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Articles 31 - 60 of 82
Full-Text Articles in Physical Sciences and Mathematics
Ur-510 Exploring The Impact Of Wavelength In Non-Invasive Blood Glucose Monitoring, John E. Oakley, Tahsin Kazi
Ur-510 Exploring The Impact Of Wavelength In Non-Invasive Blood Glucose Monitoring, John E. Oakley, Tahsin Kazi
C-Day Computing Showcase
Diabetes and metabolic diseases are some of the most crucial health issues of the 21st century. Monitoring blood glucose, the lead indicator of these diseases is a cumbersome process of constantly drawing blood or using subcutaneous needles. However, new technologies have emerged for non-invasive blood glucose monitoring that uses spectroscopy, which involves emitting light and capturing patient data with cameras. These new devices remove the cost of multiple tests, reduce the risk of skin conditions, and create more patient-friendly solutions. However, the hardware variables of these devices have not been tested thoroughly. One such avenue is via laser wavelength, which …
Eur-525 Ai-Based Quiz Generation: The Role Of Llms In Digital Education, Devananda Sreekanth
Eur-525 Ai-Based Quiz Generation: The Role Of Llms In Digital Education, Devananda Sreekanth
C-Day Computing Showcase
Our investigation delves into the application of Large Language Models (LLMs) and AI in crafting quiz-based learning tools for college students. We sifted through academic resources, utilizing keywords such as "AI," "GPT," "BERT," and "LLM," and pinpointed 24 pivotal papers out of over 80. Our findings highlight a preference for models like GPT-3, with newer technologies like BERT and RAG less represented, suggesting potential avenues for future inquiry. The research employed a structured methodology that encompassed an exhaustive literature review, trend analysis over time, and detailed textual scrutiny of AI technology mentions and innovative methods within the domain. This approach …
Gc-444 It Course Profile Website, Manikanta Voruganti
Gc-444 It Course Profile Website, Manikanta Voruganti
C-Day Computing Showcase
Build a Dynamic course profile website for Bachelor of science in information technology courses, that display all the information regarding the course.
Gr-405 Boosting Clickbait Detection Through Semantic Insights And Attention-Driven Neural Network, Lokesh Meesala
Gr-405 Boosting Clickbait Detection Through Semantic Insights And Attention-Driven Neural Network, Lokesh Meesala
C-Day Computing Showcase
The digital age has witnessed an explosion of online content, making it increasingly challenging for users to differentiate between reliable information and clickbait, which is often misleading or sensationalized. Clickbait contributes to the spread of misinformation, phishing attacks, and illegal marketing practices, and manipulates users’ decisions. Even from a business standpoint a clickbait might not lead to a conversion, A user might land on the page by following a clickbait and get frustrated and close the page. Additionally, with the increase in the usage of large language models for content writing it is even more challenging for the general user …
Gr-422 Simplified Named Entity Recognition Using Context Free Grammar, Sai Chandana Koganti, Varshini Yaganti, Vinesh Babu Yaganti, Surya Kiran Katragadda, Pavani Thulluru
Gr-422 Simplified Named Entity Recognition Using Context Free Grammar, Sai Chandana Koganti, Varshini Yaganti, Vinesh Babu Yaganti, Surya Kiran Katragadda, Pavani Thulluru
C-Day Computing Showcase
Named Entity Recognition (NER) is a crucial component of natural language processing. Although Spacy is a popular tool for NER, it faces challenges in accurately identifying individual's names. In response, Context-Free Grammar (CFG) is introduced as a complementary solution to augment Spacy's NER functionality, with the specific objective of enhancing the precision of person name recognition. This project focuses on formulating CFG rules and applying them to a sample text, showcasing improved NER accuracy. By combining the strengths of Spacy and CFG, we aim to address the limitations of current NER systems, particularly in recognizing individual's names, and contribute to …
Gr-453 Medical Records Summarization Using Prompt-Based Nlp, Rawan Masadeh, Nicholas S Servies
Gr-453 Medical Records Summarization Using Prompt-Based Nlp, Rawan Masadeh, Nicholas S Servies
C-Day Computing Showcase
In this paper, we present an innovative Natural Language Processing (NLP) algorithm for summarizing medical records extracted from the MIMIC-IV dataset using state-of-the-art (SOTA) techniques in text summarization. The increasing volume of electronic health records (EHRs) demands efficient methods for extracting meaningful insights from these complex and extensive documents. Our algorithm leverages recent advancements in NLP, including transformer-based models, to automate summarizing medical records while preserving critical information. Our algorithm is trained and tested using the Medical Information Mart for Intensive Care (MIMIC)-IV database that provides critical care data for over 40,000 patients admitted to intensive care units at the …
Gr-485 Email Summarizer And Action Item Extractor, Ryan Deem, Eric C Weese
Gr-485 Email Summarizer And Action Item Extractor, Ryan Deem, Eric C Weese
C-Day Computing Showcase
Countless emails are sent and received daily, and a lot of time is spent reading through and understanding the content of these emails. This project aims to increase the efficiency of reading and gathering relevant email information. Our solution includes two parts: abstractive text summarization and action item extraction. Currently, these two items are common in different domains, however, they have not been combined and used with email understanding. Abstractive text summarization is the process of outputting the ideas of the emails using different words without giving quotes from the document. In this way, a person would be able to …
Gr-519 Meditation As An Intervention To Improve Student Attention An Eeg Study Based On Machine Learning Prediction And Spectral Ratio Analysis, Sreekanth Gopi
Gr-519 Meditation As An Intervention To Improve Student Attention An Eeg Study Based On Machine Learning Prediction And Spectral Ratio Analysis, Sreekanth Gopi
C-Day Computing Showcase
This research aims to develop a machine learning model using EEG data to identify student inattention, serving as an early intervention tool. Attention deficit, influenced by social media, adversely affects student performance. ADHD, characterized by inattention, hyperactivity, and impulsivity, is linked to academic challenges. Early detection in academics is crucial. A Machine Learning model was designed, and trained on an attention dataset with 34 EEG recordings of young adults. The raw EEG data was pre-processed and filtered, ICA was applied, and spectral analysis was done. Guided meditation with music was developed as an intervention to improve attention. EEG recordings from …
Uc-400 Electric Vehicle Team, Brandon A Solon, Austin D Klein, Caleb Mcmaster
Uc-400 Electric Vehicle Team, Brandon A Solon, Austin D Klein, Caleb Mcmaster
C-Day Computing Showcase
The KSU Electric Vehicle Team is developing a fully autonomous electric go-kart to compete in the Autonomous Karting Series (AKS). Our team will be making two programs for the kart’s software stack. These programs include a race line optimizer, which can take the centerline of a track and generate a minimum curvature path for it to follow to get around the track faster, as well as a race controller which can switch navigation algorithms automatically based on the current conditions of the race.
Uc-408 Web Hardening, Christopher Brown, Spencer J Jackson, Lynder Kigo, Gabrielle Hooper
Uc-408 Web Hardening, Christopher Brown, Spencer J Jackson, Lynder Kigo, Gabrielle Hooper
C-Day Computing Showcase
Our project focuses on ethical hacking and defending in the form of a red/blue team. Our project was broken into 3 phases. In Phase one we were given a server stack and told to do what we could in order to analyze weak points. In phase 2 we were told to bolster the defenses of those weak points. Lastly, in phase 3 were we given an IP address of an opposing team to attack while defending against another teams advances.
Uc-413 I Spy... Water Safety, Caden M. Robertson, Danny Winters, Denice Jaquez, Tahj Brown, Maksims D. L'Hernault
Uc-413 I Spy... Water Safety, Caden M. Robertson, Danny Winters, Denice Jaquez, Tahj Brown, Maksims D. L'Hernault
C-Day Computing Showcase
I Spy Water Safety is a game that teaches people about the importance of water safety around a lake. Our goal is to teach people proper water safety etiquette and lower the amount of water-related incidents.
Uc-433 Finding The Limits Of Ai For Web Development In 2023, Christopher S. Layson, Njagi Kagika, Christian Bush-Cunningham, Ismail O. Lawal, Adam Z. Nash
Uc-433 Finding The Limits Of Ai For Web Development In 2023, Christopher S. Layson, Njagi Kagika, Christian Bush-Cunningham, Ismail O. Lawal, Adam Z. Nash
C-Day Computing Showcase
Our team was tasked with finding the limits of artificial intelligence for web development in 2023. This involved our team researching what the different parts of a website are, how to prompt an AI chatbot to provide us with source code, and how to put together a working prototype of an auction website by the end of our project. Our team produced various documents along the way that show our progress such as various slideshow files, documentation word docs, and a research report on our findings. After working with the AI to produce source code for our website, we have …
Gc-412 Ecoedconnect, Vidhi Dave, Mythili Jayaraman, Manikanta Reddy Anugu, Rohini Paithanker, Neharika Beeram
Gc-412 Ecoedconnect, Vidhi Dave, Mythili Jayaraman, Manikanta Reddy Anugu, Rohini Paithanker, Neharika Beeram
C-Day Computing Showcase
An inventive educational platform called EcoEdConnect provides high school students with various opportunities to investigate biodiversity and environmental issues. By adjusting to each user's needs and choices, the web app offers a customized educational experience such as quizzes, experiments, videos, blogs, articles, etc. The project's first analysis, methodology, and early conclusions are presented in this document. It shows the several phases of the project, such as the introduction modules, practical experiments, discussions, blog, final assessment, and presentation, among other things. The application customizes the material and complexity according to the user's inclinations. Students' knowledge of biodiversity and environmental issues and …
Gr-406 Federated Learning In Cardiac Diagnostics: Balancing Predictive Accuracy With Data Privacy In Heart Sound Classification, Sricharan Donkada
Gr-406 Federated Learning In Cardiac Diagnostics: Balancing Predictive Accuracy With Data Privacy In Heart Sound Classification, Sricharan Donkada
C-Day Computing Showcase
Cardiovascular diseases account for nearly a third of global deaths, posing a challenge that machine learning can help address. However, data privacy concerns hinder the direct application of conventional machine learning in this sensitive area. This paper explores Federated Learning (FL) as a decentralized strategy to mitigate these concerns by allowing for local data processing. FL's design ensures that only processed updates, not raw data, are shared with a central server, maintaining individual privacy. Our research assesses FL's practicality and effectiveness in predicting heart disease while adhering to ethical and legal norms. We build upon previous studies, such as Wanyong …
Uc-395 Ccse Reservation Application, Nicholas Kelley, Tykira Carreker, Keith Mutisya, Aaron Hyatt
Uc-395 Ccse Reservation Application, Nicholas Kelley, Tykira Carreker, Keith Mutisya, Aaron Hyatt
C-Day Computing Showcase
The CCSE department tasked us with creating an application to streamline the reservation of the rooms and equipment maintained by the college. To achieve this, we developed a front-end application created with PHP that allows users to view available resources, and request reservations for them. We created and maintained a back-end database configured with MySQL through phpMyAdmin to allow for the easy integration with the front end. Through the project we created new functions in the application with the user in mind, to create the best possible application to fit the needs of the CCSE department.
Ur-445 Symphony Of Silicon: Rethinking Music Creation Through Deep Learning Models, Gabriel T. Gillott
Ur-445 Symphony Of Silicon: Rethinking Music Creation Through Deep Learning Models, Gabriel T. Gillott
C-Day Computing Showcase
Generative AI has transformed music creation, blending human and machine artistry. This study presents a neural network model trained on piano MIDI files for music generation, utilizing LSTM and self-attention mechanisms to capture music's complexity. Bayesian optimization with Tree-structured Parzen Estimator (TPE) refines the model's hyperparameters. The architecture includes bidirectional GRUs and self-attention layers, trained on the extensive Magenta MAESTRO dataset. The model, bettered by TPE over conventional tuning, is assessed for accuracy and expressiveness. The paper details the model's design and validates TPE's efficiency, marking progress in AI's creative application in music.
Gc-417 It Curriculum Success Portal, Alexander Thacker, Cedric Boakye-Danquah, Damola Adeyemo, Abdoulaye Ndiaye, Lydia Asante
Gc-417 It Curriculum Success Portal, Alexander Thacker, Cedric Boakye-Danquah, Damola Adeyemo, Abdoulaye Ndiaye, Lydia Asante
C-Day Computing Showcase
In this project, we built a curriculum and course web portal to have all curriculum and course information in one place with easy search and browse interfaces. Currently course data and information are scattered in various places. These include essential information like course description, learning outcomes, sample syllabus, offering schedule and history. It also includes curriculum development information for department use, such as coordinator, developer, revision schedule, open learning materials. We collected all sources of IT course information and built a database to integrate the data in one place. Through this, we can build a complete profile of a course …
Gc-427 Elevating Ai Research: Creating A Website For Kennesaw State University's Ai Lab, Shashank Gadhe
Gc-427 Elevating Ai Research: Creating A Website For Kennesaw State University's Ai Lab, Shashank Gadhe
C-Day Computing Showcase
The project titled "Elevating AI Research: Creating a website for Kennesaw State University's AI Lab" is dedicated to developing an HTML5 Content Management System website for Kennesaw State University. This website, AILab.kennesaw.edu, serves as a dedicated platform to showcase lab facilities, ongoing projects, and cutting-edge research, with a focus on promoting global AI research and education. Our target audience encompasses university students, faculty, AI researchers, and organizations with an interest in AI innovation.Preliminary findings support our goal: engaging platforms showcasing AI Lab research effectively.The incorporation of admin access empowers university professors to customize content, thus enhancing adaptability and personalization. These …
Gc-448 Project Title: Discover, Learn, And Protect: A Mobile App For Informal Stem Learning About Local Biodiversity And Environmental Issues., Elvin Mccray, David Y. Appah, Adedunmola Banu, Binh Tran, Zenya Tucker
Gc-448 Project Title: Discover, Learn, And Protect: A Mobile App For Informal Stem Learning About Local Biodiversity And Environmental Issues., Elvin Mccray, David Y. Appah, Adedunmola Banu, Binh Tran, Zenya Tucker
C-Day Computing Showcase
Our team assignment for this project was to create a mobile application that offers informal STEM learning about local biodiversity and environmental issues. Dr. Ying Xie, Professor in the College of Computing and Software Engineering (CCSE) is the owner of this project, who also laid out required features and provided necessary information, guidance, and advice for the project development. The core function of this application is to empower users to explore, identify and gain insights into the plant and animal species native to their region. Leveraging the capabilities of their smartphone’s camera, users can effortlessly scan, record, or locate local …
Gr-430 Plant Disease Detection Using Cnn, Nandini Shankara Murthy, Divya Vasireddi, Mounika Kulkarni
Gr-430 Plant Disease Detection Using Cnn, Nandini Shankara Murthy, Divya Vasireddi, Mounika Kulkarni
C-Day Computing Showcase
Plant diseases are a major source of worry for farmers and the agricultural business. We hope to create a system that can assist in identifying and controlling these diseases more efficiently by leveraging the capabilities of deep learning. This not only protects agricultural yields but also adds to agriculture's sustainability and economic well-being. For this project we have chosen a suitable dataset from Kaggle: Kaggle Dataset: https://www.kaggle.com/datasets/emmarex/plantdisease/data Dataset Overview: The Plant Village dataset contains images of various crops, with each belonging to different classes representing diseases and healthy states. Having a diverse set of images presents an opportunity for deep …
Gr-434 Phase Estimation’S Application In Qram, Ethan K Hunt
Gr-434 Phase Estimation’S Application In Qram, Ethan K Hunt
C-Day Computing Showcase
The paper proposes a new novel way of creating QRAM through quantum phase estimation. This is done by mapping a monotonically increasing sequence of natural numbers to a binary series and, ultimately, to a characteristic constant η which is then encoded as a phase in a quantum state. This process leverages quantum phase estimation, a fundamental quantum algorithm for finding the eigenvalues of a unitary operator which can be used as a form of QRAM in either Quantum or Hybrid models of computing
Gr-450 Enhancing Sarcasm Detection With Context Sensitivity, Sai Chandana Koganti, Varshini Yaganti, Venkata Sai Ashik Yadali, Vinesh Babu Yaganti, Hemanth Borra
Gr-450 Enhancing Sarcasm Detection With Context Sensitivity, Sai Chandana Koganti, Varshini Yaganti, Venkata Sai Ashik Yadali, Vinesh Babu Yaganti, Hemanth Borra
C-Day Computing Showcase
Sarcasm identification is a vital challenge in natural language processing. In this project, we address this challenge by employing a context-sensitive approach that leverages deep learning, transformer learning, and conventional machine learning models. We conducted our research using two benchmark datasets: Twitter and Internet Argument Corpus (IAC-v2). Our three primary models—Bi-LSTM with GloVe embeddings, BERT, and feature fusion—outperformed baseline methods, achieving an 89.4% highest accuracy on Twitter datasets and an 81.2% highest precision on IAC-v2. These results highlight the effectiveness of our approach in sarcasm detection, with significant implications for sentiment analysis and opinion mining. While our project provides promising …
Gr-461 Sudoku Solver Using Brute Force Algorithm With Backtracking Approach, Md Shamsul Alam, Md Jahirul Islam, Vyghni Sudha Kommineni, Jaswanthi Vellanki, Poka Sudheer
Gr-461 Sudoku Solver Using Brute Force Algorithm With Backtracking Approach, Md Shamsul Alam, Md Jahirul Islam, Vyghni Sudha Kommineni, Jaswanthi Vellanki, Poka Sudheer
C-Day Computing Showcase
Sudoku is a fun game that challenges our brain to think logically. It only has numbers from 1 to 9 in a 9x9 matrix network where the nine numbers should not be repeated in the same column, row or each 3x3 submatrix. Although there are numerous methods to solve this problem, the most common method is the backtracking algorithm. So, we are using brute force algorithm to solve sudoku and then compare it with backtracking to ensure which algorithm gives best results.
Gr-512 A Fcfs Approach For Order Of Operations In Arithmetic Formalism In Programming Languages, Ethan K Hunt
Gr-512 A Fcfs Approach For Order Of Operations In Arithmetic Formalism In Programming Languages, Ethan K Hunt
C-Day Computing Showcase
This paper provides the description of my research project on the computational power a programming language can have that uses an arthritic model that has a first come first serve approach to the order of operations. The goal of such analysis is to verify if such a method of computation can enclose all basic arithmetic and algebraic expressions, the answer to which will help disclose the computational limitations of certain programming language frameworks.
Egr-518 A Multi-Model Approach For Detecting And Combating Fake News, Sujisha Devineni, Thrisandhya Bodakunta
Egr-518 A Multi-Model Approach For Detecting And Combating Fake News, Sujisha Devineni, Thrisandhya Bodakunta
C-Day Computing Showcase
Internet plays a vital role in our daily lives, we use it for various purposes and benefit from advancements in technology and social media. However, the same platforms which make global information exchange also promote spread of fake news,raising a significant threat. To resist this issue, fact checking has become important, leading to extensive research to identify fake news and deal problems arising with them. Our project’s mission is to find the most effective model for fake news detection. We explore different approaches and models, like BERT, Decision Trees, Logistic Regression, and Ada Boost classification and evaluate their performance by …
Uc-441 Finding The Limits Of Ai For Web Development In 2023, Jessica Chavez, Jackson A. Chastine, Joel R. Eve, Danish Khan, Alexandre D. Garcia
Uc-441 Finding The Limits Of Ai For Web Development In 2023, Jessica Chavez, Jackson A. Chastine, Joel R. Eve, Danish Khan, Alexandre D. Garcia
C-Day Computing Showcase
This Project explores the limits of artificial intelligence (AI) in web development, focusing on the year 2023. The study is conducted by AI Limits Team 1 from Kennesaw State University. The primary objective of the project is to harness the potential of ChatGPT 3.5, an advanced AI model, to create a fully functional Auction House Website. The achievements of the project include innovative web development, AI-generated content, and successful integration of AI into both frontend and backend aspects of web development. The research findings offer valuable insights into ChatGPT's proficiency in generating web application code and emphasize the importance of …
Eur-443 The Compression Connection: Ncd And Knn In Law Enforcement Text Analytics, Gabriel T. Gillott
Eur-443 The Compression Connection: Ncd And Knn In Law Enforcement Text Analytics, Gabriel T. Gillott
C-Day Computing Showcase
Facing a deluge of digital records, law enforcement needs advanced data sorting systems. This project uses a new NLP model, blending compression algorithms and KNN, to categorize Cobb County police reports by mental health, behavioral, and drug issues—vital for efficient resource allocation. The model employs Normalized Compression Distance (NCD) to discern text similarities, enhancing analysis of varying report styles. Early tests show promise in label categorization, but generalizing remains challenging, marking future research directions. This NLP advancement could revolutionize data handling in public safety, aiming to surpass current classification standards.
Data Quality Checks: Implementation With Popular Data Collection Crowdsourcing Platforms, James Down, Gregory Balkcom, Kristine Duncan, Ngan (An) Truong, Andrew Lewis
Data Quality Checks: Implementation With Popular Data Collection Crowdsourcing Platforms, James Down, Gregory Balkcom, Kristine Duncan, Ngan (An) Truong, Andrew Lewis
Symposium of Student Scholars
The utilization of online crowdsourcing platforms for data collection has increased over the past two decades in the field of public health due to the ease of use, the cost-saving benefits, the speed of the data collection process, and the accessibility of a potentially true representative population. Although these platforms offer many advantages to researchers, significant drawbacks exist, such as poor data quality, that threaten the reliability and validity of the study. Previous studies have examined data quality concerns, but differences in results arise due to variations in study designs, disciplinary contexts, and the platforms being investigated. Therefore, this study …
Machine Learning In Minecraft: Proof Of Concept For Object Detection Oriented Autonomous Bots In Minecraft, John Merkin
Machine Learning In Minecraft: Proof Of Concept For Object Detection Oriented Autonomous Bots In Minecraft, John Merkin
Symposium of Student Scholars
Machine learning provides new methods of problem solving through applied pattern recognition. An interesting challenge is to utilize machine learning in the automation of tasks and behaviors in virtual environments. Minecraft is an open-world, sandbox style game giving players nearly limitless freedom to alter a procedurally generated world. In the survival game mode, the player must collect resources to craft tools and build structures. The collection of resources can be tedious, so this project seeks to automate the standard initial task of collecting wood. By combining a convolutional neural network with API, a bot can collect resources while remaining scalable …
Toxic Comment Classification Project, Brandon Solon
Toxic Comment Classification Project, Brandon Solon
Symposium of Student Scholars
The digital landscape has blossomed thanks to the surge of online platforms, boosting the variety and volume of user-created content. But it's not without its shadows; cyberbullying and hate speech have also proliferated, making web spaces less safe. At our project centerstage, we work on creating a machine learning model skilled at spotting toxic comments with precision - this way contributing towards an internet society free from fear or discomfort. We put well-documented datasets to good use along with careful preprocessing maneuvers while trialing diverse machina-learning protocols as part of constructing solid classification architecture for usages beyond current limitations within …