Digital Commons Network^™

Barriers To Mental Health Access Among Immigrant Populations In The U.S., Cecilia Menzinger

Capstones

No abstract provided.

Mental Health In Adult Oncology Patients, Jenna Pope

Capstones

Adults with cancer suffer from mental challenges that frequently go under diagnosed and under treated (Fernando et al., 2023). This can lead to lower quality of life, resulting in reduced adherence to treatment, more frequent hospital stays, increased healthcare costs, and increased mortality rates (Matthews et al., 2025). There are currently no policies on mental health screening for adult oncology patients at every outpatient appointment. By consistently utilizing standardized screening tools such as the PHQ-9 and GAD-7 during all oncology appointments, this can close the gap in policy to address mental health needs of these individuals. It is vital to …

The Heroine's Journey: Together We Rise A Comparative Analysis Of The Forgotten Beasts Of Eld And When Women Were Dragons, Kirsten Mann

English

This thesis examines isolation, solitude, and the search for community in The Forgotten Beasts of Eld (1974) by Patricia A. McKillip and When Women Were Dragons (2022) by Kelly Barnhill through the lens of Maureen Murdock’s The Heroine’s Journey (1990). While Joseph Campbell’s Hero with a Thousand Faces (1949) has long shaped critical understandings of narrative transformation, its masculine focus leaves the solitary heroine’s experience underexplored. Murdock’s framework reframes the journey as one of healing the split between the masculine and feminine within both the individual and the culture.

Sybel and Alex, the heroines of these two novels, begin in …

Asymptote, Aybuke Yilmazer

Theses

Asymptote is a short film that is an expression of mankind’s emotional consumption through confusing love with sex. This film is a frame-by-frame hand-drawn animation that combines digital and analog techniques. It was produced between August 2024 and April 2025, and its music was re-produced in August 2025. This paper is a written declaration of the motives and intentions of the director, Aybuke Yilmazer, in making this film, and analyzes the filmmaking process. The text of the thesis is in third person except for the self-evaluation section.

Exploring The Relationship Between Social Media And Anxiety In Deaf Community Students: A Mixed-Methods Approach., Gigi Zheng

Theses

The mental health of Deaf individuals, particularly in relation to social media engagement, is an understudied area amid growing global concerns about anxiety disorders. Deaf individuals face unique challenges, including communication barriers, social isolation, and stigma, all of which can heighten anxiety levels. Although social media offers valuable opportunities for connection and self-expression, it may also amplify stress and feelings of inadequacy when accessibility barriers persist. This mixed-methods study examined anxiety among Deaf college students and explored the cultural validity of two widely used anxiety measures—the State-Trait Anxiety Inventory (STAI) and the Beck Anxiety Inventory (BAI). Quantitative data were collected …

These Yellow Stars Of Ours, Vinh Hong Nguyen

Theses

These Yellow Stars of Ours is an experimental documentary that traces the intertwined histories of Thaun and Nam Nguyen as they flee war-torn Vietnam, fall in love, and build a life in Western New York. Through their accounts and those of their two sons, the film explores the complexities of generational trauma and the ongoing experience of bicultural straddling—the negotiation between inherited Vietnamese identity and the shaping influence of an American upbringing. The project examines how trauma, memory, and cultural displacement circulate across generations, shaping identity in both visible and invisible ways. Methodologically, the film is structured around the conceptual …

Early Diabetes Prediction Using Machine Learning: A Comparative Study Of Classification Models, Ahmed Abdelqadir Bawazir

Theses

The current dissertation investigates the application of machine learning in diabetes prediction at early stages through a comparison of the performances of three classification models, including Logistic Regression, Decision Tree, and Random Forest. Inspired by the increased and spread cases of diabetes worldwide, the research objective is to facilitate early diagnosis by providing interpretable and accurate predictive models. Based on Pima Indians Diabetes Dataset containing 768 clinical records, the research implemented data preprocessing including KNN imputation and outlier processing, feature scaling, and formation of interaction features. Quantitative and comparative approach was made to train and test the models based on …

Machine Learning Approaches For Predicting And Preventing Vehicle Theft, Hamad Almutawa

Theses

This study develops a data-driven framework for predicting vehicle theft using machine-learning techniques applied to a comprehensive crime dataset containing demographic, spatial ,and operational policing variables. The dataset, sourced from publicly available crime records, included 9,712 cases and 30 variables, with minimal missing data and balanced class distribution. After performing extensive preprocessing—including outlier analysis, missing-value imputation, categorical encoding, feature selection, and correlation testing—four supervised classification models were implemented: Logistic Regression, Random Forest, Support Vector Machine, and a Neural Network. Bivariate statistical tests, including Chi-square and Mann–Whitney U, revealed significant relationships between theft occurrence and factors such as crime area, luxury …

Practice?, Pei Chen

Theses

3D animation is a combination of art and technique. Art serves to convey your perspective, express beauty, tell stories, and more. However, to accomplish these goals, we need solid technical support. Only by paying attention to both, can we achieve excellent results. The title of this film is “Practice?”, which is a deliberate pun. On one hand, "practice" refers to the martial arts training sequences of the character, during which his master provides guidance, intervenes in his movements, and progressively increases the difficulty. On the other hand, "practice" also symbolizes my own artistic and technical experimentation—exploring and refining skills in …

Modeling The Effects Of Shed Target Receptors On The Efficacy Of Cancer Immunotherapy Agents, Bridget M. Torsey

Theses

Cancer cells often shed receptors targeted by immunotherapies. Shed receptors can reduce drug efficacy by binding to free drug, preventing its binding to membrane-bound receptors. The goal of this dissertation is to investigate the effects of shed targets on the efficacy of cancer immunotherapies. First, we study liquid tumors by extending a PK/PD model to include receptor shedding, drug-induced enhancement of shedding, drug binding to shed receptors, and drug-induced tumor lysis. We use our model to elucidate the effect of shed target receptors on the efficacy of immunotherapies through uncertainty and sensitivity analyses. Our findings support the claim that the …

Symbiotic Furniture Design: A Single Chair Integrating Epiphytes With Taiwanese Window Grille Structures, Kuan-Wen Lin

Theses

Plants have been integrated into residential and interior environments for centuries, yet research on the psychological effects and interactive potential of plants in furniture design is still relatively limited. Traditional planting methods, such as individual potted plants or large green walls, often require additional floor or wall space, which is not ideal for environments with limited living space. Therefore, this study investigates how plants can be integrated into furniture design to enhance the effect of interior greenery and user engagement, and to redefine the relationship between furniture and the natural environment. This research explores a furniture design that incorporates epiphytic …

Defaking Deepfakes: Designing And Evaluating Ai-Powered Digital Media, Saniat Javid Sohrawardi

Theses

The rapid spread of generative AI has revolutionized media production, creating new challenges for information integrity as convincing deepfakes proliferate. Journalists play a critical role in upholding credible public information, yet existing deepfake detection technologies often overlook their specific workflows and requirements. This dissertation addresses these needs by identifying what journalists require from detection tools and evaluating usability in realistic scenarios through the following works: Journalists' Needs and Tool Design: Through qualitative user studies, we uncover journalists' preferences for tools that provide transparent, explainable evidence and context-aware analysis integrated into news verification routines. These insights drive the design of DeFake, …

Physics Meets Data: Merging Physics-Based Methods With Deep Learning To Model Complex Systems, Maryam Toloubidokhti

Theses

Accurate modeling of complex systems is crucial in domains such as healthcare, where personalized diagnosis and treatment planning are essential. Traditional physics-based models provide structured, theoretically grounded insights but are often computationally intensive and constrained by simplified assumptions that limit adaptability to patient-specific conditions. In contrast, data-driven models are computationally efficient and capable of capturing complex patterns, yet they often lack interpretability and fail to incorporate essential physical principles, reducing robustness and generalization. This disconnect between mechanistic understanding and computational practicality presents significant challenges in critical applications such as healthcare, where both physical accuracy and real-time performance are vital. To …

The Role Of Technology In Modernizing Prison Management Systems, Essa Anwahi

Theses

This thesis examines the role of technology in modernizing prison management systems and improving operational efficiency, security, and decision-making. It explores how digital technologies and data analytics can address challenges in traditional prison management, such as inefficient processes and limited data utilization. The study highlights the potential of technology-driven solutions to enhance system performance and support more effective management practices within correctional facilities.

Achilles, Sreelekha Samala

Theses

ACHILLES is a speculative design project and conceptual artifact. It is not intended to function as a medically certified or biomechanically operational prosthetic arm. Instead, it operates within the realm of design research, using visual realism and luxury aesthetics to explore how assistive technologies could be perceived differently in cultural, emotional, and commercial contexts. Using 3D software to experiment with color, pattern, and texture, I designed a realistic mockup to demonstrate how Achilles could appear in a high-end commercial setting. Instead of animating the model, I focused on camera motion to highlight the prosthetic from multiple angles, emphasizing its sculptural …

Predicting Employee Attrition With Machine Learning: Data-Driven Strategies For Enhancingworkforce Retention, Ali Almheiri

Theses

In this research, the dual prediction and prescription model is developed and validated so that this model can not only predict employee turnover risk, but it also proposes the appropriate retention interventions, which apply across industries. On the basis of the IBM HR Analytics Attrition dataset (n=1,470), we preprocessed demography, job and satisfaction variables and trained three machine-learning classifiers, Random Forest, Logistic Regression and XGBoost to predict voluntary turnover. XGBoost model recorded the best discrimination (AUC=0.87), sensitivity (0.76), and specificity (0.81), which signifies strong predictive power. Analysis of feature-importance was conclusive with time, rate of frequent business travel and compensation …

Potential And Low-Cost Football Talents For Uae Clubs Based On Data-Driven Analysis, Rashid Alqemzi

Theses

The use of data analytics in professional football has changed the way clubs view, value and invest in players. Meanwhile, elite European teams have consistently exploited the data-driven strategies that offer them a competitive edge, but in up-and-coming football markets, such as the UAE Pro League, nepotism has remained strong, with reputation-based and agentdriven recruitment being the transformation choice of even the biggest profile moves. This work explores whether predictive analytics can discover hidden high-quality football talent from ”hotbeds” of talent including Brazil and Argentina, in a way that matches the economic capabilities of clubs in the UAE, given the …

Investigating The Effect Of Build Direction On Mechanical Properties In Pellet-Based 3d Printing, Yahya Mohammed

Theses

This study investigates the influence of build orientation on the mechanical performance of Polylactic Acid (PLA) components fabricated using Fused Granular Fabrication (FGF), a pellet-based additive manufacturing method, and benchmarks these results against Fused Deposition Modeling (FDM). Although orientation-dependent mechanical behavior has been widely studied in filament-based extrusion, there remains a critical gap in understanding how these effects appeared in pellet-based fabrication. To address this gap, PLA tensile and compression specimens were fabricated using both FGF and FDM under identical geometries, processing parameters, and preparation procedures, ensuring that any differences in performance arise solely from the manufacturing method and build …

Predicting Residential Real Estate Prices In Dubai Using Integrated Data Analytics: A Machine Learning Approach, Mohammad Nasser

Theses

Dubai’s rapidly evolving real estate market attracts substantial global investment yet remains characterized by information asymmetry, pricing volatility, and fragmented data sources. This study examines how integrated data analytics and ensemble machine learning can be used not primarily for precise price prediction, but rather to identify and quantify the key behavioral and transactional drivers of residential property prices in Dubai. A unified dataset was constructed by integrating over 100,000 residential property transactions from the Dubai Land Department with macroeconomic indicators, web-scraped listing attributes, and sentiment measures derived from online reviews and social media discussions. Supervised learning models including Linear Regression, …

Ai-Powered Multimodal Tour Guide: Enhancing Cultural Tourism With Image Recognition, And Personalized Storytelling, Abdulla Ibrahim Aljawi

Theses

This thesis presents the design and evaluation of an AI-powered multimodal tour guide that uses image recognition and personalised storytelling to enhance cultural heritage experiences. Traditional approaches to learning about monuments rely on static plaques, generic tour content, or manual web searches, which limit personalisation, interactivity, and accessibility. To address these limitations, the study implemented a “Multimodal Monument Explorer” that allows users to upload a photo of a landmark or describe it in natural language and then receive rich, context-aware explanations in both text and audio form. The system integrates a persistent vector database of monument images, OpenCLIP-based visual embeddings, …

The Klik Chair - Designed To Move, Built To Last, Neeraj Sugumaran Menon

Theses

For the modern individual who moves housing frequently, buying furniture has become an increasingly tedious and frustrating process. Traditional furniture often presents challenges due to its bulk, weight, and complex assembly requirements, making it difficult to transport and reassemble when moving to a new living space. As a result, the true value of a piece of furniture is no longer determined solely by its price tag or aesthetic appeal but by its ability to adapt to a nomadic lifestyle. Additionally, furniture that holds long-term sentimental or functional value has become even more significant in an era where disposability is routine. …

Integrating Climate And Geospatial Features Into Machine Learning Models, Abdulaziz Ahmed Aljaziri

Theses

This thesis addresses a significant gap in real estate valuation models by investigating the economic impact of localized climate conditions and granular geospatial amenities. An abstract summarizes the following: - The main themes, ideas or areas of theory being investigated: This research investigates the integration of localized climate conditions and granular geospatial amenities into machine learning (ML) frameworks for residential real estate valuation. - The background and context of the research: In dynamic urban markets like Dubai, traditional valuation models often rely on broad location labels and structural attributes, overlooking the tangible economic impact of environmental comfort and micro-climates in …

Multilingual Identity Document Information Extraction Via Dynamic Templates And Hybrid Ocr, Khalifa Rashed

Theses

The thesis introduces a unified, automated document intelligence system that can in-house resolve significant issues in identity authentication and data OCR by two complementary technological components: advanced facial biometrics and powerful multilingual optical character recognition. The system directly addresses the inefficiencies of the slow speed of document processing by humans, human error and high cost of operation by offering a single pipeline for verifying the identity of the user via facial comparison and digitizing textual data contained in documents. The former module adopts an advanced face verification pipeline. It starts with an image pre-processing step, which improves the quality of …

Predicting Athlete Performance Using Machine Learning Models, Mohammad Abdulbasit Mohammad Alabdulla

Theses

The purpose of this research is to develop and assess multi-modal machine learning for robust performance analysis to predict athletic performance and evaluate injury risk. The study employed Data Analytics approach, where composite features, i.e., Training Stress and Recovery Score,were modelled to characterize training-recovery correlations. It had four different regression models (MLR, RFR, SVR, DNN) and four different classification models (Logistic Regression, RFC, SVM, DNN). DNN exhibited an increased degree of effectiveness in the forecasting Synthetic Performance Score (R2 =0.9998). Notably, the Random Forest Classifier (RFC) turned out to be the most valid predictor of injuries risk (F1-Score 0.7736; AUC-ROC …

Security Vulnerabilities In Cloud Storage: A Comparative Study Of Google Drive, Dropbox, And Onedrive, Sultan Majid Alshamsi

Theses

In recent years, use of internet has increased manifold. People have started creating more data, and instead of saving it locally, people have started preferring storing it “online”. Companies are also following the same path to maintain accessibility and availability of their data. Thus, data has become a central part of our lives. People, companies, and institutions rely heavily on cloud storage solutions these days for managing their data. Some of the main cloud storage solution are Google Drive, Dropbox, and OneDrive. These are sophisticated solutions developed by tech giants, and general expectation of the public is that these solutions …

Biodegradation Of Common Post-Consumer Plastic, Laura Krebs

Theses

Plastic waste is widespread throughout the Laurentian Great Lakes watershed. During environmental exposure, plastic undergoes abiotic and biotic degradation. The presence of novel plastic substrates coupled with rapid microbial turnover may lead to selection for or evolution of metabolic pathways and enzymes with enhanced biodegradation capabilities. This study investigated the biodegradation potential of bacteria isolated from debris accumulation hotspots - stormwater retention ponds, storm drains, and tributaries - in the Lake Ontario watershed within Rochester, New York. Bacterial isolates were exposed to commonly littered plastics for 240 d: cellulose acetate from smoked cigarette filters, high-density polyethylene from takeout shopping bags, …

Analyzing Airline Customer Experience Challenges And Their Impact On Dubai's Tourism Sector, Suhail Alfalasi

Theses

The paper explores whether there is a connection between operational performance, customer sentiment, and digital administrative complexity among major regional Middle Eastern airlines, such as Flag Carriers (e.g., Emirates) and Low-Cost carriers (LCCs) (e.g., Air Arabia). With the use of a highly detailed dataset of customer review and operations data, the study proves that a large service paradox is present in which, despite the high Net Promoter Scores (NPS: 48.004) of the carriers, which are positively reinforced by delivering world-class soft products, the loyalty is constantly disrupted by low-frequency but high-severe operational delays (Delay_Minutes). Since it has been analyzed that …

Ai-Driven Cyber Threat Detection, Humaid Thani Almheiri

Theses

Bycreating an AI-driven method using deep learning and statistical analysis tools, this study seeks to fill important security holes in conventional intrusion detection systems. Current signature-based systems miss new and complex cyberattacks, which have significant financial and operational consequences for companies. The suggested approach detects unusual network activity in real-time by combining statistical analysis with long short-term memory networks (LSTMs), convolutional neural networks (CNNs), and statistical analysis. This study will create and test hybrid models that can identify both known and zero-day threats while reducing false positives using publicly accessible datasets like UNSW-NB15, CIC-IDS2017, and NSL-KDD. Expected results are a …

Supervised Learning For Predicting Mental Health And Burnout In Healthcare Workers, Afra Alfalasi

Theses

This study aims to predict and analyze burnout among healthcare workers using supervised machine learning techniques and Exploratory Data Analysis (EDA). Leveraging the Healthcare Workforce Mental Health Dataset, the research identifies key demographic, occupational, and psychological factors most strongly associated with burnout. The methodology involves data preprocessing, feature selection, and model training using algorithms such as logistic regression, decision trees, random forests, and gradient boosting. Model performance will be evaluated through standard metrics, including accuracy, precision, recall, and ROC-AUC. The expected outcome is a predictive framework that highlights high-impact burnout predictors and generates actionable insights to support early intervention and …

Beyond The Surface: Exploring The Experiences Of Black Female Athletes At Power 4 Institutions, Michonné Leatrice Gamble-Rivers

Electronic Theses and Dissertations

Black female athletes, have a long history of fighting for visibility and inclusion. They are celebrated and hyper-visible as performers on the court yet deemed invisible in the institutional decision making that shapes their holistic development and success. This Dissertation in Practice (DiP) challenges this structural problem looking to amplify voices that have been historically silenced by systems that reduce these individuals to mere athletic capital.

Beginning with Manuscript I, this three-manuscript dissertation is built on a conceptual framework anchored in Womanist Theory, Intersectionality, and Athletic Identity, providing the necessary critical lens to investigate challenges like double jeopardy and limiting …