Digital Commons Network^™

A Backend Database Architecture For Persistent Epilepsy Classification Records, Attiksh A. Panda, Deep Desai, Artem Zabarov, Katrina D. Prantzalos, Satya S. Sahoo, Shuai Xu

Student Scholarship

Epilepsy affects over five million people globally each year, yet consistent clinical diagnosis remains a persistent challenge due to the lack of standardized classification workflows across medical institutions. The Four-Dimensional Epilepsy Classification (4D-EC) framework, developed by Lüders et al., provides a comprehensive structure for characterizing paroxysmal events across four dimensions: seizure semiology, epileptogenic zone, etiology, and comorbidities. Despite its clinical and educational value, no dedicated informatics platform existed to support its routine use until recently, limiting widespread adoption among clinicians and trainees. This project addresses that gap by implementing a full-stack web application that operationalizes the 4D-EC framework for clinical …

Hijacking The Prompt: A Survey Of Prompt Injection Attacks, Detection, And Defense In Large Language Models, Edward J. Griggs

Cybersecurity Undergraduate Research Showcase

Prompt injection attacks, ranked the number-one vulnerability in AI systems by OWASP's 2025 Top 10 for Large Language Model Applications, remain largely unsolved, and this survey examines why. As large language models (LLMs) are deployed across enterprise workflows, agentic systems, and consumer tools, their fundamental inability to distinguish trusted instructions from untrusted user data has created a persistent and expanding attack surface. This paper presents a structured taxonomy of prompt injection attack vectors, including direct injection, indirect injection, multimodal attacks, tool and agent exploitation, hybrid chained techniques, and autonomous propagating threats. These vectors are mapped across five impact categories (data …

Umm (Ultimate Memory Manager): A Note–Taking App Built From Scratch, Caleb M. Early

ASPIRE 2026

For my honors project, I’m building UMM, an advanced note-taking application built entirely from scratch. I’m someone who takes many notes and primarily uses OneNote and Notion, but over time have found myself wanting something faster and more flexible than any note-taking application I could find. UMM is my attempt to create the note-taking app I wish I had, as well as learn how to create such a program.

Instead of relying on pre-made code, I built my own systems for how documents are structured, edited, saved, as well as how the cursor moves, text is formatted, and how selections …

Cybersecurity Integration In Research Stage Connected Devices Within Healthcare Environments, Klemens Koszarek

Master's Theses (2009 -)

The rapid growth of connected devices in healthcare environments has significantly expanded the cybersecurity threat landscape, extending the potential risks beyond traditional hospital networks. Regulatory guidance from the FDA and risk management frameworks such as the NIST Cybersecurity Framework (NIST CSF) provide an approach for managing cybersecurity risk in connected systems. However, these principles are not always applied during early stages of device development. As a result, security consideration may be deferred until later stages of development, allowing for vulnerabilities to persist in systems as they move toward clinical or commercial deployment. This study presents a structured method for integrating …

Empowering Futures: Inspiring Young Girls In Stem Through Comics, Angel M. Griggs

Honors Theses

Women have historically been underrepresented in STEM fields. In my analysis, I explored how children’s literature representing historical women role models empower young girls to possibly pursue STEM careers. I applied Vekiri’s et. al (2024) research on attracting girls to STEM through interactive video games displaying STEM role models to comic books. In this project, I review academic literature, historical sources, and research articles to develop an educational comic book about historical women in STEM to help support the idea that creative activities and resources displaying role models can be influential to young children, specifically young girls. I focused on …

A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring, Bara Ksiksi

Thesis/ Dissertation Defenses

Air pollution is one of the most important and devastating environmental issues that heavily affects public health around the world and it’s the cause of approximately 4.2 million early deaths. This thesis focuses on further improving forecasting models by introducing a zonal approach and satellite-based spatial validation. The main objective is to explore a zonal approach with the ground station data and to add a spatial component using satellite imagery to improve the accuracy of the results. It follows a four-stage evolution framework while focusing on the three different zones chosen. The four stages introduced different aspects which include a …

Limitations Of Signature-Based Network Intrusion Detection Under Modern Traffic Conditions, Henry Guidry

Cybersecurity Undergraduate Research Showcase

Network Intrusion Detection Systems are tools used to monitor network traffic and alert to suspicious or harmful activity before it can cause harm. Signature-based versions of these systems are a foundation for intrusion detection, operating by finding common patterns and forming malicious signatures. However, three developments in modern network environments have greatly impacted the significance of Network Intrusion Detection Systems. These three developments are the near-complete adoption of end-to-end encryption, the use of sophisticated packet fragmentation techniques, and the processing demands of high-throughput networks. Encryption makes deep packet inspection practically infeasible by transforming inspectable payloads into ciphertext, forcing NIDS to …

The Efficacy Of Manganese Sulfate As A Negative Contrast Agent For Magnetic Resonance Cholangiopancreatography, Zainab Abdulla Mankhi

Karbala International Journal of Modern Science

The current study aims to find an alternate oral contrast media for use in magnetic resonance cholangiopancreatography (MRCP) that satisfies the following criteria, the greatest imaging quality safety, no or few side effects, and low cost. The present study created an oral contrast agent sample (solution) by dissolving a one tablet of manganese sulfate supplement (taken daily dose) in 200 ml of distilled water. Thirty-three volunteers assessed the sample using MRCP examine pre and post contrast. By evaluating the signal intensity to compute contrast (C), signal to noise ratios (SNR), and contrast to noise ratio (CNR), the resulting MR images …

Mathematical Logic And Computer Language, Yueun Park

SACAD: Scholarly Activities

Fundamental principles of computer programming comes from mathematical logic. Mathematics enables programming languages to interpret and execute complex instructions. This project explores the possible application of mathematical logic within programming languages by developing a Boolean logic calculator in C++. The program implements a stack-based algorithm to convert infix notation (which we often use) to postfix notation (which computers can evaluate) and uses subsequent functions to evaluate the postfix notation. The program focuses on logic operators NOT, AND, and OR, classified with specific precedence hierarchies. Program analysis shows that the processes have linear time complexity, that is, O(n). The result suggests …

Unique Combinations Of Packing Integer Squares, Keith M. Dreiling, Austin Leanna, William Mooney

SACAD: Scholarly Activities

This research investigates a function, informally named WAK(x), that describes the number of ways to divide an integer square into integer subsquares counting only the list of parts. Previous research has shown values up to 28, though finding these values is computationally complex and requires a long runtime using computer algorithms. We attempt to find patterns in the values and many aspects of the values, hoping to find a general solution. We are unsure if a solution exists, but we have ideas for how to move forward in finding a solution.

Application Identification With Pfsense, Snort, And Openappid In Academic Lab Networks, Minh-Khanh Vu

Journal of Cybersecurity Education, Research and Practice

This paper evaluates the practical capabilities and limitations of a widely used open-source network security stack—pfSense firewall, Snort Intrusion Detection System (IDS), and OpenAppID detectors—in academic cy- bersecurity laboratories and small-to-medium enterprise (SME)-like environments. In a controlled virtual testbed, we measure application-level and feature-level identifi- cation performance for major applications (Facebook, YouTube, Zoom) using the pfSense/Snort/OpenAppID configuration. The stack achieves 97% application-level identification accuracy for these applications in our lab dataset, drawing on a library of 3,374 OpenAppID detectors. However, our experiments reveal a substan- tial feature-level detection gap: specific functions such as Zoom file transfers and Facebook messaging can- …

Negotiating Digital Identities With Ai Companions: Motivations, Strategies, And Emotional Outcomes, Renkai Ma, Shuo Niu, Lingyao Li, Alexander Hirth, Ava Brehm, Rowajana Behterin Barbie

Computer Science

AI companions enable deep emotional relationships by engaging a user's sense of identity, but they also pose risks like unhealthy emotional dependence. Mitigating these risks requires first understanding the underlying process of identity construction and negotiation with AI companions. Focusing on Character.AI (C.AI), a popular AI companion, we conducted an LLM-assisted thematic analysis of 22,374 online discussions on its subreddit. Using Identity Negotiation Theory as an analytical lens, we identified a three-stage process: 1) five user motivations; 2) an identity negotiation process involving three communication expectations and four identity co-construction strategies; and 3) three emotional outcomes. Our findings surface the …

Creating Disability Story Videos With Generative Ai: Motivation, Expression, And Sharing, Shuo Niu, Dylan Clements, Hyungsin Kim

Computer Science

Generative AI (GenAI) is both promising and challenging in supporting people with disabilities (PwDs) in creating stories about disability. GenAI can reduce barriers to media production and inspire the creativity of PwDs, but it may also introduce biases and imperfections that hinder its adoption for personal expression. In this research, we examine how nine PwD from a disability advocacy group used GenAI to create videos sharing their disability experiences. Grounded in digital storytelling theory, we explore the motivations, expression, and sharing of PwD-created GenAI story videos. We conclude with a framework of momentous depiction, which highlights four core affordances of …

When Generative Ai Is Intimate, Sexy, And Violent: Examining Not-Safe-For-Work (Nsfw) Chatbots On Flowgpt, Xian Li, Yuanning Han, Di Liu, Pengcheng An, Shuo Niu

Computer Science

Content Warning: This paper contains sexually explicit and violent images and text. User-created chatbots powered by generative AI offer new ways to share and interact with Not-Safe-For-Work (NSFW) content. However, little is known about the characteristics of these GenAI-based chatbots and their user interactions. Drawing on the functional theory of NSFW on social media, this study analyzes 376 NSFW chatbots and 307 public conversation sessions on FlowGPT. Findings identify four chatbot types: roleplay characters, story generators, image generators, and do-anything-now bots. AI Characters portraying fantasy personas and enabling hangout-style interactions are most common, often using explicit avatar images to invite …

Ai’S Role In Searching For Evidence: Friend And Foe, Barbara (Basia) Delawska-Elliott, Brandon Wilkinson

Publications 2026-present

No abstract provided.

The Promises And Perils Of Using Llms For Effective Public Services, Erina Seh-Young Moon, Matthew Tamura, Angelina Zhai, Nuzaira Habib, Behnaz Shirazi, Altaf Kassam, Devansh Saxena, Shion Guha

Health Services and Informatics Research

Governments are the primary providers of essential public services and are responsible for delivering them effectively. In high-stakes decision-making domains such as child welfare (CW), agencies must protect children without unnecessarily prolonging a family’s engagement with the system. With growing optimism around AI, governments are pushing for its integration but concerns regarding feasibility and harms remain. Through collaborations with a large Canadian CW agency, we examined how LocalLLM and BERTopic models can track CW case progress. We demonstrate how the tools can potentially assist workers in opportunistically addressing gaps in their work by signaling case progress/deviations. And yet, we also …

From Oversight To Insight: Transforming Cybersecurity Governance In Boardrooms, Tooba Aamir, Georgia Psaroulis, Marthie Grobler, Helge Janicke

Research outputs 2022 to 2026

Cybersecurity governance is increasingly critical in a digital economy, with board directors playing a central role in shaping organisational resilience. Directors are pivotal in setting cybersecurity strategies and carrying fiduciary obligations that extend to digital risk oversight. This study examines the cybersecurity literacy and governance practices of Australian board directors through a qualitative interview study with 13 participants. Findings reveal a substantial gap in directors' knowledge and confidence, undermining effective oversight and informed decision-making. This deficit limits their ability to interrogate risk reports, challenge assumptions, and steer investment in line with organisational resilience goals. In response, we propose a Board …

Characterizing User-Reported Risks Across Llm Chatbots, Lingyao Li, Renkai Ma, Zhaoqian Xue, Junjie Xiong

Computer Science Faculty Research & Creative Works

As Large Language Models (LLMs) become increasingly integral to daily life, users are engaging with multiple LLM chatbots for various needs; however, prior research on LLM risks often remains lab-based or focuses on single LLMs like ChatGPT or singular risks like privacy. To gain a multi-risk, cross-chatbot understanding of user experiences, we analyze Reddit discussions around seven major LLM chatbots using the NIST AI Risk Management Framework. We find that user-reported risks are unevenly distributed and chatbot-specific: ChatGPT is associated with safety and fairness concerns, Gemini with privacy, and Claude with security and resilience. Less frequent risks, such as explainability …

Deconstructing The Black Box: An Explainability Analysis Of Deep Learning Architectures In Cytopathology, Chase A. Garrett

SACAD: Scholarly Activities

Deep learning shows strong potential in medical-image analysis, yet adoption in cyptopathology

remains limited. Cytopathology could benefit from deep learning applications by improving

diagnostic efficiency and accuracy. However deep learning comes with a notorious “black box”

that keeps the models from being transparent and trustworthy for widespread clinical adoption.

We conducted a comprehensive and comparative analysis of several deep learning architectures

for multi-class classification of acute leukemia types, ALL, AML, and normal healthy cells from

peripheral blood smear images. The models in this research include a Vision Transformer (ViT)

and a diverse selection of Convolutional Neural Network (CNN) models. The …

Dual History Enhancement With Hybrid Hypergraph-Graph Networks For Temporal Knowledge Graph Reasoning, Kailun Ye, Xiangjie Kong, Yuchao Zhang, Xuan Wang, Linan Zhu, Jiaxin Du, Guojiang Shen, Jianxin Li

Research outputs 2022 to 2026

Temporal Knowledge Graph (TKG) reasoning seeks to predict future events by analyzing historical data, where the effective leverage of both local and global historical facts proves crucial. Existing approaches employ graph neural networks (GNNs) and recurrent neural networks (RNNs) for local evolution patterns, complemented by statistical methods to enhance attention to global facts, demonstrating efficient predictive capabilities. However, traditional GNNs, constrained by their low-order neighborhood aggregation design, inherently fail to model potential high-order dependencies among facts. Furthermore, existing global history modeling approaches may introduce irrelevant historical information that interferes with prediction tasks. To address these limitations, we propose a Dual …

Pre-Experiential Constraint Reconstruction: A Structural Account Of The Prior Layer In Dialogue With Jung, Griselda Poe

Publications and Research

Experiences commonly described as pre-experiential memory—such as immediate recognition, familiarity without prior exposure, and the sense of "already knowing"—are typically interpreted as the retrieval of stored content. However, this storage-based account does not provide a structurally consistent explanation of how such content is preserved prior to experience or reactivated in a form that aligns with present input.

This paper extends the three-layer cognitive architecture developed in prior work in this series (Poe, 2026n), in which cognition operates across Core processing, Modulation, and an operationally inaccessible Prior layer that supplies constraints to all processing.

This paper proposes an alternative account in …

Artificial Intelligence Moderation In Online Gaming: A Cybersecurity Analysis Of Risks And Defenses, Labib Khan

Cybersecurity Undergraduate Research Showcase

This research paper will examine the role of artificial intelligence (AI) moderation systems in enhancing cybersecurity within online gaming environments. As multiplayer platforms increasingly rely on real-time text, voice communication, and user-generated content, developers have implemented AI-driven tools such as natural language processing (NLP), speech recognition, and behavioral analytics to detect harassment, toxic behavior, cheating coordination, and other malicious activity. These systems enable gaming companies to efficiently monitor large volumes of player interactions, improving response times and helping maintain safer and more controlled digital environments for users across global gaming communities of varying sizes and activity levels.

While these technologies …

Does Culture Translate? A Case Study On Artificial Intelligencegenerated Text Concerning Japanese-Style Employment, Kanji Kitamura

Languages, Literatures, and Cultures Faculty Publications

Translation matters to international business when it has a discernible impact on firm performance or critical business processes. Current developments include machine translation, which is evolving in tandem with generative artificial intelligence (AI). On one hand, useful translation apps have become available to help the public communicate internationally. On the other hand, recent research concludes that even machine translation's best output still requires post-editing by a human. This argument implies that a machine-translated, grammatically accurate text may not always make sense to a human audience, possibly because of a semantic-pragmatic issue beyond the lexical level. This paper regards it as …

Statistical Inference Is Not Moral Reasoning: The Case Against Ai On Hospital Ethics Boards, Elan J. Haronian

Seaver College Research And Scholarly Achievement Symposium

As generative AI becomes more integrated in healthcare, it seems inevitable that AI will eventually be used on hospital ethics committees. However, before implementation, their roles need careful consideration. Although AI promises to reduce costs, increase efficiency, and reduce human workloads, there are important ways in which it is limited, especially when human emotion and connection are crucial, as in clinical ethics boards.

In this paper, I highlight several problems preventing AI from being useful on hospital ethics boards. These include issues of opaque reasoning (the “black box” problem), liability, transparency, privacy, and consent. While there are proposed frameworks for …

Older Adults And Emerging Technology Fraud In The Ai Deepfake Era, Thiago Neves

Research Days

Artificial intelligence has accelerated faster than society's ability to adapt, leaving older adults extremely vulnerable to AI-generated fraud. Americans over age 60 lost $4.9 billion to scams in 2024, 43% more than the previous year. In this research, I investigate how digital illiteracy, combined with AI-generated deepfakes, creates this crisis. Older adults struggle with three principal vulnerabilities: distinguishing legitimate sites from scams, judging whether online information is truthful, and understanding how algorithms use their data. AI weaponizes these gaps through voice clones, synthetic video calls, and personalized phishing emails that avoid the trust cues seniors tend to rely on. I …

The Core-Modulation Architecture (Cma): A Structural Overview Of Hallucination As Structural Mismatch, Griselda Poe

Publications and Research

Hallucination is defined not as factual error but as a structural failure of alignment across target, layer, and constraint.

Within the Core-Modulation Architecture (CMA), cognition proceeds through layered processing and requires layer-specific termination conditions. Hallucination arises when Modulation-level termination is registered as completion while Core-level resolution has not occurred, producing structurally ungrounded but locally coherent outputs.

Detection is therefore structural rather than content-based, focusing on layer mismatch and termination failure.

This document presents a minimal structural account of hallucination within the CMA framework.

Library Discovery Kiosks Using Microsoft Webview2, Andres Cazares Reyes, Tom Tran

Library Services Publications

This presentation describes how our library developed a Primo discovery search kiosk using Microsoft WebView2. The session will cover kiosk inactivity reset automation, navigation controls, and deployment.

Advice For Incorporating Ai Tools Into Your Legal Practice, Celia Bigoness, Robert A. Mackenzie, David J. Reiss

Cornell Law Faculty Publications

We have been speaking with many lawyers and law students about using generative artificial intelligence (AI) tools in their legal practice. We are struck by the fact that many of them have not been experimenting much, if at all, with the tools that are available to them - although many acknowledge that their clients are increasingly integrating generative AI into their businesses. We have been integrating a lot of these tools into our own professional lives, and here are some tips to help lawyers and law students get comfortable with AI tools that can help them, in big ways and …

Ai's Double Edged Sword: Fighting Against Synthetic Csam, Shekhinah Adra Green

Cybersecurity Undergraduate Research Showcase

The rapid advancements in generative artificial intelligence has introduced new challenges in the production and distribution of synthetic child sexual abuse material (CSAM). AI has the capabilities of creating highly realistic imagery and videos, which  raises serious legal and ethical concerns, increasing the risk of harm, exploitation, and revictimization.

This paper discusses the legal improvements needed in order to lower the change of legal loopholes, how digital forensic analyst use advanced tools to identify and investigate synthetic material, and different methods to start the reduction of synthetic CSAM.

Escaping Isolation: An Analysis Of Virtual Machine And Container Breakout Vulnerabilities, Felix Iov

Cybersecurity Undergraduate Research Showcase

Cloud computing providers rely on multi-tenant architectures to maximize resource efficiency. This infrastructure depends on virtualization, which provides isolation between clients. This comes primarily in the form of Virtual Machines (VMs) and Containers. However, “breakout attacks” or “escapes” are a critical threat where attackers bypass these isolation layers to gain unauthorized access to the host system and neighboring environments. This paper surveys virtualization escape threats and analyzes three case studies: a runc container escape (Leaky Vessels), a VMware ESXi VM escape (VSOCKPuppet), and an NVIDIA GPU container escape (NVIDIAScape). Each demonstrates different attack surfaces, including file descriptor misuse, kernel driver …