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Potential And Low-Cost Football Talents For Uae Clubs Based On Data-Driven Analysis, Rashid Alqemzi
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
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
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
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
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
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
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
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
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
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
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
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
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 …
Microgrid Approach With Data-Driven Monitoring To Enhance The Resilience Of Water Distribution Systems, Binod Ale Magar
Microgrid Approach With Data-Driven Monitoring To Enhance The Resilience Of Water Distribution Systems, Binod Ale Magar
Theses
Existing centralized water supply systems are critically threatened by the joint effects of climate and socioeconomic changes, extreme weather events, and physical degradation due to aging, and their changeability. The uncertain and changing drivers pose challenges for water supply systems in providing sustainable water services during disruptions. The energy field dealing related issues has endorsed the microgrid approach with a decentralized energy supply with dispersed local energy sources. The application of energy microgrids has demonstrated their resiliency for sustainable energy supply. For improved resiliency of a water distribution system, this study investigated the application of a microgrid approach and the …
Advancing 3d Infrastructure Utilities Mapping Through The Integration Of Multi-Method Digital Modelling Techniques, Adil Abdulla Aldashti
Advancing 3d Infrastructure Utilities Mapping Through The Integration Of Multi-Method Digital Modelling Techniques, Adil Abdulla Aldashti
Theses
With urban growth accelerating, cities increasingly need precise 3D information about their underground service networks to support sustainability goals and digital systems. Older 2D maps are often outdated, incomplete, and misaligned, making them difficult to use within 3D GIS environments. Moreover, conventional surveying tools may fall short in accuracy, struggle to reach buried assets, and require high costs when dealing with existing utilities. This thesis aims to develop and evaluate a field to 3D methodology for mapping underground utilities in Dubai, integrating multi-sensor and surveying approaches, and GIS 3D models in alignment with ASCE 38-22(American Society of Civil, 2022a), PAS …
Massive Stars Behaving Badly: Exceptional Interactions And Their Remnants, Kaila Nathaniel
Massive Stars Behaving Badly: Exceptional Interactions And Their Remnants, Kaila Nathaniel
Theses
Massive stars are some of the most dynamic and influential objects in the Universe, driving galactic evolution through violent explosions and serving as progenitors to neutron stars and black holes. While the evolution of isolated massive stars already produces remarkable phenomenae, massive stars that interact with companions or evolve within extreme environments may produce even more extraordinary outcomes. In this dissertation, I investigate some exceptional circumstances in which a massive star might find itself. In a first investigation, I analyze the strong interactions between isolated pairs of stars in low-density environments. If a binary consisting of a massive star and …
Adaptive Reuse Of Underutilized Strip Malls: Creating Mixed-Use Continuum Care Campuses For Seniors, Julie Le Nguyen
Adaptive Reuse Of Underutilized Strip Malls: Creating Mixed-Use Continuum Care Campuses For Seniors, Julie Le Nguyen
Theses
As suburban commercial landscapes continue to decline, underutilized strip malls present an opportunity to reimagine aging-supportive environments through adaptive reuse. This thesis investigates how these sites can be transformed into mixed-use senior housing and continuum-care campuses through adaptive reuse strategies. Using a comparative case study methodology, the research examines a range of precedents—including senior housing retrofits, dementia villages, and community-based mixed-use developments—to identify key spatial, programmatic, and environmental principles that support aging populations. A five-part evaluative framework assesses project performance across site integration and green space, social and intergenerational engagement, programmatic and service integration, mixed-use activation, and cognitive and environmental …
A Decision Support System For Global Vaccine Funding: Data-Driven Proposal Scoring, Epidemiological Risk Modeling, And Portfolio Optimization, Ashutosh Kumar
A Decision Support System For Global Vaccine Funding: Data-Driven Proposal Scoring, Epidemiological Risk Modeling, And Portfolio Optimization, Ashutosh Kumar
Theses
Global health financing must continually stretch limited immunization resources across competing priorities, and Gavi, the Vaccine Alliance, plays a central role in this landscape. This work reframes Gavi’s funding decisions as a multi-objective portfolio optimization problem that jointly considers health impact, equity, cost-effectiveness, sustainability, and epidemiological interdependence. To operationalize this approach, this study develops a decision support system grounded in Modern Portfolio Theory, treating each proposal as an asset characterized by expected return and risk. Proposal returns are estimated through a heterogeneous data-fusion pipeline that generates quantitative, multi-objective scores aligned with Gavi’s strategic priorities, while epidemiological risk is quantified using …
Analyzing The Hidden Impact Of Work Stress On Mental Health, Shaikha Aljabry
Analyzing The Hidden Impact Of Work Stress On Mental Health, Shaikha Aljabry
Theses
Occupational stress and deteriorating mental health constitute an increasing issue in the global community, and the problem of how job demands, personal resources, and cognitive processes interrelate to determine employee well-being is hardly known. This dissertation will study these dynamics by incorporating theory-driven Structural Equation Modeling (SEM) with data-driven Machine Learning (ML) methods that offer explanatory and predictive information. The study examines the influences of job demands, personal resources, effort–reward imbalance (ERI), emotional labor, cognitive appraisal, and social support on the stress and mental health outcomes of a sample of 5,000 employees working in various industries and regions of the …
Adaptive Design Solutions For Golfers With Arm Impairment, Samuel Hao-Yu Wang
Adaptive Design Solutions For Golfers With Arm Impairment, Samuel Hao-Yu Wang
Theses
Golf is a game of precision, focus, and enjoyment for everyone, regardless of age, physical condition, or experience. However, for many people with disabilities, full participation in the game can be challenging. This project created an inclusive golfing experience for players with physical disabilities by assisting them with specific actions required in golf. The goal was to design solutions that reduce limitations caused by impairments, enabling players to enjoy the game with greater freedom. The United States Disabled Golf Association recognizes 14 sport classes of physical impairments, categorizing competitors by different types and levels of disability. This project focused on …
Exploring The Perception Of Dynamic Electrotactile Patterns On The Fingertips, Vedika Nimbalkar
Exploring The Perception Of Dynamic Electrotactile Patterns On The Fingertips, Vedika Nimbalkar
Theses
The goal of this study is to evaluate the effectiveness of electrotactile feedback on the fingertips by examining how accurately different dynamic patterns can be perceived. We designed three pattern types (Single Line, Double Line, and Box) and programmed each to move in eight distinct directions: bottom to top, top to bottom, left to right, right to left, bottom-left to top-right, top-right to bottom-left, bottom-right to top- left, and top-left to bottom-right. A study was conducted to assess these patterns’ perceived accuracy and response time on fingertips. The study results revealed that the Single Line and Double Line patterns had …
Predicting Mental Health Risk In Remote Workers: A Machine Learning Approach, Majed Al Mheiri
Predicting Mental Health Risk In Remote Workers: A Machine Learning Approach, Majed Al Mheiri
Theses
This dissertation explores the application of machine learning in mental health risk prediction of remote workers, which is increasingly becoming a significant issue, with the practise of flexible working reshaping organisational practises. It is based on the theoretical framework that has been used previously such as Job Demands Resources model and Stress-Strain model which emphasise the role of workload, support systems and personal resources in determining the well-being of employees. The context of the study indicates the growing rate of remote and hybrid employment, and the associated increase in the number of issues associated with stress and isolation, as well …
Predictive Modeling Of Tokenized Real Estate Prices Using Machine Learning, Mohammed Alteneiji
Predictive Modeling Of Tokenized Real Estate Prices Using Machine Learning, Mohammed Alteneiji
Theses
In this paper, we propose a machine learning-based model to predict the prices of tokenized real-estate assets, combining blockchain data, real-estate data, and sentiment data. Tokenization refers to partitioning a physical asset into fractional tokens on a blockchain, where each token represents a fraction of that asset. These include token liquidity, trading volume, platform activity, and the on-chain activity of investors. These new variables require data-based analytics that are capable of accounting for more complex relationships than customary real estate valuation approaches. To address this, we propose a multimodal dataset that incorporates on-chain data (token supply, number of wallet-holders, transaction …
Transgender Adolescents' Healthcare Rights: The Gap Between Gender-Affirming-Care (Gac) Policymakers’ And Healthcare Providers’ Goals, Jayden Galli
Theses
Transgender people have marginalized healthcare experiences that result in decreased health outcomes. For transgender adolescents, gender-affirming-care (GAC) is even more difficult to access and being restricted with increasing frequency. This mixed methods study was conducted to examine transgender healthcare through the gaps between GAC policymakers’ and healthcare providers’ goals. General research has focused on the relationship between GAC and transgender health, GAC policy development, and the discrepancies between GAC policy outcomes and medical professionals’ advice. This leads to the research question about how policymakers and healthcare providers can collaborate to bridge the gap between GAC policies and transgender minors' healthcare …
Predictive Maintenance For It Equipment Using Machine Learning Models, Rashed Khalid Alshirawi
Predictive Maintenance For It Equipment Using Machine Learning Models, Rashed Khalid Alshirawi
Theses
Predictive maintenance was recently introduced as a paradigm shift in the field of smart manufacturing, and it allows organizations to predict equipment failures and streamline maintenance planning based on the data-driven insights. The present work addresses the concept of the implementation of a decision tree-based predictive maintenance model based on AI4I 2020 Predictive Maintenance Dataset, a simulated environment of an actual industry through sensor data including temperature, torque, rotational velocity, and toolwear. The study uses a quantitative approach that is based on positivism philosophy, which is the focus on objectivity, empirical validation, and statistical testing of the model performance. Synthetic …
The Impact Of The 2008 Financial Crisis On Crime And Cybercrime In The United States, Rashed Adel Alsuwaidi
The Impact Of The 2008 Financial Crisis On Crime And Cybercrime In The United States, Rashed Adel Alsuwaidi
Theses
This thesis will examine how the traditional crime and cy- were affected by the 2008 financial crisis. United States are also experiencing a rise in crime between 2005 and 2012. Based on the FBI data at the national level. The Internet Crime Complaint Center (IC3), Uniform Crime Reports and important economic indicators. The study, which involves tors, including unemployment, GDP, rates of foreclosures, and mortgage rates, is a combination. correlationbased interpretation supported by exploratory descriptive trend analysis. model-fit checks. The results indicate that contrary to the conventional expectations, violent and property crime also maintained their long-term reduction during the period …
Detecting Fraud In Police Reports Using Machine Learning And Natural Language Processing, Maryam Almarar
Detecting Fraud In Police Reports Using Machine Learning And Natural Language Processing, Maryam Almarar
Theses
The paper explores how statistical analysis and machine learning can be used to identify the fraud patterns in the police reports. The study aims at establishing the most important predictive factors and indicators distinguishing fraudulent and valid cases with the use of structured data of police databases. The work was done in the background of the increase in financial fraud instances and the rising necessity of the introduction of automated detection systems in police departments. Police reports of the pastwere mined down to data and analyzed on SPSS 1, to carry out statistical operations. The sample was structured data which …
Predicting Inmate Overcrowding To Improve Facility Management, Mayed Ali Alameri
Predicting Inmate Overcrowding To Improve Facility Management, Mayed Ali Alameri
Theses
Overcrowding is a major challenge to correction systems because the conventional forecasting techniques are inaccurate and inadequate in most cases. This paper will solve this by constructing and testing a machine learning-based model to predict facility-level overcrowding. With the use of the XGBoost Regressor model on a dataset comprising of U.S. correctional facilities, the research identified key structural drivers but showed that the static facility attributes alone have limited predictive power (r-square approx 0.18) The discussion shows that overcrowding is non-linear, and a complicated problem not confined to the facility characteristics but to the larger, non-measurable regional influences, of which …
Early Electrical Fault Detection In Power Systems Using Data Analytics, Hessa Alraeesi
Early Electrical Fault Detection In Power Systems Using Data Analytics, Hessa Alraeesi
Theses
The increasing penetration of renewable energy, especially solar generation, has introduced higher variability into power system loading, making early detection of electrical faults more challenging yet more essential for maintaining network reliability. This research presents a machine-learning–based framework for early electrical fault detection using a Random Forest model developed in DataRobot. Due to confidentiality constraints on DEWA operational data, a Kaggle dataset was adopted and enriched with simulated solar irradiance variability to mirror real network conditions in the UAE. After comprehensive data preprocessing and feature engineering, the Random Forest model demonstrated strong generalization performance, accurately distinguishing early fault signatures from …
Play Of Curiosity: A Table-Top Game That Cultivates A Creative Attitude By Encouraging Curiosity In Young Adults, Kajal Shah
Theses
In a time that increasingly demands instant creativity, adaptability, and innovative thinking on a constant basis, nurturing a curious attitude among young adults must become a critical focus. Creativity and curiosity can be encouraged throughout various stages of life, and for myriads of personality types, the focus demographic of this paper is young adults, ages 18 to 26 years old. Young adulthood is when one starts to recognize post-formal thoughts. This stage of cognitive development helps to approach concepts beyond binary thinking, developing the unique abilities of ambiguous thinking and relativism. The enigmatic, ever-changing, and easygoing mind will often try …