Digital Commons Network^™

The Association Between Body Image Satisfaction And Depressive Symptoms Among Young Women In The Uae With Polycystic Ovary Syndrome (Pcos) And Non-Pcos: A Comparative Quantitative Cross-Sectional Study, Shaima Abdrahman Al-Mekhlafi

Theses

Polycystic Ovary Syndrome (PCOS) is one of the most common syndromes affecting women of reproductive age, (Laggari et al., 2009). PCOS not only impacts women's physical health but also their psychological well-being, often leading to depressive symptoms and lower body image satisfaction, Wang et al. (2023). Recent research indicates a growing prevalence of PCOS among women in the United Arab Emirates (UAE), Mirza et al. (2023). However, there is a noticeable gap in understanding the psychological effects of PCOS on women in the UAE, likely due to cultural sensitivities. This study aims to investigate the association of depressive symptoms and …

Studies On The Corrosion Of Bronze Artifacts From Sarouq Al-Hadid And Al-Qusais Archeological Sites In Dubai, Uae, Zainab Ali Salmin

Theses

This thesis compares the status of bronze artefacts from two archaeological sites in Dubai (UAE): the Sarouq Al-Hadid site (Stone Age to Early Islamic Period) and the Al- Qusais site (Late Bronze Age to Early Iron Age). The main objective of this research is to understand the two sites' environment and their influence on the corrosion of archaeological bronze artifacts found at the sites. This study uses mCed methods to comprehensively understand the corrosion behavior of bronze objects, depending on their burial environment. The two different sites presented different soil types and rates of corrosivity on the buried bronze artifacts, …

Visualizing Privately Protected Data: Exploring The Privacy-Utility Trade-Offs, Sarah Hayi Alkaabi

Theses

In a data-driven era, achieving a balance between privacy and utility is crucial. Organizations often utilize data for research, analysis, and enhancement of services, which emphasizes the significance of effective privacy-preserving techniques to protect individuals' privacy and comply with regulations. This equilibrium is vital in data visualization to derive insightful decisions from data representations. The goal is to evaluate the trade-off between privacy preservation and data utility, understanding how differentially private parameters impact effective visualizations. Valuable insights will guide strategies for achieving optimal privacy-preserving visualization techniques. The study aims to investigate the effects on privacy and data utility in different …

Relationship Between Parents’ Feeding Styles, Nutrition Practices And Risk Of Obesity Among 3-5 Years Old Children In The United Arab Emirates, Reem Mohamed Alkarbi

Theses

Previous studies suggest that parental feeding practices shape preschool eating and physical activity habits, ultimately influencing children's weight status. Despite the high obesity rate in UAE youth, preschoolers’ nutrition habits and their links to parental feeding styles are explored. This study aims to describe parental feeding styles: Emotional (E), Instrumental (I), Prompting and Encouragement (PE), Control Over Eating (COE)), and their associations with nutrition practices, socio-demographic factors, and obesity in UAE preschoolers. Using an online questionnaire, a cross-sectional study surveyed Emirati families with 3-5-year-old children. Data was analyzed using SPSS v.29. 70 preschool Emirati children living in Abu Dhabi participated. …

Neural Operator For Accelerating Coronal Magnetic Field Computations In Bifrost Mhd Model, Yutao Du

Theses

The application of the Tensorized Fourier Neural Operator (TFNO) to significantly enhance the computational efficiency of coronal magnetic field calculations within the Bifrost Magnetohydrodynamics (MHD) model is introduced in this study. Leveraging simulated data from the European Sunrise Science Data Center, the TFNO? an extension of the Fourier Neural Operator (FNO) that incorporates tensor decomposition for improved handling of high-dimensional data?is employed to solve time-varying partial differential equations (PDEs) over a 3D domain. The performance of the TFNO is compared with traditional machine learning methods, including Vision Transformer and CNN-RNN (encoder-decoder) architectures, to demonstrate its accuracy, computational efficiency, and scalability. …

Marking Estimation In Petri Nets Using Dynamic Mode Decomposition, Aditya Kale

Theses

Petri Nets (PNs) are a well-established framework for modeling and analyzing complex systems with interacting, concurrent processes. This thesis extends traditional Petri Net methodologies by integrating Dynamic Mode Decomposition (DMD), a technique originally developed for fluid dynamics, to analyze Continuous Petri Nets (CPNs). By applying DMD to CPN marking evolution, this research constructs a reduced-order model that captures its dynamics through dynamic modes and eigenvalues, enabling prediction of future markings without detailed knowledge of transition firings or underlying deterministic models. The principal contribution of this research is extending the kit of tools available for analysis of CPN dynamics, providing insights …

Effects Of Exoskeletal-Assisted Walking Rehabilitation On Gait Of Patients Post Stroke, Archisha Kanchan

Theses

Stroke can have detrimental effects on one's body. Its symptoms can range from lightheadedness to blurred vision to body paralysis. One of the more common effects of stroke is difficulty walking where many of the patients who have suffered from stroke are unable to ambulate fully. To mitigate gait difficulties, patients typically follow through with various kinds of physical therapy to help with their gait movements. Recently, robotic exoskeleton (RE) walking therapy has been used as a more innovative approach to gait rehabilitation, in conjunction with other physical therapy session techniques. However, studies involving RE therapy within the stroke population …

The Next Strike: Pioneering Forward-Thinking Attack Techniques With Rowhammer In Dram Technologies, Nakul Kochar

Theses

In the realm of DRAM technologies this study investigates RowHammer vulnerabilities in DDR4 DRAM memory across various manufacturers, employing advanced multi-sided fault injection techniques to impose attack strategies directly on physical memory rows. Our novel approach, diverging from traditional victim-focused methods, involves strategically allocating virtual memory rows to their physical counterparts for more potent attacks. These attacks, exploiting the inherent weaknesses in DRAM design, are capable of inducing bit flips in a controlled manner to undermine system integrity. We employed a strategy that compromised system integrity through a nuanced approach of targeting rows situated at a distance of two rows …

Targeted Drug Delivery: Investigating Protein Corona Behavior, Atharva Markale

Theses

Due to high specificity and less toxicity, nanoparticles have become promising for targeted drug delivery against cancer, although they face challenges when they enter the bloodstream, making their behavior unpredictable. The deposition of proteins on nanoparticles, the protein corona, changes their biosignature, affecting their circulation, drug release potency, targeting ability, and immunogenicity. The continuous exchange of protein layers on a nanoscale is complex to analyze.

Nanoparticle tracking analysis (NTA) is a method to characterize nanoparticles in blood plasma by combining principles of light scattering microscopy and Brownian motion. In this work, time-dependent experiments with plasma were conducted to analyze the …

Strawberry Nectar Preservation Through Innovative Techniques And Energy Evaluation For High-Pressure Processing, Caterina Scaioli

Theses

Strawberries are universally adored by people of all ages, owing to their richness in vitamins, nutrients, and antioxidants, offering myriad health benefits, including combating free radicals. However, despite their popularity, strawberry juices or nectars are not commonly found in markets due to their delicate structure, which makes them prone to rapid deterioration of their prized qualities and vibrant red color. In the food industry, preventing browning and nutrient deterioration are often the primary challenges faced when processing red juices. Traditional preservation methods, such as pasteurization, are inadequate in maintaining their freshness. The focus of this study is to explore alternative …

Methodology For Developing Biodegradable Polymer Blends And Composites For Agriculture, Fangzhong Xing

Theses

The use of polyethylene (PE) films to improve soil conditions and to increase crop yield has produced microplastics that are harmful to our ecosystem. The overall objective of this thesis is to develop an effective biodegradable polymer/composite to replace PE, and hence, to reduce microplastic pollution. The focus of this research is to develop a systematic protocol for assessing the suitability of the biodegradable films based on industry standards in agriculture. For this purpose, a range of biodegradable polymer blends are prepared using polylactic acid (PLA) and polybutylene adipate-co-terephthalate (PBAT) with varying PLA to PBAT ratios. Solvent casting combined with …

Comparison Of Methods For Creating Populations Of Models By Solving Stochastic Inverse Problems, Elizabeth Epstein

Theses

Given a parametric family of models and observational data, a researcher may be faced with an inverse problem: what distribution of parameters best creates a set of models that produce the observed data? Traditionally, Markov Chain Monte Carlo (MCMC) has commonly been used as a method to solve these stochastic inverse problems. In recent years, however, Generative Adversarial Networks (GANs) have been employed. The effectiveness of Markov Chain Monte Carlo methods as compared to a conditional generative adversarial network (cGAN) when applied to a family of models produced by a system of ordinary differential equations that model viral load over …

Electrochemical Nitrate Reduction To Ammonia On Cu Based Nanoparticles Using Quantum Mechanical Simulations, Kathan Bhavin Shukla

Theses

Nitrate reduction to ammonia (NRA) is critical for environmental remediation and energy conservation, as it can remove harmful nitrate (NO₃^-) from water sources while producing usable ammonia (NH₃). Cu represents one of the most promising non-noble-metal NRA electrocatalysts. However, the intrinsic catalytic activity of Cu facets and their influence under different pH conditions remain unclear, particularly in the presence of ions commonly found in wastewater such as Cl^-, Na⁺, Mg²⁺, and Ca²⁺. Using density functional theory (DFT) calculations, we evaluated the nitrate reduction to ammonia (NRA) pathways …

A Programmable Look-Up Table-Based Processing In Memory Architecture For Massively Parallel, Energy-Efficient Processing Of Data-Intensive Applications Within Dram, Purab Ranjan Sutradhar

Theses

As modern computing workloads become increasingly data-intensive, the limitations of traditional digital computing hardware, especially in terms of communication bandwidth between memory and processors, are becoming more apparent. Surprisingly, the performance and energy efficiency of the state-of-the-art are not primarily constrained by the computing power of advanced processing architectures but rather by the low communication bandwidth between the memory and the processor. This challenge necessitates a clever re-architecting of digital computing hardware to make the communication between the processor and the memory more energy-efficient, faster, and capable of supporting significantly higher bandwidth. Memory-centric computing emerges as a novel, alternate computing …

Human-Machine Interactions For Behavioral Health Care, Zhiwei Yu

Theses

About one in four American adults (26%) and 20.3% of children aged 8 to 16 years reported behavioral health concerns in 2023. However, a substantial gap remains between demand for behavioral healthcare services and access to such services. In response, research efforts have been made to advance effective and accessible approaches to provide assessments and treatments for populations with behavioral health needs. Yet, two primary challenges exist in current practice and research: 1) self-reports and manual observation-based assessments are subjective and labor-intensive, as evaluations are limited to the availability of clinical professionals; 2) they only target the general experiences but …

Spatiotemporal Alignment Of Event Stream With Images And Active Illumination, Abhijan Wasti

Theses

Unlike conventional frame-based cameras that form images by sampling all pixels within the duration of the global/rolling shutter, a pixel in an event camera can be triggered independently when the log intensity change in scene luminance at the pixel exceeds a threshold. This unique feature provides several advantages over conventional sensors, including high dynamic range (HDR) (≈120dB), high temporal rate (≈10,000Hz), low latency (< 1ms), and low power requirements (≈10mW). These properties make them excellent candidates for applications such as high-speed photography, HDR image reconstruction, object tracking, depth estimation, simultaneous localization and mapping, and surveillance and monitoring. Despite their potential, the asynchronous and spatially sparse nature of events poses challenges to event processing and interpretation. This is because most advanced image processing and computer vision algorithms are designed to work with conventional image formats, and not with temporally dense streams of asynchronous pixel events (i.e., the event stream). Although emerging techniques in supervised machine learning demonstrate promise, continued and rapid progress relies on the availability of labeled event datasets, which are scarce, and difficult to produce. Moreover, generating reliable events for training models is challenging due to the scene-dependent nature of event generation, which is further complicated by varying illumination and relative motion. In this thesis, we attempt to address these limitations with a novel imaging paradigm involving the capture of frames from a conventional frame-based camera that has been spa tially aligned and temporally synchronized with an event sensor. Our active illumination source allows us to generate events more consistently even under challenging illumination and motion in the scene. We demonstrate the feasibility of such a setup for a mobile eye tracking system and acquire subpixel and microsecond accurate spatiotemporal alignment. Our method facilitates the use of pre-trained models that operate on conventional images to detect features that can then be used to train models that can be applied directly to the event stream. This serves as the next step in event-based imaging and unlocks new possibilities in computer vision and imaging technology.

Exploring Microplastic Concentrations And The Sedimentology Of San Diego's Offshore Benthic Environments, Rachel Sarner

Theses

Marine pollution studies are showing infiltration of plastic debris in remote parts of oceans including the deep sea. Microplastics (MPs) are being discovered not only in the ocean’s water column but also benthic sediments reaching thousands of meters in depth. This is the first study to analyze MP concentrations in conjunction with sedimentary characteristics from varying deep-sea environments (coastal, deep ocean, offshore terrace) in the Southern California Continental Borderland (CCB). Our goal for this study was to observe how the concentration and type (morphology, color, size) of microplastics varied with distance from shore, with water depth, and between different submarine …

Nano Biosensing Platform For Infectious Disease Diagnostics, Li Liu

Theses

CRISPR-Cas enabled biosensors offer great potential to be at the forefront of diagnostic medicine. This thesis focuses on the principles of CRISPR-Cas technology and its application to biosensors and virus diagnostics. It also provides a detailed discussion of the different detection methods available at this stage. The breakthrough achievements of CRISPR biosensors in nucleic acid detection are summarized. The CRISPR-Cas nano biosensors exhibit high accuracy, sensitivity, selectivity, and versatility, offering great potential for next-generation diagnostic and point-of-care devices. The prospects and future trends of CRISPR biosensors are also described. From an engineering perspective, this thesis develops and applies several methods …

Using Machine Learning Algorithm For Detecting Distributed Denial Of Service Attack, Zainab Alblooshi

Theses

DDoS attacks, which stand for Distributed Denial of Service attacks, play a significant role in impacting the reliability and availability of online services and networks. Since no system is completely immune to cybersecurity threats, which evolve daily with new techniques, studying this topic is crucial for exploring machine learning methods that can effectively detect DDoS attacks. An approach has been utilized to conduct Exploratory Data Analysis (EDA) to identify patterns suggesting the presence of DDoS attacks. Multiple machine learning models have been employed, such as Random Forest, K-Nearest Neighbors (KNN), XGBoost, and Logistic Regression. These models have undergone training and …

The Future Of Smart Transport Technologies: Examining Dubai's Technological Readiness Levels (Trls) To Adopt New Smart Transport Technologies, Hamad Omran Alshizawi

Theses

This research aims to understand what Dubai is willing to do and to provide in terms of smIntelligent Transportation Systems with emphasis on capacity optimization of traffic and understanding TRLs and absorption capacity for AI in Intelligent Transportation Systems Traffic Prediction and Control Systems. The research is important in the context of the concept of a smart city for Dubai and the argument that perfect for the object of examination – transport – can and should integrate new technologies easily into the existing context. Drawing from a population of smart city literature development, traffic and Smart technology, the present study …

Examining Regulatory And Social Process Traits Associated With Experiences Of Shared Decision Making, Megan Kelly

Theses

Decision-making is an important part of healthcare. In recent years, providers have started to use shared decision-making (SDM) with consumers, wherein provider and consumer reach a decision together. Personal characteristics common to Attention-Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), such as emotion dysregulation, impulsivity, and difficulties with social communication skills may impact SDM. Self-efficacy was hypothesized to mediate this relationship, as it has been described as an integral aspect of SDM. This study utilized a sample of 141 undergraduate college students. We found that emotion regulation predicted confidence in SDM, as well as differences in how individuals with …

High Heat Flux Dissipation Techniques Using Enhancement Structures And Subcooled Boiling Chamber For High Performance Computing Applications, Maharshi Y. Shukla

Theses

With a rising need for high-performance computing in data centers, enhanced heat dissipation from microprocessors becomes critical for maintaining their surface temperature in a compact setting. While air cooling has been sufficient until now, liquid cooling proves to be superior in its heat dissipation capabilities. The present work investigates enhancing liquid cooling with boiling and enhanced boiling structures in a novel subcooled boiling chamber. The single-phase forced convection heat transfer is first studied by enhancing the heat transfer performance (CHF and HTC) by more than 50 % with the injection of air bubbles at the heater surface. A self-sustaining method …

Adaptive Parameter Tuning For Robust Event-Based Slam In Diverse Scenarios, Saber Muawiyah Sakhrieh

Theses

In the ever-changing field of contemporary robotics, Visual Simultaneous Localization and Mapping (V-SLAM) stands as a crucial technology, facilitating navigation and mapping in various environments. While traditional V-SLAM approaches excel in static environments, the need for their adaptation to handle dynamic and realistic scenes is becoming increasingly apparent. This thesis delves into the advancements within the V-SLAM field, with a focus on enhancing its adaptability and performance in dynamic and challenging conditions. Initially, a comprehensive review of V-SLAM methods in the literature is presented in this thesis, offering an in-depth examination of current cutting-edge techniques, their strengths, weaknesses, and prospects …

A Study Of Gate Valve Supply Chain And Life Cycle Impacts, Saud Bindarwish

Theses

and sustainable water supplies depend on water infrastructure. However, old infrastructure, especially valves that leak and break, can cause significant water loss, economic strain, and environmental damage. This study explores best choice of gate valves to use while replacing defected existing gate valve in the networks by examining gate valve supply chains and their life cycle consequences. Traditional gate valve supply chains are lengthy and complicated. Extracting iron ore and copper destroys habitats and pollutes air and water. Factory processing and production of these materials increases energy use and air/water pollution. Valve shipping, usually overseas, emits lots of greenhouse gases. …

Smart Technology For Enhancing Indoor Air Quality, Abdulaziz Mohammed

Theses

The COP28 emission reduction plan underscores the imperative of transitioning away from fossil fuels to combat climate change. Concurrently, the rapid adoption of Internet of Things technology has emerged as a transformative force in urban governance, offering cities enhanced resilience and operational frameworks through data analytics and real-time monitoring. In response to these trends, the present research focused on leveraging IoT technology to monitor indoor air quality within a “restaurant A” in an urban area in Dubai. Employing advanced data analytics and smart sensor technologies, particularly LoRa, the project aimed to analyze and monitor air quality parameters. Disposing the sensor …

Decentralisation Of Drone Authentication Within Iod Networks., Jarryd Tayler Brits

Theses

The applications of drones have become increasingly more versatile, with their popularity also increasing rapidly in the last decade. These applications span from entertainment within civilian markets to more military-based applications, including private security firms. However, with this rise in use, the security risks involved have also increased drastically, predominantly in a drone’s lack of ability to authenticate surrounding drones efficiently and securely without the aid of a third party. Although there have been copious amounts of research to support drone authentication, they predominantly rely on a single source of truth, such as a ground station server (GCS), which presents …

Unraveling The Role Of Asymmetry In Structural Porous Media On The Growth Of Fluid Fingers, Amir Ibrahim

Theses

Instabilities at fluid-fluid interfaces are ubiquitous in porous media, even at small flow rates. The growth of fluid fingers during fluid-fluid immiscible displacement in a porous medium results in partial saturation of the medium, and inefficiency in displacement has a tremendous economic impact on oil recovery, chemical reactors, and water filtration industries. In this study, we demonstrate that an inherent asymmetry in the structure of a porous medium controls the development of fluid fingers due to instabilities at fluid interfaces. We construct a 2D porous medium consisting of a matrix of triangles using soft lithography to investigate air displacement by …

Utilization And Justification Of Generative Ai Technologies For Schematic Architectural Design, Aaric Celeste

Theses

Today, architecture is heavily assisted by computer programs. As technology advances, these programs will be more impactful in the design space and will become more inseparable as a result. It is nearly certain that architectural design will no longer be as time-consuming and reiterative as it is today. Computer software and AI-assisted tools will be able to interpret information and produce practical designs that architects otherwise couldn’t. It may seem futuristic and a not-in-our-lifetime phenomenon, but it in fact already exists today. Algorithms are already developed to assist and in some cases take over design work. This thesis discovered existing …

Exploring The Positive Impact Of Emotionally Designed Furniture On Alleviating Negative Symptoms In Individuals With Complex Post-Traumatic Stress Disorder (C-Ptsd): A Case Study Of Chinese Families Influenced By Traditional Confucian Culture., Guangxin Zhang

Theses

This study aims to explore whether emotionally designed furniture has a positive impact on alleviating negative symptoms in individuals with Complex Post-Traumatic Stress Disorder (C-PTSD). Through a combination of literature review and empirical research, the characteristics of C-PTSD individuals and their common negative symptoms, including anxiety, depression, fatigue, etc., were first reviewed and analyzed. Then, the hypothesis of the positive impact of emotionally designed furniture on individuals with C-PTSD was proposed. The study further explores how emotionally designed furniture enhances environmental comfort and fosters emotional connections in personal spaces to provide psychological support and alleviate symptoms in individuals with C-PTSD. …

Autowaze: Automated, Real-Time, And Accurate Traffic Analytics, Vijay Bajracharya

Theses

A key factor leading to the inefficiency of transportation systems is the lack of real-time, fine-grained traffic analytics. An average motorist in the United States spends a significant amount of time looking for parking spots during their daily commute. Existing systems for traffic analytics are either not scal- able to large metropolitan areas or require a human-in-the-loop. This project focuses on automating the detection of fine-grained traffic analytics. Lever- aging on-board stereo cameras, Autowaze utilizes a crowd-sourced strategy to take time-windowed snapshots of the road containing 3D map points of the environment. These snapshots are used to extract changes in …