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A Bert-Resnet Cross-Attention Fusion Network And Modality Utilization Assessment For Multimodal Sentiment Classification, Ronen G. Gold May 2025

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. …

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Enhancing Influence Estimation In Gradient Boosted Decision Trees Through Hierarchical Analysis, Anurag Choubey May 2025

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 …

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Beyond The Badge: Predicting Military Employee Attrition In The Police Force, Alia Abdulla Alhajji May 2025

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 …

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Classification Of Linear Systems Of Equations For Quantum Computing Implementation, Mark Danza May 2025

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 …

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Instrapix – An Image-Based Digital Audio Workstation Design, Dan Qiao May 2025

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 …

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Sales Opportunities Lead Qualification In B2b Market, Hajar Hussain Ahli May 2025

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, …

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Intellimad: A Framework For Secure Machine Learning Models Evaluation And Fine-Tuning In Federated Setting, Dmitrii Korobeinikov May 2025

Intellimad: A Framework For Secure Machine Learning Models Evaluation And Fine-Tuning In Federated Setting, Dmitrii Korobeinikov

Theses

In contemporary artificial intelligence (AI) appli- cations, Machine Learning (ML) models are core components enabling AI-driven functionalities, yet selecting and fine-tuning a model and its hyperparameters remains challenging. ML model architecture, as well as key model training parameters, such as the number of training epochs, batch size, and learning rate, are highly dependent on both the dataset modalities and the specific task resolved in a particular application. More sophisticated execution setups may require determination of additional environment-related parameters, such as identifica- tion of computational capabilities required for execution of a particular AI-driven task, or discovery and establishment of desired security-related …

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Back To The Basics: Extracellular Protein Interaction Networks Of The Human Infant Immune System, Mavis Amity Irwin May 2025

Back To The Basics: Extracellular Protein Interaction Networks Of The Human Infant Immune System, Mavis Amity Irwin

Theses

Datamining without an age filter proves challenging, especially when searching for direct data from human infants. Although online databases provide immune interaction networks, they often lack information about the age of data sources, resulting in categorizations as age-unspecified. This limitation underrepresents the physiology of naïve immune systems in infants, particularly since full-term infant immunity transitions to an adult-like phenotype between 24 and 30 months of age. This study aims to reconstruct an age-specific immune interaction network for full-term infants by integrating literature-based evidence with existing online database content. A list of 60 extracellular protein candidates involved in immune responses was …

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Developing Meld-Accelerated Molecular Dynamics Protocols To Simulate The Binding Of The P53-Derived Ligand To The Mdm-2, X Protein, Maria Ciko May 2025

Developing Meld-Accelerated Molecular Dynamics Protocols To Simulate The Binding Of The P53-Derived Ligand To The Mdm-2, X Protein, Maria Ciko

Theses

In this study, we focus on developing computational methods to predict protein-ligand binding affinities, with applications in peptide drug discovery. Molecular Dynamics (MD) simulations can capture the complex conformational behavior of proteins, but their high computational cost limits their efficiency. MELD, or Modeling Employing Limited Data, is a Bayesian approach that integrates external information to accelerate sampling of low- energy, high-probability conformations. Building on previous work by Morrone et al., which successfully applied MELD to P53-MDM2 complexes, we hypothesize that we can effectively compute the relative binding affinities while reducing steric clashes and mitigating the effect of slowed diffusion on …

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Predicting The Probability Of Crime Related Danger In Los Angeles, Joshua Oghenetega Okpako May 2025

Predicting The Probability Of Crime Related Danger In Los Angeles, Joshua Oghenetega Okpako

Theses

This thesis examines the use of advanced machine learning to predict crime danger in Los Angeles, where 2023 violent crime rates (503 per 100,000) surpass the national average (363.8 per 100,000). Rooted in theories like social disorganization and victim vulnerability, it addresses the lack of combined victim-centric modeling by focusing on three questions: (1) Do blended ensemble models outperform individual models in predicting crime danger? (2) Can unsupervised learning techniques enhance supervised models’ accuracy through label generation or augmentation? (3) How can we interpret accurate machine learning models' decision-making processes? Using historical crime data from Los Angeles (2020–2025) and various …

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Data-Driven Prediction Of Vehicle Residual Value In The Uae Automotive Industry, Meera Al Hashmi May 2025

Data-Driven Prediction Of Vehicle Residual Value In The Uae Automotive Industry, Meera Al Hashmi

Theses

In this master’s thesis, machine learning methods are applied to predict the residual value of a vehicle, focusing on the problem of estimating the vehicle’s price after sale. The research addresses some of the most important drivers of depreciation which include market segmentation, country, region-specific details, transmission type, and some numerical values obtained through factor analysis. This is very important to the automotive industry, leasing businesses, and financial institutions. The data was collected from the open-source online marketplace Dubizzle and contains 25 variables and 62,922 cases. The initial data posed notable challenges as there were non-standardized feature values, incomplete data …

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Innovating Criminal Justice: Predictive Analytics For Effective Recidivism Management, Dina Ali Haidar May 2025

Innovating Criminal Justice: Predictive Analytics For Effective Recidivism Management, Dina Ali Haidar

Theses

Recidivism—the tendency of previously convicted individuals to reoffend—poses significant challenges to criminal justice systems worldwide. In the United States, a study by the Bureau of Justice Statistics revealed that approximately 68% of released prisoners were rearrested within three years, and 83% within nine years (Bureau of Justice Statistics, 2018). These high rates underscore systemic deficiencies in rehabilitation processes and resource allocation. Traditional risk assessment tools often rely on static factors, failing to account for the dynamic and individualized nature of reoffending risks. This limitation highlights the need for innovative, data-driven methodologies to enhance offender management strategies. This study proposes a …

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Predicting And Forecasting University Rankings In The Uae Using Machine Learning, Fatma Ibrahim Ahmad May 2025

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 …

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Ai-Driven Prediction Of Flight Cancellations: A Machine Learning Approach In Minimizing Airline Disruption, Hind Nasser May 2025

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 …

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Methods Of Quantum Circuit Simulation: A Comprehensive Comparative Analysis, Anthony Peter Bacchetta May 2025

Methods Of Quantum Circuit Simulation: A Comprehensive Comparative Analysis, Anthony Peter Bacchetta

Theses

The advent of quantum computing has ushered in a new era of computational capabilities, promising to solve problems that were previously intractable for classical computers. Quantum circuit simulation is an essential aspect of harnessing the potential of quantum algorithms, and understanding quantum systems. This thesis presents an exploration and comparative analysis of various methods used in the simulation of quantum circuits, aimed at providing a comprehensive understanding of their strengths, weaknesses, and practical applications. This starts with a dive into the foundational concepts of quantum circuits, quantum gates, and the fundamental principles underlying quantum computation. Quantum circuit simulation emphasizes the …

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Personalized Nutrition Recommendations For Arab Communities: Transforming Diet And Health Through Machine Learning, Khalfan Aldoobi May 2025

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 …

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Innovative Solutions For Data Accessibility: Utilizing Synthetic Data In Dewa Operations, Saif Khalid Alshahin May 2025

Innovative Solutions For Data Accessibility: Utilizing Synthetic Data In Dewa Operations, Saif Khalid Alshahin

Theses

Smart‑meter data are pivotal to modern demand‑side management and predictive maintenance, yet strict confidentiality rules at Dubai Electricity and Water Authority (DEWA) hinder internal access. Synthetic data generated by Generative Adversarial Networks (GANs) offers a promising privacy‑preserving alternative, potentially unlocking analytics without exposing customer information. This study assesses the ability of three GAN variants—vanilla GAN, Tabular GAN (TGAN), and Conditional Tabular GAN (CTGAN)—to replicate real consumption patterns. A publicly available \emph{Smart Meters in London} daily dataset comprising 3.51 million records was utilised. After exploratory data analysis (EDA) and cleansing, identifier (\texttt{LCLid}) and date (\texttt{day}) variables were removed, leaving seven numerical …

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Modelling And Load Frequency Control (Lfc) Design Of Microgrid Frame-Worked As Technological Norm To Multi Energy System (Mes), Mekonnen Shewarega Worku May 2025

Modelling And Load Frequency Control (Lfc) Design Of Microgrid Frame-Worked As Technological Norm To Multi Energy System (Mes), Mekonnen Shewarega Worku

Theses

In today's world, the trend of using renewable energy sources as an alternative energy source is becoming more and more common due to various driving factors, such as energy scarcity (fossil fuel depletion, etc.) and environmental issues (carbon footprint). This trend is leading to a steady increase in the penetration of renewable energy sources (RESs) through microgrid (MG), which is formed from combination of various distribution energy sources (DERs). The inherent intermittent nature of RESs coupled with abrupt load changes can instigate sustained frequency fluctuations and can keep the frequency deviation out of the allowable range that leads to an …

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Towards Vision Intelligence-Based Liver Surgery, Zixin Yang May 2025

Towards Vision Intelligence-Based Liver Surgery, Zixin Yang

Theses

Despite advancements in surgical interventions, modern procedures still heavily rely on surgeons' expertise, requiring extensive training while maintaining limited accuracy. Although image guidance systems have been developed, “GPS-like” surgical navigation systems have yet to become standard practice due to their high costs and accuracy limitations. This thesis aims to enhance surgical navigation and mitigate some of its current limitations by leveraging vision intelligence: integrating image processing, modeling, and computer vision to extract rich, underlying information from images. The key to achieving these improvements lies in improving surgical perception, which involves understanding the spatial relationships between the endoscopic camera, surgical instruments, …

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Crafting Human-Ai Collaborative Analysis For Usability Evaluations, Emily Kuang May 2025

Crafting Human-Ai Collaborative Analysis For Usability Evaluations, Emily Kuang

Theses

In the rapidly evolving domain of human-computer interaction (HCI), ensuring a high-quality user experience (UX), which encompasses all aspects of a user’s interaction with an interface, is critical to the success and adoption of technology. Central to this is the concept of usability: the degree to which an interface can be effectively, efficiently, and satisfactorily used by its intended audience. Usability testing is a key method for uncovering usability problems, relying on structured evaluations involving real users. However, traditional approaches to analyzing usability test recordings—where UX evaluators observe user behavior and verbalizations while taking notes—are labor-intensive and prone to human …

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Future Unleashed: Reimagining Marketing Strategies With Future Foresight, Afra Sultan Al Suwaidi May 2025

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 …

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Investigating The Performance Variation For Graphene-Based Field-Effect Transistor, Tzu-Jung William Huang May 2025

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 …

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Steering Through Change: How Aging Eyes And Stroke-Induced Vision Loss Affect Driver Control, Arianna P. Giguere May 2025

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 …

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Managing Software Dependency Risks In Web Applications, Christopher Alan Scott May 2025

Managing Software Dependency Risks In Web Applications, Christopher Alan Scott

Electronic Theses and Dissertations

Web applications commonly rely on third-party software dependencies to reduce development time. This thesis examines how vulnerabilities in a dependency chain propagate to compromise an application. It analyzes two vulnerable Markdown libraries from the npm and Composer dependency ecosystems, both of which are used for managing packages in applications developed with JavaScript and PHP. The analysis demonstrates how each library’s sanitizing functions—intended for removing unsafe user input when transforming Markdown text to HTML—are defeated to achieve a cross-site scripting exploit and take control of the application. The paper discusses potential business impacts of a compromise, underscoring the need for security …

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A Phenomenological Study Of String Teacher Perceptions Of Professional Development At Three Career Stages, Michael James Hanf May 2025

A Phenomenological Study Of String Teacher Perceptions Of Professional Development At Three Career Stages, Michael James Hanf

Doctoral Dissertations and Projects

This hermeneutic phenomenological study aims to understand the perceptions of elementary and secondary string teachers’ experiences with quality professional development from early-, middle-, and late-career stages. This study analyzes perceptions of quality professional development for music teachers, including content-related, evidence-based, applicable, relevant, collaborative, providing feedback, actively involving teachers in learning, longitudinal, coherent, and allowing for reflection. It follows a hermeneutic phenomenological research design guided by the theory of human motivation and aims to understand how professional development affects teacher needs. Participants include elementary and secondary string teachers across the United States from early-, middle-, and late-career stages. String teachers sampled …

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Faculty Perception Of Lean Thinking In Higher Education, Mikhail Shilov May 2025

Faculty Perception Of Lean Thinking In Higher Education, Mikhail Shilov

All-Inclusive List of Electronic Theses and Dissertations

There are many challenges that higher education institutions (HEI) are facing that include rising cost of education, reduction in student population, competition from other universities and alternative educational platforms, as well as reduction in public confidence. To stay competitive, HEIs could utilize performance improvement methods that have been proven to be advantageous in manufacturing and other industries, and one of these methodologies is Lean. Application of Lean in higher education is still in the early stages of development, the methods have been mostly used to improve administrative processes, but not as much in the core educational processes, teaching and research. …

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Fostering Creativity Through A Signature Creative Writing Pedagogy, Ryan Stone May 2025

Fostering Creativity Through A Signature Creative Writing Pedagogy, Ryan Stone

All-Inclusive List of Electronic Theses and Dissertations

This study offers a historical and conceptual lens to guide the proposed research. A historical account of creative writing in higher education and its relationship to progressive education and creative education is offered. The conceptual framework involves the development of the creative person through the primary pedagogical method within creative writing: the workshop. The research involves a qualitative phenomenological study. Methods utilized include coded observations and interviews.

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Making Of A Musical Meme: Wendy Carlos & Hector Berlioz, Alexander Ludwig May 2025

Making Of A Musical Meme: Wendy Carlos & Hector Berlioz, Alexander Ludwig

Faculty Works

No abstract provided.

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Decoding The Algorithm: The Mathematics Behind Tiktok’S Short-Form Content Success, Ashley N. Lynch May 2025

Decoding The Algorithm: The Mathematics Behind Tiktok’S Short-Form Content Success, Ashley N. Lynch

Honors Scholar Theses

Within the realm of social networks, TikTok has become the central hub for short-form video content. The network’s unique ability to capture individual preferences using predictive analytics has greatly contributed to its massive success, allowing the company to optimize its performance and content personalization. In an age where digital media have such a significant influence on society, it is essential that users develop an understanding of how social network algorithms function to make more informed online decisions. Although TikTok’s technological system is primarily undisclosed, the platform certifiably leverages several key mathematical principles within its algorithm to achieve its core goals …

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Critical Race Historical Examination Of Summer Programs: Impact On African American Youth, Megan Lee, June Hopps, Deryl Bailey May 2025

Critical Race Historical Examination Of Summer Programs: Impact On African American Youth, Megan Lee, June Hopps, Deryl Bailey

Journal of Youth Development

No abstract provided.

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