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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 …

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 …

Analyzing Regions For The Study Of Localized Fluctuations In The Ground Magnetic Field For The Development Of A Global Risk-Assessment Forecast, Michael Kavanagh Coughlan

Doctoral Dissertations

The dynamic relationship between the solar wind and the Earth's magnetic field can produce rapid changes in the geomagnetic field measured on the ground ($dB_H/dt$). The fluctuations can be highly localized, with differences of up to 100s of nT/min in a small geographic area. The field of space weather is entering a more data-driven era, with enormous amounts of publicly available datasets from satellites and ground measurements. In this work modern machine learning techniques were employed to make forecasting risk-assessment predictions of large and localized $dB_H/dt$, and model explainability methods were employed to understand the non-linear connections being made. These …

Counting Kelp: Development And Assessment Of Modelling Approaches To Improve Understanding Of Kelp Bed Abundance And Resilience In The Gulf Of Maine, Constance N. Tyler

Doctoral Dissertations

Kelp habitats in the Gulf of Maine are threatened by rising ocean temperatures and marine invasions. The replacement of kelps with red turf macroalgae fundamentally alters these habitats and disrupts the ecosystem services they provide. Thorough assessment and monitoring of kelp habitats is needed for proper conservation of these habitats, but most long-term monitoring is performed using traditional survey methods that are restricted in the amount of space they can cover. Habitat modelling approaches are required to expand our knowledge of Gulf of Maine kelp habitats, and to better understand the interactions between kelp and red turf habitats across the …

Verifying Interchange Reconnection Models For Magnetic Switchbacks Using The Parker Solar Probe And Mms, Emily Owen Mcdougall

Doctoral Dissertations

Ever since their initial observation by the Ulysses probe, many models of magnetic switchbacks were put forth, but relatively little empirical evidence exists to verify these models, especially in terms of the ions that make up the accompanying plasma. I take energetic particle data from the Parker Solar Probe within switchbacks to provide experimental evidence to bolster the interchange reconnection driven models with particular interest in the interchange reconnection driven linear model. Statistical Analysis of switchbacks in the vicinity of CMEs, solar flares, and high-speed streams show properties consistent with the linear interchange reconnection model, and an analysis of switchbacks …

Bio-Acoustical Statistical Signal Processing For Detection, Classification, And Population Estimation In Wildlife Monitoring, Yue Liang

Doctoral Dissertations

Sound is a primary way for many animal species to communicate, forage, navigate, and assess their environment. As a result, passive acoustic monitoring (PAM), the recording and analysis of animal vocalizations, has become a valuable, non-invasive alternative to visual surveys. However, the massive volume of acoustic data generated annually, often reaching hundreds of terabytes, presents a significant challenge for efficient analysis. Since manual inspection of every frame in such data is infeasible, it is essential to develop automated detection and classification tools.

This thesis investigates and develops several statistical signal processing and machine learning techniques to address this challenge. The …

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; …

Essays On International Trade, Aochen Xiao

Doctoral Dissertations

This dissertation has two chapters.In Chapter 1, I develop a model of international trade with innovation and trade surplus to examine the effects of China’s large trade surplus on productivity. I abstract from future benefits from holding a present trade surplus and focus on the present gains in productivity. I find that the average productivity increase caused by trade surplus ranges from 1.2 percentage points to 5.46 percentage points when the innovation cost changes. These results explain China’s long-term export promotion policies and align with its new policy goal of developing “new productivity forces”. I also identify a negative effect …

Technologies To Support Remote Work For Collaborative Groups, Alberta Ansah

Doctoral Dissertations

The nature of work continues to evolve, particularly in the aftermath of the COVID-19 pandemic. While a substantial number of employees have returned to traditional, in-person work environments, many continue to engage in remote or hybrid work arrangements. Online meetings are a significant aspect of remote work, and while there has been a significant increase in this area, there are still aspects of these meetings that are not fully understood. Existing research in this area has primarily focused on the development of tools to facilitate meeting execution and content management. In contrast, relatively few studies have explored the social dynamics …

Eastern Oyster, Crassostrea Virginica, Genomics In A Well-Mixed Estuarine System: Examining Population Structure, Viability, And Response To Stressors, Alyssa Strickland

Doctoral Dissertations

Eastern oysters, Crassostrea virginica, are foundational estuarine species that contribute to a variety of ecosystem services including water filtration, nutrient cycling, habitat creation, and shoreline protection. However, populations have declined due to disease, overharvesting, habitat loss, and climate change, especially in northern systems such as New Hampshire’s Great Bay Estuary (GBE), located in the Gulf of Maine, one of the world’s fastest warming waters. This dissertation uses genomic and transcriptomic approaches to understand the drivers of population structure, decline, and resilience in GBE oyster populations, aiming to aid restoration and aquaculture. Chapter 1 used low-coverage whole-genome sequencing to understand population …

Addressing Economic Valuation Issues Of Outdoor Recreation: Case Studies Of Lake Michigan Invasive Carp And Plum Island Visits, Iris Tryfoni

Doctoral Dissertations

Environmental valuation is the process of assigning monetary value on environmental goods and services, which do not easily have market prices. It is, however, possible to over- or underestimate the economic valuation of outdoor recreation issues, specifically (1) recreational fishing and (2) beach recreation. Despite their different focuses, both case studies share a common objective of refining methodologies to better understand and address complex environmental issues from an economic perspective. Traditional recreation valuation techniques often lack explicit connection to ecology, which can be impacted by various factors. Addressing this gap, in the first part of my dissertation, I propose a …

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, …

Posture - A Framework With Measures And Mediating Effects In Support Of A Structural Model For Attitude In Identity Formation, Christopher Kyle Prather

Doctoral Dissertations

This dissertation develops a framework and new, valid, abbreviated instruments for researching engineering identity formation as an evolving relational and attitudinal development process rather than a fixed outcome. The framework centers on “posture”, a mediating effect analogous to physical posture in human factors engineering. The investigation was unique, and developed evidence for a structural model using an interdisciplinary, systems-oriented approach. Methodologically, a clinical measure of internal emotional states from the Marriage and Family Therapy literature was administered alongside existing scales for perseverance, perceived workload, and psychological ownership. This study used the broad coverage of the clinical instrument to search for …

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, …

Encryption With Synchronized Chaos Using Fabricated Cobalt Ferrite Memristors, Kiran Sai Seetala

Doctoral Dissertations

No abstract provided.

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 …

Robust Edge Machine-Learning For The Real-Time Processing And Prediction Of Geomagnetic Anomalies And Geomagnetically Induced Currents (Gics), Talha Siddique

Doctoral Dissertations

Geomagnetically Induced Currents (GICs) are currents induced in the Earth's surface conductors and are caused by geomagnetic disturbances or storms (GMDs). Such disturbances in the Earth's magnetic field are the result of interactions between the Earth's magnetosphere (the region of space dominated by the Earth's magnetic field) and the solar wind (a continuous stream of charged particles from the Sun) \cite{camporeale_machine_2018} \cite{geosciences12010027}. These induced currents considerably threaten vital technological systems, notably the electrical power grids. This research addresses the critical challenges of robust, real-time forecasting and monitoring of GICs using machine learning (ML). The project initiative responds to the inherent …

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 …

Personal Device Use In Mathematics: An Investigation Into Access, Utilization, And Outcomes, Catherine Dennis

Doctoral Dissertations

Personal devices, such as laptops, tablets, and smartphones, have become increasingly ubiquitous in undergraduate mathematics classrooms around the world. Moreover, the increased use of technology in educational contexts has provoked questions about equity in terms of student access, utilization, and the potential impact on outcomes (Hennessy & Dunham, 2008). This dissertation adds to the body of literature that addresses the overlap of personal device use and equity in undergraduate mathematics through three different methodological approaches: systematic review, quantitative inquiry, and qualitative exploration. The systematic review synthesizes 355 studies on personal device access, utilization, and outcomes in undergraduate mathematics. One key …