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Articles 1 - 30 of 537
Full-Text Articles in Physical Sciences and Mathematics
Gc-8 Informal Learning Artificial Intelligence Large Language Model Fine-Tuning On The Select Topic Of Entrepreneurship, Kristen Gabby, Melina Castellon, Jyothi Sampathirao
Gc-8 Informal Learning Artificial Intelligence Large Language Model Fine-Tuning On The Select Topic Of Entrepreneurship, Kristen Gabby, Melina Castellon, Jyothi Sampathirao
C-Day Computing Showcase
This project explored the usage and development of open-source Large Language Model (LLM) Artificial Intelligence (AI) with a chat feature, specifically to fine-tune on the topic of entrepreneurship. This project sought to showcase the adaptability of open-source LLMs and highlight challenges and solutions faced in leveraging those LLMs. The primary goal was to show proof of concept that training a LLM on the selected subject can create a specialized AI chat for informal learning.
Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati
Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati
C-Day Computing Showcase
With the quick rise of Artificial Intelligence (AI), generative AI models have greatly increased the volume and velocity of data creation. Among that data, AI-generated images have become a highly discussed topic, especially when discussing the potential dangers of these AI models. Due to these dangers, being able to distinguish AI-generated art from human-made art is becoming a necessity. Additionally, as these AI-models improve, it is becoming increasingly difficult for humans to determine whether art is AI-generated or human-made. This paper proposes the further exploration of the effectiveness of a current state of the art AI-image identification model.
Gmr-7 A Novel Identity Verification Framework Using A Hybrid Biometric System, Namratha Tavva, Bhanu Prakash Vadlamudi, Sumanth Kunchala, Snigdha Katta
Gmr-7 A Novel Identity Verification Framework Using A Hybrid Biometric System, Namratha Tavva, Bhanu Prakash Vadlamudi, Sumanth Kunchala, Snigdha Katta
C-Day Computing Showcase
In recent years, the field of big data analytics has gained immense attention due to the increasing volume and complexity of data being generated from various sources. One of the key applications of big data analytics is in the field of identity verification, where it is used to process and analyze large amounts of biometric data to authenticate individuals. A hybrid biometric system that combines multiple biometric modalities has been shown to be more effective in identity verification than a single modality system. In this project, we propose an Identity Verification Framework using a Hybrid Biometric System that leverages big …
Uc-64 Smart Evaluator Of Indirect Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes
Uc-64 Smart Evaluator Of Indirect Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes
C-Day Computing Showcase
The Smart Evaluator is a web-based software solution that analyzes industrial tools and their vending possibilities. It aims to streamline inventory research for sales teams, reducing manual data gathering and vendibility determination. To begin, users simply upload a basic item inventory spreadsheet, and start the program. From there, the program uses web scraping and ChatGPT to gather key data about the various tools including dimensions, weight, and fragility. Each item is then evaluated based on the collected data, and the optimum storage method is calculated. Once these tasks are performed, the results are stored in the system’s database for future …
Uc-82 Trip Logger, Reese D Gassner, Jason Zhou, Justin T Barker
Uc-82 Trip Logger, Reese D Gassner, Jason Zhou, Justin T Barker
C-Day Computing Showcase
We developed an Android mobile app using the Software Development Life Cycle (SDLC) approach to enable users to track their travel distance and time via GPS, fostering greater emissions awareness through their driving habits of distance and time taken. Built with the Flutter framework and Dart language, the app features a user-friendly interface created with Flutter widgets that manage both appearance and user interactions. Our streamlined architecture comprises three layers: the presentation layer for UI elements, the application layer containing the core logic, and the data layer, which locally stores trip data in CSV format to ensure quick access and …
Uc-99 Interactive Training Games - Robins Air Force Base, Sean J Tenney, Vt Nguyen, Ian Ford, Mason Farmer, Aaron Hannah
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
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-49 Coronary Artery Segmentation Using Convolutional Neural Network, Connor Bell, Brenda Nyiam, Daron L Pracharn
Ur-49 Coronary Artery Segmentation Using Convolutional Neural Network, Connor Bell, Brenda Nyiam, Daron L Pracharn
C-Day Computing Showcase
The project contributes to the advancement of medical imaging technology by overcoming the challenges associated with segmenting coronary arteries from ICA images. By leveraging deep learning algorithms, the system can effectively extract coronary arteries with high accuracy, providing valuable information for CAD diagnosis and treatment planning. Accurate and efficient coronary artery segmentation can improve the workflow of cardiologists and enhance the quality of patient care. A robust automated segmentation model could potentially reduce the time and resources required for manual annotation by experienced cardiologists, leading to cost savings and increased efficiency in clinical settings. Additionally, the developed model could be …
Ur-70 Faster Inequivalence Testing Using Robustness, Emily G Jackson
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
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-94 Emohydra: Multimodal Emotion Classification Using Heterogenous Modality Fusion, William A Stigall
Ur-94 Emohydra: Multimodal Emotion Classification Using Heterogenous Modality Fusion, William A Stigall
C-Day Computing Showcase
Affective computing is a field of growing importance, as human society becomes more integrated with machines. Human feelings are both complex and multi-modal, expressed through various methods and nuances in behavior. In this work we introduce EmoHydra, a multi-modal model created through the fusion of three top-level models fine-tuned on text, vision, and speech respectively. Despite heterogenous heads performing well on the unseen data, as well as generalizing well to other benchmarks, logit concatenation proves to be ineffective at predicting Multimodal data, therefore we implement Multi-Head Attention as our fusion mechanism.
Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla
Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla
C-Day Computing Showcase
The educational domain is undergoing transformation due to the incorporation of Artificial Intelligence (AI), Large Language Models (LLMs), and generative AI technologies, raising the need for educators to integrate cutting-edge technological advancements and methodologies into their teaching approaches. Pedagogical Design Patterns (PDPs) have become prominent for their role in sharing effective educational practices and narrowing the divide between academic research and actual teaching methods. Despite their potential, the lack of widely accessible resources and the scattered nature of publishing outlets pose significant barriers to the broad application of PDPS. To address this issue, we propose the application of large language …
Gc-104 Edai – Ai Enabled Teaching Robot For Informal Learning, Jennifer Bower, Shane Williams, Justice Fuller
Gc-104 Edai – Ai Enabled Teaching Robot For Informal Learning, Jennifer Bower, Shane Williams, Justice Fuller
C-Day Computing Showcase
We began our project by researching various popular, open-source AI tools that are available today. After we chose to focus on ChatGPT as our AI tool, we decided on cybersecurity as our subject matter. Next, we researched traditional cybersecurity training methods used by companies to train their employees on cybersecurity issues. Our project focused on determining whether or not open-source AI tools such as ChatGPT could replace traditional cybersecurity training tools and methods for companies.
Gc-101 Learning Resource Finder: A Web Scraping Tool For Educational Materials, Ashrith Kumar Devara
Gc-101 Learning Resource Finder: A Web Scraping Tool For Educational Materials, Ashrith Kumar Devara
C-Day Computing Showcase
The Learning Resource Finder is a pioneering tool designed to alleviate the challenges associated with navigating the vast landscape of online educational content. Leveraging sophisticated web scraping techniques and API integrations, this tool empowers users to efficiently discover relevant learning materials tailored to their specific needs. Through a user-friendly Flask-based web interface, users initiate search queries, which are then encoded and utilized to fetch pertinent URLs from leading educational platforms such as JavaTPoint, W3Schools, Coursera, Udemy, and GeeksforGeeks, as well as Google search results. The core of the web scraping process lies in the meticulous extraction of URLs from HTML …
Gc-17 Crm For Ccse Department Of Ksu, Venkatesh Alla, Keerthi Nannapaneni, Vinay Kumar Rapolu
Gc-17 Crm For Ccse Department Of Ksu, Venkatesh Alla, Keerthi Nannapaneni, Vinay Kumar Rapolu
C-Day Computing Showcase
This project outlines the development of a bespoke Customer Relationship Management (CRM) system specifically designed for the College of Computer and Software Engineering (CCSE). The initiative aims to centralize customer information into a unified repository, thereby enhancing the confidentiality, management, and optimization of data and communication processes within the college. The CRM system will integrate features for detailed profiles, communication optimization, complex workflow management, document repository, and data migration to ensure efficiency and data integrity. It will also facilitate seamless interaction with Microsoft 365 and Outlook, supporting the college's operational needs and maintaining its commitment to excellence in education and …
Gc-22 Fabric Moderation Ticketing Mod For Minecraft, John Lambert, Kathy Nguyen, Hayden B Scarbrough, Dasiane Taplin
Gc-22 Fabric Moderation Ticketing Mod For Minecraft, John Lambert, Kathy Nguyen, Hayden B Scarbrough, Dasiane Taplin
C-Day Computing Showcase
This project targets enhancing the KSU Esports program’s Minecraft server by implementing an in-game ticketing system. The system will enable players to report any instances of in-game incidents/issues seamlessly within the game environment. The integration with the KSU Minecraft Discord server will facilitate efficient communication between players and administrators. With a user-friendly interface and optimized resource usage, the system aims to streamline moderation processes.
Gmr-45 Cloud Based Bus Tracking And Ticketing System, Vyghni Sudha Kommineni, Damacharla Sravani
Gmr-45 Cloud Based Bus Tracking And Ticketing System, Vyghni Sudha Kommineni, Damacharla Sravani
C-Day Computing Showcase
In many urban areas, public transportation systems frequently fail to fulfill passenger demand, causing aggravation owing to a lack of real-time information about bus locations, timetables and delays. Outdated ticketing processes, which are labor-intensive and prone to mistakes, compound the annoyance by failing to match current travelers' expectations. Furthermore, transportation operators encounter difficulties with fleet management, route optimisation, and issue response due to a lack of comprehensive data analytics. Reliable monitoring systems are required to prioritize passenger and bus safety, and achieving sustainability targets necessitates efficient operations to reduce fuel consumption and emissions. A scalable and customizable cloud-based bus tracking …
Gmr-118 Stress Detection By Wearable Devices: Integrating Multimodal Physiological Signals And Machine Learning Techniques, Pranita Subhash Shedage
Gmr-118 Stress Detection By Wearable Devices: Integrating Multimodal Physiological Signals And Machine Learning Techniques, Pranita Subhash Shedage
C-Day Computing Showcase
In the medical field, the most common complaint of patients is “stress”. Stress can cause severe effects on the human body. For example, prolonged mental stress can cause serious health issues in long term such as hypertension, cardiovascular diseases, increased susceptibility to infections, and depression. These health issues can be prevented by early detection of stress and by taking preventive measures. The most common detecting stress was determined from the questionnaires or from the interactive sessions conducted to assess the people's affective state. However, this method is not highly reliable and can be biased depending on the person who is …
Gmr-59 Customer Segmentation For Marketing Campaigns Using K-Means Clustering, Jaswanthi Vellanki, Hrithik Singh Chandel, Vyghni Sudha Kommineni, Priyanka A Bagal, Rutvikkumar K Ramani
Gmr-59 Customer Segmentation For Marketing Campaigns Using K-Means Clustering, Jaswanthi Vellanki, Hrithik Singh Chandel, Vyghni Sudha Kommineni, Priyanka A Bagal, Rutvikkumar K Ramani
C-Day Computing Showcase
The objective of this project is to use K-means clustering an unsupervised machine learning algorithm to categorize customers based on characteristics such as demograp hics, purchasing history and interaction behavior. The purpose is to discover different client segments that can be targeted with specialized marketing techniques that improve marketing campaign efficiency and increase consumer satisfaction and engagement.
Gmr-23 Jamming Signal Detection Using Extreme Gradient Boosting (Xgboost) Algorithm, Keerthana Adamana, Christian K Sao
Gmr-23 Jamming Signal Detection Using Extreme Gradient Boosting (Xgboost) Algorithm, Keerthana Adamana, Christian K Sao
C-Day Computing Showcase
Radar jamming involves sending intentionally disruptive radio waves toward the target radar, which might over-saturate its receiver so it can’t receive anything or deceive it into interpreting false information. Machine learning (ML) techniques increased the capability to automatically learn the experience without being explicitly programmed. Machine learning models usually require a large, labeled sample to perform. Building a robust jamming detection model will be challenging due to the wide variability of jamming signals and less available labeled samples. In this project, we developed an eXtreme Gradient Boosting(XGBoost) algorithms for radar jamming signal classification and achieved superior performance compared with Random …
Gc-84 Owl Cyber Defense Systems, Randolph S Gilstrap, Christopher Dunbar, Stephanie Aguirre, Ryan M Leblanc, Justin Place
Gc-84 Owl Cyber Defense Systems, Randolph S Gilstrap, Christopher Dunbar, Stephanie Aguirre, Ryan M Leblanc, Justin Place
C-Day Computing Showcase
Owl Cyber Defense Systems is a fictitious (for now?) start-up offering comprehensive cybersecurity solutions for small and medium businesses. Our premier flagship product is an AI Chatbot that answers security related questions and provides vetted code and security settings to secure and harden a variety of systems. Starting with the initial concept, we methodically progressed through the business planning process, carefully considering technology usage and design. This comprehensive approach ultimately enabled us to develop a robust set of client offerings. We used a hybrid approach combining Agile Scrum and traditional Waterfall methodologies to complete the project. We utilized Jira Project …
Uc-27 Crm Proposal, Luis A Maiocchi Castro, Crystal Misko, Steven Damico, Ethan Groves, Maryah Outlaw
Uc-27 Crm Proposal, Luis A Maiocchi Castro, Crystal Misko, Steven Damico, Ethan Groves, Maryah Outlaw
C-Day Computing Showcase
This project addresses concerns raised by a Sponsor regarding inefficiencies in managing CCSE capstone projects. Key pain points include organization, project management, and communication among stakeholders. The proposed solution involves implementing Customer Relationship Management (CRM) software. Upon gathering requirements from the Sponsor, including contact information capture, workflow management, document control, and customization capabilities, we evaluated several CRM platforms. A total of thirty-two CRMs were reviewed and Vtiger, OroCRM, and SuiteCRM were selected for testing. SuiteCRM was chosen for its comprehensive features and user-friendliness. The second step of the project involved testing SuiteCRM functionalities on a dedicated server, leading to its …
Uc-33 Big Munchin', Tabitha Reynolds, Steven M Amerson, David J Buck, Jacques P Gatipon, Aaliyah Mcelrath, Nick S Watson
Uc-33 Big Munchin', Tabitha Reynolds, Steven M Amerson, David J Buck, Jacques P Gatipon, Aaliyah Mcelrath, Nick S Watson
C-Day Computing Showcase
Big Munchin' is a video game designed to help teach portioning skills and promote healthy eating habits. The overall metabolic health of individuals in America is comparatively low to other countries. Metabolic health is bolstered by several factors including exercise and a proper diet consisting of essential vitamins, proteins, and other important biomolecules.The increased cost of healthy nutrient-rich foods and a lack of proper nutritional education have hindered the overall metabolic health of modern Americans. Engaging individuals in learning more about nutritional health can be a difficult task made easier by an engaging experience that stays in the user’s minds. …
Uc-35 Ksu Ccse Crm, Alex Curran, Dj Mitchell, Christian Miller
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 …
Gc-67 Automatic Daily Financing Headlines Collection, Storage, Analysis And Presentation, Sahithi Atimamula, Jasminn O Evans, Julian Reyes, Victoria Castro, Krista G Settle
Gc-67 Automatic Daily Financing Headlines Collection, Storage, Analysis And Presentation, Sahithi Atimamula, Jasminn O Evans, Julian Reyes, Victoria Castro, Krista G Settle
C-Day Computing Showcase
The "Automatic Daily Financing Headlines Collection, Storage, Analysis, and Presentation" project aims to streamline the process of gathering financial headlines from financial news sources, storing them systematically, performing analysis, and presenting the insights in a user-friendly format. This automation project is designed to provide timely and relevant financial information to users interested in staying informed about market trends, economic news, and financial events. By automating the entire workflow, users can stay informed, make data-driven decisions, and navigate the dynamic landscape of financial news with ease. The project embodies the fusion of automation, data analytics, and user-centric design to create a …
Gmr-90 Digimindready: Enhancing Military Readiness With Edge Ai-Driven Wellness, Education, And Digital Discipline Through Mhealth Innovation., Md Mehedi Hasan, Nafisa Anjum
Gmr-90 Digimindready: Enhancing Military Readiness With Edge Ai-Driven Wellness, Education, And Digital Discipline Through Mhealth Innovation., Md Mehedi Hasan, Nafisa Anjum
C-Day Computing Showcase
Military personnel often need to operate in high-stakes situations. Combating such volatile missions primarily includes control over cognitive overload, reckless mindset, and maintaining concentration amid distractions to sustain operational effectiveness. Military training significantly focuses on human performance, which benefits military readiness. However, the 21st century has introduced unanticipated challenges, such as adverse effects of excessive screen time, external distractions, and over-reliance on technology to the US military, on top of existing issues like anxiety and emotional stability, adversely impacting military readiness and decreasing quality of life. A strategic investigation into these issues and the advancement of effective tools to address …
Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota
Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota
C-Day Computing Showcase
Predicting house prices is a challenging task that researchers from various fields (economics, statistics, politics, etc.) have attempted to answer. An accurate house prediction is useful not only to policymakers to improve their policies, but also to help sellers and buyers in the real estate market make well- informed decisions. Commonly, prediction models are trained on the whole dataset. However, as Azimlu et al [1] suggested, such models might not perform very well on dispersed data. They propose a new approach which first divides the whole dataset into smaller clusters, and then each cluster would be trained with an appropriate …
Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam
Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam
C-Day Computing Showcase
In the rapidly evolving fields of Artificial Intelligence and Natural Language Processing, significant opportunities have emerged to transform educational practices. Discourse analysis, particularly in science education, plays a critical role in fostering scientific thinking among students. However, the manual application of tools like the Classroom Discourse Analysis Tool is resource-intensive and impractical on a large scale. This abstract proposes the development of an AI-based Discourse Analysis System tailored for educational settings, designed to automate and enrich the analysis of classroom discourse. Leveraging the latest in Artificial Intelligence and Natural Language Processing, this web-based application will provide teachers nationwide with the …
Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher
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 …
Uc-69 Interactive Training Game Suite, Garrett J Perry, Joscelyn Cauley, Issabella Du, Sergiu Ursu, Rahaf Kokash
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 …