Digital Commons Network^™

Predicting And Forecasting University Rankings In The Uae Using Machine Learning, Fatma Ibrahim Ahmad

Theses

Higher Education Institutions (HEIs) play a vital role in advancing knowledge economies, and institutional rankings are increasingly used as global benchmarks of academic performance and reputation. In the context of the United Arab Emirates (UAE), enhancing institutional competitiveness in global rankings aligns with national strategies such as UAE Vision 2030 and the Centennial Plan 2071. This research applies machine learning (ML) techniques to develop predictive models that forecast institutional ranking outcomes, enabling data-driven planning and continuous academic improvement. The study utilizes a dataset compiled from the QS World University Rankings (2020–2024), cross- referenced against the institutional listings maintained by the …

Modelling And Optimization Of A Desiccant Cooling System For Industrial Applications In Dubai, Ahmad Ababneh

Theses

The study examines the modelling and optimization of solar-assisted desiccant cooling systems (SADCS) specifically designed for industrial applications in Dubai. Four system configurations were evaluated under Dubai's extreme climate using TRNSYS 18 simulation software: classic ventilation, variable percentage recirculation, ventilation with a sensible heat exchanger that utilizes exhaust air to preheat the feed of the auxiliary heating air, and recirculation with a sensible heat exchanger that also utilizes exhaust air for preheating the auxiliary heating air feed. A parametric study comprising 60 simulation cases was performed, examining variations in desiccant wheel effectiveness, airflow rates (3–5 ACH), regeneration temperatures (50–80 °C), …

Ai-Driven Prediction Of Flight Cancellations: A Machine Learning Approach In Minimizing Airline Disruption, Hind Nasser

Theses

This thesis investigates the use of machine learning to predict flight cancellations, aiming to reduce operational disruption and improve airline decision-making. The research is motivated by the need for more proactive strategies in aviation, where flight cancellations often result in financial losses and customer dissatisfaction. The study is framed within the CRISP-DM methodology and demonstrates how historical flight data can be transformed into actionable insights using structured analytics. The research addresses three core questions: how effectively machine learning can predict cancellations, which evaluation metrics are most suitable in an imbalanced context, and how model outputs can support airline operations. A …

Personalized Nutrition Recommendations For Arab Communities: Transforming Diet And Health Through Machine Learning, Khalfan Aldoobi

Theses

A lack of cultural understanding in traditional nutrition approaches prevents proper adherence to healthy dietary patterns among individuals. The Arab population faces unique challenges due to cultural dietary customs and lifestyle changes that have made obesity and diet illnesses major global public health challenges. The rapid shift to high-calorie but undernourished foods and less physical activity has resulted in alarming rate increases of obesity, cardiovascular diseases, and type 2 diabetes. The lack of cultural understanding in traditional nutrition approaches prevents proper adherence to healthy dietary patterns among individuals. This study focuses to fills the existing gap by applying Artificial Intelligence …

Predicting Student Dropout Risk Using Machine Learning, Fatma Alameri

Theses

Student dropout remains a persistent challenge in higher education, undermining institutional performance, reducing workforce preparedness, and limiting students’ academic and economic opportunities. Accurately identifying students at risk of attrition is complex, due to the interplay of academic, financial, and behavioral factors. This thesis addresses this challenge by applying a combined machine learning framework—integrating both unsupervised and supervised techniques—to predict student dropout using structured, first-year academic and financial data. The study utilizes a comprehensive dataset of 4,424 undergraduate student records from a European higher education institution, covering ten academic years and comprising 35 variables related to academic performance, enrollment behavior, and …

Fake News Detection: Leveraging Natural Language Processing And Machine Learning For Reliable Information Verification, Roshni Rajendra Salve

Theses

This dissertation details the creation and assessment of a machine learning algorithm designed to identify fake news utilizing Natural Language Processing (NLP) methods. The research employs several machines learning models, including Long Short-Term Memory (LSTM) and other deep learning techniques, to detect and classify misleading information. Data is sourced from a variety of platforms, such as social media and online news outlets, to compile a thorough dataset. The data is pre-processed to eliminate noise, address missing values, and extract essential features through techniques like tokenization, stop-word removal, and lemmatization. The performance of the models is evaluated using key metrics such …

Enhancing Third-Party Risk Management In Aviation: A Comprehensive Framework For Modern Challenges, Shamma Hussain Hammad Bin Hammad

Theses

This thesis is focused on improving the way airlines have managed risks from third-party vendors. Emirates and Etihad have been used as case studies. The thesis identifies major issues, including cybersecurity threats, slow manual processes, and the challenges in the following global regulations. To To solve such problems, the research proposes a new framework that integrates advanced tools including machine learning, blockchain, and real-time updates about threats. The framework includes different features like automatic risk scoring and detection of unusual vendor behavior and keeping the secure digital records through the blockchain. This will highlight the need for the staff to …

Future Unleashed: Reimagining Marketing Strategies With Future Foresight, Afra Sultan Al Suwaidi

Theses

In today’s fast-paced and dynamic business landscape, marketing plays a crucial role in influencing business strategy and decision-making in an organisation. Marketing not only helps organisations identify and anticipate trends, threats, and opportunities, but also enables them to formulate and implement effective strategies to capitalise on these insights and achieve the organisation’s vision and goals. Future Foresight in marketing empowers organisations to stay ahead of the curve and gain a deeper understanding of the target audience and industry landscape. The evolving nature of marketing driven by advancements in technology, particularly artificial intelligence, machine learning, and digital marketing channels, makes it …

Energy Forecasting Inaccuracies And Their Direct Impact On Grid Performance, Rashed Khalid Alboom

Theses

Accurate energy forecasting is critical for the stability, efficiency, and cost-effectiveness of modern power grids, particularly as renewable energy sources like solar and wind become more prominent. The variability of these sources presents challenges for traditional forecasting models, which struggle with non-linearity, external dependencies, and evolving grid conditions. These limitations lead to operational inefficiencies, grid instability, and increased financial risks. This study investigates the effectiveness of traditional statistical models, advanced machine learning techniques, and hybrid forecasting approaches to enhance prediction accuracy and grid performance. Using real-world datasets from Kaggle, including historical energy generation, consumption, pricing, and weather variables, this research …

Roads Of Tomorrow: Augmented Reality For Enhanced Road Maintenance, Nasser Humaid Alshamsi

Theses

The rapid deterioration of roads creates major obstacles that affect public security, urban movement capacity, and economic durability. Standardized road maintenance operations depend heavily on human inspections that prove time-consuming while being labour-intensive and subject to human mistakes. Implementing Augmented Reality (AR) with Point Cloud Data represents a smart approach that improves delivery efficiency in road maintenance procedures for modern cities. AR enables real-time visual content and interactive displays through this research, yet Point Cloud Data delivers detailed, precise road inspections through high-definition three-dimensional mapping. These technologies are evaluated for their usability, effectiveness, and adoption barriers in research that advance …

Determining Sustainable Urban Renewal: A Case Of Quantifying Sustainability For Adaptive Reuse Within Mumbai’S Textile Mill Sector, Arundhati Rajesh Kawlekar

Theses

This study explores adaptive reuse as a sustainable approach to urban development in Mumbai, India, focusing on the revitalization of a heritage textile mill site. It investigates how historical significance and evolving community needs can shape design decisions, while assessing sustainability through Life Cycle Analysis (LCA) and energy efficiency metrics. Mumbai’s defunct textile mills, once central to its industrial growth, now pose challenges to urban vitality. Through a literature review, the paper examines their historical, social, and cultural relevance and the decline of the mill industry. Adaptive reuse emerges as a key strategy to reimagine these structures, offering an environmentally …

Through Legitimate Dissent, The Supreme Court Repairs Itself, Afnaan A. Qureshi

Theses

The decisions of the Supreme Court of the United States, along with its reasoning, influence the direction and scope of historical events. Through an analysis of landmark dissents from four of the worst Supreme Court decisions, Curtis’ dissent in Dred Scott v. Sandford (1857), Harlan’s dissent in Plessy v. Ferguson (1896), Holmes’ dissent in Abrams v. United States (1919), and Murphy’s dissent in Korematsu v. United States (1944), we can take steps towards catalyzing its self repair by stepping away from digital echo chambers and engaging in legitimate dissent. The four cases marked turning points in the efforts to protect …

Forecasting Load At Residential, Industrial, And Commercial Stations For Dubai Electricity And Water Authority: A Machine Learning Approach To Managing Generation During Peak And Off-Peak Times Over The Coming Years, Mohammad Anoohi

Theses

In Dubai, with the rapid growth of energy demand, efficient demand side management is necessary to optimize the distribution of electricity, reduce peak loads, and improve grid stability. Traditional DSM strategies are based on historical data and reactive control mechanisms that cannot adapt to evolving consumption patterns. This research uses Machine Learning techniques to enhance DSM in residential, commercial, and industrial sectors by developing predictive models that forecast energy demand based on seasonal variations. The dataset used was from Dubai Electricity and Water Authority (DEWA), covering the consumption patterns across Summer, Winter, Transition from Winter to Summer, and Transition from …

Capturing Community Memory: A Juxtaposition Of Oral History And Historic Building Preservation, Eliot Gavin

Theses

Preserving local history has always been a challenge for small communities. Traditional preservation methods like historic building preservation can be costly and take a lot of time for local historical societies. These historic sites are important to the culture of the local citizens and deserve to be saved. Using The Castle on the Hill in Dansville, New York, as a case study, oral histories will be captured to explore the role of oral history in preservation. The Castle on the Hill plays an important role in shaping Dansville’s identity as a town. In the past, the Castle has served as …

A Prototype High Power Dc-Dc Converter For Regulating Generator Output Voltage In A Series Hybrid Electric Vehicle, Alex Currie

Theses

As fully electric and hybrid electric vehicles become more commonplace, a strong incentive for innovation in electric powertrain technology has been created. Though the instantaneous power available from an electric motor may appeal to consumers of powersports vehicles, this has been an area with relatively little advancement towards electric architectures. One primary concern of electrifying such a platform is the need for large battery packs that tend not to perform well in the harsh weather conditions often seen in powersports such as snowmobiling. As such, hybrid electric architectures may prove to be a successful middle ground between fossil fuels and …

An Analysis Of Dc-Dc Converter Efficiencies, Carley Visser

Theses

With the increase in technology used in everyday life, the need for DC-DC converters has continued to increase. The efficiency of these converters is an essential parameter as an increase in a few percent can increase battery life by hours. There are several different factors that effect the efficiency of converters ranging from temperature, component selection, quiescent current and more. In this paper, a series of eleven DC-DC converters will be designed and tested in order to observe how the efficiencies and other parameters compare to the values provided in this datasheet. For this investigation two different PCBs were designed, …

Uvm Based Verification Of Ee621 Risc Processor Module, Collin Neidel

Theses

In the process of digital design, the majority of efforts are focused on verification. This is because a proper verification environment can help engineers discover bugs that otherwise would have flown under the radar. On the other hand, a poorly designed verification environment could fail to fully confirm the device’s functionality and leave the customer with a buggy mess. For obvious reasons, this should be avoided at all costs, hence the emphasis on functional verification and validation efforts. Throughout time, the complexity of the average design under test (DUT) has increased dramatically, making verification a significant challenge for today’s verification …

Glue Laminated Timber: A New Way Of Framing The Residential Architecture Of Upstate New York To Improve Thermal Performance & Energy Use Intensity, Griffin Jones

Theses

This thesis addresses the issue present within the current construction techniques for the residential architecture of Upstate New York. Modern platform framing has long been the dominant fashion for constructing homes in the United States, however the nature of this construction is instilled with the issue of thermal bridging, where the wood studs and structure allow heat to escape due to gaps in the continuous insulation. This study proposed a new way of framing residential architecture for the upstate region of New York, relying on glue-laminated timber (GLT) to replace dimensional sawn lumber. GLT has increased structural strength and stability …

A Bert-Resnet Cross-Attention Fusion Network And Modality Utilization Assessment For Multimodal Sentiment Classification, Ronen G. Gold

Theses

This study explores the growing field of Multimodal Sentiment Analysis (MSA), focusing on understanding how advanced fusion techniques can improve sentiment prediction in social media contexts. As platforms like X and TikTok continue to expand and facilitate sharing sentiment through digital media, there is an increasing need for neural network architectures that can accurately interpret sentiment across modalities. We implement a model using BERT for textual features and ResNet for visual features. A cross-attention fusion module aligns the modalities for joint representation. We conduct experiments on the MVSA-Single and MVSA-Multiple datasets, which contain over 5,000 and 17,000 labeled text-image pairs. …

Enhancing Influence Estimation In Gradient Boosted Decision Trees Through Hierarchical Analysis, Anurag Choubey

Theses

This report presents a novel influence function for gradient-boosted decision trees (GBDTs), a widely-used class of predictive models. Influence estimation aims to quantify how individual training samples affect a model’s predictions, offering valuable insights for model debugging, data quality analysis, and in- terpretability. Existing influence functions for GBDTs—such as LeafInfluence, LeafInfluenceSP, and BoostIn—have shown varying degrees of success, with BoostIn currently recognized as the state-of-the-art in terms of estimation quality and computational efficiency. In this work, we propose BoostInLCA, a new influence function that extends BoostIn by incorporating information from non-leaf nodes via the Lowest Common Ancestor (LCA) path, thereby …

Sustainable Retrofits: The Balance Between Energy Efficiency And Embodied Energy, Alexander Narvaez

Theses

This thesis looks at how to balance energy efficiency with embodied energy in small commercial retrofits, focusing on restaurant buildings. Rather than tearing down older buildings and starting from scratch—something that wipes out all the embodied energy already invested—retrofitting can improve performance while preserving what's already there. Using EnergyPlus for operational energy modeling and the Athena Impact Estimator for embodied energy analysis, this study compares different retrofit scenarios. These include retrofitting one, two, or all three major assemblies (walls, roofs, and floors) to see how each combination affects total emissions over time. The results show that not all retrofits are …

Criminal Activity Monitoring System: Targeting Africans And East Asian Communities In Dubai, Hamdan Kalantar

Theses

This dissertation investigates crime patterns among African and East Asian communities in Dubai, focusing on geographic hotspots, temporal trends, victim demographics, and the use of machine learning for predictive crime modeling. The research addresses the challenges faced by these communities, including labor exploitation, financial fraud, and human trafficking, within the socio-economic context of a rapidly growing urban city. Building on existing studies of urban crime, this research aimed to explore the spatial, temporal, and demographic dynamics of crimes and assess the potential of predictive models to assist law enforcement in crime prevention and resource allocation. A mixed-methods approach was employed, …

Steering Through Change: How Aging Eyes And Stroke-Induced Vision Loss Affect Driver Control, Arianna P. Giguere

Theses

Imaging system engineers could greatly benefit from understanding how biological systems have evolved to solve difficult imaging problems. In this thesis, we study how the human visual system has evolved to address the complex task of visually-guided steering, particularly as a person ages and experiences a prevalent type of vision loss from stroke called cortical blindness (CB) that results in the loss of one quarter to one half of the visual field. In a series of three studies, we test the hypothesis that the effects of CB on vision and steering extend beyond those that accompany healthy aging, and we …

Wide Lock-In Energy Harvesting From Vortexinduced Vibrations Of A Deformable Cylinder, Ahmed Raafat Mostafa

Theses

Energy harvesting from ambient sources has gained attention due to increasing energy demands. Despite VIV-based harvesters showing significant potential, their lock-in region, where significant power is generated, is narrow. Given the continuously varying ambient conditions of fluid currents, harvesters can easily fall into de-synchronization, yielding low energy output. Existing solutions like tunable masses or multiple degrees of freedom systems increase complexity and weight, limiting practical applications. This work introduces a novel variable diameter cylinder mechanism—a practical technique that actively tunes the cylinder’s geometry in real time to enhance energy harvesting efficiency from VIV. The mechanism employs an expanding pulley system …

الحماية الجنائية للبيانات الجينومية (دراسة تحليلية مقارنة), ميثاء حارب العميمي

Theses

Criminal Protection of Genomic Data

This research examines the criminal protection of genomic data through a comparative study between the United Arab Emirates and the United States of America, with the aim of analyzing how each legal system addresses these sensitive data and the associated risks، Genomic data, which relates to individuals' genetic information, is crucial in various fields such as medicine, insurance, and employment, making its protection essential to ensure individuals' privacy and to safeguard them from genetic discrimination or unlawful exploitation.

The UAE legislature is showing an increasing interest in regulating aspects related to genetic data and genomics, …

Evaluating The Effects Of Co₂ And Uv-B On Sporobolus Virginicus (L.) Kunth Growth Under Open Top Chamber: A Comparison Of Silicon Nanoparticle-Treated And Untreated Plants, Suhaila Humaid Ablooshi

Theses

The study focused at how silicon nanoparticles (SiNPs; 50 mg/L) affected the growth, photosynthetic efficiency, and biochemical responses of the salt-tolerant halophyte Sporobolus virginicus in four different environments. They are control, high CO₂, UV-B radiation, and a mix of high CO₂ and UV-B. Plants that were treated with SiNPs showed big changes in their shape, such as more biomass, bigger leaf area, and better root systems in all conditions. The use of combined stress treatments caused a big increase in the levels of chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids. As a result, that the plants were better at …

Identifying Barriers, Challenges And Opportunities Of Implementing Retrofitting Strategies In Existing Buildings In The Uae, Ahmad Ghalib Masri

Theses

The built environment of the UAE faces sustainability challenges because of its high energy usage and greenhouse gas emissions which require successful retrofitting methods to enhance aging buildings' performance and efficiency. This research investigates the barriers and challenges and opportunities of retrofitting strategy implementation in the UAE to provide direction for policymakers and stakeholders regarding sustainable practices. The research employed a mixed-methods approach through literature reviews and stakeholder surveys and interviews. The study shows that high upfront costs (68% of respondents) and building owner awareness limitations (54%) and fragmented regulations with inconsistent thermal insulation standards across emirates represent major barriers. …

A Study Of The Impact Of Balancing, Geometric Transformation, Generative Networks, And Roi Techniques In Eye Diseases Classification, Sghaira Hareb Alnuaimi

Theses

Automatic detection of ocular diseases helps medical professionals efficiently identify eye disorders, reduce diagnostic errors, and accelerate diagnoses to prevent blindness. Deep learning has been successfully utilized in various fields, including medical image classification. However, in spite of these advancements, challenges remain in ocular disease classification.

The objective of this work is to address these challenges using data processing, data augmentation in combination with Region of Interest (ROI) techniques. Medical datasets often suffer from scarcity, imbalance, and low-quality images, leading to inaccurate classification. To mitigate these issues, we utilize the ODIR dataset, which contains 7,000 labelled training images for both …

Groundwater Storage Dynamics In Abu Dhabi Emirate Using In-Situ And Grace Data, Tala Jalal Maksoud

Theses

Water scarcity presents a significant challenge to the sustainable development; especially in arid regions like Abu Dhabi Emirate. Addressing concerns over nonrenewable aquifer depletion, caused by agricultural expansion and lifestyle advancements, has, therefore, become crucial in such regions. This thesis investigates Groundwater Storage (GWS) dynamics in Abu Dhabi Emirate by integrating satellite data from the Gravity Recovery and Climate Experiment (GRACE) with in-situ data from 257 wells over two decades (2002-2022), employing GIS and RS technologies. The main aim of this study is to provide a comprehensive approach to evaluate GWS dynamics considering multiple perspectives including: dealing with missing datasets, …

Definitively Unfinished: Abraham Cruzvillegas’ Autoconstrucción, Disability Aesthetics, And Crip Materiality, Benjamin Brobst-Renaud

Theses

Abraham Cruzvillegas’ Autoconstrucción project is the sculptural manifestation of an approach to artmaking rooted in the self-built and continually evolving forms of the neighborhood where Cruzvillegas grew up (Colonia Ajusco near Mexico City). While it might seem surprising to draw a comparison between the forms of Autoconstrucción and Disability Studies, and while Cruzvillegas does not literally depict the disabled human form, Autoconstrucción resonates deeply with this critical space. Disability Aesthetics, in Tobin Siebers’ formulation, is “an attempt to theorize the representation of disability in modern art and visual culture.” Similarly, Jessica Cooley’s Crip Materiality is a methodology that “locates disability …