The Best Practices For Prefabrication Of Industrial Buildings, Derek Gines

Theses

Prefabrication has demonstrated measurable and repeatable advantages in productivity, cost certainty, and environmental performance, yet its adoption within industrial building typologies remains largely inconsistent. Existing research largely evaluates prefabrication through downstream performance outcomes, while offering limited insight into the upstream design and organizational decisions that enable or undermine its reliability. This thesis reframes prefabrication as a design‑led methodology rather than a construction optimization, arguing that successful hybrid prefabrication is determined primarily by early decision timing, governance structures, and the control of spatial and logistical interfaces. This study adopts a qualitative design‑research approach that combines comparative case study analysis with expert …

Toward A Unified Framework For Open World Visual Learning, Yuansheng Zhu

Theses

Artificial intelligence systems have achieved remarkable performance across a wide range of visual tasks. However, most existing models operate under the unrealistic closed-world assumption, where training and test data are drawn from the same distribution. In real-world applications such as anomaly detection, autonomous driving, and medical diagnosis, learning systems frequently encounter novel or out-of-distribution scenarios. These settings require models that can recognize unknown inputs, adapt to new information over time, and maintain reliable performance under evolving conditions. This dissertation studies the problem of Open World Visual Learning, a paradigm that enables visual learning systems to operate robustly in dynamic and …

Using Deep Learning To Increase Eye-Tracking Robustness, Accuracy, And Precision In Virtual Reality, Kevin Barkevich

Theses

Algorithms for the estimation of gaze direction from mobile and videobased eye trackers typically involve tracking a feature of the eye that moves through the eye camera image in a way that covaries with the shifting gaze direction, such as the center or boundaries of the pupil. Tracking these features using traditional computer vision techniques can be difficult due to partial occlusion and environmental reflections. Although recent efforts to use machine learning (ML) for pupil tracking have demonstrated superior results when evaluated using standard measures of segmentation performance, little is known of how these networks may affect the quality of …

Medical Detection Dogs: A Visual Exploration Of Canine Olfactory Anatomy & Volatile Organic Compounds As Applied To Non-Invasive Biomedical Detection, Kirsten Santiago

Theses

Medical detection dogs provide a non-invasive early method of disease and medical alert detection that is underrepresented in the medical visualization sector. The domesticated dog, or Canis familiaris, is known for its loving nature and has become an important member of many households, but they are also incredibly intelligent with a capacity for specialized training. Dogs have a specialized olfactory system, allowing them to detect scents with high acuity (Guest & Otto, 20). Volatile organic compounds or VOCs are molecular substances associated with metabolic processes that are often a result or byproduct of certain diseases and can be influenced by …

Horizontal Gene Transfer In Neisseria, Wen Ting Dong

Theses

Antibiotics are a special category of drugs that help treat bacterial infections by killing bacteria or hindering their growth and replication. Antibiotics are greatly significant in modern medical practices, providing an effective treatment for bacterial infections as well as enabling organ transplants, open surgeries, and chemotherapy to be possible. Unfortunately, cases of antibiotic resistance were observed shortly after the introduction of antibiotics. The appearance and spread of these resistant strains poses a significant threat to public health safety. The Centers for Disease Control (CDC) estimates there are 2,868,700 antibiotic-resistant bacterial and fungal infection cases per year in the United States, …

Software Engineering In The Age Of Coding Agents: Failure Modes And Rejection Patterns, Mahd Mohd Hindi

Theses

This thesis investigates the real-world behavior of LLM-driven coding agents that generate code changes and submit pull requests (PRs) to public software repositories. As these tools evolve from autocomplete-style assistants into more autonomous agents, their contributions increasingly interact with socio-technical review processes (human reviewers, bots, CI/CD gates, and project norms). The thesis focuses on understanding why agent-generated PRs are accepted or rejected and what these outcomes reveal about current agent limitations in practical development workflows.

The main objective of this thesis is to systematically characterize rejection patterns and failure modes of agent-generated pull requests in real repositories. Specifically, the thesis …

Ultrarenderer: Real-Time Heterogeneous Cpu-Gpu Memory Management And Adaptive View-Dependent Rendering For Massive 3d Environments, Huadong Zhang

Theses

Rendering large-scale 3D datasets in real-time presents significant challenges due to the widening gap between the ever-growing scale of dataset complexity and the limited memory capacity of modern GPUs. As datasets increasingly exceed available GPU memory, traditional methods encounter severe bottlenecks, such as restricted CPU-GPU bandwidth and inefficient memory usage, which significantly hinder rendering performance. This is especially problematic in interactive applications where high frame rates and low latency are critical. To address these limitations, this dissertation presents UltraRenderer, a novel out-of-core rendering method designed to maximize visual fidelity under strict memory and bandwidth constraints. The core of our approach …

Engineering Human Microphysiological Models To Investigate Bacterial Extracellular Vesicle–Driven Endothelial And Blood–Brain Barrier Dysfunction, Louis P. Widom

Theses

Pathogenic bacterial extracellular vesicles (BEVs) are nanoscale particles derived from bacteria that contain pro-inflammatory cargo. During bacterial infections, BEVs provoke the host inflammatory response and may cause widespread damage. Furthermore, antibiotic treatment can boost BEV production and thereby increase the number of toxic signals traveling through the circulatory system. This is especially dangerous in brain blood vessels since evidence suggests that BEVs may destabilize the protective blood–brain barrier (BBB), resulting in neuroinflammation associated with cognitive decline and development of neurological disorders. Our understanding of BEV interactions with the host remains limited, necessitating the development of in vitro models to better …

Security Evaluation Of Post-Quantum Ml-Dsa Implementations Against Software-Induced Fault Attacks, Alexis Korensky

Theses

Quantum computing is a form of computation that uses the principles of quantum mechanics to perform mathematical computations at a faster rate than classical computers. Although quantum computing is currently still in its early stages, if a general-purpose, large-scale, and fault-tolerant quantum computer were to be built, it would jeopardize the security of modern public-key cryptosystems. If these cryptosystems were broken, secure connections could not be authenticated, enabling Man-in-the-Middle (MitM) attacks, and digital messages could not be signed. All data sent over secured HTTPS and/or TLS connections would be vulnerable and potentially malicious since its origin and integrity could not …

The Usability And Influence Of Comprehensive Sports Nutrition Handouts For Adolescent-Aged Female Athletes, Chloe Brassie

Theses

Objective: This study aimed to examine the usability and influence of comprehensive sports nutrition handouts for adolescent-aged female athletes. Design: Cross-sectional online survey incorporating post retrospective-pre self-assessment Participants: Adolescent female athletes between 13 and 17 years of age Methods: Participants received a series of digital nutrition handouts every day for seven days and completed an online survey. Variables: Age, sport, engagement, knowledge, behavior, features of interest, and experience with nutrition education. Analysis: Quantitative data were analyzed with descriptive statistics and qualitative data were examined using thematic analysis. A Wilcoxon signed-rank test assessed the change in responses for both knowledge and …

Prediction Of Methane Gas By Using Hyperspectral Imageries And Remote Sensing Techniques, Aysha Ali Alhajeri

Theses

Greenhouse gases is important for sustaining life on earth as well as in mitigating climate change. Methane (CH4) is considered as one of the most important critical gases for the global climate change and have significant influences on our life. Accordingly, the prediction of this greenhouse gas emissions is very important for avoiding the climate change effects and to maintain environmental sustainability. The objective of this study is to explore the potential applications for remote sensing to predict methane levels in the Earth’s atmosphere with a combination of local ground data and data from hyperspectral satellite imagery. By using hyperspectral …

Spike-Based Architectures For Energy-Efficient Audio Enhancement, Kedar Sandip Fitwe

Theses

Deep Neural Networks (DNNs) have shown remarkable success in speech denoising; however, their high computational and energy requirements make realtime deployment on edge devices challenging. In contrast, Spiking Neural Networks (SNNs) operate using sparse, event-driven spikes—offering a biologically inspired and energy-efficient alternative. In this study, we delve into a Spiking Neural Network (SNN) model that leverages the temporal dynamics of spiking neurons to capture long-range dependencies in the audio signal. By encoding the input audio into sparse and event-driven computations, the SNN can efficiently process the temporal information while requiring significantly fewer computations compared to DNNs. We present a real-time …

Investigating The Knowledge, Attitudes And Practices Towards Type 2 Diabetes Mellitus In A Student Population In The United Kingdom: A Quantitative Study, Philip Boadu Anim

Theses

Aim: To explore the knowledge on the risk factors, signs and symptoms, management, and complications of Diabetes, attitudes, and practices towards prevention of Diabetes Mellitus among university students in the United Kingdom.

Methods: The researcher utilised a quantitative study design in carrying out the study. The study was conducted at Cardiff Metropolitan University with Cardiff Met students being the target population. Thirty (30) participants were recruited through convenient sampling. Data was collected through questionnaires using closed ended questions. The Statistical Package for Social Science (SPSS) version 27 as used to analyse the data collected. Statics were performed to form a …

Inflex : A Scalable Framework For Malware Analysis, Correlation, And Steganography Detection, Luke Bower

Theses

Modern malware campaigns operate in stages across diverse formats, including PE, ELF, shellcode, and malicious documents, some leveraging steganography to deliver payloads such as Quasar RAT and Lokibot. Because analysis tooling remains siloed by artifact type, analysts struggle to identify shared code reuse, behavioral overlap, and campaign relationships when adversaries avoid traditional indicators. This thesis presents INFLEX, a framework that normalizes diverse artifacts through a unified pipeline combining static analysis, emulated behavioral extraction, sandbox execution, and threat intelligence enrichment. Its correlation layer introduces Variant Resilient Function Hashing (VRFH), validated against fuzzy hashing baselines on targeted samples, and Weighted Artifact Fusion …

Modeling And Identification Of Thermal Interactions In Lithium-Ion Battery Modules, Saima Alam

Theses

The recent development of lithium-ion battery technology has fueled its adoption in electric vehicles (EVs) as the primary power source due to its high energy and power density. However, the high energy density comes at the cost of higher safety requirements. To ensure the lithium-ion battery pack's operational safety, performance optimization, and longevity, a Battery Management System (BMS), an electronic controller, is employed. Recent reports of battery pack overheating, fire, and explosion in EVs expose the limitations of the BMS in detecting the abnormalities and preventing them from propagating to other cells. To address these limitations, in the first part …

Discovering The Genes And Molecular Mechanisms Involved In Increasing The Expression Of The Gad Regulon In Escherichia Coli Resistant To Macrolide Antibiotics, Lea V. Freeman

Theses

Various genes have been proposed to play a role in the action of indole, a bacterial hormone involved in biofilm and quorum sensing. Previous work found that E. coli strains carrying a macrolide-resistant mutation in the uL22 ribosomal protein reduce tna operon mRNA levels and, consequently, decrease indole production. This ribosomal mutation also increases expression of the gad regulon, a genetic unit involved in acid resistance at pH below 2. The gad regulon is involved in bacterial survival under environmental challenges, primarily regulating intracellular acid resistance, and its expression appears to depend on indole production. In this work, we work …

Performance Comparison Of A 25 Mm Rotating Detonation Rocket Engine Using Multi-Ring Injection, Nathan C. Mead

Theses

Rotating detonation rocket engines (RDREs) use one or more detonation waves traveling circumferentially around an annular (center body, CB) or cylindrical (center bodiless, CBL) combustion chamber, offering theoretical advantages over conventional deflagration-based combustors. A new geometry, the center fill (CF), further enhances the CBL geometry by adding a fuel-oxidizer injector ring near the center of the combustion chamber, increasing energy density and thus propulsion performance. To evaluate CF operability and performance, a 25 mm CF RDRE running gaseous methane and oxygen is tested across varying equivalence ratios at 0.076 kg/s total mass flow rate, and across varying mass flow rates …

Deep Joint Source-Channel Coding For Semantic-Aware Adaptive Wireless Image Transmission, Sudipto Das Suvro

Theses

The growing use of AI-enabled applications has increased the demand for adaptive, efficient, and low-latency image transmission of large data volumes. This has created challenges for conventional separate source-channel coding that focuses on reliable bit sequence transmission without considering the contents or communication objectives. Deep joint source-channel coding (DeepJSCC) potentially solves this by combining source compression and error correction into a unified process. This thesis focuses on developing adaptive and computationally lightweight DeepJSCC-based transceivers for image transmission across heterogeneous channels. The framework further investigates DeepJSCC’s performance in OFDM with robust channel estimation and importance-based subcarrier allocation strategies. Comprehensive evaluation using …

Optimizing Marketing Campaigns To Maximize The Response Rate For A Supermarket Using Machine Learning Techniques, Alia Almansoori

Theses

Supermarkets must improve their marketing tactics at a time of changing consumer behavior and increasing competition in the retail industry. Engaging the wide and sophisticated consumer base of today's supermarkets is difficult using traditional methods. This proposal presents a data-driven approach using cutting-edge machine learning methods to enhance supermarket marketing strategies. The main goal is to increase the response rate of marketing initiatives, which will improve consumer engagement and ultimately increase revenue. Additional primary objectives are customer segmentation and targeting, predictive modeling, personalization, ongoing performance monitoring, and ROI evaluation. The current problem centers around personalization and accuracy. Due to the …

Evaluating The Effectiveness Of Scenario-Based Virtual Escape Rooms To Improve Student Confidence In Dosage Calculations, Jennifer A. Cuevas

Theses

Abstract

Background: Accurate dosage calculations (DCs) are critical for patient safety, as medication errors contribute to approximately 7,000-9,000 preventable deaths annually. Nearly 30% of nursing students exhibit weakness in foundational mathematical skills, and a significant confidence gap exists: 70% feel confident in mathematical abilities, yet only 45% feel confident in clinical application, necessitating innovative educational interventions.

Purpose: The purpose of this project was to implement and evaluate a scenario-based virtual escape room intervention to enhance undergraduate nursing students' confidence in DCs.

Methods: Grounded in Kolb’s experiential learning theory, this online asynchronous intervention engaged students through concrete experience, reflective observation, abstract …

Increasing Confidence Of Respiratory Therapy Students In Cardiopulmonary Resuscitation Using Rapid Cycle Deliberate Practice, Heather Ashley

Theses

Background: Rapid Cycle Deliberate Practice (RCDP) simulation has emerged as an innovative approach to strengthening confidence among healthcare learners and professionals. Grounded in Kolb’s Experiential Learning Theory, RCDP emphasizes structured repetition, immediate feedback, and skill refinement through cycles of performance, reflection, and reapplication.

Methods: Senior-level respiratory therapy students participated in either a traditional cardiopulmonary resuscitation (CPR) simulation or an RCDP CPR simulation as part of their scheduled coursework. After completing the simulation, students participated in a post‑simulation survey, and scores were compared between the two groups.

Results: Confidence was evident across both simulation methods, and students indicated increased self‑confidence following …

The Impacts Of Land Use Land Cover Change And Urbanization On Precipitation In The Kentucky–Ohio River Valley, Madison Wallner

Theses

This thesis evaluates how urban growth modifies warm-season rainfall and convection near Louisville, Cincinnati, and Evansville. From 1987–2024, rainfall increased at most stations, but MERRA-2 and statistical modeling show that regional ascent and moisture were the primary controls on seasonal precipitation. Radar analysis identified storm initiation as the dominant event type, especially near Louisville’s urban–river boundary and northeastern downwind corridor. Louisville’s developed land increased from 53.5% to 66.3%, while MODIS showed significant nighttime warming but little daytime warming. GOES cloud-frequency patterns were also locally enhanced near river, urban-edge, southeastern vegetated, and downwind areas. WRF sensitivity simulations showed that urban land …

Analysis Of Surrogate Models At Multiple Levels For Neural Acceleration Of Hpc Applications, Bibek Panthi

Theses

Due to rise of machine learning workloads, high performance computing platforms have increased GPU resources. Consequently, use of surrogate models, to utilize GPU compute and speedup scientific applications, is on the rise. Most of the time, the whole program is replaced with a surrogate model. In this work a shock simulation program (LULESH) was taken and three functions of varying complexity were replaced with small sized neural network as surrogate models. The speedup and error in output of whole program was analyzed. We found that for the smallest function, trained model lead to speedup of overall program by 40%, maintained …

'Guide The Tide' - Supervision Of International Medical Graduates In The Emergency Department: A Mixed Methods Study, Purnasankar Bhowmik

Theses

Australia’s emergency departments (EDs) have experienced significant stress since the COVID-19 pandemic. An increase in the number of patient presentations, a lack of in-patient beds for the disposition of admitted patients and long waiting times are contributing factors jeopardising patient safety. In addition, the shortage of skilled staff to look after patients in the ED is the paramount concern currently and moving forward. Similarly to many other specialty areas of medicine, EDs rely on international medical graduates (IMGs) to fill the gaps in the medical workforce. However, concerns have been raised regarding IMG diversity in training requirements, clinical skills and …

Metadata Extraction From Satellite Data Using Small Language Models, Ram Sharan Rimal

Theses

NASA’s GHG Center and VEDA platforms publish satellite Earth observation datasets through STAC catalogs. Publishing a new dataset requires a subject-matter expert to author the discovery configuration and catalog collection for the data, a task that takes three to five hours per dataset to complete. This work contributes a metadata curation pipeline that turns granules, the documentation, and usage examples into both files.Fields readable directly from the files, such as spatial and temporal extent, are extracted deterministically. Fields that require language understanding are sent to a locally hosted small language model. The small model infers the structure of the asset …

Optimisation Of Sampling For A New Skin Microbiome Assay Pilot Study, Anita Smith

Theses

Recent interest in the diverse ecosystem of bacteria, fungi and viruses that make up the skin microbiome has led to numerous studies investigating the microbiome in healthy skin and in dermatological diseases. An imbalance of the normal skin microbial flora can cause some skin diseases, and current culture techniques are often unable to detect a microorganism to further our understanding of the clinical–microbiological correlates of disease and dysbiosis. Atopic dermatitis and rosacea are presentations that General practitioners (GPs) often manage that may have an infective or microbiological component and can be challenging to treat. Further research using culture-independent techniques is …

Leveraging Open-Source Llms For Infrastructure Drift Detection And Correction, Kemoy S. Campbell

Theses

Infrastructure as Code (IaC) enables organizations to provision and manage infrastructure at scale using version-controlled, declarative specifications. Despite these advantages, infrastructure drift where deployed resources diverge from their intended configuration remains a persistent operational challenge and is often addressed manually and reactively. Recent advances in Large Language Models (LLMs) have accelerated their adoption within software engineering and DevOps workflows; however, the sensitive nature of IaC artifacts, particularly Terraform state files, has limited organizational willingness to rely on public LLM services for drift detection and remediation. This thesis investigates the feasibility of using open-source, self-hosted LLMs to assist with IaC drift …

Enhancing Json Schema Inference Via Semantic And Structural Modeling Of Heterogeneous Data, Justin R. Namba

Theses

Schema discovery is finding the structure of data. It helps users understand the meaning of data and write queries to manipulate it. This is typically easy for relational databases, but complex for non-relational (NoSQL) databases with documents. For relational databases, the schema is predefined because the data they contain is structured, but for NoSQL databases, data is usually unstructured or semi-structured. Here, we focus on a type of semi-structured data called JSON, which is a collection of documents that consists of nested key-value pairs. A JSON key and value are similar to a column name and its associated data instance …

Reflux Micro-Aspiration: Natural History, Pathophysiology, Clinical Presentation And Treatment, Oleksandr Khoma

Theses

Background

The accurate diagnosis of gastro-oesophageal reflux pulmonary micro-aspiration has only become possible recently with the introduction of a novel technique of reflux micro-aspiration scintigraphy study combined with single photon emission computed tomography (SPECT) combined with x-ray tomography (CT) in a hybrid instrument (1-3). This has allowed the accurate diagnosis of pulmonary and airway contamination with refluxate. Previously only patients with large volume symptomatic reflux aspiration were diagnosed clinically (Mendelson syndrome) or by 2-dimentional barium meal or an older plantar (2 dimensional) technique of scintigraphic aspiration studies. The concept of reflux micro-aspiration has been implicated in multiple pulmonary diseases but …

Methods For Inter-Sensor Radiometric Harmonization Of Planetscope Superdove Constellation, Biraj Bikram Pathak

Theses

The PlanetScope SuperDove constellation consists of approximately 130 CubeSats. Radiometric drift among the satellites degrades time-series workflows. We formulate inter-sensor harmonization as a supervised regression problem and train a single model across all eight spectral bands using overlapping regions from cross- sensor image pairs. Controlled experiments on same-day image pairs show that a cubic spline model with 20 uniform knots and joint Ridge regularization achieves the lowest error among the evaluated per-pixel regression approaches. The model converges to a Kullback-Leibler divergence between 0.001 and 0.003, and no alternative architecture studied achieves a statistically significant improvement. Models that fit on each …