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Particle Image Velocimetry (Piv) Measurements Of Flow Characteristics Of An Unsteady Oblique Shock Wave Train, Andrew Girgis
Particle Image Velocimetry (Piv) Measurements Of Flow Characteristics Of An Unsteady Oblique Shock Wave Train, Andrew Girgis
Theses
Presented is the development of a Particle Image Velocimetry (PIV) apparatus to quantify the velocity field produced by an oblique shock wave and its reflections in a supersonic/transonic wind tunnel. A flow seeding system is developed using mesquite wood smoke generated in a metal vessel heated with a Vevor TDGC-2KVA variable autotransformer. A pressurized K-bottle drives the smoke through a cooled copper coil and moisture trap to remove contaminants before injection. A dual-pulsed class IV Nd:YAG Big Sky laser with Thorlabs optomechanical components, including two cylindrical lenses, is used to create a pulsed light sheet to illuminate tracer particles. Image …
Safe Reinforcement Learning For Trajectory Tracking Of Mobile Robots With Minimal Intermittent Observations, Mahtab Noor Shaan
Safe Reinforcement Learning For Trajectory Tracking Of Mobile Robots With Minimal Intermittent Observations, Mahtab Noor Shaan
Theses
Autonomous wheeled mobile robots (WMRs) are widely used for safe operation in safety-critical systems, such as robotic visual inspection of confined spaces in energy infrastructure, warehouse automation, delivery robots, and autonomous vehicles. The operating environments for these safety-critical systems are often uncertain. Therefore, in such environments, it is essential for WMRs to reliably follow predetermined paths while effectively maintaining lane position and avoiding collisions. However, frequent observations required for control execution to account for environmental uncertainty result in increased sensing, computation, and energy costs. This necessity drives the research for safe and resource-aware trajectory-tracking control methods. Although several state-of-the-art trajectory …
Blockchain Poisoning Attacks In Federated Learning, Mohammad Raihan Uddin
Blockchain Poisoning Attacks In Federated Learning, Mohammad Raihan Uddin
Theses
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, thereby preserving privacy. However, conventional FL depends on a centralized aggregator, exposing it to poisoning and backdoor attacks that threaten model integrity. This thesis introduces B-ZkFed, a blockchain-based and zero-knowledge proof (ZKP)-enhanced FL framework designed to ensure verifiable trust, transparency, and robustness. The blockchain layer decentralizes aggregation through smart contracts, while the ZKP module allows clients to cryptographically prove the correctness of updates without revealing private data. A multi-layer adaptive defense combining gradient-norm filtering, model-similarity analysis, and robust aggregation mitigates poisoning threats under both IID and …
Simplified Soil-Based Approach For Maximum Pressure Prediction In Horizontal Directional Drilling Operations, India Clark
Simplified Soil-Based Approach For Maximum Pressure Prediction In Horizontal Directional Drilling Operations, India Clark
Theses
Horizontal Directional Drilling (HDD) is a trenchless pipeline installation method used in areas where traditional trenching is not feasible due to environmental concerns, existing infrastructure, or other constraints. However, HDD presents significant engineering challenges, with design failures often resulting from excessive installation stresses and Hydro Fracture. Hydro Fracture occurs when the pressure of drilling fluid exceeds the soil’s bearing capacity, leading to unintended subsurface fractures. To mitigate this risk, researchers have relied on the Delft Equation to estimate the maximum allowable mud pressure for borehole stability. However, this equation does have notable limitations and assumptions, which may not accurately reflect …
Sensor Fusion For Enhancing Motion Capture : Integrating Optical And Inertial Motion Capture Systems, Hailey Hicks
Sensor Fusion For Enhancing Motion Capture : Integrating Optical And Inertial Motion Capture Systems, Hailey Hicks
Theses
This study aimed to create and evaluate a custom sensor fusion algorithm based on Gauss-Newton optimization that combines Optical Motion Capture (OMC) and Inertial Motion Capture (IMC) measurements to combat the limitations of solely using each system. The goal was to demonstrate how inertial measurement unit (IMU) data can be seamlessly integrated into motion capture data to provide a more efficient and reliable gap filling process for future research. The algorithm takes the first and last frame of OMC data, as quaternions, and fills the rest with IMU gyroscope orientation data to simulate gaps of up to ten minutes. The …
A Deep Learning Multi-Channel Framework For Indoor Image Retrieval, Vidhi M. Bhatia
A Deep Learning Multi-Channel Framework For Indoor Image Retrieval, Vidhi M. Bhatia
Theses
Processing and analyzing multi-source image data is vital across a wide range of fields, including artificial intelligence (AI), deep learning, computer vision, geolocation, autonomous navigation, remote sensing, and forensic investigations. Although conventional image matching methods such as Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) have proven effective in controlled setting, they often face challenges when applied to diverse datasets that exhibit substantial variations in viewpoint, scale, lighting conditions, and modality. Recent developments in deep learning, including convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), and self-supervised learning, have led to the creation of more efficient and precise …
Multiscale Finite Element Analysis Of Cylindrical Jellyroll Based Energy Storage Devices, Wesley James Knee
Multiscale Finite Element Analysis Of Cylindrical Jellyroll Based Energy Storage Devices, Wesley James Knee
Theses
Lithium batteries are an ever-expanding solution for energy storage; however, their internal chemistry is highly prone to combustion. Any severe mechanical failure can lead to this scenario, which is problematic as their use in electric vehicles increases. As such, finite element modeling efforts need to improve in order to properly define the failure mechanics of these batteries. Efforts have already been made to create an accurate model of the battery as a whole, but this generalized model does not capture the short-circuiting phenomena within the internal components. To solve this problem, a representative volume model that generates input data and …
Comparing Role Differences Among Systems Architects, Systems Designers, And Systems Engineers, Kelly X. Campo
Comparing Role Differences Among Systems Architects, Systems Designers, And Systems Engineers, Kelly X. Campo
Theses
The roles of a systems architect (SA), systems designer (SD), and systems engineer (SE) often work together to develop systems, especially as the scale and complexity of engineered systems increase. However, management of these roles can result in ambiguity of task assignments and may reduce accountability for deliverables. Furthermore, there are few published works examining the roles of SAs, SDs, and SEs collectively. This research explores perceptions of the similarities and differences between the roles of SAs, SDs, and SEs by conducting a systematic literature review of 57 sources containing 1064 quotes in addition to a thematic content analysis, analyzed …
Average Heat Flux Measurements In An Additively Manufactured Rotating Detonation Rocket Engine Calorimeter, Matthew Aaron Maybee
Average Heat Flux Measurements In An Additively Manufactured Rotating Detonation Rocket Engine Calorimeter, Matthew Aaron Maybee
Theses
Rotating detonation rocket engines (RDREs) offer benefits over traditional deflagrative engines, including increased engine performance, compact combustion and negligible detrimental thermoacoustic instabilities due to mode-locking. Realizing the benefits of a detonation-based propulsion system will be accompanied by increased thermal loads due to a combination of heat release at elevated pressure and temperature, as well as compact heat release due to detonation. Managing these heat loads necessitates the development of thermal management strategies. As a first step towards establishing the requirements for detonation-based engine thermal management strategies, this work develops an additively manufactured (AM) water-based, axially resolved calorimeter for integration in …
Ammonium Perchlorate Manufacturing Effects On Propellant Burning Rate, Erin Faith Wallace
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
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
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 …
Influence Of Hot Isostatic Pressing And Quench Rate On Aluminum 2139am, A Novel Alloy For Lpbf, James Wagnon
Influence Of Hot Isostatic Pressing And Quench Rate On Aluminum 2139am, A Novel Alloy For Lpbf, James Wagnon
Theses
Mechanical and microstructural evaluation was carried out on a modified 2XXX series aluminum alloy designed for laser powder bed fusion (LPBF). Aluminum 2139AM samples printed via LPBF were given three distinct heat treatments: baseline T4 with water quench, modified T4 with hot isostatic pressing (HIP) and natural cooling, and modified T4 with HIP and rapid gas quench. This study examines the effects of the experimental HIP treatment with rapid gas cooling on the LPBF samples to increase ductility and assess the potential of the material as an AM replacement for 2024-T4 aluminum parts. Use of HIP processing on 2139AM was …
A Study Of Neural Compression Techniques For Image Compression Using A Novel Algorithmic Lossless-Ness Criteria, Abhishek Prasanna Simha
A Study Of Neural Compression Techniques For Image Compression Using A Novel Algorithmic Lossless-Ness Criteria, Abhishek Prasanna Simha
Theses
Neural compression methods claim near-lossless reconstruction capabilities based on traditional metrics such as PSNR and MS-SSIM. However, their impact on downstream machine learning tasks remains largely unexplored. This thesis evaluates three state-of-the-art CompressAI models (Cheng2020-anchor, bmshj2018-hyperprior and mbt2018 ) on high-resolution satellite imagery using semantic segmentation as a downstream task benchmark. We introduce the idea of algorithmic losslessness with respect to a downstream machine learning task and use it to benchmark existing state-of-the-art neural compression algorithms. We also compare the results with non-neural compression techniques. We conducted experiments on 11 urban satellite images using two segmentation approaches: MMSegmentation (7 classes) …
Active Learning Methodologies And Applications, Pradeep Bajracharya
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 …
How Smart City Growth Principles Can Be Adopted In The Uae To Solve The Local Housing Problems?, Shaima Abdulla Alblooki
How Smart City Growth Principles Can Be Adopted In The Uae To Solve The Local Housing Problems?, Shaima Abdulla Alblooki
Theses
Shaikh Zayed Housing Program “SZHP” is the governmental program that is responsible for local housing in the UAE. The program’s main aim is to offer a variety of housing services such as loans, grants, and ready-to-move houses. However, both the continuously growing urban population and liveability challenges are impeding the program to meet its goal. As mentioned on SZHP’s official website “We should continue to explore new ways to establish informed dialogue with different groups of society and to ensure adequate housing for national families, in achieving stability and community development by meeting future needs” (SZHP, 2022 ). Accordingly, this …
Predictive Policing - Leveraging Cctv Data And Ai For Crime Hotspots, Maitha Ahmad
Predictive Policing - Leveraging Cctv Data And Ai For Crime Hotspots, Maitha Ahmad
Theses
This thesis explores fine-grained sentiment analysis in the context of police social media posts, leveraging hybrid approaches to manage the rapid flow of big data and mitigate its negative impact on youth. As social media becomes a primary medium for public interaction, understanding sentiment within police-related posts is crucial for law enforcement agencies to gauge public opinion and address community concerns effectively. The rapid dissemination of information and the potential for negative sentiments to spread swiftly pose significant challenges, particularly for young audiences. The research begins with a comprehensive review of existing sentiment analysis techniques and their applicability to large-scale …
Automated Prioritization And Routing Of It Support Tickets Using Machine Learning, Mohamed Almarzooqi
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 …
Internet Of Things (Iot) In Developing Smart City Traffic Management Systems In Dubai, Ayesha Ahmed Alnuaimi
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 …
Jamaica: The Stories We Never Told, Vinnette Gibson
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 …
Structure/Property/Processing Of A 3d Printed Self-Healing Polymer Blend Based On A Thermoplastic Healing Agent, Vincent Mei
Structure/Property/Processing Of A 3d Printed Self-Healing Polymer Blend Based On A Thermoplastic Healing Agent, Vincent Mei
Theses
Self-healing polymers can regain mechanical performance following damage, offering increased material durability and sustainability. This thesis establishes structure/property/processing relationships for a 3D printable extrinsically self-healing polymer based on a UV polymerizable thermosetting resin system blended with a low temperature thermoplastic healing agent. This work serves as the first example of a vat polymerization 3D printed soft, low Tg low-melt thermoplastic extrinsically self-healing polymer blend. This development enables high resolution fabrication of complex geometries with self-healing functionality. This strategy of imbuing self-healing properties onto vat polymerization resins will enable functionality in many application spaces including aerospace, biomedical, soft robotics, coatings, and …
Fake News Detection In Arabic Media Using Machine Learning And The Afnd Dataset, Hussain Ali Bahri
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, …
Concentrated Benefits And Dispersed Costs: The Contributions Of Pareto, Olson, And Ostrom, Nathan John Cuthbertson
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); …
Sigrid Undset: Nordic Catholic Apologist, Brendan Edward Arthur
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 …
A Framework For Mixed Reality Within Healthcare Education, Benyamin Ebadinia
A Framework For Mixed Reality Within Healthcare Education, Benyamin Ebadinia
Theses
Understanding complex three-dimensional systems and spatial relationships is a recurring difficulty in healthcare education, where students are often expected to reason about internal structures and multi-system processes from 2D diagrams, textbook figures, and static mannequins. This thesis presents the design, implementation, and mixed-methods evaluation of Systems Simulation, a reusable mixed reality (MR) application intended to help undergraduate nursing students explore human anatomy and pathophysiology using immersive 3D visualization.
Built in C# with the StereoKit framework for Microsoft HoloLens 2, Systems Simulation organizes nine anatomical body systems within a shared application. Learners can select a system, anchor the model in their …
Predicting Airbnb Prices In Dubai Using Machine Learning, Hamad Younus Altamimi
Predicting Airbnb Prices In Dubai Using Machine Learning, Hamad Younus Altamimi
Theses
The Airbnb rental market in Dubai is dynamic and full of varying factors like location, equipment, and demand time shortages, which makes it challenging to have fair pricing for the different levels of Airbnb properties in Dubai. The goal of the project was to construct a powerful machine-learning model for the forecast of the Airbnb rental price in Dubai The method used by the project was systematic from the beginning to the end stages, which included the data collection from Kaggle, the data preprocessing which involved the handling of missing values, outlier elimination, data type conversion, and exploratory data analysis …
Resilient Power System Load Frequency Control, Ghadeer Ahmed Almahri
Resilient Power System Load Frequency Control, Ghadeer Ahmed Almahri
Theses
Standard frequency and voltage levels need to be maintained when the electric power system is running in order to keep it in a satisfactory state of operation. Between AC power generation and use, there should be a balance between active and reactive power. However, due to variations in active and reactive power requirements, the frequency and voltage provided may fluctuate from their rated values. Any unwelcome change in frequency or voltage can have an immediate effect on how the power system operates and may even cause harm to linked devices. These parts are intended to operate at certain rated frequencies …
Predicting Bus Ridership In Dubai Using Advanced Machine Learning Models, Fatma Almheiri
Predicting Bus Ridership In Dubai Using Advanced Machine Learning Models, Fatma Almheiri
Theses
In rapidly urbanizing cities, the public transport systems have to be efficient and reliable with proper demand forecasting to guarantee customer satisfaction. This paper explores how evidence-based machine learning tools can be used to forecast weekly bus ridership in Dubai, using a dataset of more than 10 million trip-level boarding observations between June 2013 and July 2014. It was aggregated to 25,195 route-week observations, and preprocessed with temporal feature engineering, lag variables and rolling statistics. Three predictive models have been tested: Linear Regression (as a baseline), Random Forest and XGBoost (as an ensemble method). Mean Absolute Error (MAE), Root Mean …
Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz
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
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 …