Digital Commons Network^™

The Baroclinic Route To Acoustic Streaming: Mechanisms Of Mean-Flow Generation And Heat Transport In Acoustically-Forced Stratified Fluids, Remil Mushthaq

Doctoral Dissertations

Standing acoustic waves in density-stratified fluids confined within horizontal channels generate fluctuating vorticity baroclinically, driving mean streaming flows that are much stronger and qualitatively distinct from classical Rayleigh streaming. Theoretical and numerical studies have shown that these baroclinic acoustic streaming flows can reach speeds comparable to the maximum speed of the oscillatory sound-wave field, enabling fully two-way wave/mean-flow coupling: the streaming flow modifies the background density field, which then alters the structure of the acoustic waves. Extending this framework, Massih (2022) quantified the heat-transfer enhancement arising from baroclinic streaming as a function of the channel aspect ratio (δ). The present …

Shared Voices: How Pk-16 Leaders Perceive School University Partnership Alignment With Caep Standards, Ann-Marie Hancock

Doctoral Dissertations

This mixed-methods study examined PK–16 leaders’ perspectives regarding the alignment of an educator preparation provider (EPP) with the Council for the Accreditation of Educator Preparation (CAEP) Standards 2 (Clinical Partnerships and Practice) and 5 (Quality Assurance System and Continuous Improvement). Data were collected through a researcher-designed survey and semi-structured interviews with principals, district administrators, and university leaders. Survey results provided descriptive insights into stakeholder perceptions, while interviews offered deeper contextual understanding of the strengths and challenges within school–university partnerships. Findings indicated that leaders valued residency programs and recruitment pipelines as key strengths, highlighting the mutual benefits of sustained clinical partnerships. …

Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn

Doctoral Dissertations

The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …

Towards Robust Autonomous Systems: Handling Multi-Modal Uncertainties In Gps-Denied Environments, Vivya Kalidindi

Doctoral Dissertations

This dissertation focuses on designing a robust and uncertainty-aware framework for autonomous systems operating in GPS-denied environments, such as indoor infrastructures, underground tunnels, and lunar surfaces. The proposed framework addresses the challenges posed by multi-modal uncertainties, including sensor noise, distributional shifts under adverse conditions, and conflicting decision-making preferences. These challenges compromise the reliability and adaptability of autonomous platforms. To overcome these challenges, the proposed framework adopts a layered architecture that integrates advanced methodologies across the sensing, perception, and decision-making layers. At the sensing layer, an Edge-Kalman Filter combined with a density ratio-based update mechanism is employed to reduce aleatoric uncertainty …

From Structure To Specificity: Biophysical Characterization Of Functional Interfaces In Protein Systems, Logan M. Brown

Doctoral Dissertations

Proteins are nature’s dynamic molecular machines, operating across a spectrum from highly ordered scaffolds to intrinsically disordered systems, and executing functions that depend on both precise structures and conformational flexibility. Yet, the mechanistic rules linking sequence, structure, and activity particularly in disordered proteins and specialized functional adaptations remain incompletely understood. This dissertation addresses that gap by integrating structural biology, biophysics, and protein engineering to dissect molecular recognition, stability, and function across three diverse yet thematically connected protein systems. Building on this understanding of protein structure and function, the following four projects apply these concepts to address diverse biological questions, ranging …

Interpolated Factored Green's Function (Ifgf) Method Of Acceleration For Electromagnetic Scattering Off Of A Perfectly Electrically Conducting Surface, Mathew D'Amico

Doctoral Dissertations

Boundary integral equation (BIE) methods are advantageous in scattering problems due to their reduction of the problem's dimensionality as well as their automatic satisfaction of far-field radiation conditions. Specifically, for electromagnetic scattering off of perfectly electrically conducting (PEC) geometries, we are concerned with the magnetic field integral equation (MFIE). Typically, BIE implementation is iterative, with each direct integration requiring $\mathcal{O}(N^2)$ operations for a grid size $N$. For large $N$, this incurs very large computation times. To date, all existing methods that reduce the asymptotic operational complexity of evaluating the MFIE integral to $\mathcal{O}(N\log N)$ rely on use of the Fast …

Investigations Into Prior Knowledge And Self-Efficacy As Predictors Of Exam Performance In General Chemistry, And Student Interactions With Chemistry Textbooks, Gordon Hunter

Doctoral Dissertations

The first chapter addresses the validity and reliability of the Motivated Strategies for Learning Questionnaire (MSLQ) as a tool for chemistry education research. The study shows that the original MSLQ did not meet modern standards of reliability and presents a modified version that better captures self-efficacy in chemistry-specific contexts. The revised instrument shows improved model fit, reinforcing the importance of refining assessment tools for chemistry education research.The effects of prior knowledge and self-efficacy on student performance in a first-semester general chemistry course are investigated in the second chapter. Self-efficacy, defined as a learner's belief in their capability to successfully accomplish …

Psychological Factors Of Acting Talent And Success: You've Got "It", Lorelei Tierney Himlin

Doctoral Dissertations

The goal of an actor is to become invisible, bringing a character to life so convincingly that the audience forgets the actor exists outside the role. Different schools of acting often describe differing methods of portraying characters to this same general effect. To followers of the Meisner school, for example, “acting is behaving truthfully under imaginary circumstances” (Meisner et al., 1987). The “truthful” part involves creating a comprehensive mental model of a character’s imagined personality in order to fully embody that personality and extrapolate it to a situation. Then the actor uses a variety of acting techniques to think and …

Black Hole-Neutron Star Mergers: Numerical Relativity Studies Of Remnant Matter, Gravitational Waveforms, And Automated Simulation Workflows, Tia Kathleen Martineau

Doctoral Dissertations

Black hole–neutron star (BHNS) mergers are key sources for multimessenger astrophysics, offering insight into strong-field gravity and the behavior of matter at supranuclear densities. This dissertation presents three independent contributions to the study of BHNS systems using the Spectral Einstein Code (SpEC). First, a set of simulations spanning a range of mass ratios, black hole spins, and neutron star equations of state is used to map disruption thresholds and quantify remnant disk masses, unbound ejecta, and ejecta composition. These results are compared to predictions from remnant mass model FNH18, to assess its reliability in accurately predicting the resulting remnant masses …

Multi-Level Characterization And Testing Of Fatigue, Fracture And Creep Of The Ultra-High Strength Low-Alloy Steel Fabricated Via Laser Powder Bed Fusion, Nemanja Kljestan

Doctoral Dissertations

This dissertation presents a comprehensive experimental investigation of the mechanical behavior of an high-strength low-alloy (HSLA) steel fabricated via laser powder bed fusion (LPBF). The work focuses on fatigue strength, laser shock peening (LSP) effects, creep behavior, fatigue crack growth and fracture toughness. Fatigue strength was assessed using rotating bending tests, showing superior performance of LPBF specimens compared to as-cast materials due to the dual-variant martensitic microstructures. Laser shock peening enhanced fatigue life by inducing compressive residual stresses, delaying crack initiation and slowing crack propagation. Creep behavior was evaluated for different layer thicknesses, with thinner layers improving secondary creep resistance …

Simulations Of Perpendicular Electron Holes, James Patrick Mcclung

Doctoral Dissertations

Bernstein–Greene–Kruskal modes commonly manifest as electron holes and electrostatic solitary waves in space plasmas. These Debye-scale structures are nonlinear solutions to the steady-state Vlasov–Poisson system. Solutions in one dimension are highly tractable mathematically, observationally, and computationally, and are relatively well-understood. Higher-dimensional, magnetized plasmas are less amenable to study, however. Following a 20-year history of theoretical developments in two-dimensional BGK modes, this thesis presents the first high-resolution 2D and 3D simulations thereof. Stability conditions and phase-space dynamics are discovered and discussed. The simulated modes are ultimately compared to observed electron holes and modern width-amplitude relations. In addition, a significant portion of …

Computational String Theory Using Machine Learning, Giorgi Butbaia

Doctoral Dissertations

Low-energy couplings of certain superstring theories are related to the masses of the particles. One of the most promising superstring theories is $\mathcal{N}=1$ supersymmetric $E_8\times E_8$ heterotic string theory. In a certain embedding of the standard model into $E_8\times E_8$ gauge group of the heterotic string, the particle spectrum consists of $(\mathbf{27})^3$, $(\overline{\mathbf{27}})^3$, $(\mathbf{1})^3$ and $\mathbf{1}\cdot \mathbf{27}\cdot\overline{\mathbf{27}}$ couplings. While the $(\overline{\mathbf{27}})^3$ couplings are quasi-topological, the $(\mathbf{27})^3$ explicitly depend on the Ricci-flat metric on Calabi-Yau.

In this dissertation, we explore recently developed techniques for calculating the normalized Yukawa couplings on various Calabi-Yau manifolds. In Chapter 2, we describe a novel architecture, …

Fine Structure Of Magnetic Reconnection: Impact On Reconnection And Dissipation Rates, Steven Ver Bryck Heuer

Doctoral Dissertations

Magnetic reconnection is a fundamental process in magnetized plasmas where stored magnetic energy is converted to heat and kinetic energy. The objective of this thesis is to examine the role of small-scale structure of the reconnection region and the background plasma conditions on the rate that reconnection converts and dissipates magnetic energy. This is done using in situ data from NASA’s Magnetospheric Multiscale (MMS) mission and particle-in-cell (PIC) simulations of reconnection for different regimes. First, we introduce a new technique for measuring the reconnection rate and demonstrate its accuracy for the simplest regime of reconnection. Next, we show that it …

Resolving The Role Of Wave-Induced Pressure Gradients On The Movement Of Sediments In Nearshore Environments, Melissa Marry

Doctoral Dissertations

Characterizing the hydrodynamic forces responsible for the initiation of sediment motion is fundamental for improved understanding of large-scale sediment transport processes in nearshore environments. Traditional sediment transport models assume incipient sediment motion is only driven by the force applied by bed stress (Bagnold, 1966; Shields, 1936) while more recent work has shown that incipient motion is influenced by the forcing of the horizontal pressure gradient due to surface gravity waves (Foster et al., 2006; Frank et al., 2015; Sleath, 1999). Wave-induced vertical pressure gradients can also destabilize the sediment bed through the process of momentary liquefaction (Florence et al., 2022b; …

A Study Of Rural Health Care For Chronic Care Management Using Machine Learning To Determine Costs, Joanna Maria Keeling

Doctoral Dissertations

Management of diabetes or heart disease may be uniquely challenging for older individuals with multiple chronic conditions[1]. Chronic Care Management would target patients living with comorbidities in Louisiana, who are not receiving sufficient healthcare services and help them receive the care they deserve[2]. This study is aimed at comparing the results of rural Louisiana Medicaid recipients with comorbidities to the National Averages. We will also use Machine Learning to predict Churn and Medical Costs. To help us identify these patients with comorbidities, we decided to use NCQA Quality Measures. We identified several measures from NCQA that we wanted to use, …

Structural And Computational Results On Equitably Dissectible Graphs, Ann Wells Clifton

Doctoral Dissertations

This dissertation introduces the class of equitably dissectible graphs — graphs whose vertex set can be recursively partitioned into two parts whose sizes differ by at most one where the two induced subgraphs are connected. In Chapter 2, we show that a graph is equitably dissectible if and only if it has a spanning tree that is equitably dissectible, and we use this result to establish connections between the class of equitably dissectible graphs and Hamiltonian graphs. We also fully characterize the equitably dissectible spiders of the form S3(a) and S3(a, b), identifying a family of unruly spiders that are …

A Backtracking Algorithm For Determining The Existence Of Regular Graphs Of Specified Girth And Excess, Stetson Ray Bosecker

Doctoral Dissertations

The study of cages focuses on finding (k, g)-graphs of minimal order. This dissertation generalizes the problem of finding cages to the determination of graphs with specified excess, thereby broadening the significance of the results. The (k, g, ε)-graph problem seeks to determine the existence or nonexistence of k-regular graphs with girth g and excess ε = n(G)−M(k, g) (where M(k, g) represents the Moore bound for cage graphs). Motivated by heuristic methods used to determine properties within the study of cages, we present a backtracking algorithm capable of constructing (k, g, ε)-graphs or determining their nonexistence. Chapter 2 provides …

Privacy-Preserving Structure Learning For Geospatial Data Using Information-Theoretic Dependency Measures, Ahmed Mudhish

Doctoral Dissertations

This dissertation proposes a privacy-preserving framework for structure learning in Bayesian networks (BNs) that addresses the challenges of distributed geospatial data face. Geospatial datasets often exhibit region-specific patterns such as sparsity and nonlinear dependencies. These patterns undermine the effectiveness of traditional machine learning models. Additionally, learned BN structures may reveal sensitive relationships in the generated graph by BNs. These relationships pose a significant privacy risk if reverse-engineered. To address these issues, three novel algorithms are introduced. First, the Selective Naïve Bayes with HSIC (SNB-HSIC) algorithm applies a kernel-based dependency measure to filter redundant and irrelevant features in sparse datasets, improving …

Advancing Rfid Systems: From Head Orientation To Robotic Localization Using Passive Tags, Guilherme Ricardo Mendes Da Silva Barreto De Figueiredo

Doctoral Dissertations

No abstract provided.

An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki

Doctoral Dissertations

The Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are revolutionizing critical infrastructures, but their expansion has also introduced severe cybersecurity vulnerabilities. Traditional IoT Bot Detection Systems (IBDS) struggle to scale in environments characterized by high-dimensional, large-scale, and redundant network traffic. These challenges hinder the development of reliable cloud-based intrusion detection systems. The limitations of static and rulebased methods in detecting evolving IoT botnet attacks—such as those launched by Mirai and Gafgyt—underscore the need for intelligent, adaptive approaches. To address this, the present study proposes a machine learning and deep learning-driven IoT Botnet Detection Model, validated through …

Detection And Mitigation Of Out-Of-Band Channel Wormhole Attack In Wireless Network Using Propagation Delay, Harry May

Doctoral Dissertations

Wireless networks, susceptible to a range of attacks due to their simplicity and ease of evasion, face a significant threat from control data attacks, notably the elusive wormhole attack. Detecting and mitigating such attacks poses challenges, particularly in the absence of a digital signature. This dissertation introduces an innovative approach that utilizes the propagation delay associated with malicious nodes’ timing characteristics for detection, employing the Ad-hoc On-Demand Distance Vector (AODV) algorithm as its foundation. The inherent propagation delay in the AODV protocol is calculated for each node link along the entire communication path, offering a distinctive timing method that provides …

The Role Of A Lower Elementary Principal In Championing Co-Teaching As A Strategy To Promote Inclusive Education, Lauren Pigue Keen

Doctoral Dissertations

This qualitative autoethnographic study explores the role of a lower elementary principal in leading a co-teaching initiative to create a more inclusive educational environment for students with disabilities. Rooted in Lewin’s Change Theory, the study examines how personal experience, professional vision, and intentional leadership contributed to the implementation and expansion of co-teaching practices within an early childhood setting. The research focuses on the principal’s dual role as both a systems-level change agent and an insider experiencing the transformation firsthand. Data were collected through reflective narrative, stakeholder interviews, and document analysis to provide a comprehensive view of the leadership decisions, cultural …

Who Should Take Responsibility For Artificial Intelligence Actions And Outcomes? Perception Of Auditors As Users Of Ai Systems, Hanh Hoang Le

Doctoral Dissertations

As artificial intelligence (AI) systems become increasingly embedded in auditing processes, questions arise regarding how professional auditors perceive and allocate responsibility for AI-assisted decisions. This study investigates the effects of AI explainability and auditors’ perceived autonomy on perceived responsibility in the context of audit decision-making. Drawing on theories of moral responsibility and professional judgment, the study employs a 2x2 experimental design using hypothetical audit scenarios to manipulate levels of AI explainability and auditors’ autonomy. Hierarchical regression analysis reveals that perceived autonomy statistically significantly increases auditors’ perception of responsibility for AI-assisted decisionmaking, whereas AI explainability is not a significant predictor. Additionally, …

Competencies For Effective Stem Leadership: Essential Knowledge, Skills, Dispositions, And Practices To Inform Stem Education Programs And Support Program Leadership, Melissa Adams Wooley

Doctoral Dissertations

The purpose of this study was to identify a set of knowledge, skills, dispositions, and practices that are important for STEM leaders to consider as constructs of a STEM theory as they plan and implement a STEM program. The research design included a modified Delphi panel to gain consensus on the knowledge, skills, dispositions, and practices, called competencies, that effective STEM leaders consider when planning and implementing a STEM program. The panel participants were experts in STEM education. Based on the literature, the researcher identified the initial set of competencies. The panel identified ten additional competencies through the Delphi process, …

Exploring Ignatian Pedagogy's Role In Shaping Holistic Student Success In The Current Neoliberal Era: A Qualitative Inquiry At Saint Ignatius High School, Rwanda, And Lycée Du Saint-Esprit, Burundi, Olivier Kayitare

Doctoral Dissertations

The growing influence of neoliberalism in education has shifted priorities toward a transactional, utilitarian model that emphasizes technical skills, standardized testing, and market-driven outcomes over holistic development. Education systems increasingly focus on preparing graduates for labor market demands, often sidelining moral, emotional, social, and spiritual formation. This shift creates tension for Jesuit schools, which emphasize a transformational approach to education rooted in ethical leadership, critical thinking, and social responsibility. In countries like Rwanda and Burundi, Jesuit schools face added pressure from state policies and parental expectations shaped by market ideologies. This study examined how Ignatian pedagogy is implemented in this …

Decolonizing Education In The Post-Independent Madagascar By Utilizing Malagasy As The Primary Language Of Instruction In Schools, Patric R Razafimahafaly

Doctoral Dissertations

When the French colonial power structured the education system in Madagascar during colonization (1896-1960), they oriented it toward French needs and interests (Rosnes & Rakotoanosy, 2016). One of the relics of the French colonial influence that significantly affected Madagascar since its independence in 1960 is the choice of language of instruction in its domain of education. Even though Madagascar has its sole spoken and written language, “Malagasy,” that people use every day, it has decided to borrow French and utilize it as the language of instruction and administration for its people (Dahl, 2011; Rosie, 2012; McCaughey, 2020; Pirbay & Rosenboom, …

Exploring Arabic, Russian, And Spanish Native Language Teachers’ Perceptions Of The Flipped Classroom Model Through The Lens Of The Technology Acceptance Model (Tam2), David I. Daoud

Doctoral Dissertations

The flipped classroom has become increasingly popular across various educational settings over the last two decades. In the flipped classroom model (FCM), the teacher spends less time on traditional in-classroom activities like lecturing and giving tests, which are instead assigned as homework, and more time on hands-on learning. Although research has shown the FCM is effective in a variety of learning settings, little is known about native language teachers' perceptions of the FCM. This study explored the perceptions of 41 native Arabic, Russian, and Spanish foreign language instructors regarding the FCM at a college-level language institution. The study aimed to …

“How Do You Replicate A Relationship?” An Exploration Of How A School-Community Partnership Was Conceptualized And Enacted, Emilie Coppinger

Doctoral Dissertations

With concerns about supporting students’ overall wellness on the rise, school-community partnerships offer a promising solution. These collaborations can improve outcomes for students, schools, and communities by bringing together diverse expertise and funding sources. However, how these partnerships are formed and maintained, as well as how stakeholders are included in them, needs further exploration. To address this gap, the current study follows a collaboration between a school district and local health agency from the project’s initiation through its execution. The research approach and study design draw on the traditions of community-based research and ethnography, guiding my data collection and representation …

A Multi-Layered, Discourse-Oriented Exploration Of Learning Assistant-Student Interaction In Calculus I, Rebecca Butler

Doctoral Dissertations

Learning Assistants (LAs) are undergraduate near-peer tutors who aid in the instruction of collegiate courses in which they have previously been successful as students. It has been consistently shown that students in LA-supported STEM courses have more positive course outcomes than their peers without LA support. The benefits include improved retention, better scores on content assessments requiring higher-order reasoning, and a greater sense of belonging in STEM. Little is known about why students in LA-supported courses evidence this range of positive course outcomes, but it is conjectured that LAs facilitate these outcomes through their frequent and engaging interactions with students. …

Socioeconomic Status And Its Relationship To Mathematics Achievement: Using A Meta-Analysis, Bitna Choi

Doctoral Dissertations

Educational inequality mirrors broader societal disparities. There are various factors that represent educational inequality, such as socioeconomic status (SES), school environment, teacher quality, gender, and support services. Among these, SES is commonly used as a key indicator of educational inequality. Consistently, studies have shown that students from higher socioeconomic backgrounds have higher academic achievement (Johnson et al., 2022; Murphy, 2019; Tate, 1997). This disparity is particularly evident in mathematics, which is crucial for academic and career opportunities. The purpose of this dissertation is to examine the relationship between socioeconomic status (SES) and mathematics achievement of K-12 students. In addition, this …