Digital Commons Network^™

Analyzing Northwest Ohio Industries And Utilizing The Shape Program To Increase Sustainable Practices, Abigail Stucker

Honors Projects

The purpose of this project is to dive deeper into the corporate perspective on sustainability and why manufacturing companies should take action on such an important topic. Is there a true balance for businesses between increasing profits and reducing waste? Why should businesses care about being branded as a sustainable company? What efforts do companies need to take to truly be branded as “sustainable?” These are questions that drove the research and development of this project. After looking into these guiding questions, this project develops a program to help monitor and measure the successful sustainability practices that various Northwest Ohio …

Stereotyping In Language (Technologies): An Examination Of Racial And Gender Stereotypes In Natural Language And Language Models, Messi Lee

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation examines stereotyping across natural language and language technologies through three interconnected studies. The first chapter applies a contemporary model of race relations from social psychology to investigate America's racial framework within American English, revealing how language encodes hierarchical associations between racial/ethnic groups and attributes of superiority and Americanness. The second chapter extends this analysis to Large Language Models (LLMs), finding that these language technologies portray socially subordinate groups as more homogeneous compared to dominant groups. The third chapter investigates stereotyping in Vision Language Models (VLMs), showing that these language technologies generate more uniform representations for women than men …

2025 Academic Conference Program

Holy Cross Undergraduate Academic Conference

No abstract provided.

Predicting The Unpredictable: Predicting The March Madness Champion Using Statistical Modeling, Jack Sweeney

Honors Projects in Information Systems and Analytics

One of the more exciting and hardest parts of the men's college basketball postseason tournament, named March Madness, is to pick who wins each game and determine the overall champion of the tournament. The data analysis conducted will help determine the overall tournament winner. A machine learning model is implemented using college basketball metrics from previous years to determine the overall winner of this prestigious tournament in 2025. The model was able to pick up the winner in 2024. The result also finds that the most important features in determining the winner of the tournament are shooting guard height, small …

Technology Anxiety In Virtual Reality Adoption: Examining The Impact Of Age, Past Experience, And Cybersickness, Eman Al Khalifah, Ramy Hammady, Mahmoud Abdelrahman, Ons Al-Shamaileh, Mostafa Marghany, Hatana El-Jarn, Alyaa Darwish, Yusuf Kurt

All Works

This study examines the role of Technology Anxiety (TA), age, past use, and cybersickness in the adoption of Virtual Reality (VR) technology. Using an extended Technology Acceptance Model (TAM), the research integrates age and past use as antecedents of TA and evaluates their influence on perceived ease of use (PEoU), perceived enjoyment (PENJ), and user attitudes. Data from 206 participants were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM) following a VR pilgrimage experience. The findings challenge conventional assumptions, revealing that past VR use increased TA, contradicting prior studies that associate familiarity with reduced anxiety. Additionally, older users exhibited …

Perceptions Of Employability With Ai Skills, Brandy Whitford, Patrick J. Cooper

Student Publications and Presentations

Artificial intelligence (AI) is making AI proficiency a key factor in hiring and career advancement. By late 2023, 75% of knowledge workers integrated AI into their workflows, with 92% reporting increased productivity and creativity (Kimbrough, 2024). Employers are adapting—66% prefer candidates with AI expertise, and 77% consider AI skills essential for career growth (Microsoft & LinkedIn, 2024). However, hiring biases related to AI-skilled applicants remain underexplored, particularly concerning gender disparities in employability perceptions. This study examines how AI-related skills influence perceived employability and whether these perceptions vary based on applicant gender. Specifically, it explores whether AI-skilled female applicants receive higher …

Optimizing Aircraft Taxi Processes: A Novel Cost-Minimizing Queue Discipline For The Pushback To Runway Process, Kevin James

Theses and Dissertations

Optimization of the aircraft taxi process can significantly decrease operating costs for air carriers, especially at major airports where congestion on the ramp is a primary contributor to taxi times. To improve the efficiency of this process, we propose a novel queue discipline which mitigates pushback delays through a dynamic reordering of clearance deliveries. As an alternative to FIFO, the proposed discipline accounts for aircraft delays at the gate before the aircraft enters the queueing system. Our proposed system implements pushback control to allow for controller-imposed variability in runway queueing. To validate our proposed queue discipline, we provide a computational …

Enhancing Animal Shelter Operations With Time Series And Machine Learning, Sakava L. Kiv, Donald L. Anderson, Shivam Negi, Jacquelyn Cheun

SMU Data Science Review

Enhancing animal shelter operations through machine learning involves employing a variety of advanced techniques aimed at increasing efficiency, promoting animal welfare, and optimizing resource allocation. This paper explores predictive analytics for adoption rates using regression models to estimate the likelihood of adoption based on historical data, encompassing variables such as breed, health status, and previous adoption trends. Additionally, classification algorithms are utilized to categorize animals by adoption probability, facilitating better resources and marketing prioritization. Clustering algorithms are employed to group animals according to behavior patterns and/or physical health, enabling tailored medical care and enrichment activities that improve their mental and …

The Evolution Of Russian And Chinese Disinformation Tactics And The Threat They Pose To The U.S. Cybersecurity, Jehovani Sese

Cybersecurity Undergraduate Research Showcase

This paper aims to discuss how disinformation has become the most powerful tool used against the United State by foreign operatives. Of these foreign operatives, Russia and China have shown the ability to use advanced tactics to truly affect the United States security. Often these tools came in the form of state-sponsored media, influence campaigns and fake online identities. This literature review explores the evolution of Russian and Chinese disinformation tactics, examining how these approaches have changed over time and become more sophisticated. This paper will highlight major campaigns which use tools such as bot networks, and social media manipulation. …

Climate Change Adaptation Through Economic Democracy, Shriraksha Mohan

Best Integrated Writing

Mohan investigates and combines three different areas of literature and social movements to discuss the problem of climate change and economic adaptation. The value of this work is that it can be used to communicate among three independent types of social movements and inquiries. This can strengthen and connect dispersed yet overlapping efforts in addressing work issues, resource utilization, economic governance and participation, and ecological problems economies face today.

Identifying The Factors Affecting The Survival Of Trauma Patients Using Logistic Regression Analysis, Maggie Smith

Honors College Theses

There is a broad interest among researchers and clinicians in identifying factors affecting clinical outcomes of patients with physical trauma. Numerous factors affect Hospital Discharge Status (HDS), one of the main binary outcome variables of trauma patients. Logistic regression is one of the widely used methods to analyze relationships between a set of predictors with a binary outcome. In this study, a logistic regression model is built for HDS. Predictors include arrival time, age, trauma level, injury severity score, arrival heart rate, arrival blood pressure, length of hospital stay, time from injury to arrival at Billings Clinic (BC), patient transfer …

Grm-120 Coding Neurodivergent, Veronica Bramlett

C-Day Computing Showcase

This literary research provides a look at neurodivergent individuals learning coding, specifically Python, and the struggles and benefits that come from the way their brains are wired. This literature research was conducted to look at the benefits and struggles of learning to code as a neurodivergent individual. One area that has not been studied extensively is the learning of Python, or coding in general, by neurodivergent populations. This includes the benefits a neurodivergent learner may glean from learning Python as well as the challenges they may encounter - anything which makes their experience different from that of a neurotypical Python …

Ur-031 Impact Of Motor Skill On Learning Experiences And Outcomes Using Note-Taking In Vr, Sawyer Strickland

C-Day Computing Showcase

Immersive learning experiences have been proposed to offer rich immersion and interaction, effectively addressing the distractions and low engagement commonly found in typical online learning environments. Research in neuroscience and psychology suggests that motor skills, such as note-taking, help students improve their learning by enhancing cognitive abilities and decision-making, ultimately leading to better performance. This study aims to investigate the impact of motor skills, specifically note-taking with a physical VR stylus, on learning experiences, outcomes, and retention in our VR classroom environment.

Ur-099 Empowering Mental Wellness: A Comprehensive Study And Design Of A Predictive System For Early Mental Health Intervention​, Anh Duong

C-Day Computing Showcase

Mental health is an essential part of living a balanced and fulfilling life, but it is often overlooked compared to physical health. While physical health is important for performing daily activities, mental health plays a crucial role in how we manage stress, build connections, and make decisions. Previous research studies have shown that nearly 60 million Americans experienced a mental illness in 2024, yet there were only 340 people for every one mental health provider in the U.S. Furthermore, young adults aged 18–25—who are the most digitally connected generation—suffer from the highest rates of severe mental illness yet are the …

Ur-112 Monarch: A Privacy-Focused Nlp Model For Emotional Pattern Detection, Tyler Clanton, Derick Burbano-Ramon

C-Day Computing Showcase

Introducing: Monarch — a privacy-focused deep learning model that interprets emotional patterns in text. Monarch is trained on large, lexicon-based datasets and uses fine-tuned NLP models (BERT) to identify patterns associated with sadness, worry, anger, and distress. It runs entirely offline with no data collection, making it ideal for private use. Monarch evaluates text and returns clear, readable probability scores across emotional categories, giving users insight into emotional trends. Monarch is interpretive, not diagnostic, displaying results based on scientifically backed linguistic patterns. Its potential use in schools could help flag early signs of distress, giving educators a chance to support …

Ai Assistance In Legal Analysis: An Empirical Study, Johnathan H. Choi, Daniel Schwarcz

Journal of Legal Education

No abstract provided.

Ai & Xr Explorations To Support Social Interactions: Speculative Design For Ubiquitous Workplace Space By And For Neurodivergent Employees, Dominique Michaud, Alejandro Reyes, Jonathan Proulx Guimond, Fafadzi Akpene Agbe, Valérie Payen, Diane Gabrielle Tremblay, Marie Claude Leblanc, Claude Vincent, Geoffreyjen Edwards, Caroline Brassard, Marie Helene Parizeau, Valéry Psyche, Martin Caouette, James Hutson, Piper Hutson, Julie Ruel, Julien Voisin, Jocelyne Kiss

Faculty Scholarship

This study explores the potential of interdisciplinary theories and advanced technologies, such as augmented realities and artificial intelligence, to address the socio-professional integration challenges faced by neurodivergent individuals, particularly those on the autism spectrum. It investigates the design of personalized, functional spaces that integrate interconnected living environments and intelligent systems tailored to support communication needs. Using speculative design methodology, the research adopts an experiential framework to examine alternative solutions, starting with a central hypothesis and testing it through debates with researchers, experts, neurodivergent individuals, and knowledge users. The premise is rooted in the recognition that neurodivergent individuals encounter significant barriers …

Phishing Attacks And Prevention, Ruth Johnson

Cybersecurity Undergraduate Research Showcase

Phishing attacks have been the number one leading cause of identity theft and financial theft since 1990. The internet is one of the leading places where individuals’ identity is stolen. Many businesses and government agencies have been at risk of cyber phishing attacks from foreign countries. Attacks on Several U.S. federal government agencies have been hit in a global cyberattack by Russian cybercriminals that exploit a vulnerability in widely used software, according to a top us cybersecurity agency (Lyngaas, Government hit cyber-attacks, 2023).

Phishing attacks are cybercrimes where one or many individuals steal sensitive information like passwords, credit card information, …

Perceptions Of Ai Skills In Resumes, Brandy Whitford, Patrick J. Cooper

Faculty and Staff Publications & Presentations

No abstract provided.

Bryant University Research And Engagement Day Program

Bryant REDay (Research and Engagement Day)

No abstract provided.

Looking Good: The Math Behind Computer Vision*, Corbin Weiss

Campus Research Month

Exploring the mathematical foundations of a Multilayer Perceptron (MLP), a foundational approach to computer vision. Then expanding this understanding to create a visualization of the representation of reality in the MLP.

The Fear Of Replacement: How Ai Panic In Journalism Mirrors Existential Crisis In Industry, James Hutson

Faculty Scholarship

This study systematically examines the portrayal of artificial intelligence (AI) errors, such as hallucinations and deepfakes, in journalistic contexts, evaluating whether these narratives reflect a broader existential anxiety about AI's role in reshaping journalism. Using a systematic literature review combined with a qualitative content analysis of recent AI-focused news reports, this study identifies recurring themes in media coverage to assess the accuracy and context of reported AI errors relative to actual technological limitations and affordances. Findings suggest that while AI errors are comparatively rare, they receive amplified coverage, often fueling public mistrust in AI technologies. Nevertheless, a balanced examination reveals …

Bringing Different Disciplines And Competitions In Your Classroom, Eric Chan-Tin, Mohammed Abuhamad

Computer Science: Faculty Publications and Other Works

It is well-known that cybersecurity does not belong only to computer science/engineering. Other disciplines such as Psychology, Criminal Justice, Sociology, and Political Science can have a great impact in cybersecurity research and education. Students taking only courses are at a disadvantage and should be encouraged to participate in cybersecurity competitions to obtain real-world skills. This lightning talk will look at incorporating two aspects in an interdisciplinary cybersecurity program/curriculum: 1) different disciplines and majors such as Psychology, Criminal Justice, Political Science, Sociology into the cybersecurity program; and 2) including cybersecurity competitions as an integral part of the cybersecurity classroom and curriculum. …

Ai In Academia: Supportive Ally Or Cheating Accomplice?, Ian Offner

INSPIRE Student Research and Engagement Conference

• The purpose of this study was to investigate student attitudes toward the use of AI for college class work in a variety of domains.
• For some situations, the use of the AI was collaborative. The students would have to utilize their own abilities in conjunction with the AI as a co-intelligence. For some situations, the AI was a dominant agent, requiring little input from the students.

Evaluating Wrist Placement And Signal Processing Techniques For Real-World Hrv Monitoring Using Ppg, Andrew Murphy

College of Computing and Digital Media Dissertations

This thesis investigates trade-offs between signal quality and data coverage in photoplethysmographic (PPG) heart rate variability (HRV) monitoring using wrist-worn devices. The goal was to evaluate whether wrist placement and signal processing techniques can improve measurement reliability in real-world conditions. Data was collected from healthy participants wearing smartwatches on both wrists during rest and a structured math task introducing natural wrist movement. Three distinct processing methodologies were compared, including a proposed Rolling-Standardized Derivative (RSD) approach. Results showed that while HRV signals from both wrists were highly correlated at rest, motion caused a measurable drop in signal quality and inter-wrist agreement, …

Living With Alzheimer’S: A Guide To How To Lower The Risk Of Memory Loss & Care For Those With Alzheimer’S, Mona Muzammil, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Despite the frequent characterization of Alzheimer's disease as a “loss of self,"" this enlightening book demonstrates unequivocally that a person's unique self persists throughout the course of the disease. The important message in Caring for People with Alzheimer’s is how much can be done in care settings to support a person's sense of identity and thereby enrich the lives of people experiencing the many losses associated with dementia. Drawing from a diverse body of research, this book brings together the recommendations of the best thinkers and practitioners in multiple disciplines to illustrate the meaning of self and the importance of …

Tiny Creatures, Big Lessons: Using Music Education And Ecoliteracy To Impact Young Learners' Perspectives On Bugs And Nature, Paige Burgess '25

Honor Scholar Theses

This thesis aims to demonstrate that relationships between students and nature can be improved through teaching young learners about music and bugs together, potentially leading to a greater overall love for and willingness to protect nature. The thesis features original teacher action research conducted over multiple weeks in a first grade classroom, with observations and data to support the efficacy of the methods discussed. This thesis analyzes literature that supports how increasing empathy toward bugs at a young age can have tangible benefits for the environment, how ecoliteracy as a framework is an effective means of teaching about nature, and …

From Adversarial Attacks To Robust Classifiers - A Study In Social Media Spam Detection - Black Box & White Box, Jonathan Jose Penaloza Rumie

Undergraduate Theses

Adversarial attacks pose a significant threat to the reliability of machine learning-based spam detection systems in social media. This undergraduate thesis, "From Adversarial Attacks to Robust Classifiers: A Study in Social Media Spam Detection – Black Box & White Box," systematically examines the impact of both black-box and white-box adversarial attacks on a range of spam classifiers, including Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Bagging, Gradient Boosting, and Support Vector Machines. Leveraging a novel dataset derived from Twitter spam messages and enhanced with adversarial perturbations such as synonym replacement and character-level modifications, this study evaluates classifier performance under …

A Neutrosophic Micro Vague Correlation Measure: Application To Multi-Criteria Decision Making Problems, Vargees Vahini T, Trinita Pricilla M

Neutrosophic Systems with Applications

Statistical methods called correlation measures are employed to express the degree of association or relationship between two variables. The correlation coefficient which may be computed in a variety of ways is the most often used kind of correlation measure in many disciplines including biology, psychology, economics, and finance. Knowing the correlations between variables is essential for analysis and decision-making. This paper aims to commence a novel type of correlation measure called Neutrosophic Micro vague Correlation Measure and Neutrosophic Micro Vague Weighted Correlation Measure. Further demonstrates the implementation of the Neutrosophic Micro Vague correlation measure in the MCDM Problem. By adopting …

A Neutrosophic Micro Vague Correlation Measure: Application To Multi-Criteria Decision Making Problems, Vargees Vahini T, Trinita Pricilla M

Neutrosophic Systems with Applications

Statistical methods called correlation measures are employed to express the degree of association or relationship between two variables. The correlation coefficient which may be computed in a variety of ways is the most often used kind of correlation measure in many disciplines including biology, psychology, economics, and finance. Knowing the correlations between variables is essential for analysis and decision-making. This paper aims to commence a novel type of correlation measure called Neutrosophic Micro vague Correlation Measure and Neutrosophic Micro Vague Weighted Correlation Measure. Further demonstrates the implementation of the Neutrosophic Micro Vague correlation measure in the MCDM Problem. By adopting …