Digital Commons Network^™

Classroom To Campus: A Qualitative Case Study Of Exemplary First-Year Seminar Instructors In Student Transitions At A Louisiana University, Brianna J. Doucet

Doctoral Dissertations

This qualitative case study examined how exemplary first-year seminar (FYS) instructors design and implement pedagogical strategies that support students’ transitions into higher education through the lens of Schlossberg’s (1981) Transition Theory. Conducted at a public university in Louisiana, the study explored how university-identified, award-winning instructors foster academic, social, and emotional adjustment among first-year students, a critical priority amid the impending enrollment cliff and the growing need to retain enrolled students. Using semi-structured interviews and thematic analysis, findings revealed exemplary instructors design intentional, relational, and reflective learning environments. They view transition as a shared institutional process, model adaptability and lifelong learning, …

Geometric Effects Of Warfighters On Body Armor Fit And Protective Capabilities Against Shock Wave Energy, Melissa Lynn Sutter

Doctoral Dissertations

Body armor is a vital piece of protective equipment for warfighters to defend against threats, necessitating continued development to improve comfort, weight, and protection. However, female warfighters often wear unisex body armor, designed primarily for the male torso. Current research has evaluated the short- and long-term detriments of female warfighters wearing these armors, focusing on comfort and performance. However, these studies do not comprehensively consider how a non-form-fitting armor compromises warfighter safety from battlefield threats. This research examines the geometric effects of female warfighters on armor protection level when defending against shock threats by evaluating the energy distribution on a …

Fully Differential Studies On Dissociative Capture In P + D2 Collisions And On Ionization In P + He Collisions, Shruti Majumdar

Doctoral Dissertations

Advancing our understanding of few-body dynamics in simple atomic systems is a fundamental objective in atomic scattering research. The underlying problem is that the Schrödinger equation is not analytically solvable for more than two mutually interacting particles. This involves a comprehensive exploration of various channels, such as ionization, capture, and excitation. A common theoretical approach to describe ion-atom collisions is based on perturbation theory, where the scattering amplitude is expanded in powers of the interaction potential. Here, understanding the few-body problem means accurately describing the relative importance of the higher- vs the first order terms.

In the case of ionization, …

Reframing Coral Reef Monitoring With Machine Learning And Remote Sensing: Detection, Classification, And Change, Gabrielle Ann Trudeau

Doctoral Dissertations

Coral reefs are vital ecosystems facing rapid decline from climate-driven stressors, yet existing monitoring approaches lack the spatial coverage and temporal resolution needed to capture ecosystem dynamics at meaningful scales. This thesis develops a scalable, integrated remote sensing framework by combining ICESat-2 LiDAR, multispectral imagery, and machine learning to move beyond static habitat maps toward quantitative, multi-factor characterization of reef structure and change. First, machine learning models were applied to ICESat-2-derived rugosity, slope, and bathymetric metrics to detect and delineate coral reef habitats at large scales. Next, a novel nonlinear spectral unmixing approach integrating Planet imagery and ICESat-2 terrain metrics …

The Long And Short Of It: Exploring The Essential Dynamics Of Select Geophysical Flows, Adhithiya Sivakumar

Doctoral Dissertations

Geophysical flows are central to important climatological processes, yet their strong turbulence and additional complexities -- density stratification, wave-current interaction, and phase change -- make analytical prediction and direct numerical simulation infeasible in many regimes. This dissertation adopts a reductionist approach in which simplified representations -- often inspired by observed scale disparities -- are utilized to isolate and investigate the organizing mechanisms of these complex flows. Within this framework, three distinct but thematically connected problems are studied.

We first study Langmuir turbulence in the open ocean, in which surface gravity waves interact with wind-driven currents to organize the mixed layer …

Analysis Of The Complex Nmr Lineshape Of Polarized Deuterons, Michael Joseph Mcclellan

Doctoral Dissertations

To determine the spin polarization of deuterons, nuclear magnetic resonance (NMR) is used. This is necessary for polarized targets, such as for the upcoming $A_{zz}$ and $b_{1}$ experiment at Jefferson Lab. These polarized target experiments are expected to discriminate between different models of the deuteron, which in turn could lead to a better understanding of short-range correlations (SRCs). NMR measures the impedance of a solenoid around a deuterated sample. Although the impedance is a complex value, conventionally only the real part of the impedance has been used for this purpose. However, often the tune is not precisely real, meaning the …

Temperature-Dependent Dielectric Function Of Solids From Coupled Oscillators With Radiation Reaction: Application To Atom–Surface Interactions, Tuhin Kanti Das

Doctoral Dissertations

In this dissertation, we propose a uniform functional form of the dielectric function of solids that is applicable over a wide range of frequencies. We apply our model to describe the dielectric function of two technologically important materials: silicon and calcium fluoride. The temperature dependence of their dielectric functions is also described using simple analytic forms. We found that a generalized Sellmeier-type model with complex denominators (“damped oscillators”) does not lead to a satisfactory fit of experimental data for the dielectric function. In contrast, our model, which is analytically only slightly more involved (“complex oscillator strengths”, complex numerators), allows us …

Architecting A Complex Adaptive System Model For Selecting Policies To Reduce Kidney Discard, Lirim Ashiku

Doctoral Dissertations

"The kidney allocation system is a complex, evolving system involving multiple heterogeneous agents. Each agent exhibits emergent behavior that may not fully align with the complex system goals. Therefore, there is a need for a transdisciplinary systems approach to visualize the interdependency among agents and understand the dominant patterns that shape the kidney allocation system.

First, this research presented an incremental hierarchical system engineering approach in identifying the agents’ needs and behaviors toward the complex systems’ goal of maximizing deceased donor kidney utilization and reducing kidney discard. The hierarchical systems approach linked with model-based system engineering aided in eliciting agents’ …

Theoretical Study Of Long-Range Molecular Interactions, Adrian Luis Batista-Planas

Doctoral Dissertations

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions—with electrostatic, induction, and dispersion as main components—play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well-established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed Long-Range-Fit (LRF), an interactive and user-friendly software package designed to automate …

Security And Energy-Efficiency In Federated Learning, Priyesh Ranjan

Doctoral Dissertations

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, the participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the participants' identities, FL may attract adversaries aiming to hamper the underlying model. These adversaries aim to submit malicious weight updates that corrupt the performance of the server model. Further, these models when communicated to the participating clients extend the behavior which is undesirable. Additionally, FL suffers from increased energy consumption at the edge device level due to …

Adaptive Machine Learning Framework For Microstructural Optimization And Mechanical Performance Prediction In Steels, Henry Adekola Haffner

Doctoral Dissertations

Evolution of microstructures, such as polygonal ferrite, acicular ferrite, bainite, and martensite, plays a pivotal role in determining the final microstructural and mechanical properties of steel products. Given the established inter-relationship between processing parameters, microstructure, properties, and performance, precise control of phase transformation is essential to achieve pre-determined properties. To understand transformation routes in different steel grades, time-temperature-transformation (TTT) and continuous-cooling-transformation (CCT) diagrams are necessary and can be described using the Johnson-Mehl-Avrami-Kolmogorov equation and Scheil’s additivity rule. This study presents a comprehensive computational framework for predicting and optimizing microstructure and mechanical properties in advanced high-strength steels (AHSS) using adaptive machine …

Exploring New Poly-Anion Based Materials For Lithium – Ion Battery Cathodes, Sutapa Bhattacharya

Doctoral Dissertations

The escalating global demand for sustainable energy storage solutions has driven intensive research into novel electrode materials. Polyanion-based cathode materials have emerged as promising candidates due to their structural stability, safety, and voltage tunability enabled by the inductive effect of polyanionic groups. This research explores the synthesis, crystal structure, and electrochemical performance of new polyanion-based cathode materials featuring vanadium, molybdenum, and iron within phosphate and selenite frameworks.

Novel selenite-based materials, such as LiFe(SeO₃)₂ and Li₀.₂₅V₂O₃(SeO₃)₂, were synthesized and characterized, revealing stable electrochemical cycling associated with Fe2+/Fe3+ and V⁴⁺/V⁵⁺ transitions. Additionally, a systematic investigation was conducted on molybdenum phosphate compounds, including …

Investigations In Hydrogen Ironmaking, Joseph William Govro

Doctoral Dissertations

The purpose of this research is to contribute to the Grid Interactive Steelmaking with Hydrogen (GISH) project. This research investigates the viability of both producing and melting Direct-Reduced Iron (DRI) utilizing hydrogen. Conventional CO reduced DRI will be referred to as “C-DRI” and DRI produced using hydrogen gas will be referred to as “H-DRI”.

An H-DRI pilot plant was constructed in Golden Colorado. The pilot plant was commissioned and successfully operated four campaigns. Process improvements were made throughout the campaigns and the process was optimized. In addition to running the pilot plant in a pure hydrogen condition, the pilot plant …

Trust-Aware Algorithms For Stackelberg Ground Vehicle Routing, Doris Evelyn Meredith Brown

Doctoral Dissertations

Despite decades of research focused on reducing ground vehicle traffic congestion, urban traffic networks worldwide continue to experience traffic flows that lead to increased network travel times, largely resulting from the routing decisions of individual vehicles. To address this challenge, this work leverages a Stackelberg game framework to model the interaction between a vehicle agent and a routing authority as a leader–follower game, in which the routing authority proposes routing interventions to which the agent responds. This research contributes to existing traffic mitigation literature by exploring the role of trust in route decision-making and providing trust-aware algorithms that influence vehicle …

Essays On Accelerated Failure Time Models For Recurrent Event Data, Emmanuel Masavo Djegou

Doctoral Dissertations

Recurrent event data arise in many fields such as medicine, reliability, insurance, and economics, where the same event may occur repeatedly for a subject. Accelerated Failure Time (AFT) models provide an intuitive framework for relating covariates to event times and offer a useful alternative to proportional hazards models, allowing direct prediction of event timing under right censoring. However, existing AFT extensions for recurrent events, such as accelerated gap time (AGT) models, often fail to account for interventions between events and may not capture complex temporal patterns.

In this work, we first propose a class of semiparametric AGT models incorporating an …

Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton

Doctoral Dissertations

Clustering and supervised learning are often treated as distinct paradigms, yet both rely on structure in feature space. This dissertation investigates the relationship between cluster validity indices (CVIs) and supervised learning in real-time and lifelong learning settings where data arrive incrementally and cannot be revisited. Across four studies, it develops methods for online cluster validation, uses supervised learning to improve their interpretability, and applies these ideas to evaluating performance degradation in continual learning.

The first study extends incremental cluster validity indices (iCVIs), enabling widely used validation metrics to operate in streaming environments. Experiments on synthetic and real-world datasets show systematic …

Advancing Coal Rib Support Design Through The Integration Of Field Studies And Numerical Simulations, Alper Kirmaci

Doctoral Dissertations

Coal rib stability remains a major safety concern in U.S. underground coal mines, with rib failure-related injuries and fatalities still occurring. A key challenge is the lack of a standardized methodology for designing rib support systems that can address varying geological conditions. As a result, many mines rely on trial-and-error or traditional practices, leading to inconsistent designs. This research aims to develop a systematic methodology for rib support design to improve coal rib stability in U.S. mining operations.

The study consists of: i) field monitoring in active room-and-pillar coal mines, ii) in-situ pull-out tests on coal ribs, iii) numerical model …

Accelerating Circular Economy Transition For A Sustainable Built Environment: A Systems-Based Framework, Radwa Walid Yassin Eissa

Doctoral Dissertations

"The Circular Economy (CE) has gained momentum as a transformative framework for steering the construction value chain towards greater sustainability. However, this transition requires shifts in production and consumption patterns, adoption of circular business models, and the replacement of linear practices. Despite growing interest, CE adoption in construction faces persistent challenges, including sectoral fragmentation, lack of integrated governance frameworks, and limited coordination among stakeholders. This dissertation aims to accelerate the CE transition in the built environment through a multi-scale, interdisciplinary approach spanning five modules: (1) Module 1 develops a construction value chain-structured portfolio of CE strategies and assesses their implementation; …

Milankovitch Paleoclimatic Signals In Upper Permian–Lower Triassic Fluvial-Lacustrine Records, Bogda Mountains, Greater Turpan-Junggar Intracontinental Rift Basin, Nw China, Wentao Zhang

Doctoral Dissertations

"The objective of this study is to understand whether Milankovitch climatic and/or tectonic processes influenced the sedimentation of the upper Permian–Lower Triassic fluvial-lacustrine cyclic deposits in Bogda Mountains, greater Turpan-Junggar intracontinental rift basin, Xinjiang Uygur Autonomous Region, NW China. This study carried out gamma analysis, gamma and astronomical tuning, and spectral analysis on the Wutonggou, Jiucaiyuan, and Shaofanggou low-order cycles of the South and Central Taodonggou, South and North Tarlong, Dalongkou, and Zhaobishan sections. Stable and positive gamma values support the assumption of facies-dependent sedimentation rates for non-marine facies. The sedimentation rates range from 0.04 to 2.43 m/kyr, and 0.21 …

Analytical And Empirical Data-Driven Risk-Governance Design Across The Different Phases: Creating Informed Policy Adjustments For The Transportation Project Lifecycle, Mariam A. Elazhary

Doctoral Dissertations

"Transportation infrastructure is a critical foundation for economic productivity, yet agencies still face challenges in translating the expanding transportation datasets into defensible, phase-specific risk-governance tools. This dissertation addresses this gap by developing analytical and empirical, data-driven approaches to support risk governance across the transportation project lifecycle. Module 1 uses a panel model with bid-letting data to examine how out-of-state contractor participation affects pre-award competition and to derive entry-governance rules. Module 2 analyzes nonfatal injury data through iterative multiple linear regression and fatality data through association-rule change mining to identify multi-factor safety-risk configurations and develop adaptive safety-governance provisions. Module 3 develops …

Bond Graph And Extended Generalized Average Method With Applications In Cyber-Physical Systems And Power Electronics, Arnold Anthony Fernandes

Doctoral Dissertations

"This research examines two applications of control theory. The first application considers the bond graph (BG) modeling technique, which is used to develop the MATLAB structural analysis toolbox (MATSAT), an open-source toolbox for sensor placement and qualitative system analysis that considers the observability and fault-detection capabilities of multi-domain cyberphysical systems. The toolbox provides information on redundant sensors, guiding the system designer in cost and security trade-offs. The toolbox uses traditional BG causality assignment procedures. Additionally, MATSAT provides optimal causality assignment methods that perform significantly better at assigning causality to BGs with increased junctions, sources, and simple meshes, without encountering causality …

Quantifying, Forecasting, And Mitigating Construction Labor And Material Challenges In A Dynamic Global Economy Using Econometrics And Deep Learning, Ahmed Gamal Elsayed Mohamed Shiha

Doctoral Dissertations

"The construction industry contributes to the global economy, yet its cost management practices remain constrained by labor shortages and material price volatility. These challenges are intensified by economic disruptions, geopolitical tensions, and trade policy shifts. Despite a growing body of literature, five knowledge gaps remain unaddressed: (1) the absence of dynamic, and localized measures of construction labor shortages; (2) limited empirical investigation of macroeconomic leading indicators of labor shortages; (3) underutilization of deep learning (DL) algorithms in forecasting local construction labor earnings; (4) the limited treatment of structural breaks in existing construction material price forecasting models; and (5) the lack …

An Energy-Stable Mixed Cg-Dg Scheme For A Full Shliomis Phase Field Model Of Two-Phase Ferrofluid Flows, Mahdi Gharehbaygloo

Doctoral Dissertations

"Ferrofluids are magnetic nanoparticle suspensions whose motion couples surface tension, flow field, magnetostatics, and magnetization dynamics. This dissertation develops, analyzes, and validates an energy-stable finite element method for a two-phase ferrofluid model that couples the Cahn-Hilliard equations with the full Shliomis model of single-phase ferrofluids, retaining its damping torque term, magnetic torque term, and magnetic stress term.

The spatial discretization is a mixed continuous Galerkin (CG) and discontinuous Galerkin (DG) formulation. It uses continuous ��2 elements for the phase field, chemical potential, velocity, and magnetostatic potential, discontinuous ��2 elements for the magnetization, and discontinuous ��1 elements for the pressure. The …

Innovative Methods In Intact Rock Deformation Detection, Ali Abdullah M Alzahrani

Doctoral Dissertations

"An accurate assessment of intact rock deformation is imperative in engineering activities carried out either in or above rock masses. However, instruments used for post-peak deformation are easily debonded and cannot record the whole process of post-peak deformation required in the failure modeling of rocks. This dissertation focuses on the investigation of the performance of two non-contact measuring systems (Laser Displacement Sensor (LDS) and Inductive Proximity Sensor (IPS)) compared to the contact type instrument (conventional Strain Gauge System (SGS)) in monitoring intact rock deformations. Subsequently, an IPS was installed in a high-pressure triaxial testing system before investigating its performance in …

Harnessing Coherent-Wave Control For Sensing Applications In Scattering Media, Pablo Xavier Jara Palacios

Doctoral Dissertations

"Diffuse electromagnetic waves are widely used for non-invasive sensing and imaging in complex scattering media such as biological tissues. A fundamental limitation of such techniques is the scarcity of detected photons: as the source-detector separation increases to access deeper regions of the medium, the signal strength decays rapidly, leading to poor signal-to-noise ratio and limited sensitivity. This dissertation addresses this challenge through a combination of theory and computation.

We show that coherent control of the incident optical wavefront can compensate for the scarcity of detected photons that limits conventional diffuse optical imaging, typically performed in the near-infrared spectral region. By …

Relationship Between Working Memory And Reading Comprehension: A Secondary Meta-Analysis, Gennadi Mikhailik

Doctoral Dissertations

Although working memory (WM) capacity has been highlighted in many theories of first-language (L1) and second-language (L2) reading comprehension, some scholars argue that its importance may be overstated and that existing findings are still inconclusive. Even with extensive research since 1995, the literature has lacked a thorough quantitative review of these results. This study shows that WM capacity is positively related to reading comprehension. The current secondary meta-analysis examined the relationship between WM capacity and reading comprehension in both L1 and L2, using two authoritative meta-analytic datasets: Daneman and Merikle’s (1996) for L1 and Jeon and Yamashita’s (2022) for L2. …

The Effects Of Applying Self-Regulated Learning Prompts On Academic Achievement In A Public Middle-School Science Classroom, Andrew Barham

Doctoral Dissertations

Student success in science courses is a critical focus for K–12 educators, particularly during the transition period of middle-school, where students face increasing academic and social demands. Self-regulated learning (SRL) strategies have been shown to enhance academic outcomes by fostering independent learning and metacognitive awareness. However, research on the implementation and effectiveness of SRL interventions in middle school science classrooms, particularly within the constraints of public school settings, remains limited.

This study investigated the effects of an SRL intervention on the academic achievement of eighth-grade students during a six-week astronomy unit. Students from a public middle school in the San …

A Comprehensive Study Of Uncertainties In The Modeling Of Binary Neutron Star Outflows, Amelia Michele Henkel

Doctoral Dissertations

Binary neutron star (BNS) mergers have recently become a tool to study extreme gravity, nucleosynthesis, and the chemical composition of the Universe in a new way. In order to accurately identify electromagnetic signals of neutron star mergers, both in the future and retroactively, better constraints on their merger signatures are required. Specifically, BNS outflow properties (such as the mass and composition) are particularly insightful, as they provide a link between the intrinsic properties (such as the stellar masses and radii) and observables. In this thesis, I put forth multiple ways of classifying uncertainties associated with BNS mass outflow models. First, …

Efficient Algorithms For Mitigating Uncertainty And Risk In Reinforcement Learning, Xihong Su

Doctoral Dissertations

Reinforcement learning~(RL) studies the methodologies of improving the performance of sequential decision-making for autonomous agents and has achieved remarkable success in domains such as games, robotics, autonomous systems, finance, and healthcare. The Markov Decision Process~(MDP) is a mathematical framework for modeling agent-environment interactions in sequential decision-making problems. There are two primary sources of uncertainty in RL: epistemic uncertainty and aleatoric uncertainty. In RL, risk refers to the potential for an agent's policy to lead to undesirable outcomes, especially when the environment is uncertain. In many domains, researchers seek policies that maximize the objectives while mitigating the uncertainty and risk in …

Teachers' Evaluation And Reporting Orientations And Their Impact On Elementary Students' Motivation: A Secondary Analysis Of Ecls-K: 2011 Data, Melissa L. Lefebvre

Doctoral Dissertations

Few studies examine the specific component of teacher evaluation and reporting and its relationship with student motivation. Student motivation to learn and achieve is a fundamental element of academic success in school. Motivation has been linked to educational outcomes like curiosity, persistence, learning, conceptual understanding, and long-term achievement (Vallerand et al., 1992). Diminished motivation can lead to consequences such as higher dropout rates and increased anxiety. Research indicates that classroom climate and student-teacher relationships have the most significant impact on student motivation (Jansen et al., 2022). This dissertation explores the association of teachers’ evaluation and reporting practices with student motivation. …