Digital Commons Network^™

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 …

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, …

Predicting Loan Defaults: A Behavioral Scoring Approach For Portfolio Risk Monitoring In Banking And P2p Lending, Humaid Sultan Almarri

Theses

The critical challenge of lending institutions and peer-to-peer investors is to single out high-risk active borrowers in order to avoid defaults and corresponding losses. This thesis is devoted to the development of a data-driven approach to predict loan defaults, which balances predictive accuracy with interpretability and cost-sensitive evaluation. Using a large dataset of loans from LendingClub, we applied the CRISP-DM methodology, performing extensive data preprocessing and exploratory analysis before training several machine learning models-logistic regression, decision tree, random forest, and XGBoost-to classify loans as default or non-default. Class imbalance was addressed through resampling, and models were tuned via cross-validation with …

Predictive Analysis Of Residential Property In Urban Areas, Hamad Adnan Alzarooni

Theses

This paper aims to determine the predictive modelling of residential property prices in urban Scotland with the help of an integrated framework in which machine learning methods are applied in combination with detailed socio-economic, health, housing, and geographic indicators. Conventional valuation methods tend to be based on the concept of few structural variables and ignore the effect of multidimensional variables in determining spatial variation in housing markets. To cope with this, the study uses Linear Regression, random forest, Multi-layer perceptron, and XGBoost models, which are assisted by a broad range of feature engineering, outlier management, and data preprocessing. Compared with …

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 …

Deepfake Audio Detection, Rashed Alfalasi

Theses

The rise of deepfake audio technology has introduced a serious threat to information credibility, personal security, and media integrity. This thesis investigates the application of machine learning techniques for detecting synthetic audio through the analysis of acoustic features, including Mel-Frequency Cepstral Coefficients (MFCCs), spectral centroid, chroma_stft, and zero-crossing rate. The dataset used in this study was sourced from Kaggle and contains labeled samples of real and fake audio clips. The research aimed to train and evaluate multiple machine learning models—Support Vector Machines (SVM), Random Forest, XGBoost, Logistic Regression, and Neural Networks—to determine the most effective approach for deepfake audio classification. …

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 …

A Comparative Analysis Of Machine Learning And Deep Learning Models For Human Activity Recognition Using Wearable Sensor Data, Fares Shaban

Theses

Wearable sensors have become vital for health monitoring, evaluation of sport performance, and recognition of activities of daily life in Human Activity Recognition (HAR). With the combination of machine learning and inertial sensing, new possibilities for the collection of data pertaining to human motion in daily life have emerged. Nevertheless, problems remain to be resolved in the field of modeling in relation to tradeoffs in classification. The focus remains on imaging, signal variability, and sensor noise. This study aims to determine the usefulness of Inertial Measurement Unit (IMU) data for activity recognition and compares classical machine learning methods with a …

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 …

Assessing Large Language Models As An Interpretive Layer In Marketing Mix Modeling: Implications For Marketing Analytics, Mohammad Bin Haider

Theses

Marketing mix modelling (MMM) remains a core technique for guiding budget allocation, yet its outputs are often difficult for non-technical planners to interpret and govern. At the same time, large language models (LLMs) offer new possibilities for translating complex model artefacts into narrative guidance, but raise concerns about hallucination, reproducibility, and alignment with model-risk governance. This thesis examines whether an open-source MMM framework can be engineered as a repro- ducible, governance-ready pipeline and then augmented with a tightly constrained LLM interpretive layer. The empirical setting is a multi-brand, multi-country retail portfolio with several years of digital marketing and outcome data …

Five-Year Analysis Of Efficacy And Safety Of A Bidirectional Aav Gene Therapy In Tay-Sachs Sheep, Toloo Taghian, Xuntian Jiang, Et Al.

2020-Current year OA Pubs

Tay-Sachs disease (TSD) and Sandhoff disease are fatal neurodegenerative diseases without an effective therapy that are caused by mutations in the HEXA and HEXB genes, respectively. Together they encode the heterodimeric isozyme of hexosaminidase, hexosaminidase A (HexA), that degrades GM2 ganglioside. This report describes a 5-year-long study using a bidirectional adeno-associated virus 9 (AAV9) vector (AAV9-Bic_HexA/HexB) encoding both HEXA and HEXB in the TSD sheep model. Bidirectional AAV9 was delivered i.v. or through various cerebrospinal fluid (CSF) delivery routes: intracerebroventricular (ICV), cisterna magna (CM), and lumbar intrathecal space (LIT). The longest survival and best distribution were achieved by multipoint CSF …

Southern / Appalachian Migrants And Urban Development Politics In Uptown Chicago, 1950-1972, Charles Wayne Dowdy

Electronic Theses and Dissertations

This thesis investigates how ideas of interregional migration were used in service of urban renewal agendas in Uptown Chicago from 1950 to 1972. It argues that The South and Appalachia as regional ideas were impactful in postwar midwestern urban development politics, even as regional identity was less powerful as an adhering force for actual migrants in comparison with factors of race and class. Chapter 1 examines the development and use of the urban enclave model of interregional migration by the Uptown Chicago Commission in the late 1950s. It argues that anxieties around suburbanization and urban decline fueled the production of …

Knowing One's Place At The Table: Taste As A Means Of Othering In The American Colonies, 1700-1775, Nicholas Harp

Master's Theses or Doctor of Nursing Practice

This thesis began as an inquiry into a simple question. How did people in the American colonies talk about the food that they ate? This question led to a fascinating look into the social dynamics of the people living in eighteenth century America. Their own personal writings demonstrate how they understood their place in society through the food that they ate. Moreover, they often wrote about the way that other people ate in ways that alienated or discriminated against different ethnic groups. A look into the secondary historiography revealed that other historians had noticed this trend. However, very few addressed …

The Relationship Between Exercise And Prospective Memory: A Meta-Analysis, Shaykhah Salman Alqahtani

Electronic Theses and Dissertations

Prospective memory (PM)—the ability to remember and carry out future intentions—is essential for everyday functioning. This cognitive process involves intention formation, retention, cue detection, and execution. Emerging research suggests that physical exercise may influence prospective memory performance through potential enhancements in attention, executive functioning, and neuroplasticity. This thesis examines the relationship between physical exercise and prospective memory through a systematic review and meta-analysis of the existing literature.

This review synthesized evidence from experimental studies to evaluate the effects of acute and chronic exercise interventions on prospective memory in diverse populations. Six studies met the eligibility criteria and were included in …

Racial And Ethnic Differences In The Associations Between Alcohol Use Disorder, Aggression, And Suicidality Among Adolescents With Ptsd, Gabrielle Armstrong

Electronic Theses and Dissertations

The comorbidity of posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) is well documented and associated with elevated risk of aggression and suicidality among certain populations. However, no research to date has examined these associations among adolescents. Using data from the National Comorbidity Survey-Adolescent Supplement (NCS-A), the present study examined whether the presence of AUD was associated with greater outward aggression, suicidal ideation, and attempts, and whether these associations differed across race/ethnicity, in a weighted sample of 737,996 adolescents with PTSD (10.3% Hispanic, 16.4% Black, 73.3% White). AUD presence was significantly associated with higher odds of breaking items, attacking …

The Impact Of State-Mandated High-Stakes Standardized Testing On The Job Satisfaction Of Third-Grade Reading Teachers In Mississippi, Jenny Kate Ernst

Electronic Theses and Dissertations

This qualitative study examined how state-mandated standardized testing influences the job satisfaction of current and former third-grade reading teachers in Mississippi. Guided by Self-Determination Theory, Herzberg’s Two-Factor Theory, and the Job Demands-Resources Model, the research explored how accountability pressures shape teachers’ motivation, emotional well-being, and instructional autonomy. Data were collected through an open-ended online survey of current and former Mississippi third-grade reading teachers. Analysis of responses revealed four central themes: emotional strain and burnout, loss of autonomy and creativity, impact on instructional practices, and student impact. Findings indicated that teachers perceive standardized testing as a major source of stress that …

Design And Prototyping Of An Acoustic Positioning System For Gps-Denied Environment, Harley Hogan Garrett

Electronic Theses and Dissertations

Finding the placement of sensors is known as sensor localization, and is a necessary task to ensure that a network is capable of array processing operations, such as direction of arrival measurements. This thesis proposes a method to perform sensor localization for a wireless sensor network using acoustics. Each sensor is equipped with a microphone, speaker, and processor. Using these, the proposed system is able to find the distance between each sensor and later the geometry of the network. A series of optimizations help reduce error and improve the final accuracy of the system to within 6.5 cm. The proposed …

Reading Teacher Perceptions: The Impact Of Educator Preparation Program Literacy Coursework And Clinical Experiences On Teacher Efficacy In Historically Underrepresented Populations, Emily Taubken

Electronic Theses and Dissertations

Despite research that indicates the critical importance and lifelong impact of early reading proficiency for students, national reading proficiency trends demonstrate most students in the United States are not yet reading at grade level, with disparities existing among historically underrepresented subgroups. Additionally, research shows that preservice and in-service teachers have documented limited feelings of self-efficacy in teaching reading specifically, suggesting limitations in preservice training for educators. To better understand how reading teachers perceive the efficacy of their preservice teacher academic and clinical experiences, especially for those who serve historically underrepresented student populations, this study seeks to document the perspectives of …

Knowledge Acquisition On Mass-Shooting Events Via Llms For Ai-Driven Justice, Benign Ihugba

All Theses

Mass-shooting events pose a significant challenge to public safety because they generate large volumes of unstructured textual data, making it difficult to conduct effective investigations and formulate public policy. The proposed knowledge acquisition system utilized Large Language Models (LLMs) with few-shot prompting to extract vital information from news articles, police reports, and social media content at high speed. The system used entity recognition to detect vital information, which included offenders, victims, locations, and criminal instruments that support legal investigations. An experimental study conducted on actual mass-shooting datasets showed GPT-4o performs best for mass-shooting NER. The o1-mini delivered competitive performance while …

Visualizing The Fretboard: Arpeggiated Patterns, Muscle Memory, And Neurocognitive Strategies For The 5-String Electric Bass, Matthew Alexander Woisin

Electronic Theses and Dissertations

Proficient navigation of the 5-string electric bass requires a comprehensive mastery of various techniques and a solid understanding of music theory. This includes a detailed grasp of arpeggios, chord extensions, and the development of deeply ingrained muscle memory for precise execution. This thesis introduces a structured methodology that refines existing fretboard visualization techniques and applies a unique manner of fretboard mapping, offering a more precise framework for comprehending and unlocking the full range of the instrument. By drawing insights from music theory, music education, cognitive science, neuroscience, and technology this approach is achieved by synthesizing research on visual pattern recognition, …

Llu Dentistry 2025 Winter Edition, Loma Linda University School Of Dentistry

Articulator (Dentistry)

In this issue:

4 | Dean's Message
5 | Transforming the Future of Dental Education: The Strategic Vision and Growth Plan
8 | Honoring a Legacy of Excellence: Celebrating Leif K. Bakland, DDS
12 | Transitions
14 | Welcome New Faculty
16 | Celebrating Excellence in Dentistry: 2025 ICD USA Section Annual Meeting & Convocation
18 | LLUSD faculty publish study on Dental Unit Waterline treatment in the Journal of the American Dental Association
21 | Celebrating 15 Years of PNAM Treatment at LLUSD
23 | A Journey of Healing: Shirely's Transformation
24 | Exploring Future Careers in STEM: The …

Flood-Level Estimation Using Aerial Imagery, Yisen Zhang

Electrical & Computer Engineering Projects for D. Eng. Degree

Reliable flood-level estimation using aerial UAV (Unmanned aerial vehicle) imagery is essential for effective post-disaster assessment and rapid emergency response. This study utilizes a UAV-based dataset, referred to as the UVA dataset, which integrates multiple public datasets and manually labeled UAV images, together with a multi-stage vehicle-centric framework for flood-depth estimation. The UVA dataset integrates images from multiple public sources, including Unmanned Drone Water Assessment (UDWA), Unmanned Aerial Vehicle Detection and Tracking (UAVDT), Car Parking Lot (CARPK), and additional UAV-view images collected from the internet, followed by manual annotation for water depth, viewing angle, and altitude labels. In the proposed …

An Analysis Of Portuguese Colonial Representations Of Sinhalese Women, Chandra R. De Silva, Ramani Hettiarchchi

History Faculty Publications

The history of Sri Lanka until recently has been written mostly as the history of men in the country. This has been particularly true of the early modern period, for which existing records are mostly those of visiting colonizers who were mostly men, writing about their dealings with those in power or with those from whom they could gain profit. This article is an attempt to collect and analyze the admittedly limited data on how the Portuguese who gained political authority over parts of the coastal areas saw local women. It is limited to the women of the majority community …

Early Childhood Educators' Perception Of Burnout: Impact On Educator Self-Efficacy, Teacher-Child Relationships, And Children's Emotional Regulation, Isaac M.D. Bowman

College of Education and Human Sciences: Dissertations, Theses, and Student Research

Early childhood educators (ECE) play a critical role in the academic advancement and nurturing care provided to children in their care, a distinct difference in role and responsibilities compared to traditional K-12 schooling. Published by the Buffett Early Childhood Institute, a report pertaining to ECE turnover revealed a nearly 40% annual turnover rate. Factors ECEs previously attributed to their exit of the early childhood education field involve low wage, low self-efficacy, and dealing with challenging behaviors. While not an exhaustive list, in a field relying predominantly on routine and consistency, ECE turnover rate highlights a necessity in exploring potential indirect …

Assessing The Language And Reading Abilities Of Students With Mosaic Down Syndrome, Emma G. Conradi

College of Education and Human Sciences: Dissertations, Theses, and Student Research

Language and reading are important skills for academic and social success, yet individuals with Down syndrome often face significant challenges developing these skills (Abbeduto et al., 2007; Martin et al., 2009). However, almost all the available research on the language and reading abilities of individuals with Down syndrome comes from research focused on individuals with Full Trisomy 21. To date, there has been virtually no research specifically examining the language and reading skills of individuals with mosaic Down syndrome (Buckley & Bird, 2002), a rare karyotype of Down syndrome. Therefore, the purpose of this study is to describe the language …

Investigating Molecular Rotation And Vibration With Ultrafast Electron Diffraction, Haoran Zhao

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Ultrafast electron diffraction (UED) has emerged since the late 20th century as a powerful technique for resolving molecular dynamics. With its high spatial and temporal resolution, UED can now measure rotational motion induced by linearly polarized, nonresonant, nonadiabatic laser pulses—one of the fundamental molecular degrees of freedom with broad applications. By combining laser-induced alignment with UED, new capabilities such as three-dimensional structural retrieval and isotope detection have been demonstrated, as discussed in Chapter 2.

In Chapter 3, three symmetry relations in the coefficients of rotational wave packets are identified and derived, reducing the computational cost of simulating asymmetric-top molecular alignment …