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Voice Honors Recital
Full text linkEach year, the Bailey School of Music Voice Faculty selects students that have demonstrated significant artistry and scholarship to be featured in the KSU Voice Honors Recital. This evening\u27s program features our brightest and best singers performing their favorite music from this academic year. We thank you so much for joining us this evening and hope you enjoy this beautiful night of singing.https://digitalcommons.kennesaw.edu/musicprograms/2878/thumbnail.jp
GRM-011 Non-Invasive Convolution-Based Coronary Artery Blood Pressure Prediction
Full text linkThe primary objective of this proposal is to develop an innovative technique for determining the functional significance of coronary artery lesions in patients with coronary artery disease (CAD) and evaluate its utility for clinical decision-making using coronary computed tomography angiography (CCTA)
GRM-038 Optimizing Prompts for Alzheimer\u27s Speech Classification Using LLM
Full text linkLarge Language Models (LLMs) are widely used in Alzheimer\u27s disease research to classify speech patterns. However, there is no standardized framework to ensure the reliability of prompts used in these classifications. This study investigates the sensitivity of Alzheimer’s disease classification prompts to small variations and finds that these prompts are indeed sensitive, leading to inconsistencies in model performance. To address this, we implement an automatic prompt optimization framework to refine the base prompt. Experimental results demonstrate that the optimized prompt improves classification accuracy by 12.83% compared to the baseline, underscoring the significance of systematic prompt engineering in enhancing the reliability of LLM-based Alzheimer’s disease detection. Although the optimized prompt remained sensitive to variations, it consistently showed improved overall accuracy
UC-020 Indy Micro - Virtual 8-Bit Computer
Full text linkThe Indy Micro is a desktop application which simulates the functionality of an eight-bit personal computer. Its aim is to mimic the feel of owning one such computer in that era, as well as provide an engaging way to learn about low-level computing concepts. The Micro consists of two components: the virtual machine, which is based on the Von Neumann architecture, and the code editor, which allows users to write assembly code and execute it on the virtual machine. The aim is for the Indy Micro to serve as an educational jumping-off point, a step between the casual programmer and the dedicated hobbyist, developing software for real eight-bit systems. One of the ways students get started with programming is with Scratch (scratch.mit.edu), a visual drag-and-drop programming experience. The project’s goal is to create something like Scratch, but for assembly language, allowing students and hobbyists to learn about low level programming
UC-046 Cat Classification of 20 Distinct Breeds
Full text linkCat breed classification algorithms have been made time and time before due to cats being such a popular and beloved animal. As such, classification algorithms aim to identify their breeds for veterinary pursuits and wildlife tracking which necessitates accurate classification. Our classification algorithm identifies 20 different CFA-recognized pedigreed cat breeds utilizing TensorFlow with the MobileNetV3 Large model as the base for training. Our preliminary results over 25 initial epochs and 25 fine tuning epochs resulted in a model with a test accuracy of 65%. In the future, we plan to add more techniques to prevent overfitting and experimenting with a more robust dataset which we hope will allow us to achieve our target accuracy of 80%
UC-066 Thought-Memory Model for Multi-Agent Simulation
Full text linkA 2D web-based multi-agent simulation leverages Large Language Models to model human-like interactions among generative agents. A Thought-Memory system retrieves relevant data and prior memories from a database to construct JSON-style prompts for the LLM, which outputs intended agent actions. The system allows for observable, emergent interactions between agents within the simulated space
UC-101 Sight-Singing Feedback
Full text linkThis project creates an engaging and interactive music-learning experience. Users start by selecting a tempo and melody number. The app then displays sheet music to guide them through the exercise. While singing, performers receive real-time visual feedback on pitch accuracy and tempo progression, allowing for dynamic adjustments and improved performance precision. The system continuously updates the music staff based on user performance, ensuring seamless interaction. This approach integrates technology with musical education, enhancing skill development through intuitive, data-driven feedback. By combining user-driven selections, interactive visualization, and real-time analysis, the application provides a structured, engaging platform for improving musical skills
UC-111 Accessible Interactive Map
Full text linkFinding that walking campus gets you out of breath? We did too! Using React and Flask, we are building a web application that directs KSU students to the path with the lowest elevation and shows the shifts in between. It also displays accessible doors. The purpose of this app is to develop a more inclusive application so people with asthma, cardiovascular issues, and wheelchairs at KSU can safely traverse campus
UR-018 Towards Bounding the Behavior of Deep Neural Networks
Full text linkRecent 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, we developed an improved approach to bounding the behavior of individual neurons within artificial neural networks. In this research we demonstrate, both theoretically and empirically, the utility of our approach
UR-114 K86: 16-Bit Computer Design, Optimization, and Implementation
Full text linkThis 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\u27s GCD algorithm, generating the binaries with a custom assembler written in Python