Digital Commons Network^™

Ammonium Perchlorate Manufacturing Effects On Propellant Burning Rate, Erin Faith Wallace

Theses

This thesis investigates the effect of ingredient variations on the burning rate of reduced smoke, low burning rate composite solid propellant. The effort focused on identical propellant formulations which presented significant burning rate differences correlated with the ammonium perchlorate (AP) source. A series of 1-gallon propellant mixes were prepared and tested utilizing both Manufacturer A and Manufacturer B ammonium perchlorate to investigate the propellant burning rate and pressure exponent shift anomaly and correlate those findings to the differing ingredient properties between the two AP lots. Each propellant mix was evaluated for burning rate utilizing subscale test motors and a scanning …

Near-Field Analysis Of Horn Antennas For Electromagnetic Compatibility Testing, Landon Riley Carroll

Theses

Standard gain horn antennas are widely used in electromagnetic compatibility (EMC) testing and antenna measurements. In EMC testing, it is often required to generate high electric field intensities across a wide frequency range within the near-field region. However, the focusing properties of antennas are deteriorated in the radiating near-field region. In order to increase engineering confidence in EMC testing, it is desirable to understand the root causes of the aforementioned radiation degradation. In this thesis, the near-field characteristics of three different pyramidal standard gain horns are investigated using full-wave analysis, analytical methods, and measurement. The causes of near-field gain reduction …

Factors Affecting Freshwater Fish Communities In Two North Alabama Counties, Joshua Fitts

Theses

This study examined how physical habitat characteristics influence freshwater fish diversity in streams of Madison and Limestone Counties, Alabama. Ten 150-meter stream reaches were sampled using backpack electrofishing and seining, with habitat variables measured at fixed transects. Principal component analysis identified four main habitat gradients representing flow and substrate, channel size, gravel dominance, and canopy–bedrock conditions. Although overall species richness and Shannon diversity were not significantly related to these gradients, species-specific correlations revealed clear ecological preferences. Regression models showed that root wads, herbaceous vegetation, and riprap modestly increased richness, emphasizing the role of structural diversity. These findings highlight the importance …

Active Learning Methodologies And Applications, Pradeep Bajracharya

Theses

Active learning (AL) is a Machine Learning (ML) strategy that offers a promising solution to challenges posed by the data-intensive tasks by selectively querying the most informative data, reducing the need for extensive labeled datasets. This approach is particularly valuable for fields like cardiac research and scientific simulations, where data labeling becomes expensive and often impractical. Deep Active Learning (DAL) extends this concept to deep learning models, which are typically data hungry, where the focus is more to optimize data selection in discrete search spaces. Conversely, Explorative Active Learning (EAL), is tailored for exploration of continuous search spaces, employing machine …

Gai Research - A Case Study On The Implications Of Generative Artificial Intelligence (Gai) On Teaching Within An Irish Technological University., Moya Cronin

Theses

The rapid emergence of Generative Artificial Intelligence (GAI) has introduced a transformative age of technology, gaining prominent attention in higher education. This mixed-methods case study examined how GAI was understood, applied, and managed within an Irish Technological University at a time of turbulence when no official GAI policies were available as a point of reference. Lecturing and research staff were invited to participate in an online survey (𝑛 = 145) and semi-structured interviews (𝑛 = 8) to share their experiences with GAI technology within the case study university. Lack of guidance was seen to affect staff’s confidence and adoption, but …

Upper And Lower Body Volume-Equated Resistance Exercise Increases Post-Exercise Lipid Oxidation In Trained Eumenorrheic Females., Alyssa L. Parten, Abbie E. Smith-Ryan, Eric K. O'Neal, T Scott Lyons, Hunter S. Waldman

Theses

Exercise strategies targeted to increase lipid oxidation (LOx) in the resting state present an opportunity to optimize long-term metabolic health. However, research examining the effects of resistance training (RT) on LOx in females remains scarce, particularly with no studies yet examining whether differences exist in LOx between upper and lower body RT. This study examined LOx changes following volume-load equated upper and lower body RT in well-trained, eumenorrheic females. Twenty-two (age: 25.4 ± 5.6 years, BMI: 24.6 ± 2.7) females completed a 3-repetition-maximum (RM) and 1RM test for the barbell back squat (BS) and bench press (BP), respectively. From these …

Jamaica: The Stories We Never Told, Vinnette Gibson

Theses

Jamaica: The Stories We Never Told is a memoir project that describes the realities of Jamaican life through personal narratives that detail the cultural and social nuances of Jamaican experiences. Its purpose is to broaden the global perception of Jamaican culture beyond tourism, beaches, music, and sports by representing everyday realities of Jamaican life, often overlooked by the global community. It details multifaceted experiences, including challenges and positive encounters, the transition from youth to adulthood, and complex emotions throughout. This project documents the author’s lived experiences and reveals cultural nuances, including friendships, family dynamics, and the use of Patois to …

Digital Threads: Fashion Design With Clo3d, Maya Herring

Theses

CLO3D (CLO) has emerged as a prominent software service within the fashion industry, molding the conceptualization and development of 3D fashion designs. By eliminating the constraints of customary manufacturing processes and real-life production costs, CLO equips designers with tools to bring their fashion garments and designs to life. This study aims to explore the capabilities of CLO software by developing five digital bridal dresses while also examining the learning curve, challenges, and benefits associated with its usage. The objective is to identify how CLO can provide aspiring fashion designers with the tools to produce high-quality designs without traditional training.

By …

Estimating Surface Sulfur Dioxide Concentrations Over Eastern China Using Omi Satellite Data, Zachary Watson

Theses

Sulfur dioxide (SO2) is a key air pollutant as it contributes to negative health effects, acid rain, and aerosol formation. Using satellite data to monitor surface SO2 concentrations can fill in the gaps of ground-based air quality networks in less populated areas. In this study, SO2 retrievals from the Ozone Monitoring Instrument (OMI) were employed to estimate annual and seasonal average surface SO2 concentrations over eastern China, a major anthropogenic source region, from 2015 to 2018. The OMI-derived surface SO2 concentrations had a similar spatial distribution and temporal trends as ground-based measurements from an air quality monitoring network, but they …

Concentrated Benefits And Dispersed Costs: The Contributions Of Pareto, Olson, And Ostrom, Nathan John Cuthbertson

Theses

Concentrated benefits and dispersed costs (CBDC) is a central concept in the field of public choice as well as economics more broadly. The phrase concentrated benefits and dispersed costs refers to a situation in which economic benefits are concentrated and the associated costs are borne by a larger group. This thesis argues that the elements of CBDC are common in the literature without the term being used directly. This study is an exercise in the history of economic thought. The study is structured into three case studies, with each dedicated to the work of an influential economist: Vilfredo Pareto (1848-1923); …

Negotiating With-Ness: Midwives' Lived Experiences Of Gender, Inclusive Language, And Professional Identity., Kimberley-Ann De Wet

Theses

This research investigated midwives lived experiences of using gender-inclusive language in public maternity care, examining how linguistic practices intersect with professional identity, ethical commitment, and institutional constraint. Informed by feminist theory and guided by descriptive phenomenology with a constructivist paradigm, the study explored how midwives navigate the profession’s foundational ethos of being ‘with woman’ while responding to the ethical imperative to provide inclusive care in an increasingly diverse society. Semi-structured interviews were conducted with eight practising midwives in Western Australia, generating rich descriptions of how inclusive language is enacted, negotiated, and constrained in practice. Reflexive thematic analysis produced three overarching …

Sigrid Undset: Nordic Catholic Apologist, Brendan Edward Arthur

Theses

This thesis explores the depth and breadth of Sigrid Undset’s non-fiction Catholic writing, a substantial body of work that has largely remained inaccessible to all but readers of Norwegian. Through original translations and analysis, it synthesises these texts into broad themes while situating them within their historical contexts of the intellectual and cultural debates in early twentieth-century Norway. The study addresses three research questions: (1) the general themes in Undset’s Catholic non-fiction; (2) the contemporary relevance of these writings; and (3) whether Undset merits the designation “Catholic apologist.” In its method, the thesis employs textual analysis of Undset’s essays, articles …

Leadership In The Digital Economy: An Investigation Into How Digitalisation Is Changing The Role And Practice Of Leadership In The Australian Defence Industry, Rhogan Aitken

Theses

Digitalisation is a phenomenon that is transforming society and is the process that moves an organisation to become digital. Research was conducted on senior leaders in the Australian defence industry with the purpose of investigating how the role and practice of leadership was changing because of digitalisation. A two-phased qualitative methodology was employed. An initial Delphi study on 13 experts in digital transformation was adopted to gain consensus on key issues, with the results informing a second stage of semi-structured interviews with 32 senior leaders in the Australian defence industry. The results identified factors that were influencing leadership, including increased …

Defining Barriers In Pulmonary Hypertension: Pulmonary Hypertension In Remote And Rural Settings In Australia: An Epidemiologic Study Aided By Echocardiography, Pyi Naing

Theses

Pulmonary hypertension (PH) is a common, complex, and potentially lethal haemodynamic condition with many underlying aetiologies. It is poorly understood, and diagnosis is usually made late in the disease process resulting in poor outcomes even in the developed world. An innovative universal framework is required to achieve early and accurate diagnosis for improved outcomes, especially in remote and rural areas. The thesis documents my substantial body of work that unlocks a collective framework to assist patients with PH, particularly in areas not classically serviced by tertiary level PH care.

The first chapter of my thesis outlines the history, important milestones …

Uncertainty-Aware Meta-Learning For Learning From Limited Data, Deep Shankar Pandey

Theses

Deep Learning (DL) models have achieved great success in large data fields ranging from computer vision and natural language processing to digital arts and robotics. However, the effectiveness of the DL models is challenged by many real-world limited data problems (e.g., medicine, healthcare, and security intelligence) where data for model training is scarce. Unlike DL models, humans can use the prior knowledge stored in their brains to quickly learn new tasks with limited data. Inspired by such human learning, various meta-learning models have been developed that aim to address the challenge of learning from limited data. However, existing models are …

Fake News Detection In Arabic Media Using Machine Learning And The Afnd Dataset, Hussain Ali Bahri

Theses

The proliferation of fake news in digital media poses a significant challenge to information credibility, particularly in linguistically diverse regions such as the Arab world. This study addresses the critical problem of detecting fake news in Arabic media by leveraging advanced natural language processing (NLP) techniques and the AFND dataset, which contains over 600,000 news articles categorized into "credible," "not credible," and "undecided" classes. The research focuses on developing a robust system using AraBERT, a transformer-based model specifically pre-trained for Arabic text. Key contributions of this work include a comprehensive preprocessing pipeline tailored to Arabic linguistic complexities, incorporating stopword removal, …

Exploring The Perceived Impact Of Hearing Impairment On The Mental Health And Well-Being Of Adults, Jacinta Ruth Marks

Theses

This thesis explores the perceived impact of hearing impairment on the mental health and well-being of Australian adults, responding to a growing need to understand how hearing challenges affect people beyond clinical or audiological measures. While hearing impairment is commonly framed through medical or functional models, its psychosocial effects remain underexplored, particularly in relation to stigma, identity, and mental well-being. This study addresses that gap by centring lived experience and examining how adults with hearing impairment navigate everyday life, social expectations, and systemic barriers. Grounded in a constructivist-interpretivist paradigm and informed by a disability studies lens, the research investigates the …

Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz

Theses

This thesis addresses a operational challenge in modern industrial operations: the increasing complexity of systems and the consequent cognitive burden on operators. As industrial technologies advance, the human-computer interface has become the primary conduit for information flow, playing a pivotal role in operational decision-making. However, the proliferation of data often leads to information overload, potentially compromising rather than enhancing operator performance. This research explores an approach to this pressing issue through the application of Bayesian networks as decision support systems in safety- critical scenarios. Our study employs a multi-faceted approach, combining theoretical modeling with empirical testing. Through collaboration with industry …

Dual-Mode Linear Phased Array Antennas For Monopulse Radars, Jonathan Waters

Theses

Phased array antennas are widely used around the world. Much research is focused on extending capabilities of modern wireless systems and radars. Dual-mode elements are researched for use in beamforming, monopulse radar and multi-frequency applications. Beamforming in itself is an extensively researched topic, aimed at canceling interference and/or finding signal angle-of-arrivals. The goals of this thesis are two-fold. Firstly, to take the monopulse capabilities of a dual-mode antenna element to allow for a linear phased array antenna to generate the sum, delta-azimuth, and delta-elevation channels whereas normal linear phased array antennas can only generate a single difference channel. Secondly, to …

Heat Transfer Of Additively Manufactured Turbine Alloy Blade Tips With Different Surface Enhancement Post-Processing Methods, Morgan Tatge

Theses

The investigation results presented here consider the heat transfer characteristics of seven different turbine blade tips. Six of the blades are additive manufactured with GRX-810, followed by different surface enhancement post processing techniques. Those techniques include as built, abrasive flow machining, chemical polishing with chemical mechanical polishing, micromachining, chemical polishing, and electropolishing. The seventh blade is machined with 1016 steel. These procedures give a different surface texture roughness for each blade. A transonic linear cascade within a transonic/supersonic wind tunnel is utilized. The impulse response method is employed to determine heat transfer coefficient distributions for the blades. The Tad/T0i temperature …

Design, Development, And Analysis Of A Pulsed Power System Using A Thyristor To Fire A Coaxial Plasma Gun, Neil P. Laya

Theses

A first of a kind fiber-optically controlled and thyristor switched coaxial plasma gun pulsed power system has been designed, built, and fired at up to 2 kV and 6.4 kA, with a 6.65 MW momentary peak power output from the capacitor. Total system firing jitter from initial digital signal to 90% peak current rise has been measured at 78.15 ns, representing 0.18% of the total pulse time of 44.10 µs. This includes both thyristor turn-on and coaxial plasma gun breakdown. Standard deviation of peak current over repeated firings has been measured to be 21.09 A (0.33%). The system has experienced …

Augmenting Attention : An Ooda-Centric Framework For Explainable Ai In Ar Human-Ai Teaming Applications, Dylan Wright

Theses

Artificial Intelligence (AI) is increasingly deployed in high-stakes environments where success depends on more than computational accuracy; it also requires alignment with human perception and attention. Traditional explainable AI (XAI) methods provide static, post-hoc justifications that are poorly suited to time-critical decision cycles. This thesis investigates whether perceptually aligned, real-time explanations in Augmented Reality (AR) can enhance performance, workload balance, and trust within the Observe–Orient–Decide–Act (OODA) loop. A custom AR search-and-rescue simulation tested three conditions: no assistance, static overlays, and perceptually aligned explanations using adaptive cues such as occlusion-aware tethers and urgency-based visuals. The results show that any explanation improved …

Multi-Factor Mathematical Optimization For Healthcare Referral And Facility Placement, Mitchell Moody

Theses

This thesis addresses the challenge of optimizing patient referrals in healthcare systems by integrating clinical needs, geographic proximity, and dynamic infection risk. Healthcare referral networks (HRNs), which capture patient transfers between hospitals, serve as the foundation of the study. First, a recommendation algorithm is developed to assign patients by jointly considering clinical compatibility and logistical considerations like travel distance, striking a balance between quality and accessibility. Building on this, a reinforcement learning framework is proposed to dynamically adjust referral strategies for vulnerable patients by incorporating the evolving risk of hospital-acquired infections. Finally, long-term planning is explored through methods that recommend …

Utilizing Ground-Based Radar Analyses To Investigate Ocean-To-Land Differences In The Tropical Cyclone Wind Profile And Their Impacts On Tornadogenesis, Elizabeth M. Seiler

Theses

On 20 August 2008, the MAX radar was deployed southeast of the Jacksonville, FL WSR-88D radar to monitor the boundary layer before, during, and after the landfall of TS Fay. During the 57-hour deployment, MAX sampled around a tornadic rainband that produced at least one confirmed tornado. To illustrate TCBL changes across a coastal zone, VAD profiles from MAX and KJAX are compared, and a dual- Doppler analysis is performed. One key finding from the DDA was the consistent presence of southeasterly background flow, vertical vorticity, enhanced cyclonic shear zones, and minisupercells throughout the 1650-1725 UTC analysis period. The primary …

Generation Of True Random Numbers With Actively Stabilized, Low Dimensional Chaos, Aidan Barton

Theses

True Random Number Generators (TRNGs) are heavily used and their design often relies on empirical validation from statistical test suites. Reliance solely on empirical observations to estimate entropy rates for cryptographic applications introduces risk, as accurately inferring long-term correlations demands prohibitively large datasets. Empirical validation of TRNGs must be supplemented by strong theoretical backing to justify estimated information theoretic quantities. We present an electronic, hardware TRNG scheme that produces a maximally random output guaranteed from first principles. This TRNG uses a pulse-width based hardware realization of an iterated map that produces physical entropy via low-dimensional chaotic dynamics. The simple dynamics …

A Comprehensive Study On Explainable Artificial Intelligence : A User-Centric, Cognitive Workload, And Feasibility-Driven Analysis, Josiah Taylor

Theses

Explainable Artificial Intelligence aims to open up the “black box” of artificial intelligence, thereby improving user trust, decreasing cognitive load, and improving task performance. As the number of machine learning models has grown, so has the number of explanation methods, making it necessary to select the most suitable explanation method for a given context. However, current selection methods often fail to account for all the factors that contribute significantly to an explanation method’s suitability. This thesis proposes a novel methodology for selecting and evaluating explanation methods. Subjective workload, objective performance, and feasibility are considered. This three-pronged “pitchfork” methodology is put …

Development Of A Constitutive Model Free Method To Determine Full-Field Stresses Based Upon Fundamental Physics Principles, Joel David Barnes

Theses

Advances in imaging techniques allow for the determination of full-field displacements and strains during materials testing. However, most analysis techniques rely on strain gages and virtual extensometers instead of utilizing all available full-field data. Those methods that do utilize the full-field strain and displacement measurements, such as Finite Element Model Updating and the Virtual Fields Method, must also rely on a user-defined constitutive material models to relate the stresses and strains. While these methods can provide accurate full-field stresses and insights into complex material behavior in some cases, they are constrained by the fact that they require a pre-selected constitutive …

Leveraging Future Foresight And Planning In Human Resource Management: Preparing Organizations For The Workforce Of Tomorrow, Naser Althehli

Theses

As organizations face unprecedented uncertainty as they navigate a complicated and fast-changing world, the ability to anticipate and adapt to workforce shifts has become more crucial than ever. This thesis examines how future foresight and strategic planning in human resource management (HRM) can reinforce organizational adaptability and maintain a competitive edge. By analyzing key drivers of change—including technological advancements, demographic shifts, political dynamics, and socio-economic trends—the study identifies innovative HRM strategies that enable organizations to address emerging workforce challenges and opportunities proactively. Through a structured evaluation of foresight techniques, this research highlights best practices for cultivating a resilient and future-ready …

Internet Of Things (Iot) In Developing Smart City Traffic Management Systems In Dubai, Ayesha Ahmed Alnuaimi

Theses

Traffic congestion is an ever-present problem affecting most cities, negatively affecting the economy, the environment, and people’s quality of life. Dubai is one of the rapidly growing cities in terms of urbanization and the usage of technologies, and it is aware of the ability of IoT to design intelligent city traffic control systems to resolve this problem. Consequently, this study sought to assess the implication of IoT in improving traffic management systems within the Emirate of Dubai, gleaning data concerning the factors that have a direct impact on the implementation of the IoT, the challenges, and barriers met during the …

Automated Prioritization And Routing Of It Support Tickets Using Machine Learning, Mohamed Almarzooqi

Theses

The increasing complexity of IT service management underscores the need for efficient and scalable solutions to manage IT tickets. This thesis explores the application of machine learning techniques for automated prioritization & routing of IT tickets. So by leveraging publicly available dataset from Kaggle containing IT ticket the study aims to reduce manual intervention, improve resolution times, & optimize resource allocation within IT environments. The study will evaluate various machine learning algorithms, including SVM, Random Forest, & ensemble models, for their ability to classify and prioritize tickets accurately. to accurately classify and prioritize tickets. Advanced data preprocessing techniques like TF-IDF …