Digital Commons Network^™

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 …

Investigating The Performance Variation For Graphene-Based Field-Effect Transistor, Tzu-Jung William Huang

Theses

As silicon CMOS technology approaches its scaling limits, two-dimensional (2D) materials such as graphene offer promising alternatives due to its atomically thin material property and high carrier mobility. Graphene field-effect transistors (GFETs) are especially suited for high-frequency and RF applications; however, large-scale integration is hindered by substantial device-to-device variability. Primary contributors include inconsistent graphene transfer, contact resistance, poor dielectric interfaces, and underlying substrate topography. This work presents a comparative study of three GFET architectures to address variability: (a) raised Al gate with 15 nm Al2O3, (b) raised Al gate with monolayer hexagonal boron nitride (hBN), and (c) recessed Al gate …

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 …

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, …

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 …

Customer Flow Prediction At Emirates Id Centers, Humaid Ahmed Saeed Alkhuroosi

Theses

Emirates ID centers face significant resource management challenges due to fluctuating customer traffic, leading to long wait times, customer dissatisfaction, and inefficient resource use. This thesis explores the application of time series analysis to predict customer traffic at Emirates ID centers, focusing on the Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) models. The primary research question is: “Can historical queue data from the Qmatic system be effectively used to forecast customer traffic at Emirates ID centers?” To answer this question, 800,000 observations of historical ticket issuance data from the Qmatic queue management system were analyzed. The study …

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 …

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 …

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. …

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, …

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 …

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 …

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 …

Beyond The Badge: Predicting Military Employee Attrition In The Police Force, Alia Abdulla Alhajji

Theses

This study explores the issue of employee attrition within the military police force, with a focus on predicting which employees are at risk of leaving. Attrition in law enforcement is costly and disruptive, especially in roles that require long training periods and operational readiness. The research specifically targets the internal organizational factors influencing turnover in military police environments and aims to leverage machine learning models to support the early identification of high-risk individuals. Guided by the CRISP-DM framework, the study followed a structured process across six stages: business understanding, data exploration, preparation, modeling, evaluation, and insight generation. A simulated dataset …

Using Generative Ai For Tutoring Data Science, Yusra Khalid

Theses

A large increase in the use of Generative AI has been observed in the last few years. Data science is also a rapidly growing field with a high demand for skilled professionals. The goal of this thesis is to explore the potential of Generative AI, specifically ChatGPT, in facilitating data science education. The focus is on how ChatGPT can be used as a tutor to help solve practical exercises. The capabilities of Generative AI were explored along with the comparison of a few different models in terms of data science. Exploratory analysis was conducted to compare Generative AI models and …

Classification Of Linear Systems Of Equations For Quantum Computing Implementation, Mark Danza

Theses

Drawing nearer to an error-corrected era of quantum computing, it is necessary to understand the suitability of certain post-NISQ algorithms for practical problems. One of the most promising, applicable, and yet difficult to implement in practical terms is the Harrow, Hassidim and Lloyd (HHL) algorithm for linear systems of equations. An enormous number of problems can be expressed as linear systems of equations, from machine learning to fluid dynamics to electrical circuit analysis. However, in most cases, HHL will not be able to provide a practical, reasonable solution to these problems. This work seeks to determine whether problems can be …

Sales Opportunities Lead Qualification In B2b Market, Hajar Hussain Ahli

Theses

This thesis addresses the challenge of inefficient lead qualification in the business-to-business (B2B) market by applying machine learning techniques to predict the likelihood of winning a sales opportunity. Using a real-world dataset of over 78,000 records and 17 variables, the study aims to improve how sales teams identify and prioritize high-conversion leads. A thorough data preparation process was conducted, including handling of missing values, outlier detection, and under-sampling to resolve class imbalance between won and lost opportunities. After thorough data cleaning, preprocessing, and under-sampling to address class imbalance, five machine learning models were developed: Logistic Regression, Random Forest, Neural Network, …

Instrapix – An Image-Based Digital Audio Workstation Design, Dan Qiao

Theses

InstraPix, a UI project designed by Dan Qiao, is groundbreaking image-and-audio conversion software and a digital audio workstation (DAW). enables bidirectional conversion between images and sound, opening new creative possibilities. With powerful image processing tools, it allows users to directly use pictures as audio sources, shaping unique sonic compositions. InstraPix also supports sound presets, VST plugins, and note editing, allowing seamless integration with other instruments. This all-in-one audio workstation could mark the beginning of a new era where music can be created entirely from images. Assigning images significant importance in audio production and minimizing the middle steps, it breaks the …

Deleting Values May Either Increase Or Decrease Variance, David L. Farnsworth

Articles

The impact upon variance when a value is deleted is addressed. It is shown that the cutoff for the deleted value yielding an increase or a decrease in variance is approximately one standard deviation from the mean for a univariate random variable with equally distributed probability on a finite set of elements and for a univariate set of observations. The influence of truncation of the domain for such a discrete random variable and for observations is considered.

Antidote, Sinicization, And Discipline Construction: Reading Hongbing Ge’S Theories Of Creative Writing Scholarship, Zhiyuan Chen, Weidong Liu

Journal of Creative Writing Studies

Review of Hongbing Ge, editor. Theories of Creative Writing Scholarship. Chinese Higher Education Press, 2020. 167 pages.

The Dx7 Of Literature? Creative Writing In The Age Of Genai, Laura Valeri

Journal of Creative Writing Studies

Abstract:

This paper examines the impact of artificial intelligence on contemporary literature, focusing on how writers are incorporating AI into their creative processes. Through case studies of avant-garde artists, mainstream literary authors, and genre fiction writers, the study explores various approaches to AI collaboration in writing. The analysis reveals that while AI offers new possibilities for artistic expression, it also presents ethical challenges and potential threats to traditional notions of authorship. The paper concludes by discussing the implications of AI in creative writing education, emphasizing the need for a balanced approach that embraces technological advancements while preserving the human element …

An Investigation Of Electrical Surface Impact As A Three-Dimensional Low-Energy Defibrillation Method, Rhiannan Ruef

Theses

Ventricular fibrillation is a medical emergency that leaves the heart unable to beat properly, and is fatal within minutes if left untreated. Furthermore, it’s the leading cause of sudden cardiac arrest according to the NIH, killing over 400,000 Americans every year. Previously, we’ve proposed a new low-energy defibrillation method to restore the heart to its normal rhythm during fibrillation. Our method required further investigation due to the presence of several important dynamical processes. In this dissertation, we report the results of these investigations. First, we will present our results related to a novel behavior called “flopping,” which occurs when a …

Narrow Band Random Vibration Reliability Of A Doped Near Eutectic Tin-Bismuth-Based Alloy With A Large Fine-Pitch Ball Grid Array Device, Gregory Derr-Haverlach

Theses

This thesis investigates the vibration reliability and microstructure of two low temperature lead-free solder alloys. The experimental design involved a 2x2 factorial setup, with solder paste type and time above liquidus (TAL) as the primary factors. The solder pastes tested were Indalloy 281 and Indalloy 303, with TALs of two minutes and three minutes. Indalloy 281 is a eutectic Sn42/Bi58 solder and Indalloy 303 is a doped near eutectic Sn-Bi solder. The objective of the study is to identify how reliability changes between solders and the time above liquidous and to also examine the microstructure and the significant factors that …

Impact Of Repeated Washing Cycles On Surface Integrity And Mechanical Properties Of Glass Bottles, Siwat Patamakam Mr., Thitisilp Kijchavengkul, Siriyupa Netramai, Gong Yaijam

Journal of Applied Packaging Research

Glass bottles are a top choice in the global beverage industry, but their inherent brittleness poses challenges in maintaining durability. This study focused on investigating the impact of numbers of washing processes from reusing on the surface quality and mechanical properties of glass bottles after each washing cycle. Contact angle technique was used to determine surface quality of glass bottles. It was found that mechanical integrity, as reflected in internal pressure resistance values, and surface quality of glass bottles exhibited an exponential decline with each washing cycle. Furthermore, a predictive model (R² = 0.8882) was developed to estimate its …

Colloidal Control Via Micellar Solutions, Timothy F. Niper

Theses

Mesoscale colloids composed of polyoctahedral silsesquioxanes (POSS) are promising candidates for the self-assembly of hierarchical structures as a continuum of size and morphology can be readily synthesized. However, there are substantial challenges in creating customized colloids that exhibit specific structural features, programmable binding, and stimuli responsiveness. Here, we explore a novel route to gain structural and directable control of these colloids by pairing them with thermoresponsive, polymeric micelles. These polymeric micelles cannot only swell the interstices of oligomeric colloidal droplets with the accuracy provided by the well-defined polymer micellization transition, but also act as absorbable colloidal depletants—a new class of …

Intersectional Experiences Of Stem Students With Disabilities, Sandy Heath, Jade Metzger, Tarah Loy-Ashe

Journal of Science Education for Students with Disabilities

Students with disabilities experience barriers to accessing Science, Technology, Engineering, and Mathematics (STEM) careers during academic preparation for these careers. This pilot project explored the experiences of postsecondary STEM students who have a disability. The six students interviewed gave their insights into the need to further diversify who has access to STEM careers by describing that cultural and structural barriers posed more of a barrier than the course content during their STEM education. Academic preparation often starts in early childhood education with exposure to STEM topics and continues through postsecondary education. The implications impact both the individual student and society. …