Digital Commons Network^™

Study Of The Effect Of Biodiesel Derived From Jojoba Oil With Alcohols Blends On Diesel Engine Performance, Exhaust Emissions, Vibration, And Noise, Yassir Abdelrahman Elbashier

Theses

This study presents a mutual investigation on the properties of the fuels and the performance of an engine using biofuels from mixtures of jojoba oil biodiesel with alcohols. The work consists of mainly two phases, examining the properties of the jojoba biodiesel-alcohols mixtures and the performance and emission behavior in a single piston diesel engine. A base mixture of 50% jojoba biodiesel and 50% diesel produced, and this was fractionally mixed with 5, 10, and 20% methanol and with 5, 10, and 20% diethyl ether (DEE). The rheological properties namely viscosity and shear stresses of all biodiesel blend mixtures were …

A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring, Bara Ksiksi

Theses

Air pollution is one of the most critical environmental challenges affecting public health globally, responsible for approximately 4.2 million premature deaths annually according to the World Health Organisation. This thesis presents a comparative study of IoT-driven machine learning forecasting models for air quality monitoring in Abu Dhabi, UAE, introducing a zonal approach combined with satellite-based spatial validation. The primary objective is to evaluate forecasting performance across three distinct activity zones using ground station data from the Environment Agency Abu Dhabi (EAD), and to incorporate a spatial validation component using satellite imagery to assess the consistency of ground-based predictions at a …

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 …

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, …

What Do Future Nutrition Professionals Think About Wic Jobs? A Study Of Nutrition Career Perceptions, Madison Degenfelder

Theses

Background: The Special Supplemental Nutrition Program for Women, Infants and Children (WIC) program faces a critical workforce shortage, yet little is known about the knowledge, attitudes, and beliefs of nutrition students and recent graduates regarding WIC career pathways, requirements, and compensation. Understanding these factors is essential to design strategies to strengthen recruitment and build a sustainable WIC workforce. Objective: To identify and describe knowledge, attitudes and beliefs on entering the WIC workforce among college nutrition and dietetics students and recent graduates. Design: A mixed-methods, sequential study design which included a cross-sectional survey and two focus groups was employed to ascertain …

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 …

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 …

The Disney Adult: A Consumer That Creates Free Marketing, Emily Elizabeth Kempf

Theses

This research looks at the evolving complex relationship between the Walt Disney Company, The Disney Adult content creators and the fan base. It focuses on how user-generated content (UGC) and social media can play a large role in contemporary marketing strategies. As the target audience has expanded to include Disney Adult, this new audience has become a central part in the company’s marketing strategy encouraging fan engagement across all social media platforms. This research is a qualitative case study on the Disney Adult and how social media content can be used as a core marketing strategy. The Disney Adult influencer …

The Gospel Of Glamour: A Christian Woman's Style Blueprint, Osaromwenyeke Osemwota

Theses

The Gospel of Glamour: The Christian Woman’s Style Blueprint was a luxury-branded, sustainability-focused, faith-based style guide that addressed a gap in fashion, theology, and sustainability scholarship. Existing literature had either systematized fashion, explored the spiritual significance of dress, or examined sustainable and luxury practices—but none had integrated these dimensions into a prescriptive, actionable guide for Christian women. Drawing on Scripture as the foundational authority, including passages from Genesis, Exodus, Psalms, and Proverbs, the guide framed clothing as both practical provision and visible expression of covenantal identity. The style guide synthesized secular fashion methodology, modest-fashion scholarship, and sustainable luxury principles to …

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 …

Optimizing Traffic Signal Timings Using Real Time Data Analytics, Hamad Abdulla Binsultan

Theses

City traffic jams have become a major challenge for contemporary cities, causing delays, increased fuel consumption, and other environmental impacts. Conventional traffic signal controlling systems usually depend on fixed or preset signal plans that are incompetent to adjust themselves with changing traffic conditions. Traffic signal timings are optimized across the intersection health of the system by processing real-time data analytics. Through real-time data analytics, traffic flow efficiency is improved while waiting time at signalized intersections is reduced. Using traffic real-time data like vehicle counts, vehicle types, time of day and day of the week to see howtraffic behaves under different …

Model Free Sliding Mode Control For Uavs, Aashrita Mandalapu

Theses

Sliding Mode Control (SMC) is a robust and adaptable control strategy recognized for its ability to withstand uncertainties, disturbances, and parameter variations. Although the straightforward implementation of SMC along with its insensitivity to modeling inaccuracies make it effective for a wide range of applications, it still relies heavily on an accurate system model. In dynamic environments where system characteristics vary over time, a model-independent SMC framework becomes necessary. So, a Model-Free Sliding Mode Control (MFSMC) approach is proposed as a compelling solution for complex nonlinear systems where deriving an accurate model is difficult. In contrast to conventional SMC approach, MFSMC …

Inflection Points In Academic Career Trajectories: Statistical Modeling And Interactive Visualization, Aicha Malouche

Theses

This thesis examines the temporal structure of academic career trajectories, with a particular focus on identifying non-linear patterns of research productivity and moments of maximum acceleration in scientific impact. Situated within the broader context of bibliometric evaluation, the study responds to long-standing limitations of aggregate and linear career models that obscure heterogeneity across disciplines and national research systems. Drawing on theories of cumulative advantage, life-cycle productivity, and structural stratification, the research seeks to clarify how and when elite researchers experience peak growth in impact over the course of their careers. The study is guided by four research questions: (1) when …

Optimizing Motor Insurance Premiums In The Uae Using Predictive Analytics, Samar Abdelsalam

Theses

The car insurance industry in the UAE and GCC faces growing challenges including premium inflation, fraudulent claims, inconsistent pricing models, and lagging innovation in underwriting. This study investigates how predictive analytics and machine learning can enhance motor insurance premium optimization, with a focus on incorporating socio-demographic, behavioral, environmental, and vehicle-specific risk factors. Using a publicly available dataset of over 125,000 insurance policy records, this research applies a CRISP-DM framework to develop and evaluate supervised learning models including Linear Regression, Decision Trees, and Random Forests. Results highlight Linear Regression as the most effective model (RMSE = 193.62, R² = 0.9016), enabling …

Stimuli-Responsive Chemotherapy For Glioblastoma: Sequence-Dependent Synergy Of Cold Atmospheric Plasma And Ultrasound With Cationic Lipo-Doxo, Alessandro Cazzolla

Theses

Glioblastoma (GBM) is an aggressive, infiltrative astrocytic tumour in which pharmacotherapy remains constrained by the blood-brain barrier (BBB) and the heterogeneously altered blood brain tumour barrier, with additional limitations imposed by active efflux and the complexity of the tumour microenvironment. In this setting, externally addressable strategies that modulate transport and uptake at the site of disease are required. A stimuli-responsive chemotherapy platform was developed in which Lipo-DOXO was combined with two non-invasive physical modalities, low-frequency ultrasound (US) and cold atmospheric plasma (CAP), to enhance intratumoural delivery while limiting off-target effects. Liposomes were produced by thin-film hydration followed by a controlled, …

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 …

Evaluating The Effectiveness Of Smart City & Iot Solutions In Improving Urban Sustainability, Mobility, And Quality Of Life In The Uae, Aisha Alnuaimi

Theses

The United Arab Emirates has an aim to develop smart cities incorporating advanced technologies such as the Internet of Things (IoT), to enhance urban sustainability, mobility, and improve citizens quality of life. However, based on the significant funds invested by the government, there exists an important gap within the government systems in measuring the effectiveness of such activities given the lack of data quantifying the benefits gained from such smart initiatives. To address this gap, this study delivers the benefits gained from smart initiatives by using a mixed-methods approach combining both quantitative and qualitative data. The research is based on …

Multipath Exploitation For Radar Sensing In An Urban Environment Using The Music Algorithm For Jammer Mitigation, Daniel De Zutter

Theses

With the increased push for spectrum sharing techniques, the technological world surrounding radar has been constantly pushing to find new methodologies. From being able to integrate with a communication system to mitigating the effects of other users on a system, the research community is pushing forward. We look to tackle the problem of mitigating a jammer using a multipath MUltiple SIgnal Classification (MUSIC) based approach. We take multiple steps to implement this and generate a framework for future work. We first take a look at understanding the current state of the art research surrounding DFRC, multipath exploitation, MUSIC algorithms, RIS …

Customer Lifetime Value Prediction In E-Commerce, Shaimaa Alantali

Theses

The e-commerce market across the world currently deals with an urgent problem which has emerged because businesses now use automated pricing systems everywhere. Online merchants who automate their decision processes to handle changing customer needs and limited stock situations must face external business forces which push their teams to start destructive pricing battles that harm all businesses in the sector. The research investigates how a unified computational framework which combines demand modeling with advanced data analytics methods can enhance pricing strategies through market instability detection and prevention systems. The study creates a market simulator through data-driven methods which uses retail …

Exploring Interpenetrating Networks Derived From Compostable Polymers In Separations, Hailey Holshouser

Theses

The increasing demand for environmentally friendly and sustainable water treatment technologies drives the development of membranes that work to balance mechanical durability, tunable selectivity, and long-term stability. In this exploratory work, an interpenetrating polymer network (IPN) membrane system composed of poly(butylene adipate-co-terephthalate) (PBAT) and poly(2-hydroxyethyl methacrylate) (pHEMA) was developed to provide a more compostable and compatible platform for advanced separation applications. While the compostability of the entire framework was not tested, the dominant presence of PBAT in the matrix makes the membrane intrinsically favorable for composting. Mechanochemical Ionic Electrochromic Generators (IEGens) were synthesized and incorporated into the PBAT backbone for …

Urban Effects On Cloud Formation, Boundary Layer Circulation, And Rainfall Over Miami, Aaron A. Serre

Theses

The sensitivity of cloud and precipitation formation is expected to be enhanced over urban areas due to persistent sea-breeze forcing. This study combines surface observations, satellite data, and numerical modeling to investigate the impacts of urbanization in the Miami Metropolitan Region (MMR) on surface meteorology, cloud formation, and precipitation. Satellite observations reveal urban expansion of approximately 348 km², along the western boundary of the MMR. These areas also exhibit statistically significant increases in land surface and air temperatures. Geostationary satellite data show enhanced morning cloud formation over the MMR, while increasing rainfall and interannual variability in cloudiness are observed along …

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 …

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 …

Leveraging Ai, Iot, And Predictive Analytics For Crisis Management And Urban Resilience In Dubai, Suhail Bin Kalli

Theses

The thesis will discuss how smart technologies could be incorporated in the crisis management structures of Dubai to make the city more resilient. As Dubai grows more urbanized, it experiences increased problems with managing its crisis especially in the high population density places, traffic congestion, utility disruption, and extreme weather. This paper discusses how artificial intelligence (AI), the Internet of Things (IoT), and predictive analytics can be used to ameliorate the response to emergencies, manage the allocation of resources, and enhance the coordination between different agencies. The crisis management systems at Dubai are still ineffective despite the level of technologies …

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 …

Examining Preoperative Health And Lifestyle Risk Factors In Patients Awaiting Surgery During Covid-19 In Western Australia, Nadine Radin

Theses

This study investigated the prevalence of modifiable preoperative lifestyle risk factors among patients undergoing upper gastrointestinal and colorectal surgery at a metropolitan hospital in Perth, Western Australia (WA). It aimed to characterise behaviours such as smoking, alcohol and drug use, nutritional risk, physical fitness, frailty, and body mass index (BMI), and to examine whether these changed during the early phase of the COVID-19 pandemic in 2020 compared to 2019.

A retrospective audit of 2,340 patient medical records was conducted, with data extracted from routinely collected preadmission documentation. Regression models compared the prevalence of risk factors across matched calendar periods, adjusting …

Ties Of Influence: The Armistead-Winston Network And Elite Mobility From Virginia To The Southern Frontier., Mindy L D Bates

Theses

This thesis examines how the Armistead and Winston families leveraged intergenerational kinship networks to preserve and reproduce elite authority as they migrated from colonial Virginia to the southern frontier. Rather than viewing migration as an individual pursuit, this study demonstrates that family alliances, shared resources, and long-standing ties shaped opportunity and authority across generations. Using family papers, letters, land deeds, wills, journals, and family trees, this project highlights how these connections functioned as forms of social capital that guided settlement, land acquisition, and community leadership on the frontier. This study serves as a guide for understanding how kinship networks operated …

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 …