Digital Commons Network^™

Leveraging Generative Artificial Intelligence To Launch An Independent Game Studio, Douglas Evans

Theses

This project report examines how Generative Artificial Intelligence (Generative AI) can be integrated into the early formation and operations of an independent/indie game studio. Using a qualitative, practice-based single-case study approach, the project focused on Boar’s Head Studio, LLC. A human-in-the-loop approach was maintained with Generative AI used to support company formation, ideation, planning, documentation, analysis, coding assistance, marketing preparation, and community-building preparation

The report concludes that Generative AI can serve as a meaningful system integrated into the studio pipeline when used with structured, repeatable, human-in-the-loop processes. The project contributes a practical, case-based framework that may be useful to other …

Integrating Artificial Intelligence Into Academic Writing: Development Of A Student-Centered Ethical Toolkit, Matteo Landais

Theses

The rapid growth of generative artificial intelligence in higher education has introduced new challenges surrounding authorship, academic integrity, and the role of writing in student learning. While institutional responses have often focused on restriction, surveillance, and AI detection, students continue to incorporate AI tools into their writing practices in increasingly normalized ways. This project argues that the issue is not simply whether students use AI, but how they use it and whether that use supports meaningful engagement with the writing process.

This applied project proposes a process-oriented and student-centered framework for the ethical integration of AI into academic writing. Learning …

Edvard Munch And The Feminine Sublime, Saralyn Goodspeed

Theses

This paper explores the theory of the sublime in relation to Edvard Munch’s depictions of women. Departing from the common view that Munch was simply anxious about the “New Woman” that emerged in the late nineteenth-century, I argue that Munch’s conflicting emotions regarding women were sublime in nature, rooted in his childhood relationship with his mother. A formal analysis is conducted on three of Munch’s works: Inheritance (1897), Three Stages of Woman or Sphinx (1894), and Madonna (1895). These analyses link Munch’s representations of women to a maternal sublime.

Integrating Embodied Expertise Into Dress History Academia Through Practice-Led Actualistic Recreations: A New Methodology And Test Thereof, Rowan Paramour

Theses

This thesis examines the usage of practice-led methodology for historic dress recreation projects and how to implement and objectively analyze the findings from such research in an academically rigorous fashion. In section one, I examine the distinction between different types of recreation practices, the establishment of embodied practice within historic dress research, address concerns centering practice-led methodology, and develop a methodology for practice-led historic dress recreation projects and rubric for assessment of that methodology. In section two, I fully test the methodology and rubric by utilizing it in my own recreation and present this process using the methodology’s proposed deliverables …

Artificial Intelligence In Video Production, Jonathan Ringor

Theses

This project examines the role of artificial intelligence in video advertisement production and explores whether AI can help bridge the gap between everyday users and professional advertising. The project combined both creative production and audience research. To do this, three original AI-generated advertisements were created in distinct commercial formats: a pharmaceutical advertisement, a petcentered narrative commercial, and a lifestyle montage advertisement. After the advertisements were completed, audience response was measured through a survey of U.S.-based participants. Participants evaluated each advertisement on realism, emotional engagement, trustworthiness, polish, and authenticity. The results showed that the advertisements were not perceived equally. The pet …

Political Legacies Of Malcolm X, Sumair Ahluwalia

Theses

This study explores the ways in which Malcolm X’s legacy has been co-opted by various institutions and actors, including, but not limited to, politicians, historians, the general public, the federal government, and other commentators. As a result of this co-optation, Malcolm’s revolutionary ideals have been diluted or sanitized in the years since his assassination in 1965. Different approaches have been utilized to reframe Malcolm’s legacy, which include associating him with American liberalism, framing his arguments at the end of his life as markedly less radical, and external interference with popular works about Malcolm, including The Autobiography of Malcolm X. Additionally, …

Traumatic Stress Recruits An Excitatory Orbitofrontal-Amygdala Pathway To Drive Maladaptive Aggression, Mikaela Aholt

Theses

Traumatic stress is a reliable predictor of heightened aggression, yet the mechanisms linking stress exposure to aggression remain poorly understood. The Nordman lab previously found that traumatic stress activates the posterior ventral segment of the medial amygdala (MeApv) to drive persistent increases in aggressive behavior. However, why traumatic stress would engage an aggression-promoting pathway is unclear. To address this, the inputs to the MeApv were mapped and a population of excitatory, but not inhibitory, neurons in layer 5 of the medial orbitofrontal cortex (mOFC) were identified. The OFC is classically viewed as an inhibitory brake on amygdala-driven impulses, yet emerging …

Study Of Global Panel Of Soybean Accessions For Nitrogen Use Efficiency Using Association Mapping, Rita Bhandari

Theses

Soybean (Glycine max [L.] Merr.) is a leguminous crop valued for its high protein, oil content, and other essential nutrients. Global production has significantly increased, with Brazil, the United States, and Argentina being the leading producers. In the U.S., Illinois, Iowa, and Minnesota rank as the top soybean-producing states. Nitrogen (N) is a predominant nutrient required for optimal soybean growth and productivity, particularly in high-yielding varieties. While biological nitrogen fixation and soil mineral N supply part of the plant’s N requirement, synthetic fertilizers are commonly used to meet the remaining demand. However, only 30–50% of applied N is taken up …

The Developmental And Emotional Journey Of Bear Trap Garden From Proposal To Production, Mikayla Delos-Santos

Theses

Beginning with the conception of an idea and ending with a three-year reflection, this thesis outlines the creation of a full-length play: Bear Trap Garden by Mikayla Delos-Santos, which will have a production with the School of Theatre and Dance at Southern Illinois University Carbondale on April 23-26, 2026. Bear Trap Garden is a dystopian crime drama that takes place in a matriarchal society in the distant future. Emme, a bright and eager sixteen-year- old volunteers in the boys’ school. She meets Elliot, a boy who was raised outside the system by his mother, now dead, and his father, now …

Evaluation Of Otolith Microchemistry For Identifying Walleye Stocked As Fry Or Fingerlings, Joshua Fluur

Theses

Walleye (Sander vitreus) is a popular sport fish whose populations are often supported by maintenance or supplemental stocking, with most fish stocked as fry, fingerlings, or advanced fingerlings. Evaluation of stocking efficacy is important to inform decisions regarding fish stocking rates and sizes and allocating hatchery fish to locations where maintenance or supplemental stocking is most needed. Several types of artificial tags or marks have been proven useful in the identification of stocked fish, but they often have various drawbacks. Natural chemical markers in otoliths offer several advantages compared to conventional tags or marks and can be used to identify …

Indiana Bat Population Dynamics In The Midst Of Climate Change And White-Nose Syndrome, Lexie Ann Schwartz

Theses

Climate change and emerging diseases are altering species distributions and ecosystem dynamics worldwide. For temperate insectivorous bats in North America, food availability and winter climate influence hibernation energetics and survival. As climate warming alters insect phenology, these changes are likely to have an impact on hibernating bats. Many cavernicolous bats in North America are also threatened by white-nose syndrome (WNS), a newly emerged fungal disease devastating bat populations. This study examined the distribution of hibernating Indiana bats (Myotis sodalis) over time throughout their range. I used long-term weather data to simulate seasonal insect availability, the spring and autumn transitory periods, …

Navigating The Polycrisis: A Systems-Foresight Approach To Career Guidance For Generation Alpha In Dubai, Sumaiya Abdul Samad Muhammed

Theses

The global labor market is navigating a ”polycrisis” of technological disruption and macroeconomic volatility, rendering linear career trajectories obsolete. Traditional K-12 career guidance relies on industrial-era ”predict-and-place” methodologies, which fail to equip Generation Alpha for an economy defined by structural job churn. This misalignment is especially critical in Dubai, where the ambitious mandates of the Dubai Economic Agenda (D33) and Education 33 (E33) require an agile, future-ready talent pipeline. This study aimed to design and validate a foresight-driven advisory framework to replace static vocational matching with continuous futures literacy. Employing the Systemic Foresight Methodology (SFM), the research diagnosed the structural …

Like A Rolling Lychee, George Meng

Theses

I grew up in Shanghai, China—a megacity with over 25 million people. I was privileged enough to avoid the grueling fate of taking the National College Entrance Examination (Gaokao). At 16, I moved to Sewanee, a small college town in rural Appalachia with a population of only 3,000. Overshadowed by that curiosity was the collision of two worlds and my sense of belonging and identity. I wasn’t fully aware of how I watched and copied others’ behaviors and mannerisms to blend in as an adolescent. Being a minority in the middle of nowhere Tennessee meant I was conditioned into fitting …

A Machine Learning Based Analysis Of Traffic Accident Severity Using Environmental, Temporal And Road Condition Factors, Khalid Alaleeli

Theses

Traffic accidents on the road have been one of the most significant global issues as far as public safety is concerned, with the severity of crashes, as well as their fatalities, representing an undue burden on human and economic damages. The research constructs a machine learning-based model to examine and forecast the level of traffic accidents based on environmental and time, road and human variables. There were 798 valid observations and 14 variables discussing a dataset using the exploratory data analysis tool, supervised classification models (Decision Tree and Random Forest), and unsupervised K-Means clustering. The technique of feature engineering was …

أثر الفيتو على فعالية مجلس الامن في النزاعات الدولية المعاصرة "دراسة تحليلية", محمد سلطان الكويتي

Theses

The Impact of the Veto on the Effectiveness of the Security Council in Contemporary International Conflicts: "An Analytical Study"

The League of Nations, which was established in 1919 after World War I to maintain peace, failed in its mission. Therefore, in 1945 the victorious allies established the United Nations through San Francisco Conference on June 25, 1945. This was followed by the establishment of the Security Council, with its primary responsibility in maintaining international peace and security. The establishment of the Security Council represented a tremendous hope for achieving world peace after the horrors of World War II. However, The …

Predicting Flight Fares With Machine Learning: Enhancing Aviation Industry Pricing Forecasting, Reem Almulla

Theses

This research investigates the increasing challenge of accurate flight fare prediction for travel agencies that are functioning and working in the post-pandemic aviation market. As the prices fluctuate while demand is unstable and competition pressure increases, therefore it influences decision-making and profitability. In most cases, traditional ticket pricing methods often can be ineffective when capturing complex and non-linear relationships within factors that influence the ticket fare dynamics. As a result, highlighting the urge of more adaptive pricing and data-driven predictive machine learning models. In response to this challenge, the research examines the effectiveness of machine learning techniques for enhancing flight …

Evaluating Smart Mobility Performance In Dubai Using Airport Flight Operations Data: A Data-Driven Approach, Hamda Alshamsi

Theses

Airports are more than aviation facilities; they function as critical nodes within modern urban mobility systems. In globally connected cities such as Dubai, airport performance directly influences tourism, trade, economic activity, and the overall efficiency of the transport network. At the same time, airports generate large volumes of detailed operational data on a daily basis. However, this information is often summarized into high-level statistics that do not fully capture temporal variations, congestion patterns, or operational reliability. This thesis investigates how flight-level operational data can be used to evaluate airport mobility performance in Dubai within a smart city context. The study …

Designing A Uae-Centric Integrated Mobility System: Linking Transport,Traffic, And Urban Data For Smarter Travel, Alreem Jabir Alshamsi

Theses

Urban mobility systems are central to smart city performance; however, in many rapidly developing cities, mobility services remain fragmented across agencies, platforms, and datasets. In the United Arab Emirates (UAE), cities such as Dubai and Abu Dhabi have made significant investments in digital infrastructure and intelligent transport solutions. Despite this progress, existing mobility applications continue to operate in functional silos, limiting real-time adaptability and cross-domain integration. Current platforms primarily focus on transport coordination and congestion avoidance, with limited integration of broader urban datasets such as building access schedules, environmental conditions, and localized service availability. This research addresses the absence of …

Optimizing Product Placement Using Purchase Pattern Analysis, Mohra Shamaa

Theses

Retail product placement has traditionally relied on static shelf layouts and techniques such as market basket analysis, often guided by managerial intuition and category based organization. However, such approaches frequently overlook the complexity of consumer purchasing behavior as reflected in the transactional data, and this study investigates how data driven analysis of purchase relationships can inform more effective product placement strategies in physical retail environments. Unlike the sequential models, this study focuses on co occurrence relationships due to dataset constraints, prioritizing interpretability for retail applications. Using transaction level data from the Instacart dataset, this research applies association rule mining through …

Mathamr+: A Unified Graph Neural Network Framework For Multimodal Mathematical Information Retrieval, Jacob Yoon

Theses

Mathematical Information Retrieval (MIR) focuses on developing systems that enable users to search for and retrieve documents containing mathematical content. A key challenge in building effective math-aware retrieval systems lies in jointly modeling the symbolic and operational structure of mathematical expressions together with their surrounding linguistic context. Existing approaches often use linear token sequences, losing structural information, or rely on separate models for text and math, limiting their ability to capture cross-modal patterns and learn contextualized representations. This thesis proposes MathAMR+, a graph neural network-based retrieval framework that jointly models Abstract Meaning Representation (AMR) graphs, Operator Trees (OPTs), and Symbol …

Inverse Laplacian Solution For Spherical Harmonic Decomposition Of Black Hole Initial Data, Nikolaus Vernon Kent

Theses

In the construction of initial data, by way of describing one or more black holes for Numerical Relativity, solving the Hamiltonian Constraint remains a fundamental challenge, as the presence of coordinate singularities in the so-called "puncture" formalism often complicates traditional grid-based numerical methods. This thesis addresses this challenge by developing a semi-analytical framework based on an iterative spherical harmonic modal expansion. We begin by decomposing the source term of the Hamiltonian Constraint, given in terms of the extrinsic curvature, into a basis of spherical harmonics. To navigate the non-linearity of the governing equation, we implement an iterative scheme derived from …

Assessing Programmatic Gaps In The Community Engagement To Reduce Victimization (Cerv) Program, Sam Marino

Theses

This capstone project examines and analyzes data for the Community Engagement to Reduce Victimization (CERV) program in Rochester, New York. By developing a logic model, gap analysis, and utilizing statistical models, the project not only better understands the program design, but also assesses gaps and their patterns in the data to provide structured recommendations to strengthen the data infrastructure, improving data completeness and reliability. These improvements will strengthen the program overall, helping to reduce community violence throughout Rochester. Across three working papers, the project begins by examining the current data and analyses on the program and develops a detailed logic …

Personalized Design Learning Paths Using Artificial Intelligence, Rahma Al-Assaf

Theses

Design education attracts students with highly diverse visual spatial abilities, prior experiences, and preferred learning styles. However, most design programs continue to place all first-year students into the same foundational courses, which can lead to cognitive overload for beginners and insufficient challenge for advanced learners. This dissertation investigates how the use of artificial intelligence (AI) can support more personalized placement by integrating diagnostic sketching assessments with validated learning-style measures. The study collected 101 primary sketches from students who are interested in the field of design. The dataset is expanded to 600 images using synthetic augmentation to ensure balanced and enough …

This Moon In Your Throat, Hankyung Ryu,

Theses

This Moon in Your Throat examines the concept of Han, a haunted and inherited Korean affect that moves across bodies, generations, and diasporic life. Rather than treating Han as a fixed emotion, this thesis understands it as a lasting force shaped by historical trauma, family memory, and the unfinished effects of colonialism, war, capitalism, and displacement. Drawing on hauntology, the project asks how the past remains present through sensation, habit, bodily tension, and emotional atmosphere, especially in the lives of Koreans living in the United States. Night serves as the project’s spatial, temporal, and emotional ground, a setting in which …

The University Of 2035: Rise Of On-Demand Learning And Alternative Credentials, Abdalla Bassaleh

Theses

Higher education is changing fast with new technology, shifting job market needs, and the growing popularity of alternative learning options like executive education, microcredentials, and short-term programs. Traditional degrees still matter, but flexible, industry-focused credentials are often seen by employers as more in tune with what the workforce needs. This study examines how universities in the United Arab Emirates (UAE) can integrate microcredentials into their institutional frameworks to stay competitive by 2035. It addresses a gap in UAE-centered research by combining stakeholder data with a structured foresight analysis. The research reviews national policy documents, including the UAE National Strategy for …

Ai In Action: Redefining Loan Default Prediction For The Digital Lending Era, Joe Vinson Ukken

Theses

Credit risk assessment remains a very important part of financial institutions, particularly within the rapidly evolving digital lending environment. The research explores the effectiveness of five machine learning models—Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, and Support Vector Machine—in predicting loan default using both financial indicators and categorical borrower attributes. The study is motivated by the growing availability of structured borrower data and the need to evaluate whether advanced machine learning algorithms can be implemented over conventional credit scoring methods. A publicly available L&T Vehicle Loan Default Prediction dataset comprising 233,154 borrower records and 41 structured attributes, the CRISP-DM …

The Emergent Wild, Allen Douglas

Theses

This thesis investigates a shift from the structured, approval-driven process of illustration to a more exploratory and intuitive painting studio practice. While my training has emphasized careful planning and technical precision, it has also limited spontaneity and material engagement. In response, I adopt a process-driven approach that privileges improvisation and material agency, repositioning painting as a site in which control is negotiated rather than maintained. This change marks not only a methodological departure but an internal reorientation—from adherence to external standards toward a more self-directed and responsive mode of making. The expansion of my visual universe—through expressive mark-making, increased ambiguity, …

The Efficacy Of Ethical Data: An Analytical Study By, Lamar Gebara

Theses

As artificial intelligence and machine learning models become increasingly embedded in decision-making systems across industries, questions about the ethical sourcing of data have grown more pressing; model performance relies heavily on vast, diverse datasets, many of which are harvested without consent, transparency, or equitable representation. This study aims to compare analytics outcomes (accuracy, bias, fairness, and explainability) between ethically sourced and unethically sourced datasets. Using CRISP-DM methodology, the study will develop matched classification models on both dataset types, evaluate their performance and fairness using open-source tools such as Fairlearn and AIF360, and assess broader implications for trust, accountability, and regulatory …

An Evidence-Based Ethical Risk Classification Framework (Ercf) For Ai Policies, Ahmad Almarri

Theses

This thesis develops and evaluates an evidence-based Ethical Risk Classification Framework (ERCF) for analyzing substantive ethical engagement in AI policy documents. The study addresses the gap between high-level AI ethics principles and reproducible computational methods for comparative governance analysis. A secondary dataset of AI ethics policy recordswas used as the starting point. After retrieval, text extraction, and validation, a corpus of 44 policy documents was constructed from an initial 112 records (110 link-bearing entries). Supervised classification was implemented for four core dimensions: Accountability, Bias & Fairness, Privacy, and Transparency. A TF-IDF + Logistic Regression baseline was evaluated using stratified 5-fold …

Tom: Toward A Design Language For Object Personality, Mike Minerva

Theses

Design has been chasing seamless efficiency for decades, creating smoother interactions, more compliant objects, and experiences that disappear entirely. When an object is frictionless, it does not lack personality. It has a personality. One that is obedient, meaningless, and remarkably boring. An object that pushes back has boundaries, and that resistance comes from a position of caring. Objects have always been able to refuse. What is new is that the refusal can now come from inside the object, from memory, adaptive thinking and a disposition toward the person using it. Expressed consistently over time, that agency is perceived as personality. …