Digital Commons Network^™

Specialization Or Diversification? Creators’ Strategies On User-Generated Content Platforms, Ziwei Ye

Theses and Dissertations in Business Administration

Recent advancements in digital platforms have reshaped content creation and distribution. User-generated content (UGC), created and shared by internet users, is transforming entertainment, communication, and information sharing. The rise of UGC has fueled the growth of the "creator economy"—an ecosystem of creators, users, and advertisers facilitated by platforms such as YouTube and TikTok. While prior research has primarily explored how UGC platforms incentivize content quantity and quality, this study advances the literature by examining how creators' content strategies influence consumer attention and how platform mechanisms shape this relationship, offering new insights into the interplay between creator behavior and platform design. …

Evidence For Distal Bolide Impact And Tsunami Deposits In The Upper Atlantic Coastal Plain Of Moore County (North Carolina, Usa) Generated By The Eocene Chesapeake Bay Bolide Impact, G. Robert Ganis, Ralph H. Willoughby, David J. Cicimurri, G. Richard Whittecar, Steven J. Hageman

OES Faculty Publications

Beds interpreted as Eocene bolide-generated impact and tsunami deposits occur at Paint Hill in the Upper Atlantic Coastal Plain of Moore County, North Carolina, USA. These strata, herein named the Mount Helicon Formation, consist of four distinct beds comprising about one meter of total section. Bed 1 (the basal bed) is approximately 43 cm thick and consists of sandy carbonaceous clay with carbon glass and rock fragments and contains 14-18 parts per billion (ppb) iridium (interpreted as bolide impact ejecta). Bed 2 is approximately 9 cm thick and consists of non-cohesive silt-size particles and loosely bound sand-size accretionary lapilli-like masses …

Investigating The Ability To Perceive Nonverbal Behaviors In Different Interaction Formats, Amanda J. Ashdown

Psychology Theses & Dissertations

The rapid rise in interactive video-based communication has raised important questions about how it affects the perception of nonverbal behavior and impression formation. Guided by the Parallel Process Model (PPM), Multiple Resource Theory (MRT), and Working Memory (WM) models, this study investigated the ability of individuals to observe and assess another person’s nonverbal behaviors and form accurate impressions during conversations in live, face-to-face interactions compared to virtual formats. The study employed a 2 (interaction format: live vs. virtual; within-subjects) × 2 (observation type: active vs. passive; between-subjects) × 2 (genuineness: genuine vs. nongenuine behavior; between-subjects) mixed design. Participants either actively …

The Evolution Of The Divine Feminine: How Religious Upheaval Changed Female Devotions, Nicole M. Honeycutt

Institute for the Humanities Master's Papers, Projects, and Capstones

The transformation in the depiction of women in Christian religious art from pre-Reformation through the Counter-Reformation mirrored and molded shifting theological, cultural, and gender paradigms. While much scholarship has addressed the symbolic and doctrinal significance of female figures in sacred imagery, less attention has been paid to how such portrayals influenced women’s own devotional experiences and sense of spiritual agency. This study argues that the religious imagery was not merely a passive reflection of male-dominated ecclesiastical values, but an evolving communicative medium through which women could engage with and reshape their spiritual roles. By analyzing key artworks, patronage trends, and …

Not Right Now: Factors Affecting Interruption Decisions In A Healthcare Paradigm, Matthew G. Pacailler

Psychology Theses & Dissertations

Interruptions are common in the workplace, but when they happen during high-stakes critical tasks, they can have serious consequences. In the field of healthcare, interruptions can lead to serious adverse events or medication errors. Research on interruption management strategies addresses the potentially harmful outcomes of interruptions but often fails to account for the initial decision to accept or reject the interrupting task. Two experiments were performed to examine the decision-making outcomes for interruptions.

In experiment I, the participants monitored two EKG displays while simultaneously entering medication information into a patient chart. The decision to accept or reject an interruption was …

"Exploring The Training Data Landscape For Ai Based Threathunting For Protecting Intellectual Property", Manzi Siibo, Christopher Kreider

Cybersecurity Undergraduate Research Showcase

This study provides a comprehensive evaluation of the effectiveness that would result in the integration of AI into traditional threat hunting systems. To do so, 10-15 scholarly articles and data sets were evaluated to see the results of AI and machine learning threat hunting versus traditional systems. With so many proven benefits of this integration, this paper also explores how it impacts the protection of Intellectual property which is some of the most important forms of information that threat hunting systems aim to protect.

Digital Thread: Bridging Macro–Micro Services In System-Of-Systems, Joshit Mohanty

Graduate Student Government Association Research Conference

Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.

This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the …

Meta-Clustering For Specialized Language Models: Enhancing Contextual Adaptation And Mitigating Hallucinations In Diverse Healthcare Environments, Joshit Mohanty, Vaishali Vaishali, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large Language Models (LLMs) have significantly advanced conversational AI by enabling dialogic information-seeking and task execution across diverse domains. However, their extensive parameters and broad domain scope lead to “data hallucinations.” These shortcomings are particularly evident in dynamic and diverse environments like India’s healthcare sector, where myriad languages, regional practices, and cultural nuances demand specialized, localized expertise rather than one-size-fits-all generalist models. This paper introduces a meta-clustering framework that integrates Distilled Language Models (DLMs) and Small/Specialized Language Models (SLMs) with meta-learning principles to address these limitations. By drawing on evidence from works such as MedHalu and Med-HALT, the framework seeks …

Tamos: Task-Aware Multi-Agent Orchestrator System, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large language models (LLMs) are increasingly at the core of multi-agent systems (MAS). However, the high resource demand, error propagation, and lack of adaptive evaluation mechanisms pose significant challenges in deploying these agentic solutions at scale. To address these concerns, this research proposes a Task-Aware Multi-Agent Orchestrator System designed to refine the agentic framework, categorizing tasks autonomously, assigning specialized evaluation datasets, and balancing token usage against functional effectiveness. This approach underscores robust data management, including AsyncHow, Mosaic AI, and Synthetic Preference Optimization (PO) corpora. Each dataset targets specific dimensions of agent performance, such as dynamic task decomposition and tool integration …

Graphtreemed: A Hybrid Graph-Tree Rag Architecture For Mission-Critical Medical Applications, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Studies within engineering management indicate that decision-making is often based on the cognitive processing of grouped and pictographic information clusters entangled with high-level pattern recognition. Similarly, graph-based retrieval-augmented generation (RAG) architectures substantially improve diagnostic accuracy and interpretability, while tree-structured systems reduce critical misses through hierarchical reasoning. However, existing solutions often lack a unified framework that seamlessly integrates these two paradigms to address the multifaceted demands of mission-critical healthcare settings. This proposal introduces GraphTreeMed, a novel hybrid RAG architecture designed to harness the complementary strengths of graph-based and tree-based retrieval mechanisms, thereby advancing the safety and efficacy of clinical decision support …

Fids: Accelerating Network Intrusion Detection Through Strategic Feature Selection, James Elmore

Cybersecurity Undergraduate Research Showcase

Network intrusion detection systems (IDS) typically analyze complete network flows to identify malicious traffic, requiring flows to conclude before classification. This approach creates detection delays for attacks like Slowloris that intentionally keep connections open for extended periods of time. This paper introduces a novel approach that classifies network traffic using only features available from the first few packets of a flow, enabling faster detection while maintaining high accuracy. We evaluate three random forest models on the CICIDS2017 dataset using expanding sets of features: the first-packet model trained on on features available from the first backward packet, the few-packet model which …

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. …

Shaped Adversarial Patches And The Ability They Hold, Nathan Hallberg

Cybersecurity Undergraduate Research Showcase

In more recent years the development of computer vision has advanced to be more comprehensive than in the past, with newer applications ranging from autonomous vehicles to security systems. The main application I will be talking about throughout this paper is an object detection algorithm called YOLO (You only look once), this algorithm is particularly significant due to their real-time performance of being able to identify and localize objects within an image in quick timing. However, the strength of these computer vision models is increasingly challenged by adversarial attacks, which manipulate the computer's vision to block a certain part of …

Elder Fraud Metrics And Preventative Measures Of Chesapeake, Virginia, Joey J. Whitmore Jr.

Cybersecurity Undergraduate Research Showcase

Geriatric crime continues to escalate in the digital era, where older individuals are disproportionately being targeted because of their low digital literacy and high susceptibility to online frauds. In this paper, we examine the breadth of elder fraud in Chesapeake, Virginia using FBI Internet Crime Complaint Center (IC3) data and state-level cybersecurity initiatives and survey responses. Older adults aged 60 and up have reported losses of over $3.4 billion in 2023 alone, underscoring the importance of proactive measures. It assesses the public awareness from traditional and AI-based perspectives revealing significant gaps in digital safety literacy and fraud reporting mechanism among …

Believing In Simulation Theory, Aeve Boucher

Undergraduate Research Symposium

This paper utilizes the frameworks, terms, and methodology used by David Chalmers in his recent book “Reality+”, along with ancient Chinese philosophers Zhuangzi and Mozi in order to make an argument for why we ought to believe that we are currently living in a simulation while at the same time withholding judgment on the metaphysical reality of whether or not we are currently living in a simulation. The argument uses Chalmers’ five different concepts of reality along with his own views of how being in a simulation would not negatively impact our currently held beliefs, especially in regards to language …

The Horror Of Memory In The Southern Gothic, Caelainn Robertson

Undergraduate Research Symposium

Scenes of expansive cotton fields and rotting Manor houses lined by moss covered oaks where strange fruit once hung induce an acute sense of horror from an audience familiar with these relics. The genre of “Southern Gothic” spans literature, film and music and is built on themes of cultural repression in the Southern United States. This tradition explores fears rooted in lingering memories of human enslavement and patriarchal domination. In a culture marked by racial violence and class oppression, evil is, often, identifiable by markers of wealth and white skin. Historical memories only exacerbate suffering. Many contemporary works use the …

Leveraging Benford’S Law And Machine Learning For Financial Fraud Detection, Benjamin R. Fu

Cybersecurity Undergraduate Research Showcase

Financial fraud, particularly credit card fraud, continues to pose substantial challenges to financial institutions due to its increasing frequency and impact on consumer trust. While traditional rule-based methods have provided foundational defenses, their limitations in scalability and adaptability have accelerated the adoption of machine learning (ML) techniques. Concurrently, Benford’s Law—a statistical principle often used in forensic accounting—has demonstrated efficacy in detecting anomalies within naturally occurring numerical datasets. This study explores a hybrid fraud detection approach that integrates Benford’s Law with supervised machine learning algorithms, including Logistic Regression, Random Forest, and k-Nearest Neighbors. Using the publicly available European credit card fraud …

17 - Mpark: A Humanities Makerspace, Margaret Konkol Kilcline, Ola Swatek, Xianzhong Meng, Elena Knudsen, Bridget Dolan

Undergraduate Research Symposium

Our mission is to promote nontraditional understandings of the textual object and to recover and celebrate the historical contributions of women and other marginalized groups to textual cultural heritage. We explore text-making with materials like thread, fiber, leather, wood, and plastic as well as a wide range of digital tools and visual recording equipment. We are devoted to expanding the impact of the humanities by supporting cross-disciplinary collaboration and by reaching beyond the university to engage with innovations and challenges that face our larger geographical and social contexts. Founded in Fall 2023 and occupying 400 square feet on the second …

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, …

How Can We Improve Our Security Measures To Safeguard Against Cyber Threats?, Mattea Trotter-Hicks

Cybersecurity Undergraduate Research Showcase

Many people face the issue of having their information stolen without their knowledge of what is happening. I understand that some people don’t pay attention to everything when it comes to making sure their information is being secured properly. There must be set stages for those who don’t know technology as well and will need help with knowing what to do. There are many stories of people going through issues with getting hacked or scammed out of their money or important information. We are going to dive into finding ways to fix the outcome of others knowing what to do …

Learning With Errors Parameter Analysis, Archana Parameswaran

Cybersecurity Undergraduate Research Showcase

We implement a systematic approach for generating, evaluating, and benchmarking Learning with Errors implementations in Sage Math by varying lattice dimensions, moduli, error standard deviations, and multiple error distributions to observe concrete security-efficiency tradeoffs. The security estimator maps parameter sets to concrete security levels and bits, while performance metrics measured computational efficiency and memory requirements. Results indicate that various distribution types do not significantly impact security, though binomial distributions require more computational overhead than discrete gaussian or uniform. Memory requirements increased when modulus q increased from 12289 to 65537. Larger dimensions have an exponentially growing requirement for memory, but this …

Securing Biometric Data, Alyssa F. Carroll

Cybersecurity Undergraduate Research Showcase

Biometric data has been widely adopted across various sectors, including digital identity, artificial intelligence (AI), border control, digital wallets, and national identification systems. While biometric identifiers—such as fingerprints, retina scans, and facial recognition—offer reliable and convenient authentication, they also raise significant concerns regarding privacy and security. This paper examines how biometric data is stored, the vulnerabilities it faces, and the most effective methods for safeguarding it. By highlighting the critical importance of biometric data protection, this study reviews current research on approaches, strategies, and policies that enhance security while preserving the functionality and efficiency of biometric systems.

82 - Characterization Of Manganese Ferrites For Combined Mph/Mpi Treatments, Alana Canty, Robert Ivkov, Hayden Carlton

Undergraduate Research Symposium

Magnetic particle hyperthermia (MPH) is a form of cancer treatment in which cancer cells are made more susceptible to treatments, primarily radiation, through heating. The heat is generated from exciting magnetic nanoparticles (MNPs) within an alternating magnetic field (AMF)—nanoparticles which have been injected into a tumor—and both the heating quality and imaging quality of these MNPs are determined by their magnetic properties, with the primary one being anisotropy. Magnetic nanoparticles have been introduced as both a treatment option as well as a diagnostic tool through magnetic particle imaging (MPI). When used as a diagnostic tool, MNPs act as tracers to …

76 - Cochlear Implant Candidacy In Adults: Evidence From Systematic Reviews, Madison Hastain, Stacie Raymer

Undergraduate Research Symposium

This poster provides recommendations for cochlear implant candidacy in adults based on data collected from several systematic reviews, along with information regarding the efficacy of cochlear implants in adults with varied types of hearing loss.

56 - Body Composition Change In Women Treated For Breast Cancer Before And 24 Months After Treatment, Aissatou Lo, Gregory Hundley Md, Leila Mabudian, Susan Workman, Ricardo Peral, Daniel Miller, Nathaniel Sean O'Connell, Amy Ladd Md

Undergraduate Research Symposium

Background: Breast cancer (BC) treatments including chemotherapy and radiation can alter body composition leading to significant changes of subcutaneous and visceral adiposity. Increases in fat impact physical health and influence survivorship outcomes such as quality of life and metabolic health. We hypothesized that breast cancer treatment could induce increases in body composition, especially abdominal fats. Objective: Investigate body composition change in women treated for breast cancer before and 24 months after treatment.

Methods: Case-control cohort study design that included 29 BC patients treated with anthracycline chemotherapy and 37 comparators without cancer.To assess body composition, abdominal MRIs were obtained at baseline …

48 - Improving Worship Experience: A Secure Application For Generating Worship Questions Using Ai, Hind Aldabagh, Rhys Ferris

Undergraduate Research Symposium

Improving worship Experience: A Secure application for generating worship questions using AI

Rhys Ferris

Under the direction of Hind Aldabagh, School of Cybersecurity

Generating discussion questions for family worship time during the week based on sermon notes presents an innovative and helpful tool to assist pastors in developing worship questions. Instead of using ChatGPT, hosting a small AI model with Mistral provides an alternative solution that better suits our project.

Using prompt engineering, a custom prompt was created within the statement of faith to guide the AI in reading the text file of the sermon notes. The front end consists …

47 - Enhancing Patient Experience: A Secure Self-Service Kiosk For Prescription Status In Pharmacies, Raneem Alarian

Undergraduate Research Symposium

Creating secure and dependable pharmacy kiosk systems is essential for improving both patient satisfaction and the overall efficiency of pharmacy operations. Patients often experience frustration due to long wait times at the pharmacy counter, especially when prescriptions are not ready. As a licensed pharmacy technician, I have witnessed this issue firsthand, which led me to develop a software solution developed to improve pharmacy workflow. This project focuses on the design and execution of a client-server application for a self-service pharmacy kiosk, enabling patients to securely check the status of their prescriptions before they reach the counter. Developed using Visual Studio …

36 - Investigation Of The Digital Footprint Of Scientific Research In Social Media – Preliminary Findings, Lee Logan, Dominik Soos, Sean Baker, Jian Wu

Undergraduate Research Symposium

Title: Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings

Authors: Lee Logan, Sean Baker, Dominik Soos, Jian Wu

The spread of scientific information and research beyond the confines of academic institutions plays a central role in how the public understands and trusts modern sciences. Social media has become an essential means of dissemination for scholarly news, papers, and other forms of engagement. This research aims to explore how scientific research is disseminated over social media to understand its role as a bridge between peer-reviewed research and the public's overall understanding. To support the research …

32 - Nested Two Level Decomposition For Quantum Computing, Andrew Maciejunes, John Stenger, Dan Gunlycke, Nikos Chrisochoides

Undergraduate Research Symposium

Abstract—We present a two-level decomposition strategy for solving the Vehicle Routing Problem (VRP) using the Quantum Approximate Optimization Algorithm (QAOA). A Problem-Level Decomposition (PLD) partitions a 9-node (72-qubit) VRP into smaller Traveling Salesman Problem (TSP) instances. Each TSP is then further simplified via Circuit-Level Decomposition (CLD), enabling execution on near-term quantum devices. Our approach achieves up to 90% reductions in circuit depth and qubit count. These results demonstrate the feasibility of solving VRPs previously too complex for quantum simulators and provide early evidence of potential quantum utility.

31 - Shaped Adversarial Patches, Huong Quach

Undergraduate Research Symposium

In recent years, the development and deployment of computer vision models have become widespread, with applications ranging from autonomous vehicles to security systems. Among these, object detection algorithms like YOLO are particularly significant due to their real-time performance and accuracy in identifying and localizing objects within an image. However, the robustness of these models is increasingly challenged by adversarial attacks, which are deliberate manipulations designed to deceive the model's predictions.

In this paper, I present an approach to advancing the deception capabilities of adversarial patches, specifically targeting YOLO-based person detectors. The objective is to design and implement shaped adversarial patches …