Digital Commons Network^™

Reimagining Math Instruction: An Improvement Science Study On Student Choice And Teacher Support Systems In 5th Grade, Nikki G. Gilmore

Theses and Dissertations

This improvement study investigates the potential impact of implementing choice-based assignments on student performance in fifth-grade mathematics. Recognizing that traditional, one-size-fits-all instructional models often limit student engagement and ownership, this study explores how offering students meaningful choices in their learning tasks can improve academic outcomes. Grounded in the principles of improvement science, the study began with an examination of student data, empathy interviews, and root cause analysis using tools such as the Five Whys, fishbone diagram, and driver diagram to better understand the problem of practice. This process positioned choice not as a luxury but as a strategic lever for …

The Effect Of Ionic Components On The Performance Of A Model Direct Seawater Electrolyzers, Fethi Mustafa Cimen

Theses and Dissertations

Direct seawater electrolysis (DSE) has gained increasing attention as a sustainable method for hydrogen production that does not require purified water resources. The ionic composition of seawater, especially the concentrations of sodium (Na+) and chloride (Cl-) ions, plays a critical role in determining the electrochemical behavior, membrane transport properties, and overall system performance. This thesis presents a numerical investigation of a model direct seawater electrolyzer with a focus on understanding how changes in seawater ionic strength influence device operation.

A three-dimensional multiphysics Computational Fluid Dynamics (CFD) model was developed in STAR-CCM+ to simultaneously solve heat and mass transport, charge transport, …

Examining Shifts In Attitudes Toward Mathematics: A Mixed Methods Study In Undergraduate Business Calculus, Kathryn Pedings-Behling

Theses and Dissertations

Students in my non-theoretical Business Calculus course at the College of Eastshore almost never begin the class with a positive attitude towards mathematics. They are taking the course to fulfill their general education requirements in mathematics, and for most of them, this will be their last experience in a formal classroom setting with a mathematics educator. This profile of a math-reluctant student is not unique to my Business Calculus course; I have spoken with many fellow educators in similar situations who experience the same persistence of negative attitudes toward mathematics from their own students. Their attitude not only has implications …

I Fina’Nå’Guen I Famagu’On Put I Tåsi: The Impact Of Phenomena-Based Learning On Explaining And Conceptualizing Ocean Acidification In The Pacific, Angelia Jean Blas-Lizama

Theses and Dissertations

This convergent mixed methods study examined the impact of a new phenomena-based (PhBL) lesson plan—grounded by social constructivism and the NGSS framework—on 1) student ability to explain and contextualize a phenomenon, and 2) assess student perceptions of PhBL compared to traditional science instruction. This addressed the shift towards science education reform that better prepares K-12 students for the STEM pipeline and creates student agency surrounding human impact on the environment. Ocean acidification was the selected phenomenon for this study as it was culturally and locally relevant to the participants—sixth-grade science students at a Pacific Island public middle school. Findings revealed …

Simulating K-Distributed Sea Clutter For Improvement Of X- Band Radar Littoral Object Detection Performance, Hudson Richard Dye

Theses and Dissertations

This thesis provides a statistically based method of simulating K- distributed sea clutter for littoral X-band radar object detection. Littoral radar systems must detect small objects in cluttered environments dominated by return from the sea surface. Accurate modeling of sea clutter is fundamental for improving radar detection performance. The clutter synthesizer presented here is an effort to enable computer modeling of realistic sea clutter even with restricted knowledge of sea clutter behavior.

The K-distribution is widely used to model sea clutter in X-band radar systems. Its parameters 𝜈 and 𝑏 are closely tied to third and fourth statistical moments and …

Advanced Modeling Techniques And Crosstalk Mitigation Methodology For High-Speed Interconnects In Modern Communication Systems, Yingcong Zhang

Theses and Dissertations

The increasing demand for higher data rates, greater computational performance, and continued PCB miniaturization has rendered interconnects a critical bottleneck in modern communication and computing systems. High-density routing, while enabling compact designs, significantly exacerbates signal integrity (SI) challenges such as impedance mismatch, far-end crosstalk (FEXT), and propagation delay. Despite advances in design practices, efficient closed-form analytical models capable of accurately characterizing complex, high-frequency interconnect geometries remain limited, necessitating reliance on computationally intensive numerical simulations. This dissertation addresses these limitations by developing analytical modeling methodologies and proposing novel interconnect structures to ensure robust SI in high-speed PCB systems.

The first part …

Generalized Planning Using Language Models And Its Applications, Vishal Pallagani

Theses and Dissertations

Planning is a fundamental capability for intelligent systems, yet classical planners remain difcult to scale and generalize across domains due to their reliance on hand- engineered models, brittle search procedures, and limited adaptability. These limita- tions constrain real-world applications that require fexible reasoning, robust decision- making, and the ability to operate across diverse environments.

Large language models have emerged as powerful learners supported by their ar- chitectures and large-scale training data, demonstrating strong capabilities in tasks such as question answering, code generation, summarization, and reasoning. Moti- vated by their broad generalization abilities, I investigate whether language models can be systematically …

Development And Optimization Of Aluminum-Water Reactors For Efficient And Sustainable Hydrogen Production, Guru Prasad Dhungel

Theses and Dissertations

Hydrogen is a promising clean energy carrier; however, safe, controllable, and on- demand hydrogen generation remains a significant engineering challenge. Aluminum– water reactions offer high theoretical hydrogen yield, but practical implementation is limited by oxide passivation and difficulty in maintaining stable thermal and pressure conditions.

This study investigates hydrogen generation from aluminum foam–steam reactions under controlled temperature and pressure using engineered reactor configurations. Three reactor designs, horizontal, vertical, and cylindrical—were experimentally optimized, developed and evaluated to enhance hydrogen production rate and pressure stability without chemical additives. The experiments focused on heat transfer behavior, steam management, pressure buildup, and reaction stability. …

Strain-Induced Oxygen Vacancy Effect On Thermoelectric Properties In Oxide Thin Films, Ebenezer Seesi

Theses and Dissertations

The development of highly efficient and cost-effective thermoelectric (TE) materials is critical for converting waste heat into electricity in advanced power generators. For high-temperature TE applications, transition metal oxides (TMOs) have attracted significant interest because they are comparatively safe, earth-abundant, and stable under oxidizing conditions where many conventional heavy-metal and chalcogenide TE materials degrade. However, the TE performance of TMOs is limited by the intrinsic trade-off between the Seebeck coefficient (S) and electrical conductivity (σ), both of which depend inversely on charge carrier concentration. This constraint limits the achievable power factor (PF = S²∙σ) and remains a central obstacle for …

Plasma Dynamics And Chemistry In Atmospheric Pressure, Ayoub Al Wahaibi

Theses and Dissertations

Atmospheric-pressure plasmas are attractive for practical chemical and energy applications because they can be generated without vacuum systems and can produce reactive environments under relatively mild bulk conditions. However, these discharges are often non-uniform and highly sensitive to operating conditions, especially when water or multiphase flows are introduced. This dissertation investigates how atmospheric- pressure plasma behavior and plasma-driven chemistry change in three challenging but application-relevant regimes: water-mist dielectric barrier discharges (DBDs), multiphase plasma-assisted fuel reforming, and striated AC glow discharges. The work combines optical and electrical diagnostics, imaging, chemical analysis, and time-dependent analysis to connect discharge characteristics with measurable chemical …

A Pcb-Based Three-Level Active-Neutral-Point-Clamp Converter With Gan Devices, Mohammad Hassan Adeli

Theses and Dissertations

Modern microgrids, EV chargers, and renewable energy systems require power converters that are efficient, compact, and capable of high-frequency, high-power operation. However, in tightly packaged high-power designs, parasitic inductances and capacitances become significant, leading to voltage overshoot and elevated electromagnetic interference (EMI) under rapid dv/dt transitions. To address these challenges, this work presents a PCB-based 25kW, 480V, 200kHz grid-connected three-level active neutral-point-clamped (3L-ANPC) converter employing GaN devices. The PCB design emphasizes the optimization of parasitic inductances and capacitances to enhance high-voltage safety and reliability. A multilayer PCB busbar structure is implemented to minimize parasitic loops, enabling fast switching with minimal …

A Conductor’S Guide To Charles Villiers Stanford’S Songs Of The Sea & Songs Of The Fleet, Brian Niu

Theses and Dissertations

Charles Villiers Stanford is best known for his contributions as a composer to the sacred choral genre and his role as Professor of Composition at the Royal College of Music in London during the Second English Musical Renaissance. Beyond his church music, which is still regularly performed today, Stanford’s secular compositions are largely underperformed, especially for a composer and teacher of his stature. This document provides a conductor’s guide to Charles V. Stanford’s two works: Songs of the Sea and Songs of the Fleet. These two choral-orchestral works are less than 25 minutes in duration each and are scored for …

Deep Learning Models For Anomaly Detection In Industrial Inspection, Jiawei Guo

Theses and Dissertations

Anomaly detection plays a pivotal role in ensuring the longevity and safety of engineered systems, particularly in domains where defects can have significant operational or economic consequences. From internal damage in structural parts to subtle visual defects in manufactured components, identifying abnormal patterns requires models that are both computationally efficient and suitable for real-world deployment. This dissertation explores deep learning-based solutions designed to address these challenges, with a focus on Structural Health Monitoring (SHM) and industrial defect inspection under real-world scenarios.

This dissertation first addresses the problem of efficient and reliable component- level perception with limited supervision and strict hardware …

Laser-Based Wideband Guided Ultrasonic Wave Inspection Of Isotropic And Anisotropic Materials, Andrew Philip Campbell

Theses and Dissertations

Non-destructive evaluation (NDE) and structural health monitoring (SHM) have experienced significant growth in both capability and utility as material evaluation and damage detection methods for structural components throughout various industries over the past two decades. Evaluating a structure throughout its life cycle or on demand as needed can identify critical weaknesses that impact safe operation and may prevent failures. Various NDE/SHM methods have been shown to be effective; among them, guided ultrasonic waves (GUW), particularly Lamb wave-based methods, have been intensively studied due to their capability to interrogate internal defects and their relatively larger coverage. With the advancements in new …

The Importance Of Being Present: Presence Over Performance, De'on Turner

Theses and Dissertations

This thesis examines the development of presence as the foundational element of the actor’s craft through a sustained analysis of four major roles performed during the Master of Fine Arts Acting program at the University of South Carolina: Walter Lee Younger in A Raisin in the Sun (Spring 2024), Kesi/the Astronaut in Moon Man Walk (Fall 2024), Dennis in Mauritius (Spring 2025), and Jack Worthing in The Importance of Being Earnest (Fall 2025).

The central argument of this thesis is that the actor does not bring the character to life — at full depth; it is the character who brings …

Acoustics Of The Kettle Drum: A Scientific Approach To Timpani Performance, Yuesen Yang

Theses and Dissertations

This dissertation bridges the gap between scientific and performance approaches in timpani pedagogy. While the timpani have long been a member of various ensembles, its pedagogy often relies on experiential knowledge of the performers. This study synthesizes findings from acoustical research with traditional teaching sources to establish a coherent framework for timpani pedagogy.

Chapter one introduces the study’s purpose, states the problem, and presents the methodology. It also clarifies the scope of this dissertation. It identifies the lack of consistency between acoustic research and current pedagogical approach, proposing a comparative analysis of scientific literature and established pedagogical texts.

Chapter two …

Deep Learning Algorithms For Generative Materials Design And Composition Based Property Prediction, Rongzhi Dong

Theses and Dissertations

The accelerated discovery of novel functional materials is critical for advancing trans- formative technologies in energy storage, electronics, and catalysis. Current discovery strategies, whether experimental trial-and-error or DFT-based computational screen- ing, are fundamentally constrained by the limited size and diversity of existing materials databases and the difculty of building predictive models that generalize beyond known compounds. Despite signifcant progress in both experimental and computational approaches, two central challenges persist in modern materials science: generating large numbers of realistic, stable, and synthesizable materials outside existing databases, and developing machine learning models capable of accurately inferring structures and predicting properties under realistic …

Machine Learning Toward Materials Discovery: From Crystal Mapping And Out-Of-Distribution Property Prediction To Radiation Detection And Emerging Foundation Models., Qinyang Li

Theses and Dissertations

The discovery and optimization of advanced materials are central to addressing global challenges in energy, healthcare, and sustainability. This dissertation develops representation-aware and distribution-aware machine learning frameworks to improve robustness, generalization, and interpretability in materials informatics and radiation detection. The work spans crystal structure mapping, adversarial learning for out-of- distribution prediction, foundation-model-based property prediction, and deep neural classifcation of photon interactions.

A global mapping framework is frst introduced to analyze the inorganic materials space using compositional, structural, physical, and neural descriptors derived from the Materials Project database. By embedding materials into low-dimensional mani- folds, the framework reveals clustering behavior and …

From Experience To Reasoning: Offline Rl Subroutines And Llm-Based Grounding For Sample-Efficient Reinforcement Learning, Jianhai Su

Theses and Dissertations

Improving the learning efficiency of reinforcement learning (RL) agents remains a fundamental challenge, particularly in environments characterized by sparse rewards, long horizons, or partial observability. This dissertation investigates how RL agents can learn more efficiently through two complementary forms of guidance: mechanisms derived purely from an agent’s own experience and mechanisms that leverage reasoning priors from pretrained large language models (LLMs).

On the experience-driven side, the frst study develops a general framework for incorporating ofine RL algorithms as subroutines within an online RL process. In this framework, an agent periodically repurposes its replay bufer as an ofine dataset and applies …

An Autoethnography Of Organic Representation In Queer Arts Documentation, Eden Joyce Prime

Theses and Dissertations

The goal of this project is to illustrate the importance of documentation processes grounded in ‘organic representation,’ a media practice paradigm from the work of A. J. Christian (2020). Organic representation prioritizes narrative co-creation, informed consent, and intersections of identity and cultural knowledge. To effectively document a subject’s lived experience, a media professional must share intersections of identity and/or culture with the subject and provide opportunities for narrative co-creation. Intersectional positionality gives media practitioners authority to document important narratives in a way that honors the identity and contextual significance of the subject. For journalists documenting the life and work of …

The Role Of Emerin In Myogenic Differentiation, Nicholas Marano

Theses and Dissertations

The nucleus harbors genetic material encapsulated by the nuclear envelope which is composed of an inner and outer nuclear membrane. The establishment and organization of chromatin at the INM is essential for cell fate during the differentiation program. Integral INM proteins are responsible for chromatin organization at the nuclear envelope. Emerin is a highly conserved type II integral INM protein with roles in chromatin organization, cell signaling, and nuclear structure. Mutations in the emerin gene cause Emery Dreifuss Muscular Dystrophy 1 (EDMD1). Emerin is ubiquitously expressed, but loss of emerin function affects specifically skeletal muscle and cardiac tissue. The precise …

An Interpretable Hybrid Deep And Reinforcement Learning Paradigm For Glioma Prognosis, Renuga Devi M Ms

Theses and Dissertations

Brain tumors are highly aggressive and lethal types of cancer, particularly gliomas. These cancerous growths show complicated pathophysiological behaviours and with poor prognosis despite therapeutic advances. Due to their biological differences and infiltrating growth, as well as overlapping radiological characteristics, they pose great difficulty in diagnosis, grading, and survival prediction. Artificial intelligence technology, which includes machine learning , deep learning, and reinforcement learning has developed into a new paradigm for the automation of brain tumor diagnostics and personalized treatment. The main goal of this study is to create an integrated AI-based framework that can perform brain tumor segmentation, grading and …

Development Of Deep Fused Neural Architecture For Ancient Tamil Palm-Leaf Manuscript Recognition, Hariharan P Mr

Theses and Dissertations

Digitizing Tamil palm-leaf manuscripts is important for education, communication, and the preservation of cultural heritage. The complex structure of the Tamil script, the wide range of handwriting styles, and the degradation seen in ancient Tamil palm-leaf manuscripts make these texts very difficult to read and understand. Digital Image Processing (DIP), document analysis techniques, and traditional Optical Character Recognition (OCR) are unable to handle noise, background interference, faded ink, and limited labelled data, motivating the need for robust, effective Deep Learning (DL)- based solutions.

As a prerequisite to understanding and designing effective recognition systems for ancient manuscripts, this thesis first examines …

Electrochemical Sensors And Processes In Molten Salts: Chlorine Production, Electroanalytical Chemistry, And Thin-Layer Electrodes, Tyler Williams

Theses and Dissertations

Molten salt electrochemistry has historically played a substantial role in the metallurgical industry, and this trend is only accelerating in areas of green steel, direct ore processing, and rare-earth processing. In addition, the recent surge of interest in molten salt nuclear reactors has provided an additional application for molten salt electrochemical processes, including the reprocessing of used nuclear fuels and the development of electrochemical sensors for nuclear applications. In this work, the development of a chloride volatility separation process for used nuclear fuel is advanced; electroanalytical methods are improved for identifying and quantifying unknown analytes with and without the presence …

Rigorous Electromagnetic Beamforming Simulations For Realistic Vehicular-To-Infrastructure (V2i) Scenarios In 5g Systems, Mohanad Hussam Aldean Ahmed Almuzian

Theses and Dissertations

Millimeter-wave (mmWave) Vehicle-to-Infrastructure (V2I) communication is a key enabling technology for next-generation intelligent transportation systems, offering high data rates and low latency to support safety-critical and autonomous driving applications. However, mmWave communication at 28 GHz suffers from severe path loss, sensitivity to blockage, and strong dependence on antenna directivity and beam alignment, particularly in complex urban environments. As a result, advanced beamforming and multi-antenna techniques are essential to ensure reliable and high-capacity V2I links. This thesis investigates mmWave V2I communication performance using realistic electromagnetic modeling and beamforming techniques. Full-wave antenna simulations and deterministic ray-tracing are employed using Ansys Electronics Desktop, …

Governing Bme Amplification In Large Language Models: A Standards-Aligned Framework For Llm Data Lifecycle Risk Detection And Ethical Ai Governance, Dale A. Rutherford

Theses and Dissertations

Large Language Models (LLMs) now underpin critical systems in education, healthcare, and policy advisory contexts, yet remain susceptible to the recursive amplification of bias, misinformation, and error (BME). These distortions, driven by feedback loops between user interactions, model retraining, and data reuse, accelerate epistemic drift and erode information quality over time. This dissertation advances a comprehensive governance architecture to detect, quantify, and mitigate these risks across the full AI lifecycle. The research introduces the BME Metric Suite, a standards-aligned diagnostic framework comprising five original metrics: Bias Amplification Rate (BAR), Echo Chamber Propagation Index (ECPI), Information Quality Decay (IQD), Pretraining Diversity …

Generalizing Networks To Address Data Imbalance For Facial Action Unit Recognition, Andrew W. Sumsion

Theses and Dissertations

Facial action unit (AU) recognition is used in a variety of downstream applications, including sign language translation, dementia detection, pain detection, and other high-impact tasks that require understanding facial motion. Although AU recognition is a well-established field, a number of unresolved issues remain. An initial problem is the need to improve overall performance on the benchmark datasets, as measured by the average F1 score. Also, the performance across all individual AUs, not just the average F1 score, needs to be increased. Recently, the field has shifted its attention towards ensuring that AU recognition models generalize beyond the distributions represented in …

Tusqh: Topological Control Of Volume-Fraction Meshes Near Small Features And Dirty Geometry, Brian Reese Shawcroft

Theses and Dissertations

This work develops a framework to create meshes with user-specified homology from potentially dirty geometry by coupling background grids, persistent homology, and a generalization of volume fractions. For a mesh with fixed grid size, the topology of the output mesh changes predictably and monotonically as its volume-fraction threshold decreases. Topological anti-aliasing methods are introduced to resolve pinch points and disconnected regions that are artifacts of user choice of grid size and orientation, making the output meshes suitable for downstream processes including analysis. The methodology is demonstrated on geographical, mechanical, and graphics models in two-dimensions (2D) and three-dimensions (3D) using a …

Database-Driven Revelations In Epilepsy: Patient Reporting Accuracy And The Circadian Timing Of Seizures, Ithay Biton

Theses and Dissertations

For over thirty years, patients have been visiting the Arkansas Epilepsy Program for diagnosis and treatment for seizures and seizure-like episodes. As part of their clinical evaluation, patients often undergo ambulatory EEG (electroencephalogram) monitoring. This routine process produces valuable data for treating the patient. In this study, over 2000 ambulatory EEG reports from 1998 to 2016 were reviewed. A large database of seizures was created from the reports, with information on 407 patients, 1611 EEG-confirmed seizures, and 1726 patient-reported seizures (IRB Protocol #17-093). The database was used to address two important issues in epilepsy. The first topic of the study …

Tunable 3d-Printed Biomaterials For Perfused In Vitro Models Of The Blood-Brain Barrier, Louis Salvatore Paone

Theses and Dissertations

In vitro models have tremendous utility for improving our understanding of complex physiological and pathophysiological processes in a more controlled environment than animal models, in addition to incorporating human cells to overcome species-specific disparities. This dissertation describes innovations in biomaterial-based fabrication processes that advance in vitro models of the blood-brain barrier, providing the opportunity to evaluate the effects of cell-matrix interactions on barrier integrity, additives to reduce viscous drag of blood flow, and molecular mechanisms underlying the cellular response to amyloid beta in the context of Alzheimer’s disease. The core technology underlying this advance is a biomaterial compatible with digital …