Computer Sciences Commons^™

Ur-114 K86: 16-Bit Computer Design, Optimization, And Implementation​, Calvin Crose, Juan Ferreira, Brendan Moore, Caleb Oglesby, Jack Vega

C-Day Computing Showcase

This research focused on the implementation of modern computing systems by designing and simulating a 16-bit RISC-based ISA computer. The computer is built on a Von Neumann memory architecture with 1024×16-bit word-addressable space and a 6-bit ISA with 36 implemented instructions. The central processing unit (CPU) includes a control unit (CU) that automatically drives the fetch-decode-execute (FDE) cycle, four addressable general-purpose registers (GPRs), and an Arithmetic Logic Unit (ALU) comprising 21 operations and producing four flags. We validated the system by executing Euclid's GCD algorithm, generating the binaries with a custom assembler written in Python.

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 …

Uc-130 Some Kind Of Tundra Escape, Tiffany Field, Patrynna Mensah, Tahjir Beene, Daniel Worrel

C-Day Computing Showcase

Some Kind of Tundra Escape is an action-adventure game where you play as a penguin trying to escape a vast, walled-in tundra. As you explore, you’ll rescue other penguins scattered throughout the area. Your goal is to gather all the penguins and escape together, but the journey is far from easy. The tundra is full of danger, including snowmen who ambush you and ice golems who patrol certain areas. You'll need to avoid these monsters and set traps to stay safe while rescuing your fellow penguins. As your group grows, so does the challenge—more penguins means more obstacles to overcome. …

Ur-017 Sherlock: Self-Supervised Histopathological Evaluation For Recognition Of Lymphocytes And Other Cancerous Kinds, Charles Pagano

C-Day Computing Showcase

Whole Slide Images (WSI) are gigantic images (e.g. 100k x 100k pixels) of tissue samples. The goal of SHERLOCK is to detect cancer cells in those tissue samples. We do this by using a pretrained Masked Autoencoder (MAE), from Facebook’s research lab, that we finetune on the PanNuke dataset. The benefit of using an MAE is that unlike supervised learning the WSI’s don’t need to be labeled. This is important because it will save a lot of time and money that would be spent on labeling WSI’s.

Ur-018 Towards Bounding The Behavior Of Deep Neural Networks, Aidan Boyce

C-Day Computing Showcase

Recent advances in Artificial Intelligence (AI) have unlocked many new possibilities but have also brought with it many new challenges. While modern AI systems have been continuously exceeding expectations, our ability to interpret and understand their behavior lags behind. For example, an AI model trained to detect pneumonia from X-rays may fail in new hospitals because it learned to recognize hospital logos instead of medical patterns. Why do some succeed while others fail? Do they truly understand their tasks, or are they relying on patterns that may not always hold? To enumerate the most informative explanations of a neuron’s behavior, …

Ur-047 Empathetic Vr Classroom, Seth Brice

C-Day Computing Showcase

We used a virtual reality classroom setting to investigate how accurately humans can determine the emotional state of NPC avatars based on nonverbal body language. Volunteers presented a topic in front of several virtual agents, who would respond with a gesture that reflected their current emotional state, giving the presenter the opportunity to physically and emotionally respond to these changes.

Ur-063 K86: 16b Computer And Assembler Design And Implementation​, Vera Warren-Aliff, Ethan Dingle

C-Day Computing Showcase

With this project, we designed a general-purpose 16-bit RISC+CISC computer architecture, alongside an assembler, instruction embedder, and preliminary compiler. Our computer architecture, K86 (Kennesaw 86), is inspired by the Intel x86 and ARM architectures that have enabled computing systems to perform many of the modern functionalities we rely on today. To allow for fluid programming and processing, KASM (Kennesaw Assembler) translates assembly code into machine instructions which will be stored in the computer memory by the embedder. With the addition of a preliminary compiler to produce assembly from high-level source code, our project defines much of the foundation of a …

The National Cybersecurity Teaching Coalition: Expanding Cybersecurity Education Opportunities, Paul Wagner, Melissa Dark, Robert Honomichl, Filipo Sharevski, Sandra Leiterman

Journal of Cybersecurity Education, Research and Practice

The increasing prevalence of cybersecurity threats and the shortage of qualified professionals necessitate innovative solutions for cybersecurity education at all levels. Despite the expansion of post-secondary cybersecurity programs, employer dissatisfaction with graduates and a lack of standardized introductory curricula highlights the need for structured secondary education pathways. The National Cybersecurity Teaching Coalition (NCTC) and its National Cybersecurity Teaching Academy (NCTA) address this gap by equipping high school educators with the necessary knowledge and credentials to teach cybersecurity effectively. NCTA offers an 18-credit cybersecurity graduate certificate program to ensure teachers are competent and confident to develop and teach cybersecurity curriculum with …

The Impact Of Ai Use In Programming Courses On Critical Thinking Skills, Christian Jay St Francis Clarke, Abdullah Konak

Journal of Cybersecurity Education, Research and Practice

Proficiency in computer programming extends far beyond memorizing syntax; it depends on the cultivation of critical thinking. Computer programming requires multiple interconnected competencies, including systematic problem analysis, algorithmic reasoning, mastery of programming languages, debugging capabilities, a comprehensive understanding of software development methodologies, rigorous testing practices, and systematic troubleshooting approaches. These skills are also essential for cybersecurity experts; cybersecurity programs require several programming courses to enhance students’ technical and critical thinking skills. Generative AI (GenAI) technologies have fundamentally changed the process of developing applications and approaches to teaching coding. The growing use of GenAI technologies by students in writing computer code …

The Urgency Of Instituting Systemic Cybersecurity Curriculum Within Stem At Secondary Educational Levels In Preparation For Postsecondary Institutions., Robert Spencer

Journal of Cybersecurity Education, Research and Practice

Over the last 20 years, many secondary institutions have made advances developing curriculum defined as “STEM (Science, Engineering and Mathematics)” in order to ensure secondary students are eligible to apply as well excel in technology degree programs at the college and university levels. Although various initiatives exist, there are studies however, which allude to a great possibility that there will be a lack of cybersecurity professionals filling present day and anticipated future positions. Despite a large number of federal and educational enhancements there is need for additional research regarding instituting overall systemic processes and curriculum which supports secondary student transition …

Bloom: Behavioral Learning And Outcome Observation In Microbes, Sean Sarwar Haque, Luke Compton Wharton, Ming Lin, Razvan Voicu

Symposium of Student Scholars

Understanding how pathogens respond to physical changes in their environment is crucial for developing effective treatments and preventative measures. Current research often relies on static models or experimental data that either fail to capture the dynamic interactions within cellular environments or are not generalizable to other types of pathogens. This project aims to address this gap by creating a comprehensive cell simulation that models pathogens and their response to chemical, physical, and physiological changes. The proposed solution is a simulation that integrates biological data and computational modeling to replicate the behavior of pathogens in real time as they are affected …

Educating Students On The Behavioral And Psychological Aspects Of Romance Scam Victimization Via A Social Engineering Competition, Rachel Bleiman, Hwanhee Park, Aunshul Rege

Journal of Cybersecurity Education, Research and Practice

The online dating industry generated 2.98 billion USD in 2023 and is estimated to reach 3.6 billion USD by 2025. Not surprisingly, online dating platforms are rife with romance scams that cause financial damages, with estimated losses of 1.3 billion USD in 2022 alone. Additionally, victims suffer emotional and psychological harms. This paper shares findings from a 2023 Romance Scam and Social Engineering Competition (RSSEC) that introduced students to the behavioral and psychological aspects of romance scams. Specifically, the competition aimed to expose students to (i) understanding how victims experience social engineering (SE) - the psychological manipulation of human behavior, …

Managing Cybersecurity In Local Governments: 2022, Donald F. Norris Phd, Laura K. Mateczun Jd

Journal of Cybersecurity Education, Research and Practice

This paper, based on data from our second nationwide survey of cybersecurity among local or grassroots governments in the U.S., examines how these governments manage this important function. As we have shown elsewhere, cybersecurity among local governments is increasingly important because these governments are under constant or nearly constant cyberattack. Due to the frequency of cyberattacks, as well as the probability that at least some attacks will succeed and cause damage to local government information systems, these governments have great responsibility to protect their information assets. This, in turn, requires these governments to manage cybersecurity effectively, something our data show …

Exploring School Teachers' Cyber Security Awareness, Experiences, And Practices In The Digital Age, R Ravichandran, Sonam Singh, P Sasikala

Journal of Cybersecurity Education, Research and Practice

This study investigates the awareness and practices of cyber security among school teachers, exploring their understanding of cyber threats, online behaviours, and response mechanisms to cyber incidents. A structured questionnaire was administered to gather data on demographic information, cyber security training, online practices, and experiences with cybercrime. The findings reveal varying levels of awareness among teachers, with many reporting limited knowledge of prevalent cyber threats such as phishing and identity theft. Despite the increasing reliance on digital tools for teaching, a significant number of respondents indicated a lack of formal training in cyber security. The study highlights the necessity for …

Uc-221 Accounting Treasury Industries Web Application, Ibrahima Diallo, Alexandra Baker, Tyler J Hood

C-Day Computing Showcase

This accounting software project is designed to provide a comprehensive and efficient solution for financial management within an organization. By focusing on ease of usability, accuracy, and compliance, the software enables users to record, manage, and analyze accounts, journals, and financial transactions seamlessly. Core features include transaction journalization, chart of accounts setup, financial statement generation, and robust account management, all of which are supported by strong data validation and secure access controls. This system seeks to streamline accounting workflows, minimize human/manual errors, and enhance user experience. The ultimate aim is to deliver an intuitive yet powerful tool that supports effective …

Ur-213 Generative Ai & Cybersecurity, Seth G Canada, Shreya Katare

C-Day Computing Showcase

This research project details the impact of Generative AI on Cybersecurity through both its potential enhancements and threats. Using advanced AI algorithms, this project explores how Generative AI can strengthen cybersecurity through systems like Anomaly Detection, Intrusion Detection Systems (IDS), and Malware Analysis. Also, this project addresses the growing challenges posed from Generative AI. In particular, issues surrounding Deepfake Phishing and Polymorphic Malware are discussed. Solutions to mitigate these issues are also provided to engage further understanding in the field. The goal of this research is to offer practical solutions for addressing the growing field of AI-driven cybersecurity.

Insights In Cybersecurity Of A Smart Campus - A Review, Mircea Ţălu

Journal of Cybersecurity Education, Research and Practice

The profound impact of the Internet of Things (IoT) on various fronts, is driven by technological advancements, the ubiquitous spread of information, and the emergence of transformative events. IoT presents a diverse array of possibilities within university environments, fostering a more connected and enhanced educational experience. This research undertakes a comprehensive review of existing literature to provide context to the IoT and underscore its crucial significance in the realm of smart campuses. Additionally, the paper explores the intricate connections between IoT and key concepts such as cybersecurity and wireless sensor networks to present a holistic perspective. It delves into the …

Data Privacy Regulations In The Gaming Industry: A Comparative Analysis Of Singapore, Macau, And Japan, Miloslava Plachkinova

Faculty Articles

This study explores the relatively under-researched area of comparing data privacy regulations and best practices across different countries, with a focus on the gaming industry. It provides an overview of general data privacy principles and existing global regulations, analyzing how gaming operators leverage personal data for competitive advantage. Specifically, the research examines the data privacy approaches and regulatory requirements in Singapore, Macau, and Japan, highlighting the cultural and historical contexts influencing these regulations. Through a comparative analysis, the article discusses the compliance needs for gaming operators in these jurisdictions.

Leveraging Data Science For Resilience: Improving Trauma-Informed Care Practice For Adverse Childhood Experience With Ai & Data Science Application, Mohmmad Arif Shaik

Master's Theses

Adverse Childhood Experiences (ACEs) have long-lasting effects on physical health, mental well-being, education, and socioeconomic outcomes. Resilient Georgia (RG), a statewide initiative, seeks to address ACEs through trauma-informed care and data-driven strategies. However, challenges in data collection, analysis, and tracking set back the effectiveness of these efforts. This study explores the role of data science and interactive visualization tools in improving outcomes for individuals and communities affected by ACEs. A key focus of this research is the development of a data science management application designed to enhance data collection and improve real-time decision-making. The application features interactive dashboards that allow …

Including Individuals' Sense Of Self In Digital Information Privacy, Peter N. Meso, Solomon Negash, Humayun Zafar, Gurpreet Dhillon

Faculty Articles

The nature of contemporary digital ecosystems causes concerns that affect the person, the individual-self, an integral part of an individual’s information privacy calculus and hence a component of individuals’ Information Privacy Concerns (IPC). Yet, prior IPC models overlook self-focused concerns. This study articulates two constructs, termed “loss of autonomy” (i.e., autonomy) and “control over profiling” (i.e., profiling), that reflect individuals’ self-focused privacy concerns. Combining these new constructs with conventional IPC constructs that capture data-focused and device-focused concerns yields an IPC model made up of three dimensions: self-focused concerns, data-focused concerns, and device-focused concerns. The authors first develop instrument items for …

Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang

Journal of Cybersecurity Education, Research and Practice

Additive manufacturing (AM) has been applied to automotive, aerospace, medical sectors, etc., but there are still challenges such as parts’ porosity, cracks, surface roughness, intrinsic anisotropy, and residual stress because of the high level of thermal gradient. It is significant to conduct the modeling and simulation of the AM process and achieve quality products. Digital Twin (DT) can help AM with forecasting defects/errors through simulation and real-time process monitoring. DT is a concept of Industry 4.0, and its digital structure reflects the real-time behaviors of a cyber-physical or physical system. This paper introduces the progress of DT applications in AM, …

Gmr-4234 Evaluating Instance Segmentation Models On Histopathology Datasets, Sai Chandana Koganti

C-Day Computing Showcase

Instance segmentation is transforming digital pathology by enhancing the speed and accuracy of tissue sample analysis through advanced image processing techniques. Whole Slide Imaging (WSI) converts traditional microscope slides into high-resolution digital formats, enabling detailed examinations. This paper presents a brief experimental survey of instance segmentation models on two prominent histopathology datasets: PanNuke and NuCLS. Unlike previous surveys that merely describe deep learning models for general pathology images, we conduct experiments using state-of-the-art models including Mask R-CNN, Detectron2, YOLOv8, YOLOv9, and HoverNet on both datasets. Our study evaluates these models for both binary and multiclass instance segmentation tasks. The NuCLS …

Gpr-187 Deep Learning Models For Protein-Protein Binding Affinity Prediction, Lingtao Chen

C-Day Computing Showcase

Binding affinity (BA) prediction is important for drug discovery and protein engineering. It seeks to understand the interaction strength between proteins and their ligands (or proteins). This information assists in the design of proteins with enhanced or novel functions, as well as understanding the molecular mechanisms of drug action. This paper presents the development and comparative analysis of two deep learning models, a convolutional neural network (CNN) and a transformer model. Many variants of models in this research were developed using TensorFlow. One model that utilizes ProteinBERT was developed using PyTorch. The CNN model captures local sequence features effectively, while …

Gmr-196 Integrated Sentiment And Behavioral Analysis Of Online Product Reviews, Kiran Yepuri, Naveen Mahankali

C-Day Computing Showcase

The "Integrated Sentiment and Behavioral Analysis of Online Product Reviews" project helps businesses gain actionable insights from Product reviews by combining sentiment and behavioral analysis using NLP models like VADER and BERT. This dual approach categorizes reviews as positive, neutral, or negative and identifies themes such as preferences and complaints through Named Entity Recognition and topic modeling. By capturing both the emotional tone and specific product feedback, this method highlights consumer likes and pain points, assisting in targeted improvements for product design and customer service. The project addresses challenges in analyzing complex expressions like sarcasm, providing a robust framework for …

Gpr-185 A Multimodal Approach To Quiz Generation: Leveraging Rag Models For Educational Assessments, Mourya Teja Kunuku

C-Day Computing Showcase

Crafting quiz questions that effectively assess students’ understanding of lectures and course materials, such as textbooks, poses significant challenges. Recent AI-based quiz generation efforts have predominantly concentrated on static resources, like textbooks and slides, often overlooking the dynamic and interactive elements of live lectures—contextual cues, discussions, and interactions—that contribute to the learning experience. In this work, we propose a Retrieval-Augmented Generation (RAG) model that processes multimodal inputs by combining text, audio, and video to produce quizzes that capture a fuller context. Our method incorporates Whisper for audio transcription and utilizes a Large Vision-Language Model (LVLM) to extract essential visual data …

Uc-184 Onaccount A Web-Based Accounting Software, Manuel A Jackson, Russell E Steele, Grzegorz Loj, Zachary B Powell

C-Day Computing Showcase

This project streamline and improve the efficiency of the whole accounting process, by using current best practices for user interaction engineering and current design practices. Our software should be able to provide secure, user-friendly, and accessible financial management solutions anywhere and everywhere through various devices including desktop and mobile. Allowing users to manage their accounts whenever it seems necessary while still maintaining a high level of security. The project is inspired by the various complexity and problems regarding the accounting process in the real world such as financial reporting, miscalculations, and data security; by streamlining this process and making it …

Closed Domain Question Answering With Language Models: Application Of Retrieval-Augmented Generation And Parameter Efficient Fine-Tuning In Healthcare, Aaron Cummings

Master's Theses

Dementia care presents significant challenges for informal caregivers, particularly in managing behavioral symptoms that affect over 90% of individuals with Alzheimer’s Disease and Related Dementias (ADRD) during the moderate-to-severe stages. These symptoms, including agitation, wandering, and repetitive activities, impose emotional and physical burdens on caregivers, often exacerbated by a lack of reliable, accessible, and personalized resources. Non-pharmacological interventions, while evidence-based, are underutilized due to knowledge gaps and the inefficiency of traditional training and information retrieval methods.

This research explores the adaptation of large language models (LLMs) to address these challenges by developing a framework for closed-domain Question Answering (QA) systems, …

Real-Time Feedback-Driven Framework For Automated Cybersickness Mitigation, Md Jahirul Islam

Master's Theses

As technologies are becoming more advanced day by day, the embracement of virtual reality (VR) technology among users is also increasing in daily activities for various purposes, and subsequently, the barrier between the real and virtual world is fading. Despite the versatile uses, cybersickness (CS) is a major problem which is induced among users due to the immersive VR experience. There is a plethora of research findings and methods to measure the users’ CS such as virtual reality sickness questionnaire (VRSQ), simulator sickness questionnaire (SSQ), fast motion scale questionnaire (FMS), and others. Recently, machine learning approaches have also been adopted …

Screensafefuture: A Parent-Empathetic And Pragmatic Mhealth Application For Toddlers' Brain Development Addressing Screen-Addiction Challenges, Nafisa Anjum, Md. Mehedi Hasan, Syeda Umme Salma, Liang Zhao, Maria Valero, Nazmus Sakib

Faculty Articles

The surging incidents of infants and toddlers screen addiction in the United States are becoming a pressing concern, given its compound impact on cognitive, mental, and physical growth. To address this era's critical child health and development problem, in this paper an innovative mHealth application—ScreenSafeFuture—is proposed. ScreenSafeFuture provides practical solutions that seamlessly fit into parents' busy lifestyles, acknowledging the effectiveness and convenience of smartphones as a healthcare tool. The solution includes essential features designed to enhance the experience between parents and their children under 3 years old encompassing an alternative activity advocator for a personalized parent-offspring scenario, screen time tracking …

Exploring Customer Behavior Through Emotion Detection, Darlington Omoifo

Master's Theses

This thesis investigates the potential of emotion detection, gaze tracking, and hand movement analysis as tools to enhance understanding of customer behavior in retail environments. In retail, subtle indicators such as facial expressions, gaze direction, and hand gestures provide valuable insights into customer preferences and decision-making processes. The study leverages real-time video processing with a multithreaded approach on a Raspberry Pi-powered system embedded in a gift cart equipped with dual cameras. Using FER for emotion detection and a custom model for gaze and hand tracking, this research identifies customer engagement patterns, focusing on how emotions like happiness correlate with purchasing …