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Uc-35 Ksu Ccse Crm, Alex Curran, DJ Mitchell, Christian Miller 2024 Kennesaw State University

Uc-35 Ksu Ccse Crm, Alex Curran, Dj Mitchell, Christian Miller

C-Day Computing Showcase

Our task was to select, implement and customize a CRM solution for the College of Computing and Software Engineering to more effectively manage communication with industry partners and manage projects such as capstones, and C-Day. Our team selected SuiteCRM as our recommendation and have implemented an instance on a virtual machine provided by UITS. We have customized branding including using a KSU logo provided by the Office of Strategic Communications and Marketing, as well as customizations based on the official KSU color pallete. The process we used to select our CRM recommendation involved gathering requirements from our sponsor and comparing …


Uc-69 Interactive Training Game Suite, Garrett J Perry, Joscelyn Cauley, Issabella Du, Sergiu Ursu, Rahaf Kokash 2024 Kennesaw State University

Uc-69 Interactive Training Game Suite, Garrett J Perry, Joscelyn Cauley, Issabella Du, Sergiu Ursu, Rahaf Kokash

C-Day Computing Showcase

It is now common knowledge that simple lectures are not the most effective way for the average person to learn and retain knowledge. The Core of Engineers at the Warner Robins Air Logistic Center have tasked us to transform their PowerPoint presentations into interactive training games to improve comprehension, interaction and retention while saving time and logistical resources compared to giving a traditional lecture. We been tasked with creating game modules covering STINFO or what is or is not considered classified information, Records Management, and the No FEAR Act detailing whistleblower rights and protocols. Our team has developed a log …


Uc-105 Model Un Crisis Software, Gregory Hicks, James Ritzi, Vincent K Kipchoge 2024 Kennesaw State University

Uc-105 Model Un Crisis Software, Gregory Hicks, James Ritzi, Vincent K Kipchoge

C-Day Computing Showcase

Utilizing an Agile approach, this project develops a web-based solution, the Model UN Crisis Software, to streamline the management of crisis committees in Model UN conferences. The software is developed using Microsoft Visual Studio and Microsoft SQL Server Management Studio, adhering to the .NET framework and related conventions. It leverages Microsoft Azure SQL Database for back-end data storage and follows the ASP.NET core MVC framework, utilizing powerful .NET tools such as C# and Razor. The developed software provides comprehensive features to reduce the strain of hosting a crisis committee, such as directive and news management, user management, and a messaging …


Gpr-16 Attention Driven Framework For Detecting Mental Illness Causes From Social Media, Abm Adnan Azmee, Dinesh Chowdary Attota, Francis E Nweke 2024 Kennesaw State University

Gpr-16 Attention Driven Framework For Detecting Mental Illness Causes From Social Media, Abm Adnan Azmee, Dinesh Chowdary Attota, Francis E Nweke

C-Day Computing Showcase

Mental health is a critical aspect of our overall well-being. Mental illness refers to conditions that impact an individual's psychological state, resulting in considerable distress, and limitations in functioning day-to-day tasks. Due to the progress of technology, social media has merged as the platform, for individuals to share their thoughts and emotions. The psychological state of individuals can be accessed with the help of data from these platforms. However, it is challenging for conventional machine learning models to analyze the diverse linguistic contexts of social media data. In this work, we propose a novel attention-driven deep framework to overcome these …


Gpr-18 Case Exploration: Automatic Keyword Matching Framework For Behavioral Health, Francis E Nweke, Abm Adnan Azmee 2024 Kennesaw State University

Gpr-18 Case Exploration: Automatic Keyword Matching Framework For Behavioral Health, Francis E Nweke, Abm Adnan Azmee

C-Day Computing Showcase

In this demonstration, we propose a framework for exploring, identifying, and matching repeated behavioral health keywords in first-responder reports to the current set of Behavioral Health Index Terms provided by subject matter experts (SMEs). The tool incorporates behavioral health-related keywords and has a Graphical User Interface (GUI) that allows non-technical users to explore and analyze 911 first-responder reports. We utilized an inverted index, best-matching (BM25), and plain-text searching algorithms to match keywords in first-responder reports. This tool provides a comprehensive approach to report analysis by identifying indicators of mental health disorders and taking into account the assessments of humanities and …


Gpr-63 Adaptive Attention Aware Fusion For Human-In-Loop Behavioral Health Detection, Martin Brown, Abm Adnan Azmee 2024 Kennesaw State University

Gpr-63 Adaptive Attention Aware Fusion For Human-In-Loop Behavioral Health Detection, Martin Brown, Abm Adnan Azmee

C-Day Computing Showcase

Identifying behavioral health is paramount for law enforcement officers to provide appropriate follow-up community care. In the current practice, law enforcement offices manually identify these behavioral health cases to allow the designation of the relevant follow-up resources. In this work, we develop a tool to automatically detect behavioral health cases from police public narrative reports by identifying behavioral health indicator signals. We propose a novel adaptive attention-aware fusion model for detecting behavioral health signals in sensitive police reports. Our model leverages contextual and semantic information from the reports and relevant behavioral health cues as keywords from a pre-trained attention-weighted keyword-based …


Uc-100 Indy 7 - Nutrition App, Silas E Hammond, Tho Mai, Christopher P Sarzen, Michael Ehme 2024 Kennesaw State University

Uc-100 Indy 7 - Nutrition App, Silas E Hammond, Tho Mai, Christopher P Sarzen, Michael Ehme

C-Day Computing Showcase

This project’s objective is to develop a fully functioning and polished mobile app for keeping track of caloric intake and monitoring other aspects of one’s health. To accomplish this, we will be using React Native to develop a front end which allows users to select their goals and get active assistance in moderating what they eat. This will be done through the scanning of barcodes of any food purchased. These barcodes will then be used to query the Food Data Central API to provide the user with as much information as needed. This will include possible allergies, calorie totals, protein …


Gpr-108 Revolutionizing Reflective Learning In Higher Education: An Llm-Based Analytical Approach, Bharath Y Yadla, Mourya Teja Kunuku 2024 Kennesaw State University

Gpr-108 Revolutionizing Reflective Learning In Higher Education: An Llm-Based Analytical Approach, Bharath Y Yadla, Mourya Teja Kunuku

C-Day Computing Showcase

This project introduces a novel LLM-based system to automate The analysis of student reflections, enhancing reflective learning in higher education. Leveraging advanced ML and NLP technologies, the system provides personalized, in-depth feedback by identifying learning outcomes and challenges. Employing the OpenAI API and LangChain framework, it offers a nuanced understanding of student learning trajectories. The methodology involves collecting data via the Minute Paper technique, enabling targeted instructional adjustments. Preliminary results indicate a significant improvement in analyzing and addressing students' educational needs.


Gpr-13 Effect Of Noise And Topologies On Multi-Photon Quantum Protocols, Nitin Jha 2024 Kennesaw State University

Gpr-13 Effect Of Noise And Topologies On Multi-Photon Quantum Protocols, Nitin Jha

C-Day Computing Showcase

Quantum-augmented networks aim to use quantum phenomena to improve detection and protection against malicious actors in a classical communication network. This may include multiplexing quantum signals into classical fiber optical channels and incorporating purely quantum links alongside classical links in the network. In such hybrid networks, quantum protocols based on single photons become a bottleneck for transmission distances and data speeds, thereby reducing entire network performance. Furthermore, many of the security assumptions of the single-photon protocols do not hold up in practice because of the impossibility of manufacturing single-photon emitters. Multi-photon quantum protocols, on the other hand, are designed to …


Uc-40 Asynchronous, Ryan A Whisenhunt, Peyton T Lee, Kenneth Wardlaw, Benjamin T Haaf, Carter L Good, Cory A Ridley 2024 Kennesaw State University

Uc-40 Asynchronous, Ryan A Whisenhunt, Peyton T Lee, Kenneth Wardlaw, Benjamin T Haaf, Carter L Good, Cory A Ridley

C-Day Computing Showcase

Cultural assimilation is the topic on the mind of the protagonist of our game, Asynchronous. Maxwell, a diplomat from a real-time world, must adapt in a foreign land where the people live turn-based lives. We explore this topic through the lens of traditional JRPG gameplay where the player must decide when to adapt to this new culture and when to act on their own accord. By representing this idea ludically, we hope to better convey the mindset and emotional state of being an outsider to the player.


Uc-99 Interactive Training Games - Robins Air Force Base, Sean J Tenney, VT Nguyen, Ian Ford, Mason Farmer, Aaron Hannah 2024 Kennesaw State University

Uc-99 Interactive Training Games - Robins Air Force Base, Sean J Tenney, Vt Nguyen, Ian Ford, Mason Farmer, Aaron Hannah

C-Day Computing Showcase

Our project involves converting three PowerPoint training presentations on STINFO, No Fears Act, and Records Management into engaging web-based games. Commissioned by Robins Air Force Base, our team utilizes Unity WebGL for game development and React/Firebase for website hosting. The goal is to provide Air Force personnel with interactive training modules accessible from their desks, enhancing learning retention and engagement. By gamifying the content, we aim to make learning enjoyable while ensuring critical information retention. This interdisciplinary project merges game development and web technologies to modernize training methods and improve educational outcomes for military personnel.


Ur-116 Enhancing Engineering Education Through Llm-Driven Adaptive Quiz Generation, Devananda Sreekanth, Sreekanth Gopi 2024 Kennesaw State University

Ur-116 Enhancing Engineering Education Through Llm-Driven Adaptive Quiz Generation, Devananda Sreekanth, Sreekanth Gopi

C-Day Computing Showcase

This study aims to develop an Artificial Intelligence (AI) quiz generation system for engineering students to enhance personalized learning. In the rapidly evolving field of educational education, the emergence of AI and, more specifically, Large Language Models (LLMs) such as GPT-4, Llama, Claude, and Gemini, has marked a significant advancement. Our literature review method employs a systematic approach, analyzing peer-reviewed articles, conference papers, and authoritative reports to uncover the trends and challenges in AI-driven quiz generation. The notable gap identified in our literature review is the lack of LLM-based quiz generation methods specifically for engineering education, which incorporate interactive and …


Ur-12 Multiple Myeloma: Increase Longevity And Quality Of Life Through Early Detection, Desyne Martinez 2024 Kennesaw State University

Ur-12 Multiple Myeloma: Increase Longevity And Quality Of Life Through Early Detection, Desyne Martinez

C-Day Computing Showcase

Multiple Myeloma is a rare form of bone marrow cancer where plasma cells accumulate in the blood stream attacking the skeletal system, nervous system, and kidneys of predominantly African Americans. The disease results in high mortality rates within 5 years of initial diagnosis. Multiple Myeloma has subtle symptoms of bone pain; doctors often send people to physical therapy missing the diagnosis. Current research on the International Myeloma Foundation website includes summaries of blood tests of Multiple Myeloma patients. This study seeks to identify the best blood test predictors of Stage 3, the most aggressive stage of Multiple Myeloma. The cost …


Ur-15 Analyzing Breast Cancer Histopathology Images Using Deep Neural Network Models, Je'dae Lisbon, Michael Bolnik, Sepehr Eshaghian 2024 Kennesaw State University

Ur-15 Analyzing Breast Cancer Histopathology Images Using Deep Neural Network Models, Je'dae Lisbon, Michael Bolnik, Sepehr Eshaghian

C-Day Computing Showcase

Our project aims to explore human tissue cells digitized by whole slide scanners for a better understanding of complex tumor microenvironments in breast cancer histopathology images, using various deep neural network models. First, we experimented with 70% percentages of tumor cells on image classification using ResNet50, VGG16, and Inception-ResNet. Second, we performed instance image segmentation using Mask-RCNN. Third, we applied two well-known explainable artificial intelligence (AI) techniques including Gradient-weighted Class Activation Mapping (Grad-CAM) and Shapley Additive Explanations (SHAP) to determine the effectiveness of the models.


Uc-41 Spectrum Play, Alisa Harrell, Wyatt Haston, Patrick Mahon, Rusty J. Hodge, Dharani Baradi 2024 Kennesaw State University

Uc-41 Spectrum Play, Alisa Harrell, Wyatt Haston, Patrick Mahon, Rusty J. Hodge, Dharani Baradi

C-Day Computing Showcase

For our capstone project we are creating a web-based application that simplifies music to aid students in learning music notation. It will be used as a guidance tool for students to reference as they play instruments. Students can pick from a selection of songs with four levels of complexity. For level one just color-coded circles are displayed on screen and as the levels increase more aspects of the song measure are added. At the highest level, the colors are removed and only the song measure is displayed. Students are able to scroll back and forth along the measure using vertical …


Uc-43 Aletheianomous Ai: The Chat Bot Providing The Most Accurate Knowledge Information, David E Chavarro, Aimi Tran, Ethan B Byrd, Matthew J Fincher 2024 Kennesaw State University

Uc-43 Aletheianomous Ai: The Chat Bot Providing The Most Accurate Knowledge Information, David E Chavarro, Aimi Tran, Ethan B Byrd, Matthew J Fincher

C-Day Computing Showcase

For this project, our group aimed to create an intelligent chat bot that was accessible through the web client interface. Aletheianomous, our chat bot, was designed to provide accurate information ethically, aligned with human values. When applicable, the AI would offer the user citations to support its responses. For the back-end, a virtual machine (VM) server in AWS with access to the Graphics Processing Unit (GPU) would run three types of models: Sentence Separation Model, Search Query Extractor Model, and the Response Model. The front-end server using Microsoft Azure generates the web page for the user, exchanges chat data with …


Uc-48 Birding With Buddy, Lazare V Sawadogo, Ikhelowa E Adeji, Blake Graham, Zach Alpine, Troy C Sorrells 2024 Kennesaw State University

Uc-48 Birding With Buddy, Lazare V Sawadogo, Ikhelowa E Adeji, Blake Graham, Zach Alpine, Troy C Sorrells

C-Day Computing Showcase

Birding with Buddy is an educational and entertaining immersive virtual 3D low-poly birdwatching to be experienced at the Carter Lake Nature Center to enable kids to embark on a quest to learn more about birds. Buddy the Beaver guides the user through different terrain types to identify diverse bird species with sounds. Integrate a bird identification system where players click on the binocular icon to switch to a binocular view. In this view, players can choose to Identify (multiple-choice) the correct bird, Hear the Call Again, or Consult a Field Guide. Featuring flippable pages with images and notable markings of …


Ur-70 Faster Inequivalence Testing Using Robustness, Emily G Jackson 2024 Kennesaw State University

Ur-70 Faster Inequivalence Testing Using Robustness, Emily G Jackson

C-Day Computing Showcase

We propose a new method for quickly testing the inequivalence of two Boolean functions, when one function is represented as an ordered binary decision diagram (OBDD), and the other is represented in conjunctive normal form (CNF). Our approach is based on a notion of classifier robustness from the fields of explainable AI (XAI) and adversarial machine learning. In particular, we show that two Boolean functions that are very similar in terms of their truth values, can be very different in terms of their robustness, which in turn, provides a witness to their inequivalence. A more efficient approach to inequivalence testing …


Ur-78 Transforming Game Play: A Comparative Study Of Cnn And Transformer Based Q-Networks In Reinforcement Learning, William A Stigall 2024 Kennesaw State University

Ur-78 Transforming Game Play: A Comparative Study Of Cnn And Transformer Based Q-Networks In Reinforcement Learning, William A Stigall

C-Day Computing Showcase

In this study we investigate the performance of Deep Q-Networks utilizing Convolutional Neural Networks (CNNs) and Transformer architectures across 3 different Atari Games. The advent of DQNs have significantly advanced Reinforcement Learning, enabling agents to directly learn optimal policy from high dimensional sensory inputs from pixel or RAM data. While CNN based DQNs have been extensively studied and deployed in various domains Transformer based DQNs are relatively unexplored. Our research aims to fill this gap by benchmarking the performance of both DCQNs and DTQNs across the Atari games' Asteroids, Space Invaders and Centipede. Our research finds that our Transformer Agent …


Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher 2024 Kennesaw State University

Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher

C-Day Computing Showcase

Advancements in the field of machine learning have led to object detection systems that can approach or even improve upon human performance. Based on deep learning, these systems play a crucial role in many aspects, and continue to be improved on and see expanded adoption. However, these systems are vulnerable to adversarial attacks that rely on targeted noise to spoof detection. Researchers have applied this concept to increase real world adversarial performance by restricting this noise to a patch that can be placed on new images to disrupt object detection. Previous research has focused on patches applied to person recognition …


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