Digital Commons Network^™

Summit Disease: The Ecological Horror Of Empire, Nicholas Moore

Theses

This project focuses on the use of insect imagery in art and media and the theories and concepts that have been instrumental in understanding the cultural and political significance of insect species extinction and decline. I center my work on the concept of ecohorror and highlight several artists whose work depicts insect species and conveys anxieties over ecoprecarity and climate dysfunction. I argue that depictions of insects in art and media can be interpreted in two ways - insects as destructive, monstrous contaminants and insects as constructive, beneficial terraformers - and I rely on Hayao Miyazaki’s Nausicaa of the Valley …

The Transformative Impact Of User-Created Mods Within Fallout: New Vegas, Tanner Webb

Theses

Video game modding is one of the fastest growing trends in the gaming industry and it is changing how players interact with games. Review of current literature and research shows that these modders are an integral part of the gaming market. Using the principles of participatory culture and digital aesthetics, this research investigates how modding practices serve as both a form of creative expression and an inspiration for technological innovation within the video game industry. Video game modifications serve as catalysts for creative expression, foster the development of innovative user communities, prolong the life of game titles, cultivate a pool …

Nextgen Humanities: A Digital Art History Pedagogical Revolution, Analisa Soverns-Reed

Theses

In response to the urgent need for more accessible, inclusive, and technologically relevant humanities education, the NextGen Humanities project was conceived as a digital initiative to reimagine pedagogical practices within art history and the broader humanities. Traditional perceptions of humanities disciplines as elite and static have contributed to declining engagement, necessitating innovative solutions that integrate open-access resources, digital tools, and inclusive frameworks. This project developed a publicly accessible platform curating free, vetted resources grounded in artificial intelligence (AI), virtual reality (VR), and open educational resources (OER), emphasizing critical engagement, cultural inclusivity, and technological adaptability. Methodologically, NextGen Humanities combined extensive literature …

A Systematic Literature Review Of Behavior Analysis In Psychiatric Inpatient Settings, Stephanie Henry, Robbie Hanson

Theses

Applied behavior analysis (ABA) may be best known for the treatment of individuals with intellectual or developmental disabilities, such as those with autism spectrum disorder (ASD). However, ABA also has a long history of effective outcomes with other populations, such as with individuals who are admitted to inpatient psychiatric facilities (Dougher, 2004; Harvey et al., 2009). In 2018, 187,877 individuals in the United States were reported as receiving treatment for mental health disorders (Lutterman, 2022). Given behavior analysis’ success implementing operant procedures with these populations, an updated review of the literature on the use of behavior analysis within these settings …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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, …

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 …

Proactive Approach To Identify And Mitigate Cybersecurity Threats In Smart Building Using Ai, Shayma Abdulla Alhayyas

Theses

Smart buildings form a cornerstone of modern urban development. The integration of Internet of Things (IoT) devices in buildings has revolutionized facility management, improving system intelligence and user experience. However, these smart devices also introduce cybersecurity challenges and risks. The initiative "Identifying and Mitigating Cybersecurity Threats in Smart Building using AI" focuses on leveraging advanced artificial intelligence (AI) to address and mitigate cybersecurity threats within smart buildings. This study integrates predictive analytics, deep learning, and machine learning to identify and prevent cyberattacks, protecting sensitive data and networked IoT devices. By analyzing previous attack patterns, network behaviors, and potential vulnerabilities, this …

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 …

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 …

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 …

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 …

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 …

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 …

A Computational Framework For Investigating Novel Bacterial Conjugation Inhibitors, Serena Tuytschaevers

Theses

Antimicrobial resistance (AMR) is a major global threat, contributing to an estimated 700,000 deaths annually. One of the main ways that AMR genes spread among bacteria is through conjugation. Therefore, it is crucial to develop conjugation inhibitors (COINs) to combat AMR. Shared characteristics between known COIN molecules are a hydrophobic tail, unsaturations, and a polar head. Considering these characteristics and accounting for the efficacy of 2-hexadecynoic acid and Tanzawaic Acids (TZAs) low toxicity, we designed a new set of TZA analogs. The predicted protein target of previously identified COINs is TrwD, an ATPase in the type IV secretion system (T4SS). …

Protpen: A Pipeline That Combines Sequence- And Structure-Based Approaches To Predict Protein Functions, Diya Mathai

Theses

Proteins of unknown function represent a significant gap in our understanding of biological processes, with many organisms, especially prokaryotes, harboring large portions of their proteomes that remain uncharacterized. For example, in Pseudomonas aeruginosa, a major human pathogen, a large proportion of proteins are categorized as unknown or hypothetical in function. The precise number varies across species, but studies have shown that up to 30–50% of proteins in bacterial proteomes can lack functional annotations. Addressing this gap is critical to understanding the biology and pathogenicity of such organisms. Recent advancements in computational tools, particularly those in sequence and structure-based prediction, offer …

Application Of Science And Technology Studies To Global Medical Device Donation Policy, Jolie Crunelle

Theses

In low and middle income countries, the World Health Organization estimates that nearly 80% of medical devices and equipment are procured through donation (WHO 2000). While these donations have the potential to play a critical role in the recipient communities’ health, the donated devices sometimes fall short of their potential due to improper use or lack of support—despite the existence of a variety of guidelines and regulations for medical equipment donations. While conducting volunteer biomedical equipment technician work in Guatemala and Uganda, I came to notice the disparity between the guidelines and the reality on the ground. This study aims …

Combination Of Hdac And Fyn Inhibitors In Synovial Sarcoma, Kyra Parker

Theses

The SS18-SSX fusion protein is an oncogenic driver in synovial sarcoma. At the molecular level, SS18-SSX functions as both an activator and a repressor to coordinate transcription of different genes responsible for tumorigenesis. Here, we identify the proto-oncogene FYN as a new SS18-SSX target gene and examine its relation to synovial sarcoma therapy. FYN is a tyrosine kinase that promotes cancer growth, metastasis and therapeutic resistance, but SS18-SSX appears to negatively regulate FYN expression in synovial sarcoma cells. Using both genetic and histone deacetylase inhibitor (HDACi)-based pharmacologic approaches, we show that suppression of SS18-SSX leads to FYN reactivation. In support …

Enhancing Pedestrian Safety Around Jacksonville State University: A Gis-Based Perception And Crash Analysis, Husain O. Alegimenlen

Theses

This study uses a Geographic Information Systems (GIS) based approach to assess pedestrian safety around Jacksonville State University (JSU) by combining vehicle crash data with perception surveys from 111 pedestrians and 97 drivers. The research identifies high-risk areas, explores contributing factors, and recommends targeted safety improvements.

A total of 209 geocoded crash records (2021 to 2024) were analyzed using Kernel Density Estimation (KDE) and hotspot analysis in ArcGIS Pro. Crash clusters appeared along Pelham Road North and Mountain Street, marking key vehicular risk zones. Three major pedestrian danger areas were found: (1) Nisbet Street NW and Cardinal Lane NW, (2) …

Flood Risk Assessment In Humanitarian Contexts: A Remote Sensing And Gis Methodology Applied To Nyarugusu Refugee Camp, Tanzania, Carolyne Vincent Mbirika

Theses

Flooding is a global challenge, with effects mostly experienced in developing countries due to insufficient data for effective flood risk assessment and management. Refugee settlements are particularly vulnerable to flooding due to their remote locations, high population density, and temporary shelters, necessitating flood susceptibility mapping to effectively mitigate risks and minimize damage prior to flooding events. This study assessed flood susceptibility in the Nyarugusu refugee camp, Tanzania, through Multi-criteria Decision Analysis (MCDA) and Analytical Hierarchy Process using remote sensing and Geographic Information Systems (GIS) approaches. The flood susceptibility map that resulted from this process categorizes flood-prone areas into three classes: …