Digital Commons Network^™

Green Hpc: Optimizing Software Stack Energy Efficiency Of Large Data Systems, Grant Wilkins

Honors College Theses

High-performance computing (HPC) is indispensable in modern scientific research and industry applications, but its energy consumption is a growing concern. This thesis presents two novel approaches to optimize energy consumption in large data systems. The first chapter of the thesis will discuss the use of Dynamic Voltage and Frequency Scaling (DVFS) to optimize the energy efficiency of two popular lossy compression algorithms: SZ and ZFP. By adjusting the voltage and frequency levels of computing resources, DVFS can reduce energy consumption while maintaining the desired level of performance and accuracy. The second chapter of the thesis will focus on a detailed …

Design And Data-Driven Identification Of A Quadruped Robot, Dakota Rufino

All Theses

The existence of nonlinearities and the lack of sufficient equations are fundamental challenges in modeling, analyzing, and controlling complex systems. However, recent developments revolutionizing the study of dynamical systems. An emerging method in nonlinear dynamical systems is the Koopman operator theory, which provides us with key advantages in performing the modeling, prediction, and control of nonlinear systems. The linear system representation allows us to leverage linear stability analysis. The first section of this thesis briefly covers the construction of a quadrupedal robot, a sufficiently complex nonlinear dynamical system, for the use of analyzing data-driven modeling techniques. The second section details …

Comparing The Economic Efficiency Of Payment Structures To Subsidize On-Farm Greenhouse Gas Abatement In Iowa, David Mansfield

All Theses

Abating greenhouse gas (GHG) emissions in the agricultural sector can help
combat climate change and meet the goals of the 2015 Paris Climate Agree-
ment. The agricultural sector can sequester soil organic carbon and, by adopt-
ing conservation-driven land-use decisions, such as reducing or stopping tillage,
increase carbon storage in soil and reduce nitrous oxide (N2O) emissions.
This thesis will compare the cost of achieving different levels of GHG emis-
sions reduction through payments based on: 1) region averages for GHG emis-
sions by crop and practice, without considering additionality, 2) region averages
for GHG emissions by crop and practice …

Using Visual Effects As A Means Of Establishing Or Reinforcing Scale In 3d Visual Works, Eric Dinicolantonio

All Theses

In 3D animation, visual effects help to establish and reinforce the scale of different characters and objects that are otherwise unclear. In the Fall of 2022, I taught a class about visual effects to several students. At the time, I had difficulty explaining the importance of properly scaling your 3D effects in order to add realism. With physically based effects, we must respect the laws of physics to create a visually realistic and understandable visual effect. Going through several of my previous projects, I found that I had made mistakes with scaling several of my effects. With this paper, I …

Network Effects Of Emergency Department Clinician Strain And Patient Congestion, Aisha Nelson

All Theses

We develop a discrete-event simulation model to study how staffing strain affects patient outcomes across a network of Emergency Departments (EDs). The aim is to observe how clinician staffing and transfers throughout the system affect the system’s behavior. We will study the network of the seven EDs in the Prisma Health-Upstate system. Patient acuity and resource need are stratified using the five-level Emergency Severity Index (ESI). Patient flow data within and between EDs are collected from EPIC, staffing data from ShiftAdmin, and environmental COVID-19 prevalence data from the Department of Health and Environmental Control. Time periods include the Omicron wave …

A Multi-Agent Modeling Social Network Analysis Of Cooperative Learning Groups Within A Simulated Adult Education Classroom Learning Environment, Leverett Bruner

All Dissertations

Illiteracy and a lack of a high school diploma are impediments to a fulfilled and meaningful life. Low or reduced literacy and non-attainment of a high school diploma are significant problems in the United States. Adult education can be a vehicle to address these ever-present issues. A disproportionate number of students in adult education are minorities, members of lower socioeconomic statuses and traditionally marginalized groups who lack effective literacy skills and/or a high school diploma. Adult education and its related entities can serve as a vehicle to address these pervasive issues, but adult education as a program type is a …

Mesoscale Modeling And Machine Learning Studies Of Grain Boundary Segregation In Metallic Alloys, Malek Alkayyali

All Dissertations

Nearly all structural and functional materials are polycrystalline alloys; they are composed of differently oriented crystalline grains that are joined at internal interfaces termed grain boundaries (GBs). It is well accepted that GB dynamics play a critical role in many phenomena during materials processing or under operating environments. Of particular interest are GB migration and grain growth processes, as they influence many crystal-size dependent properties, such as mechanical strength and electrical conductivity.

In metallic alloys, GBs offer a plethora of preferential atomic sites for alloying elements to occupy. Indeed, recent experimental studies employing in-situ microscopy revealed strong GB solute segregation …

Partitioning And Microdosimetry Of Plutonium-239 And 55-Iron In Environmental Bacteria Grown In Liquid Cultures, Lisa Manglass

All Dissertations

The work presented herein provides quantitative data related to bacteria exposed in situ to two radionuclides relevant to nuclear sensing: plutonium-239 (²³⁹Pu) and iron-55 (⁵⁵Fe). Originally motivated by the fundamental science underlying biosensing, liquid cultures of Pseudomonas putida and Escherichia coli were exposed to radionuclides over the course of 15-day experimental periods with the intent of gaining insight into the response of these bacteria. An essential component of characterizing or utilizing this response in a meaningful way is an understanding of the dose leading to that response. This dissertation narrows the knowledge gap associated with dose-response …

To Give Or Not To Give: A Qualitative Descriptive Study On Alumni Giving Behavior At A Historically Black College And University, Shanaee Bodrick

All Dissertations

This qualitative descriptive study explores alumni giving behavior at a private North Carolina Historically Black College and University (HBCU). Specifically, this research examined HBCU alumni experiences, perceptions, and motivations and how these factors influence their decision-making process when contributing financially to their alma mater. This research provides the historical background of HBCUs and how these institutions have been critical in shaping their education and communities. The findings of this study provide the basis for future research on HBCU alumni donors and non-donors. It exposes commonalities and differences between donors and non-donors. In all, this study may act as a reference …

Adversarial Deep Learning And Security With A Hardware Perspective, Joseph Clements

All Dissertations

Adversarial deep learning is the field of study which analyzes deep learning in the presence of adversarial entities. This entails understanding the capabilities, objectives, and attack scenarios available to the adversary to develop defensive mechanisms and avenues of robustness available to the benign parties. Understanding this facet of deep learning helps us improve the safety of the deep learning systems against external threats from adversaries. However, of equal importance, this perspective also helps the industry understand and respond to critical failures in the technology. The expectation of future success has driven significant interest in developing this technology broadly. Adversarial deep …

Using Immersive Technology To Improve Mechanical Design: Use Cases, A Review Of Current Technology, And An Experiment In Requirement Elicitation In Virtual Reality, William Hawthorne

All Theses

There has been a growing trend in the use of immersive technologies within engineering design. This research is focused on understanding how Virtual Reality (VR) technologies support design reviews. Modern tools including virtual reality hardware and software were tested for current capabilities and challenges. In a review of literature, two key gaps are identified: the rapid advancements of VR and AR technology and limited formal studies to determine the costs and benefits of immersive technology within engineering design reviews. This research has resulted in three key outcomes. First, use cases of immersive reality technologies are identified, through the lens of …

Comparative Design Space For Bistable Composites: An Integrated Framework Of Optimization, Finite Element Analysis, And Experimental Testing, Jonathan Bolanos

All Theses

Bistable composites are a class of advanced materials that can actuate between two stable shapes, making them attractive for a wide range of engineering applications. However, designing these composites to achieve optimal performance remains a challenging task. To address the challenge, this research develops an integrated framework that combines a genetic algorithm optimization technique, finite element analysis in Abaqus, and experimental testing to explore the design comparative space for square bistable composites composed of DA 409 carbon fibers. This leads to the study of generating an optimization algorithm to account for the relationship between the chances of a successful maximum …

Analyzing The Influence Of Stale Data On Autonomous Intelligent Transportation Systems, August St. Louis

All Theses

Intelligent transportation has been at the forefront of recent technological advancement. Individuals have developed a number of algorithms intended to automate and improve essential intelligent transportation functions. New developments include the incorporation of vehicle platooning and path planning algorithms within a number of use cases. Data perturbation can affect both algorithms significantly. We define data perturbation as any natural or unnatural phenomenon that causes the data to be skewed in any way. Perturbations within either system can cause its respective algorithm to operate with stale or incorrect data. This can significantly affect performance. This paper conducts a fault injection campaign …

Visualizing Project Life-Cycle Data In A Hybrid Dashboard For Federal Capital Projects, Prajakta Bapat

All Theses

Capital project owners face several challenges in extracting meaningful information from large and complex data sets generated throughout the life cycle of a construction project. Capital projects must strike a balance between intuition-driven and data-driven decision-making due to their sensitive and change-averse nature. The main objective of this study is to improve the structure, clarity, and interpretation of the construction data, and enhance the decision-making processes for federal capital projects. To achieve this goal, this study developed a hybrid dashboard tailored to the federal agencies’ requirements of performance assessment. This study is a sub-section of broader research – the Federal …

Cohen-Macaulay Properties Of Closed Neighborhood Ideals, Jackson Leaman

All Theses

This thesis investigates Cohen-Macaulay properties of squarefree monomial ideals, which is an important line of inquiry in the field of combinatorial commutative algebra. A famous example of this is Villareal’s edge ideal [11]: given a finite simple graph G with vertices x1, . . . , xn, the edge ideal of G is generated by all the monomials of the form xixj where xi and xj are adjacent in G. Villareal’s characterization of Cohen-Macaulay edge ideals associated to trees is an often-cited result in the literature. This was extended to chordal and bipartite graphs by Herzog, Hibi, and Zheng in …

Investigating Barriers To Conservation Of Freshwater Mussels In South Carolina, Olivia Poelmann

All Theses

Freshwater mussels are a diverse group of filter-feeding bivalves inhabiting freshwater systems; however, ~70% of U.S. species are imperiled. Many freshwater mussel species use fish hosts to complete juvenile transformation making host fish knowledge important for conservation efforts like captive propagation. While captive propagation programs have produced thousands of juveniles, survival post-release into natural systems is poorly studied. To address these absences of information, my first objective was to investigate differences among host use of naturally infested fishes and timing of larval release. My second objective was to evaluate survivorship of laboratory propagated juvenile Carolina Heelsplitter (Lasmigona decorata), …

Quantifying Heterogeneity Along A Hillslope Using Seismic Refraction, Structure From Motion, And X-Ray Fluorescence In The Piedmont, South Carolina, Leah Topping

All Theses

The critical zone (CZ) is the life sustaining outer layer of the earth that spans from the top of unweathered bedrock to the tops of the trees. This dynamic zone is always evolving because a variety of chemical, physical, and biological processes transform bedrock into regolith, creating a spatially heterogeneous CZ architecture. This study aims to investigate the relationships between regolith thickness, seismic velocities, and chemical profiles as a function of slope position and it is hypothesized bedrock composition, fracture density, and foliation are the key factors controlling the physical heterogeneity in the top 1-2 meters of the CZ. To …

Considerations Of The Impacts And System-Level Mitigation Of Electric Vehicle Charging On The Integrated Resource Planning Process, Grant Wollam

All Theses

Electric vehicles (EV) are growing in popularity and therefore adoption rate. Best estimates predict a 6.2% EV adoption rate by 2035 in the southeastern United States. With this level of EV adoption, utility planners must begin to consider the impact that EVs will have on the power grid. This paper aims to help predict these EV impacts on the power grid. Specifically, an urban-commercial feeder is analyzed in detail to provide worst-case and most-likely results of varying levels of EV impact. Results show that a 26.2% peak increase is the most likely result for this feeder in 2035.

Mitigation techniques …

Development And Evaluation Of Machine Learning Models For Fugitive Methane Detection And Intensity Prediction, Jacquan Pollard

All Theses

The environmental impacts of global warming driven by fugitive methane (CH4) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH4 emissions. This study evaluated the performance of data-driven machine learning (ML) models using support vector machines (SVM) to detect the presence of trace CH4 emissions and the corresponding intensity amongst various meteorological conditions. The author used simulation data comprising various meteorological parameters such as temperature, relative humidity, wind speed, water vapor, pressure, precipitation rate, and a parameter possessing trace concentrations of CH4 emissions. The novelty of the SVM models developed in …

Assessing Key Factors Influencing Fire-Induced Spalling Of Concrete Using Explainable Artificial Intelligence (Xai), Mohammad Khaled Gazi Albashiti

All Theses

This thesis adopts eXplainable Artificial Intelligence (XAI) to identify the key factors influencing the fire-induced spalling of concrete and to extract new insights into the fire-induced spalling phenomenon. In this pursuit, an XAI model was developed, validated, and then augmented with two explainability measures, namely, Shapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). The proposed XAI model not only can predict the fire-induced spalling with high accuracy (i.e., >92 %) but can also articulate the reasoning behind its predictions (as in, the proposed model can specify the rationale for each prediction instance); thus, providing us with valuable insights …

Net-Zero Target And Emissions From Land Conversions: A Case Study Of Maryland's Climate Solutions Now Act, Philip Hutton

All Theses

Many climate change “solution” plans include net-zero goals, which involve balancing the anthropogenic greenhouse gas emissions (GHG) with their removal. Achieving net-zero goals is particularly problematic for soils because they are often excluded from GHG inventories and reduction plans. For example, Maryland’s Climate Solutions Now Act (Senate Bill 528) put forward a target of net-zero emissions by 2045. To achieve these goals, the state of Maryland (MD) needs to quantify GHG emissions. Soils are currently excluded from MD’s GHG assessments. This study examines the challenges in meeting net-zero goals by using carbon dioxide (CO₂). The current study quantified …

Evaluation Of Zero-Net-Rate Pumping Tests, Austin Smith-Jones

All Theses

Accurately estimating the distribution of aquifer properties is key to understanding contaminant movement in the subsurface. The distribution of aquifer properties is typically addressed using slug or constant-rate well tests, and the pros and cons of these tests are well known. Slug tests are appealing because they avoid removing contaminated water, but their results are affected by well skin and the small volume of displaced water limits the volume of aquifer that can be evaluated. Constant-rate well tests have the disadvantage of requiring disposal of potentially contaminated water, but they can generate properties that are more representative than slug tests, …

Use Of Vocabulary Strategies To Aid English Language Learners In A General Education Biology Classroom, Virginia Perry

All Dissertations

The demographics of the typical American classroom continue to present as a more diverse student population with the increase of English Language Learners (ELL) entering public schools. General education teachers on a secondary level are challenged with incorporating academic language instruction into content instruction for ELLs. Many of these teachers seek appropriate instructional strategies to teach ELLs academic language skills related to literacy to comprehend the specific content taught at the secondary level. A deeper understanding of language and skill acquisition within a secondary classroom can help guide future efforts in implementing effective literacy strategies to address ELLs’ academic language …

Probing The Structure Of Water On Surfaces: From Water Absorption To Ice Nucleation, Jiarun Zhou

All Dissertations

Water, essential for all life forms, is the most abundant, simple, yet mysterious molecule in the world. This molecule, consisting of only three atoms, behaves in unexpectedly different ways with the change of environment. In the past, studies of water under different conditions (temperature, pressure, on the surfaces, with confinement) have been conducted using experimental and computational methods. However, the influence of a given environment on water properties is yet to be fully understood. This dissertation studies water at complex interfaces (surfaces with various chemistry and physics properties) in both the liquid and crystalline states. Various heterogeneous systems used to …

A Narrative Inquiry Of Selected Women’S Career Pathways To State-Level Leadership In Agriculture, Timothy Keown

All Dissertations

In this study, I used a qualitative narrative inquiry to examine stories from three individually selected state-level agricultural sector women leaders as they described their career paths to leadership roles. This purpose of the study was to address the problem of a lack of practical understanding of women leaders’ experiences in pursuing, achieving, and keeping leadership roles within the agricultural industry. The existing literature shows that women are less likely to hold an agriculture leadership role in their career. To establish the research question, I used feminist educational theory. This theoretical framework and the associated epistemology of narrative inquiry served …

A Predictive Analysis Of The Influence Of Thickness And Length On The Curvature Of Square Bistable Carbon Fiber Reinforced Composite Laminates, Stephan Terry

All Theses

This thesis presents a predictive analysis of the stability of square bistable carbon fiber reinforced composite laminates under various loading conditions. The stability of these laminates is essential to their performance and longevity and is influenced by factors such as thickness and length. Analytical and numerical techniques are used to model the behavior of these laminates, and experimental tests are conducted to validate the models. The findings of this research have implications for the design and optimization of square bistable carbon fiber reinforced composites.

The study investigates the relationships between the side length and thickness of square laminates for bistability. …

An Agricultural Literacy Assessment Of Social Studies Teachers In South Carolina, Walker Reid

All Theses

Studies in the career development of youth identify middle school as the optimum time for career exploration, as it advances young adolescents’ self-awareness, knowledge of prospective careers, and goal setting. In South Carolina (SC), only 5% (13 of 248) of public middle schools provide agricultural education. The purpose of this study is to measure any increase in agricultural awareness and literacy of South Carolina 8^th-grade social studies teachers participating in a five-day study tour (SOCIAL tour) through mixed method procedures. A pre and post-tour survey given to participants indicated a significant increase in knowledge and perception of agriculture …

Procedural City Generation With Combined Architectures For Real-Time Visualization, Griffin Poyck

All Theses

The work and research of this paper sought to build upon traditional city generation and simulation in creating a tool that both realistically simulates cities and their prominent features and also creates aesthetic and artistically rich cities using assets that combine several contemporary or near contemporary architectural styles. The major city features simulated are the surrounding terrain, road networks, individual buildings, and building placement. The tools used to both create and integrate these features were created in Houdini with Unreal Engine 5 as the intended final destination. This research was influenced by the city, town, and road networking of Ghost …

Economic Impact Assessment Of Nature-Based Coastal Resilience Solutions In Charleston. Estimating Local Economic Effects With Algorithm-Based Supporting Tool., Oksana Veselkova

All Theses

Coastal cities are at the forefront of the risks induced by climate change. Local communities are adversely affected, but the essential cultural assets and economies are also at risk of damage or destruction. In the efforts to limit hazard risk exposure, local governments are increasingly planning for long-term flood protection. One prospective flood risk mitigation measure is living shorelines or nature-based adaptation. The coastal ecosystems, such as beaches, wetlands, barrier islands, oyster reefs, and salt marshes, deliver multiple benefits to communities, including recreation, natural resources, freshwater, and carbon sequestration. Moreover, when combined with structural solutions, they can effectively reduce water …

Gaslight: Attacking Hard-Label Black-Box Classifiers Via Deep Reinforcement Learning, Rajat Sethi

All Theses

Through artificial intelligence, algorithms can classify arrays of data, such as images or videos, into a predefined set of categories. With enough labeled data, a classifier can analyze an input’s components and calculate confidence scores for each category. However, machine learning relies heavily on approximation, which allows attackers to exploit classifiers by providing adversarial
examples. Specifically, attackers can modify their input so that the victim classifier cannot correctly label it, while a human observer would be unable to notice the difference.
This thesis proposes Gaslight, a system that uses deep reinforcement learning to generate adversarial examples against a victim classifier. …