Digital Commons Network^™

Study Of The Extension Of Cavities In Jebel Hafeet By Implementing Geophysical Methods, Mai Rashed Alkaabi

Theses

Subsurface cavities pose challenges to the buildings and their stability, leading to ground instability and subsidence. In Al Ain City, UAE, particularly in Jebel Hafeet, cavities within carbonate formations and sedimentary rocks present risks to infrastructure and urban development. This study employs Electrical Resistivity Tomography (ERT) and Gravity Surveys to detect, locate, and determine the depth of these cavities, enhancing geological understanding and geohazard assessment. The ERT survey, using a pole-dipole array, was conducted along eight lines to identify subsurface anomalies. It revealed high-resistivity anomalies (> 45 Ω·m), indicative of air-filled cavities, and low-resistivity zones (< 6 Ω·m), corresponding to water-saturated or clay-rich deposits. The ERT survey detected resistivity variations, highlighting anomalies ranging from 45 to 120 Ω·m at depths between 1 m and 17 m. The gravity survey, conducted at 28 stations, detected low-density anomalies, which aligned with high-resistivity ERT zones, confirming subsurface cavities at depths between 10 m and 220 m (below ground level). Five 3D gravity inversion models visualized density variations, revealing cavities at different depths for the models from 0 m to 195 m (a.s.l). The integration of ERT and gravity methods significantly improved cavity detection accuracy, demonstrating a strong correlation between low-density gravity anomalies and high-resistivity features. This study recommends increasing gravity station density, and avoiding heavy infrastructure in cavity-prone areas. The findings contribute to the geological understanding of Jebel Hafeet, providing insights for sustainable urban planning, risk mitigation, and infrastructure safety in Al Ain City.

Study Of Falāj Pathways And Their Unknown Extension In Al Ain City Using Geophysical Methods, Saud Mohammed Alsenaani

Theses

Historically, the city of Al Ain has relied on its Falāj systems as historic water resources for freshwater, which is vital for drinking and irrigating its oases and essential for supporting life in the region for centuries, providing the foundation for communities and farming. The remarkable rainfall in 2024 uncovered several hidden ancient Falāj systems and newly enlarged versions of previously recorded ones, highlighting the importance of ongoing research for their preservation. This research project aims to examine the current Falāj systems in Al Ain, particularly Falāj Mezyad, using geophysical methods to identify uncharted extensions and to examine current Falāj …

خصوصيات التقاضي في منازعات العمل الفردية وفق المرسوم بقانون اتحادي رقم (33) لسنة 2021 وتعديلاته, علي مبارك البريكي

Theses

The Specificities of Litigation in Individual Labor Disputes According to Federal Decree-Law No. (33) of 2021 and its Amendments

Modern legislations are increasingly adopting alternative methods for dispute resolution, introducing new mechanisms to reduce reliance on the courts while preserving the parties' right to litigation. Among these disputes, labour disputes—whether individual or collective.

Despite the legislator's adoption of alternative dispute resolution mechanisms, the unique nature of labour disputes has not been overlooked. These disputes require special protection for the worker, who is considered the weaker party in the contractual relationship. Based on this principle, the legislator has introduced modern mechanisms …

The Relationship Between Perceived Stress, Rumination, And Sleep Quality Among University Students, Aljazeeya Almansoori

Theses

Sleep is a crucial physiological function that underpins human health and wellbeing, profoundly affecting cognitive abilities, emotional stability, and the overall quality of life. Disruptions in sleep quality and quantity are commonly associated with increased perceived stress and rumination. This study aimed to investigate the correlations among perceived stress, rumination, and sleep quality in university students in the UAE, while also considering demographic factors such as age, gender, marital status, and educational level. It was hypothesized that higher levels of perceived stress and rumination would be associated with lower sleep quality. The study employed a cross-sectional design, involving a sample …

Culex Quinquefasciatus Mosquitoes In Abu Dhabi Emirate: Assessing Deltamethrin Insecticide Resistance And Associated Microbial Communities, Amgdsayed Ismat Ali

Theses

Culex quinquefasciatus is a major vector of West Nile virus, lymphatic filariasis, and arboviruses, which represent public health risk. Widespread application of pyrethroid insecticides has increased resistance in mosquito populations threatening the effectiveness of control strategies. This study aims to (1) assess deltamethrin resistance in Culex quinquefasciatus populations across the Abu Dhabi Emirate, (2) characterize the microbial communities associated with these mosquitoes.

Mosquitoes from sites around the Abu Dhabi Emirate were collected and genomic DNA extracted for molecular analysis. PCR and allele-specific primers were used to detect knockdown resistance (kdr) mutations in the sodium channel gene, classifying mosquitoes as susceptible …

The Impact Of Rubric-Based Feedback On Efl Writing Proficiency: Exploring Revision Skills And Learning Transfer, Ahmed Abdelraheem Elyan

Theses

This study explores how rubric-based feedback influences the writing development of English as a Foreign Language (EFL) learners, with a particular focus on their revision practices, learning transfer, and the challenges they face with cognitive overload. The research was carried out in a high school context in the United Arab Emirates (UAE), aiming to understand the real impact of structured feedback on students’ writing performance.

Twenty Arabic-speaking students participated in the study, completing four essay writing tasks over eight weeks. These included a pre-test, two feedback-supported drafts, and a post-test. Their essays were assessed using an analytic rubric designed to …

Construction Of Stock Portfolios By Machine Learning Methods, Alfan Gehad Abulehia

Theses

We study the theory and application of two machine learning (ML) algorithms: Long-Short Term Memory Network (LSTM) and Random Forest. The study begins by providing an overview of mathematical foundation, highlighting the significance of mathematics in machine learning. We study and explain the mathematical details involved in these two algorithms. We also study closely related subjects which include but not limited to gradient descent, automatic differentiation, and recurrent neural network. The main ideas behind these topics form the foundation of any ML algorithms.

As an application of the ML algorithms, we focus on the U.S. stock market. We build stock …

A Bayesian Belief Networks Approach To Prioritize Road Safety Mitigation Measures For Eco-Mobility Modes, Fatmah Mohamed Alyammahi

Theses

This study presents an innovative decision-making approach that enables the prioritization of road safety measures for eco-mobility users—pedestrians, cyclists and light-electric micromobility riders—in Abu Dhabi. The analysis uses 2032 eco-mobility crash records (1016 pedestrian, 567 bicycle, 449 e-scooter) from 2020-2023 supplied by Abu Dhabi Police and the Department of Municipalities and Transport. A supervised Bayesian Belief Network (BBN) was constructed around six empirically estimated variables: visibility, predictability, road curvature, obstructions, lighting and speed limit. Maximum-likelihood conditional-probability tables were derived from the cleaned dataset; Beta priors were applied only where cell counts were sparse. Ten conventional machine-learning models—including Random Forest, Gradient …

Continuous Professional Development (Cpd) For Inclusive Education In Uae Schools: Current Practices And In-Service Teachers’ Preferences, Hafsa Khaled Aishan

Theses

Professional development serves as a driving force in empowering teachers within inclusive education settings. The purpose of this study was to investigate the perspectives of both general and special education teachers about the effectiveness of currently implemented professional development practices. Data were collected using explanatory mixed-methods design, which included a questionnaire and semi-structured interviews. This method was utilized to improve the depth of research through the integration of quantitative and qualitative data. The combination of these two methods strengthens validity, reduces bias, and increases reliability. Non-probabilistic purposive sampling method was employed to collect the data as a total of 115 …

Collaborative Network Traffic Management Strategies Using Distributed Reinforcement Learning And Large Language Models, Saeed Rashed Alkuwaiti

Theses

The focus of this research is to explore collaborative network traffic management strategies using the Distributed Reinforcement Learning (DRL) and Large Language Models (LLMs) approaches. It emphasizes exploring a new tool for addressing network traffic by utilizing Distributed Reinforcement Learning (DRL) and Large Language Models (LLMs). This is achieved by utilizing self-organizing and self-directing techniques to optimize the network performance. Using the NF-TON-IOT dataset, various classifiers such as Random Forest, AdaBoost, C4. 5, Multi-Layer Perceptron (MLP), and SVM with an RBF kernel were tested for traffic classification and intrusion detection. Research recommends that DRL optimizes the complexity of the network …

Enhancing Cyber Threat Detection In Tweets Using Diffusion Models And Convolutional Neural Networks, Amer Abdulfattah Mohamad Abdulrahman

Theses

This study looks at how two advanced methods, DDPM-v4 and uViT, work with CNN models to find cyber threats from X data. Two datasets were used—one dataset taken from GitHub and another dataset created using the X Developer API. The dataset created had two sizes: small with 500 rows and larger with 2500 rows. The study compares models with diffusion techniques (DDPM-v4 and uViT) and without diffusion techniques. The results show that DDPM-v4 performed the best overall, with the highest accuracy and F1 score. For example, on the X API dataset with 2500 rows, DDPM achieved 98.20% accuracy. The uViT …

A High-Efficiency Ldo Regulator With Adaptive Psrr And Transient Enhancements, Daniel Zeznick

Theses

Reliable power delivery is essential for all computing systems, particularly those operating with limited or constrained energy sources, such as batteries. Power management circuits must provide energy efficiency, stability, and resilience to disturbances to support accurate and consistent system performance. This thesis presents a high-efficiency low-dropout (LDO) regulator featuring adaptive power supply rejection ratio (PSRR) and transient response enhancement techniques. By leveraging adaptive analog design strategies, the proposed regulator dynamically boosts performance at high load currents, maintaining optimal efficiency across the full load range while circumventing key trade-offs inherent to conventional LDO architectures. The design incorporates several novel circuit techniques …

Mapping Accessibility In Dubai: Evaluating Al Wasl And Mirdif Against 20-Minute City Principles And The Dubai 2040 Urban Master Plan, Fatima Mohammed Almulla

Theses

The 15-minute city is a planning concept that aims to give people easy access to daily services such as schools, shops, healthcare, and recreation within a short walk or bike ride. Dubai has adapted this concept into a 20-minute city model under the Dubai 2040 Urban Master Plan. The goal is to reduce car use, improve quality of life, and create connected and sustainable neighborhoods. This study evaluates how well two neighborhoods in Dubai, Al Wasl and Mirdif, match the 20-minute city model. It analyzes three main goals from the Urban Master Plan: having 55% of residents within 800 meters …

Insights Into Covid-19 Dynamics Via The Integration Of Subpopulations, Vaccinations, And Bayesian Calibration In A Semi-Enclosed Community Model Framework, Meghan Rowan Childs

Theses

From the beginning of the COVID-19 pandemic, universities have experienced unique challenges due to their multifaceted nature as a place of education, residence, and employment. Previous work has used mathematical models to explore varying approaches to combating COVID-19 and tailored these models to local contexts, such as hospitals. However, previous work has not broadly incorporated pharmaceutical mitigation strategies into university models. We address this gap in research by integrating subpopulations, vaccines, and COVID-19 variants into a semi-enclosed population model framework. We further improve the quantification of uncertainty in the model parameters by implementing a formal Bayesian model calibration, fusing real-world …

Towards Robust Deep Learning For Medical Imaging With Limited And Noisy Labeled Data, Bidur Khanal

Theses

Deep learning has emerged as a powerful tool in medical imaging, assisting healthcare professionals with several decision-making tasks, such as disease diagnosis, surgical intervention, and treatment planning. Supervised deep learning methods typically require large amounts of high-quality labeled data for training. However, acquiring high-quality labeled data in the medical domain is challenging due to factors such as the high cost of expert annotation and the presence of label noise, often due to inherent user/expert annotation variability. Models trained on limited or noisy labeled data suffer from poor performance due to overfitting, thus reducing their generalizability and trustworthiness for medical applications. …

An Ultra-Low-Power, Area-Efficient All-Analog Trojan With Temporal Power Supply Triggering, Roberto Ramos-Brito

Theses

With the rapid expansion of the Internet of Things and rising concerns over intellectual property protection, hardware security has become increasingly vital—particularly in defending against hardware trojans. While much of the existing research targets digital trojans, analog hardware trojans remain largely unexplored, presenting unique opportunities for developing innovative attack vectors and mitigation strategies. This thesis introduces a novel all-analog temporal trojan that functions entirely within the analog domain. The design incorporates power supply noise detection and charge-accumulator techniques to enable precise control over attack execution and payload delivery. It also leverages novel circuit techniques to reduce power and area overhead, …

Enhancing Pedestrian Safety Around Jacksonville State University: A Gis-Based Perception And Crash Analysis, Husain O. Alegimenlen

Theses

This study uses a Geographic Information Systems (GIS) based approach to assess pedestrian safety around Jacksonville State University (JSU) by combining vehicle crash data with perception surveys from 111 pedestrians and 97 drivers. The research identifies high-risk areas, explores contributing factors, and recommends targeted safety improvements.

A total of 209 geocoded crash records (2021 to 2024) were analyzed using Kernel Density Estimation (KDE) and hotspot analysis in ArcGIS Pro. Crash clusters appeared along Pelham Road North and Mountain Street, marking key vehicular risk zones. Three major pedestrian danger areas were found: (1) Nisbet Street NW and Cardinal Lane NW, (2) …

Flood Risk Assessment In Humanitarian Contexts: A Remote Sensing And Gis Methodology Applied To Nyarugusu Refugee Camp, Tanzania, Carolyne Vincent Mbirika

Theses

Flooding is a global challenge, with effects mostly experienced in developing countries due to insufficient data for effective flood risk assessment and management. Refugee settlements are particularly vulnerable to flooding due to their remote locations, high population density, and temporary shelters, necessitating flood susceptibility mapping to effectively mitigate risks and minimize damage prior to flooding events. This study assessed flood susceptibility in the Nyarugusu refugee camp, Tanzania, through Multi-criteria Decision Analysis (MCDA) and Analytical Hierarchy Process using remote sensing and Geographic Information Systems (GIS) approaches. The flood susceptibility map that resulted from this process categorizes flood-prone areas into three classes: …

From Skepticism To Loyalty: A Whitepaper For Companies On Building Consumer Trust In Digital Marketing, Grace Darcy Pora

Theses

Trust is the foundation of business and works as a dynamic relationship between customers and businesses. As social media continues to evolve as the main way that companies promote and sell their products, trust must align with these marketing efforts. Through the analysis of past research, case studies, and current surveys, data, and trends, the relationship between consumer trust and online advertisements can be examined. Consumer trust online is experiencing a consistent downward trend, where consumers are losing trust in the companies and products they purchase from online. There is a heavy amount of skepticism online with the content that …

Bridging Human Expertise And Ai In Qualitative Research: Understanding Ownership, Trust And Bias In Ai-Assisted Coding, Anoushka Jagadeesh Puranik

Theses

Qualitative research is a multifaceted process involving data collection, transcription, organization, coding, and thematic analysis. As qualitative data analysis (QDA) tools gain popularity, artificial intelligence (AI) is increasingly integrated to automate aspects of this workflow. This study investigates researchers’ QDA practices, their experiences with existing tools, and their perspectives on AI involvement in qualitative research. We introduce ChromaScribe, a prototype QDA tool, and gather feedback to assess whether it addresses the limitations of current tools. Through interviews with 16 qualitative researchers, we examine their preferences for traditional coding, AI-initiated coding, and human-initiated coding, exploring factors such as ownership, trust and …

Scenes Of Self: Redressing Patriarchy Ii, C. Rose Smith

Theses

Drawing together self-portraits and photographic documents, Scenes of Self: Redressing Patriarchy II threads a narrative in black and white on the underpinnings of elitism in US history and culture—a history dating back to the 19th century—of an emerging wealthy economy sustained by the slave market and commodities of its production. A meticulous interpretation of a historicized past eliding with the future, this thesis charts a path toward ancestral recollection to critique the livelihoods of merchants who were also enslavers. This thesis takes up the concept of Afro-surrealism (a movement led by Black artists of the 1970s concerned with the future-past) …

Implementation Of Machine Learning To Predict Cable Failures In Electrical Networks, Sultan Bader Albahri

Theses

Electrical networks are critical infrastructures that power industries, businesses, and households. Among their key components, electrical cables play a vital role in ensuring uninterrupted power distribution. However, cable failures due to aging, environmental factors, mechanical stress, and load imbalances pose significant challenges, leading to outages, financial losses, and reputational damage. Traditional maintenance approaches, which rely on periodic inspections and reactive repairs, have proven inadequate in preventing unexpected failures. In response to this challenge, predictive maintenance using Machine Learning (ML) has emerged as an effective solution. This research focuses on developing an ML-based predictive model to forecast cable failures in Dubai …

Color Constancy In Virtual Environments With Head-Mounted And Flat-Panel Displays Across Different Illuminants And Lightness Levels, Andrea Avendano Martinez

Theses

Virtual reality (VR) is commonly used as a tool for enhancing immersion within virtual environments, with one of its primary goals being to approximate real-world perception as closely as possible. In everyday life, variations in lighting conditions significantly influence how colors are perceived across different times and settings. However, the human visual system compensates for these changes, maintaining relatively stable color perception; a phenomenon known as color constancy. This process is driven by chromatic adaptation, the visual system’s adjustment to changes in illumination. Despite the growing use of VR, little research has explored how color constancy operates in virtual environments …

This Night, Roshni Jayakrishnan Nair

Theses

"This Night" is a 2D animated Graduate Thesis Film. The story centers on a devout elderly woman who receives a vision foreshadowing her departure from life. Guided by this vision, she embarks on a profound journey. In her garden, she plucks a hibiscus and offers it to the deities in her home. As she prays with closed eyes, she envisions her hibiscus offering reaching the temple doors. Recognizing this as her sign to depart, she resolves to set out on her journey to meet the goddess at the temple. Plucking another hibiscus to carry with her, a sudden gust of …

Network-On-Chip Packet Obfuscation And Encoding For Hardware Trojan Mitigation, Sydale John Ayi

Theses

Networks-on-Chip (NoCs) represent a transformative advancement in System-on- Chip (SoC) communication architectures, addressing the scalability and performance limitations of traditional bus-based systems. The increasing reliance on NoCs in modern SoCs has raised security concerns, particularly in untrusted fabrication environments. This thesis investigates the vulnerabilities posed by malicious hardware Trojans and untrusted IP cores, such as reverse engineering, misdirection attacks, and brute-force decryption. To counter these threats, the study introduces a robust security framework leveraging encoding and obfuscation techniques. Hamming codes are employed to detect and correct errors, ensuring data integrity and correcting misdirection attacks. Discrepancies between codewords and data words …

Implementation And Dissemination Of The 'About Eating' Program: Evaluating Participant Engagement, Usability, And Module Interest, Justin Konrad Walker

Theses

Abstract Background: Online nutrition education can improve food choices among underserved populations. The About Eating New York (AENY) program is a web-based, self-paced series of modules designed to enhance nutritional literacy, resource management, and confidence in healthy eating. Leveraging dissemination and implementation (D&I) science, AE partnered with community organizations across New York’s ten fiscal regions to extend its reach. Methods: This study analyzed secondary data from the AENY dissemination effort. Participants were recruited via social media and community organizations. Pre- and post-program surveys and end-of-lesson surveys assessed demographics, engagement, and perceptions of usability. Quantitative analyses included descriptive statistics, t-tests, ANOVAs, …

Beyond The Food: A Scoping Review Of Avoidant/Restrictive Food Intake Disorder (Arfid)'S Comorbidities, Nutrition, And Growth Outcomes, Emily Szewczyk

Theses

Objective A scoping review design was chosen for this study to appropriately assess and understand the knowledge on ARFID and to identify psychological or developmental comorbidities, growth outcomes, and nutrient deficiencies and/or excesses in children and adolescents. Introduction Avoidant/Restrictive Food Intake Disorder (ARFID) is a relatively new eating disorder, characterized by the DSM-5 in 2013.1 Individuals with ARFID exhibit selective eating due to lack of interest in eating food, sensory sensitivity, or a fear of possible vomiting or choking.2 The malnutrition seen in individuals with ARFID can result in physical health complications including weight loss, malnutrition, growth delay, decreased bone …

Energy-Efficient Distributed Algorithms: A Survey, Visualizations, And New Results In Radio Networks, Dominick Banasik

Theses

Distributed algorithms have been studied for decades, with a particular focus on round and message complexities. Recent works have presented energy-efficient distributed algorithms, where nodes are allowed to sleep, sacrificing the ability to communicate, and the goal is to minimize the amount of time nodes spend in an awake state. This thesis further explores the area and can broadly be divided into three parts. In the first part of this thesis, we provide a literature survey of existing works. Several fundamental graph problems have been studied in this context. Our survey compares the known results from different models, highlights the …

On Studying Transformer Networks For Volume-To-Surface Registration Of Inhomogeneous Soft Bodies For Liver Laparoscopy, Michael Adam Young

Theses

An important practical consideration in laparoscopic liver surgery is the limited visual information relative to open surgery. In laparoscopic interventions, the surgeon’s view of the liver surface is generally limited to the scene provided by a single scope with a narrow field-of-view. This limits the ability to navigate towards internal lesions previously identified through pre-procedural imaging. Surgical navigation during laparoscopy could be enhanced by registration of full preoperative liver models derived from pre-procedural imaging scans onto the partial laparoscopic view of the liver. This entails both a rigid registration to match the liver surface view to the preoperative volume, as …

Interspecific Sources Of Resistance For Neisseria Gonorrhoeae: Investigating Horizontally Transferred Antimicrobial Resistance Markers, Makenna Swartz

Theses

Antibiotic resistance is a growing public health crisis, limiting treatment options and increasing the burden of infectious diseases. Bacteria can rapidly gain resistance through mutations and horizontal gene transfer (HGT). Understanding these mechanisms is critical for developing strategies to mitigate resistance and preserve antibiotic efficiency. Neisseria gonorrhoeae, the causative agent of gonorrhea, has developed resistance to multiple antibiotics, and has only one remaining treatment option. Commensal species are constantly exposed to antibiotics in humans, and over time acquire resistant mutations that then transfer to pathogenic species through HGT. Investigating these exchanges can provide insight into how resistance evolves and spreads …