burns, Alessandra Angelino, Danielle Heims-Waldron, Allison Empey, Jason Deen

Journal of Youth Development

American Indian/Alaska Native (AI/AN) voices are critical in the climate movement, as numerous social drivers have rendered these communities particularly vulnerable to the consequences of environmental change. In recent years, specific events, including the Dakota Access Pipeline, have galvanized AI/AN youth, who have been increasingly involved as leaders in the climate movement both in the United States and internationally. This yields a significant opportunity to promote leadership development for Indigenous youth, both through local, national, and international organizing and through curricular development to spark interests in environmental science. This review aims to discuss the role of AI/AN youth leadership in …

Spatially Mapped Statewide Estimated Potential Evapotranspiration Using An Efficient Surface Interpolation Method: A Case Study Of South Carolina, Sudhanshu S. Panda, Devendra M. Amatya, Ka Kit Liu, Augustine Muwamba, Timothy J. Callahan

Journal of South Carolina Water Resources

Potential evapotranspiration (PET) exhibits substantial spatial and temporal variability across large landscapes, necessitating site-specific estimation for accurate environmental and water resource assessments. However, obtaining PET or ET data for specific locations across an entire state remains challenging due to the limited number of weather stations and associated environmental datasets. This study aimed to develop an automated geospatial modeling framework to map PET distribution across South Carolina, USA, using PET estimated by the temperature-based Hargreaves–Samani (H–S) method with daily weather data from 59 NOAA stations. Because the accuracy of spatial interpolation depends on both the target variable and the desired spatial …

Rapallo Notebook C: A Vision, Poetry, And Sundry Writings, Wayne Chapman

International Yeats Studies

No abstract provided.

Rapallo Notebooks A And B: A Packet For Ezra Pound, A Vision, And Articles, Neil Mann

International Yeats Studies

No abstract provided.

Stream Temperature Responses To Summer Urban Rain Events Along The Savannah River, Joseph E. Wermter, Vivian L. Turner, Max K. Appelbaum, James M. Shepherd, Jacob Z. Lott

Journal of South Carolina Water Resources

The hydrological urban heat island (HUHI) is a recent facet of the urban heat island (UHI), describing thermal enhancement of bodies of water in response to urbanization. Although the forefront of this work has been studied for large Metropolitan areas, this effect on developing cities is currently unknown. To locally measure and quantify HUHI effects in a developing city, we utilized Multi-Radar Multi Sensor (MRMS) radar-derived rainfall data to estimate rainfall in the Augusta Metropolitan Area (AMA) and the Savannah Metropolitan Area (SMA), two developing communities adjacent to the Savannah River. We analyzed mean temperature trends of two stream gauges …

Strategies For Out-Of-School Time Stem Educators Working With Youth Experiencing Diverse Abilities, Joelle Lemer, Rasha Elsayed, Kirsten Daehler, Nena Bloom

Journal of Youth Development

Out-of-school time learning occurs in a variety of settings including formal-learning environments, such as afterschool programs, or informal-learning environments, such as museums or youth clubs. Educators in out-of-school time contexts serve diverse youth populations. Many educators often have limited experience or preparation in how to support STEM learning, particularly with learners experiencing diverse physical and/or sensory abilities, such as mobility, dexterity, vision, or hearing. The purpose of this article is to share research-to-practice strategies for STEM in out-of-school time settings for professionals working with youth experiencing diverse physical and/or sensory abilities. These strategies are derived from a review of available …

Culturally Responsive Stem Education: Integrating Mapping Techniques And Drone Technology For Youth, Mayra Rodriguez Gonzalez, Kevin G. Torres Garrido

Journal of Youth Development

Integrating drone and geospatial technologies with participatory techniques offers a promising approach to culturally responsive STEM education. However, these areas are rarely combined in existing literature. Drone and geospatial education for youth generally focuses on technical skills, while participatory methods in youth-led initiatives often aim to foster community connection and a sense of place. Unfortunately, these approaches typically exist in isolation within youth programming. This disconnect limits the potential to engage underrepresented youth in STEM by not linking spatial data to local contexts and culturally meaningful narratives. By combining these approaches, both technical learning and personal engagement could be enhanced, …

A. Syllabus His 207 Comparative Twentieth Century South African And United States Civil Rights And Voting Rights Histories, Frankie Nicole Weaver

Frankie Nicole Weaver, Comparative Twentieth Century South African and United States Civil Rights and Voting Rights Histories

Originally shared as an in-person comparative upper-level undergraduate history course, this course was adapted for online, virtual use. It works well in either format; however, if you share it virtually, I strongly encourage at least one weekly synchronous class meeting and utilizing breakout rooms to promote discussion. Also, provide discussion questions and randomly enter breakout rooms to facilitate discussion --ensuring that engaging discussions occur. I recommend offering both in-person and virtual office hours, regardless.

Full Issue, Volume 20, Issue 3

Journal of Youth Development

No abstract provided.

Clemson Commencement Program, August 2025, Clemson University

Clemson Commencement Programs

No abstract provided.

Multi-Stage Stochastic Programming For Disaster Relief Logistics Under Forecast Uncertainty, Sudhan Bhattarai

All Dissertations

Hurricanes are among the most destructive annual disasters in the United States, presenting interdependent challenges for evacuation planning and relief-supply logistics. Coordinating evacuation and relief operations is crucial to ensure the timely and effective movement of at-risk populations and the delivery of essential supplies. This dissertation develops and evaluates three progressively advanced multi-stage stochastic programming (MSSP) frameworks that integrate evacuation and relief-item pre-positioning while explicitly accounting for uncertainty in hurricane forecasts.

Chapter 1 introduces a fully adaptive MSSP model for the integrated hurricane relief logistics and evacuation planning (IHRLEP) problem. The model simultaneously optimizes evacuation flows and inventory pre-positioning over …