Digital Commons Network^™

Towards Inclusive Digital Futures Of Cultural Heritage: Insights From A Critical Discourse Analysis Of Unesco Dialogues, Shiqing Huang, Keng Siau, Xiaoting Chen

Research Collection School Of Computing and Information Systems

Digital technologies are shaping many aspects of cultural heritage, but very little research has examined the implications of digital transformation. Drawing on concepts from Fairclough’s three-dimensional critical discourse analysis, this research examines the discourse using seven online dialogues (available on the UNESCO website) between 18 professionals who have different backgrounds and cultures to identify social practices related to the digital transformation of cultural heritage. We identify four digital transformation discourse types in professional dialogues: documentation, management, interpretation, and interaction. We also identify seven main groups: memory institutions including libraries, archives, and museums (LAMs), governments, international organizations, art and creative supporters, …

Early Conceptual Sketches Of Blended Reality And The Precursor To The Bbs Quad (2022), David Smith

Publications and Research

This document contains two original hand-drawn conceptual sketches created in early 2022, representing the earliest visual formulations of what would later evolve into the Balanced Blended Space (BBS) framework. The drawings predate my first conversations with ChatGPT and were produced as part of my independent sabbatical research into blended environments, mediated performance, and human–machine interaction.

The first drawing examines human–computational mediation, perception, and internal mapping. The second sketch—later referred to informally as the “BBS Quad”—extends this idea by reconciling cognition–computation symmetry with physical–virtual spatial relationships. Published together, these images document the conceptual foundations of the BBS framework prior to its …

Social Media Mining For Extracting The Experience Of Neurodivergent Individuals On Twitter (X) And Reddit, Kartik Thakkar

All Graduate Theses and Dissertations, Fall 2023 to Present

Neurodiversity refers to the natural neurological variations in the human brain such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), dyslexia, dyspraxia, Tourette syndrome and other neurological disorders. it’s estimated that around 15% to 20% of the world’s population is neurodivergent. This means a significant portion of people experience neurological differences in how they think, learn, and interact with the world.

Social Media has become an important space for neurodivergent individuals to share their experiences, build communities, and seek support. This thesis explores how the online venues like X (Twitter) and Reddit offer themselves as digital spaces where …

Predicting Stock Price Movement With Llm-Enhanced Tweet Emotion Analysis, An Vuong

Graduate Theses and Dissertations

Accurately predicting short-term stock price movement remains a challenging task due to the market’s inherent volatility and sensitivity to investor sentiment. In this thesis, we present a published paper that discusses a deep learning framework integrating emo- tion features extracted from tweet data with historical stock price information to forecast significant price changes on the following day. We utilize Meta’s LLaMA 3.1-8B-Instruct model to preprocess tweet data, thereby enhancing the quality of emotion features derived from three emotion analysis approaches: a transformer-based DistilRoBERTa classifier from the Hugging Face library and two lexicon-based methods using National Research Council Canada (NRC) resources. …

When The Grid Goes Dark: A Digital Forensics Study Of Industrial Control System Cyberattacks, Katie Kettler

Graduate Theses and Dissertations

Industrial Control Systems (ICS) and Operational Technology (OT) maintain the grid, ensure water safety, and keep transportation running. Because they influence nearly every aspect of daily life, these systems have become prime targets for cyberattacks. The need for this research arises from the fact that when ICS and OT systems are compromised, the consequences go beyond data loss, and they can directly disrupt communities and endanger public safety. This thesis introduces digital forensics fundamentals and explains how investigations in ICS environments differ from those in traditional IT environments. This work then examines major attacks, including Stuxnet, the Ukrainian Grid Attacks …

Synthetic Dataset For Understanding Negation In Text-Guided Image Editing, Nhat-Tan Bui

Graduate Theses and Dissertations

Negation is a fundamental linguistic concept used by humans to convey information that they do not desire. Despite this, minimal research has focused on negation within text-guided image editing. This lack of research means that vision-language models (VLMs) for image editing may struggle to understand negation, implying that they struggle to provide accurate results. One barrier to achieving human-level intelligence is the lack of a standard collection by which research into negation can be evaluated. This thesis presents the first large-scale dataset, Negative Instruction (NeIn), for studying negation within instruction-based image editing. Our dataset comprises 366,957 quintuplets, i.e., source image, …

Digital Reflections: Evaluating Body Dissatisfaction In Xr Through Eye- And Body-Tracked Virtual Humans, Deyrel Diaz

All Dissertations

In an era where digital and physical realities increasingly intertwine, the perception of body image is undergoing a significant transformation. Traditional understandings of body dissatisfaction, long studied in relation to psychological distress and eating disorders, are now being reshaped by technologies such as Virtual Reality (VR), Augmented Reality (AR), and Artificially Intelligent (AI)- generated media. These technologies have introduced novel ways of experiencing and interacting with the human form, raising critical questions about their impact on self-perception and internalization of beauty standards.

As virtual representations become more prevalent in entertainment, social media, and interactive platforms, it is becoming more crucial …

A Socio-Technical Analysis Of Market Reactions On Meme Coins: Trump’S Presidential Effect, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Meme coins are a unique type of cryptocurrency whose value is shaped by internet culture and viral trends. This study introduces a socio-technical research model to examine key factors influencing meme coin dynamics and applies it to analyze market reactions to Donald Trump’s 2024 U.S. presidential election victory and inauguration, focusing on the $TRUMP meme coin and other politics-related meme coins, known as PolitiFi. Using a mixed-methods approach, we analyze publicly available news, social media activity, and marketplace data to investigate the interaction between social engagement and technical infrastructure. Econometric analysis shows that Trump-related events triggered short-term price surges, increased …

Safe-Sora: Safe Text-To-Video Generation Via Graphical Watermarking, Zihan Su, Xuerui Qiu, Hongbin Xu, Tangyu Jiang, Jun-Hao Zhuang, Chun Yuan, Ming Li, Shengfeng He, Fei Yu

Research Collection School Of Computing and Information Systems

The explosive growth of generative video models has amplified the demand for reliable copyright preservation of AI-generated content. Despite its popularity in image synthesis, invisible generative watermarking remains largely underexplored in video generation. To address this gap, we propose Safe-Sora, the first framework to embed graphical watermarks directly into the video generation process. Motivated by the observation that watermarking performance is closely tied to the visual similarity between the watermark and cover content, we introduce a hierarchical coarse-to-fine adaptive matching mechanism. Specifically, the watermark image is divided into patches, each assigned to the most visually similar video frame, and further …

A Study Of Configuration Management Database (Cmdb) Adoption In It Service Management (Itsm) Implementations Within Nj Community Colleges, Fredrick Dande

All-Inclusive List of Electronic Theses and Dissertations

This study examines the adoption of Configuration Management Databases (CMDBs) in IT Service Management (ITSM) implementations within New Jersey (NJ) community colleges. Despite the well-documented benefits of CMDBs—such as faster issue resolution, improved compliance, and greater visibility across IT infrastructures—implementation success rates remain low. As technology continues to enhance production capabilities and expand access to information, the need for centralized configuration visibility has become critical. A CMDB provides a single system of record for IT assets and services, helping organizations manage outages, assess changes, maintain compliance, and improve asset tracking. This research used an online survey to collect data from …

Navigating Ai-Nature Frictions: Autonomous Vehicle Testing And Nature-Based Constraints, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

In cities, the application of Artificial Intelligence (AI) is being directed towards transforming different aspects of urban life. These applications take material form in urban spaces, with autonomous vehicles (AVs) providing a prominent example. AI systems rely on large volumes of data on their surroundings to refine the algorithms and enhance the accuracy of prediction for operational efficiency and safety. However, such algorithmic learning and execution can present challenges when dealing with the unpredictable, complex, and dynamic aspects of urban spaces. Nature is a paradigmatic example of such unpredictability, because natural phenomena usually defy consistent patterns and precise data-based modelling. …

Design Principles For Customer‑Engaging Digital Service Systems: An Action Research Study, Keng Siau, Xiaofeng Chen, Xin Tan

Research Collection School Of Computing and Information Systems

Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.

Toward Personalizing Quantum Computing Education: An Evolutionary Llm-Powered Approach, Iizalaarab Elhaimeur

Computer Science Theses & Dissertations

Quantum computing education faces significant challenges due to its complexity and the limitations of current tools. This thesis introduces a novel Intelligent Teaching Assistant for quantum computing education and details its evolutionary design process. The system combines a knowledge-graph-augmented architecture with two specialized LLM agents: a Teaching Agent for dynamic interaction and a Lesson Planning Agent for lesson generation. The system is designed to adapt to individual student needs, with interactions meticulously tracked and stored in a knowledge graph. This graph represents student actions, learning resources, and their relationships, aiming to enable reasoning about effective learning pathways. We describe the …

Stableguard: Towards Unified Copyright Protection And Tamper Localization In Latent Diffusion Models, Haoxin Yang, Bangzhen Liu, Xuemiao Xu, Cheng Xu, Yuyang Yu, Zikai Huang, Yi Wang, Shengfeng He

Research Collection School Of Computing and Information Systems

The advancement of diffusion models has enhanced the realism of AI-generated content but also raised concerns about misuse, necessitating robust copyright protection and tampering localization. Although recent methods have made progress toward unified solutions, their reliance on post hoc processing introduces considerable application inconvenience and compromises forensic reliability. We propose StableGuard, a novel framework that seamlessly integrates a binary watermark into the diffusion generation process, ensuring copyright protection and tampering localization in Latent Diffusion Models through an end-to-end design. We develop a Multiplexing Watermark VAE (MPW-VAE) by equipping a pretrained Variational Autoencoder (VAE) with a lightweight latent residual-based adapter, enabling …

Security Vulnerabilities And Defense Tactics For Generative Ai Application Development, Kyle Klein

University Honors Theses

Generative AI (GenAI) applications such as OpenAI's ChatGPT leverage large language models (LLMs) trained on enormous amounts of data to accomplish tasks such as document editing, summarization, and query response. Chatbots and LLM programs that are equipped with retrieval-augmented generation (RAG) have the ability to draw upon data provided by developers and users to improve the quality of the program's responses. LLM technology has even expanded to generate images, audio, and video from user instructions. Designed around unpredictable user input and typically composed of many opaque components, LLM software products face a paradigm shift of new, constantly evolving security challenges. …

From Digital Divide To Equity-Enhancing Diffusion: Generative Ai And Writing Quality, Rebecca Tukachinsky Forster, Kerk Kee, Gabriel Miao Li

Communication Faculty Articles and Research

This study investigates whether generative AI can narrow the gap between stronger and developing writers and explores the mechanisms underlying these effects. In a within-subject experiment, students wrote two essays, with and without AI assistance. Computer-aided analysis of the writing quality confirmed that while all students benefited from AI, that less skillful writers gained more. There was also no evidence of skillful writers using AI in more sophisticated and beneficial ways. The study contributes to theorizing the digital divide and offers insights into maximizing the benefits of AI tools. Theoretically, we situate generative-AI use within Diffusion of Innovations, treating ChatGPT …

Fraud Detection And Explanation In Medical Claims Using Gnn Architectures, Reem Muhammad, Dina Tbaishat, Amril Nazir, Seif Yacoub, Mustafa Abdulrazek, Mohamed Ahmed Abo El-Enen, Ahmed T. Sahlol

All Works

This paper addresses the critical challenge of fraud detection in medical insurance claims-a pervasive issue causing significant financial losses in healthcare-using Graph Neural Networks (GNNs). Given the intricate nature of healthcare data, traditional fraud detection methods do not inherently capture the complex relationships and patterns among different entities. We explore the potential of GNNs to effectively identify fraudulent claims by modeling the interactions among various entities-such as patients, healthcare providers, diagnoses, and services-as a heterogeneous graph. We employ two state-of-the-art heterogeneous GNN architectures, HINormer (Heterogeneous Information Network Transformer) and HybridGNN, along with a modified homogeneous GNN, RE-GraphSAGE (GraphSAGE Graph Sample …

Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …

Ur-1167 Owlexchange, Laura Chaplin, Caitlin Johnson, Alexin D'Haiti, Jamaul Gordon, Leonardo Barranco

C-Day Computing Showcase

OwlExchange is a secure, role-based campus marketplace designed to help Kennesaw State University students buy, sell, exchange, and donate items in a trusted digital environment. The platform replaces unorganized and unsafe exchanges occurring across group chats and social media by providing a centralized system with authenticated user accounts, item listings, and transparent communication. Built with a Flask (Python) MVC architecture, Auth0 for secure identity management, and MySQL for persistent storage, OwlExchange supports modular dashboards for buyers, sellers, and administrators, enabling item management, interest requests, and platform oversight. By promoting reuse and donation of textbooks, furniture, electronics, and other student items, …

Gc-1198 Onboarding Tool For New Smartphone Users, Namita Velagapudi, Bhagya Surekha Dasari, Yaswanth Maddineni, Rohith Venkata Sai Chekka, Balachandar Pinninti

C-Day Computing Showcase

The Smartphone Onboarding Tool is an interactive web platform created to help seniors and new smartphone users become comfortable with mobile technology. It offers a realistic, simulated smartphone interface, guided walkthroughs, and an easy-to-use design that builds confidence in performing everyday tasks. Caregivers can monitor user progress, while learners can practice safely without affecting an actual device. The solution is developed with a React frontend, a Node.js/Express backend, and an SQLite database, all built with a strong focus on mobile-first accessibility.

Uc-1183 Morphyxcam: Instant Photo Transformation Tool, Priscilla Awatey, Long Doan, Shaokun Weng, Aryan Merchant

C-Day Computing Showcase

MorphyxCam is an interactive browser-based application that lets users capture live images and apply real-time visual effects. The system performs color filtering, shading adjustments, dynamic warping, and expressive distortion effects. Users can instantly reshape features, apply artistic styles, and wrap their photos onto 3D surfaces, creating engaging and playful visual transformations. By capturing live camera images and transforming them through pixel-level filtering, distortion effects, and 3D surface mapping, the system shows how multimedia techniques can be applied creatively within a web browser. Overall, MorphyxCam showcases the potential of interactive digital imaging and highlights how accessible web technologies can be used …

Uc-0224 Loving Arms: Website Audit & Redesign, Marcus Harrison, Chris Stropoli, Katherine Gibson, Vaughn Berger, Jesus Flores Valdez

C-Day Computing Showcase

Our team’s project aims to enhance the Loving Arms Cancer Outreach website, making it more accessible and user-friendly for all visitors. Loving Arms is a nonprofit supporting individuals and families affected by cancer, and their website plays a key role in sharing information, connecting people to support programs, and reaching those in need. To achieve this, we first audited the current site to identify areas of confusion or outdated content, and we are currently in the process of providing a redesigned website. These updates are intended to improve the visitor experience while giving staff a reliable, easy-to-use platform that better …

Privacy In Flux: A 35-Year Review Of Trends, Legal Evolution, And Emerging Challenges, Kong Phang, Jihene Kaabi

Research & Publications

Privacy harms have expanded alongside rapid technological change, challenging the adequacy of existing regulatory frameworks. This systematic review (1990–2025) systematically maps documented privacy harms to specific legal mechanisms and observed enforcement outcomes across jurisdictions, using PRISMA-guided methods and ROBIS risk-of-bias assessment. We synthesize evidence on major regimes (e.g., GDPR, COPPA, CCPA, HIPAA, GLBA) and conduct comparative legal analysis across the U.S., E.U., and underexplored regions in Asia, Latin America, and Africa. Key findings indicate increased recognition of data subject rights, persistent gaps in cross-border data governance, and emerging risks from AI/ML/LLMs, IoT, and blockchain, including data breaches, algorithmic discrimination, and …

Enhancing Recommendation Performance Via Stacking Ensemble And Synthetic Data Augmentation, Zahraa Yaareb Hani, Mohsin Hasan Hussein

Karbala International Journal of Modern Science

Recommendation systems are essential tools that primarily aim to help users navigate through a large volume of information. They simplify the decision-making process by suggesting relevant items based on users’ historical behaviour. However, their performance is often affected by common problems such as data sparsity. This work proposes a stacking-based ensemble recommendation system that integrates multiple machine learning models to enhance the model’s predictive performance. A new synthetic data augmentation technique is introduced to address the sparsity issue in the user–item rating matrix. This method uses the Naïve Bayes algorithm to predict additional ratings for each user. These are then …

Creating An Iot User Centric Security And Privacy Label, Luke Joseph Gleba

Theses and Dissertations

Concerns for cybersecurity awareness and training in the public have been rising at astronomical rates over the past few years. People globally have entered a critical intersection with computers. Computers are being used in everyday life, and users do not have an easy way to understand their own cyber risk. Consumers deserve to know how secure their new Internet of Things (IoT) system is in a quick, efficient way before they purchase the device and while they own it. The following research looks to improve on ideas for the criteria and the development of a security label. Few prototypes currently …

Fair Use In The Age Of Generative Ai: Navigating Copyright Challenges In Educational Contexts, Wendy Wallberg

Faculty and Staff Publications & Presentations

Generative AI tools are everywhere, but what’s actually allowed when it comes to copyright and teaching? This session breaks down what fair use means in the age of AI, covers current legal cases, and offers practical tools to help educators and institutions use AI responsibly and confidently.

Quality Assessment Of Pathology Board-Exam-Style Mcqs Produced By Chatgpt3.5: A Comparative Study, Arianna B. Morton, Zunaira Naeem, Allison F. Goldberg, Alexis R. Peedin, Joanna Chan

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Residents preparing for pathology board exams frequently use multiple-choice questions (MCQs) from question banks (QBs) like PathDojo and PathPrimer, which can be costly. ChatGPT, a free tool, has been used to generate MCQs for other tests like the SAT. This study compared the quality of pathology MCQs created by ChatGPT versus commercially available study questions for the American Board of Pathology’s (ABPath) certifying exams. A rubric adapted from the National Board of Medical Examiners’ (NBME) question writing guide was validated by two pathologists using commercially available pathology board exam questions. This rubric was then used to evaluate MCQs from commercially …

Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn

Doctoral Dissertations

The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …

Chronosort: Revealing Hidden Dynamics In Alphafold3 Structure Predictions, Matthew J. Argyle, William P. Heaps, Corbyn Kubalek, Spencer Gardiner, Bradley C. Bundy, Dennis Della Corte

Faculty Publications

Protein function emerges from dynamic conformational changes, yet structure prediction methods provide only static snapshots. While AlphaFold3 (AF3) predicts protein structures, the potential for extracting dynamic information from its ensemble predictions has remained underexplored. Here, we demonstrate that AF3 structural ensembles contain substantial dynamic information that correlates remarkably well with molecular dynamics simulations (MD). We developed ChronoSort, a novel algorithm that organizes static structure predictions into temporally coherent trajectories by minimizing structural differences between neighboring frames. Through systematic analysis of four diverse protein targets, we show that root-mean-square fluctuations derived from AF3 ensembles can correlate strongly with those from MD …

Efficient Multimodal Streaming Recommendation Via Expandable Side Mixture-Of-Experts, Yunke Qu, Liang Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin

Research outputs 2022 to 2026

Streaming recommender systems (SRSs) are widely deployed in real-world applications, where user interests shift and new items arrive over time. As a result, effectively capturing users' latest preferences is challenging, as interactions reflecting recent interests are limited and new items often lack sufficient feedback. A common solution is to enrich item representations using multimodal encoders (e.g., BERT or ViT) to extract visual and textual features. However, these encoders are pretrained on general-purpose tasks: they are not tailored to user preference modeling, and they overlook the fact that user tastes toward modality-specific features such as visual styles and textual tones can …