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Kennesaw State University

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Articles 541 - 570 of 1161

Full-Text Articles in Computer Sciences

Ur-409 Enhancing Aircraft Electronic Warfare Testing With Automated Rf Spectrum Analysis, Anthony De Santiago, Matthew T. Morgan, Geonhyeong Kim, Jalon L. Bailey, Camille Reaves Nov 2023

Ur-409 Enhancing Aircraft Electronic Warfare Testing With Automated Rf Spectrum Analysis, Anthony De Santiago, Matthew T. Morgan, Geonhyeong Kim, Jalon L. Bailey, Camille Reaves

C-Day Computing Showcase

Military test ranges utilize a variety of Radio Frequency (RF) threat systems, to assess the effectiveness of Electronic Warfare (EW) systems during flight tests. A component of this process involves monitoring RF transmissions. Traditionally, system engineers at Robins Airforce Base have manually analyzed video from spectrum analyzers to confirm properties of specific threat systems. To streamline this analysis, our team's aim was to develop an automated solution for RF spectrum analysis. We employed a custom YOLO V8 model to isolate the analyzer screen and used a novel combination of frame differencing, summing, and agglomerative clustering techniques to extract relevant properties …

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Eur-443 The Compression Connection: Ncd And Knn In Law Enforcement Text Analytics, Gabriel T. Gillott Nov 2023

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.

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Gc-412 Ecoedconnect, Vidhi Dave, Mythili Jayaraman, Manikanta Reddy Anugu, Rohini Paithanker, Neharika Beeram Nov 2023

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 …

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Gc-427 Elevating Ai Research: Creating A Website For Kennesaw State University's Ai Lab, Shashank Gadhe Nov 2023

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 …

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Egc-442 Sars-Cov-2 Spike And Ace2 Protein-Protein Interactions Database, Jovanny Duran Salgado, Durga Narayana Varma Addepalli, Travis Meeks, Pooja Venkata Ramana Adapa, Divya Sri Ambati Nov 2023

Egc-442 Sars-Cov-2 Spike And Ace2 Protein-Protein Interactions Database, Jovanny Duran Salgado, Durga Narayana Varma Addepalli, Travis Meeks, Pooja Venkata Ramana Adapa, Divya Sri Ambati

C-Day Computing Showcase

SARS-CoV-2 protein interactions are essential for viral replication and pathogenesis. To better understand these interactions, we have created a database using AWS (Amazon Web Services) to store data extracted from protein simulations. This database can be used to study the structure and function of SARS-CoV-2 proteins and their interactions with each other and with host cell proteins.

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Gc-447 Bio-Contribute, Tejaswi Divi, Kiranmayi Tandra, Sainath Reddy Bheemireddy, Chandrasekhar Reddy Bheemireddy, Sharanya Chinthakuntla Nov 2023

Gc-447 Bio-Contribute, Tejaswi Divi, Kiranmayi Tandra, Sainath Reddy Bheemireddy, Chandrasekhar Reddy Bheemireddy, Sharanya Chinthakuntla

C-Day Computing Showcase

The "Bio-Contribute" challenge is an ambitious initiative aimed at revolutionizing the way facts are generated and shared in lifestyle sciences. Bio-Contribute encompasses various aspects, including design, development, and facts collection. It leverages Figma for innovation, ensuring a user-friendly and collaborative interface. The challenge has completed the frontend development section, permitting customers to carry out various movements, which include content advent and information seizure with the help of the GPT-3 era. This report gives an in-depth analysis of the venture's progression, strategies used, and initial outcomes, demonstrating its potential to convert statistics introduction and sharing in the discipline of lifestyles sciences.

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Gc-479 Bioeduhub, Tejesh R Chintam, Shiswa Preethi Chopparapu, Viswa Narendra Reddy Panati, Lithin Venkata Sai Pasupuleti, Aravind Chopparapu Nov 2023

Gc-479 Bioeduhub, Tejesh R Chintam, Shiswa Preethi Chopparapu, Viswa Narendra Reddy Panati, Lithin Venkata Sai Pasupuleti, Aravind Chopparapu

C-Day Computing Showcase

Our project introduces an interactive and personalized learning experience aligned with the Next Generation Science Standards (NGSS). Users can explore a diverse range of topics related to biodiversity and environmental issues through quizzes, games, simulations, experiments, videos, podcasts, and articles. The web app adapts content to individual interests and provides tailored feedback to enhance knowledge, skills, attitudes, and behaviors related to these critical subjects. The user-friendly interface and comprehensive modules, including video lectures, readings, quizzes, hands-on experiments, debates, and assessments, ensure a holistic learning journey. Join us on a pathway to understanding and mitigating climate change while making a positive …

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Gr-406 Federated Learning In Cardiac Diagnostics: Balancing Predictive Accuracy With Data Privacy In Heart Sound Classification, Sricharan Donkada Nov 2023

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 …

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Gr-422 Simplified Named Entity Recognition Using Context Free Grammar, Sai Chandana Koganti, Varshini Yaganti, Vinesh Babu Yaganti, Surya Kiran Katragadda, Pavani Thulluru Nov 2023

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 …

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Gr-430 Plant Disease Detection Using Cnn, Nandini Shankara Murthy, Divya Vasireddi, Mounika Kulkarni Nov 2023

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 …

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Gr-450 Enhancing Sarcasm Detection With Context Sensitivity, Sai Chandana Koganti, Varshini Yaganti, Venkata Sai Ashik Yadali, Vinesh Babu Yaganti, Hemanth Borra Nov 2023

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 …

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Egr-470 Optimizing The Search In Location Using Svm, Naive Bayes, K-Means And Knn, Lalitha Sangamithra Mantha, Krishna Chaitanya Naraparaju, Abhishikth Vadlamani Nov 2023

Egr-470 Optimizing The Search In Location Using Svm, Naive Bayes, K-Means And Knn, Lalitha Sangamithra Mantha, Krishna Chaitanya Naraparaju, Abhishikth Vadlamani

C-Day Computing Showcase

The widespread adoption of global positioning technology has led to an increase in products featuring GPS functionality. These devices gather large amounts of location data. However, inherent inaccuracies in GPS data collection are unavoidable. To address these challenges, we shift our focus to identifying the closest points in a location. This requires gathering data to measure distances between a point and all others, and keeping a record of the nearest points. In this project, the Naive Bayes,SVM, k-means, and KNN algorithms are employed to determine the nearest points.

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Gr-485 Email Summarizer And Action Item Extractor, Ryan Deem, Eric C Weese Nov 2023

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 …

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Egr-494 Using A Non-System Language To Implement An Optimized Round Robin Scheduling Algorithm, Francis E Nweke Nov 2023

Egr-494 Using A Non-System Language To Implement An Optimized Round Robin Scheduling Algorithm, Francis E Nweke

C-Day Computing Showcase

The objective of this project is to create an optimized Round Robin scheduling algorithm in C# and examine the related performance metrics. In this study, I will evaluate performance by implementing the optimized model in a non-system language such as (C#). Our simulation would provide insight into the execution of many processes while taking into account arrival times, burst timings, and user-defined time quantum. We can interact with the simulator because it is a Graphical User Interface (GUI) software.

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Gr-504 Synthetic Dna Sequence Generation And Classification For Species Discrimination, Nishat Tasnim Nov 2023

Gr-504 Synthetic Dna Sequence Generation And Classification For Species Discrimination, Nishat Tasnim

C-Day Computing Showcase

The two main goals of this research are to apply machine learning models in computational biology to classify DNA sequences from different species and to create synthetic DNA sequences using GANs. Generative Adversarial Networks (GANs) synthesize DNA sequences while preserving key characteristics like sequence length and GC content. The dataset is enhanced by these artificial sequences, which makes classification jobs better. The classification accuracy of black rat and human genome sequences is evaluated using machine learning models, including Random Forest, SVM, and Logistic Regression. Notably, when trained with synthetic data, all models perform better.

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Gr-512 A Fcfs Approach For Order Of Operations In Arithmetic Formalism In Programming Languages, Ethan K Hunt Nov 2023

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.

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Egr-518 A Multi-Model Approach For Detecting And Combating Fake News, Sujisha Devineni, Thrisandhya Bodakunta Nov 2023

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 …

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Gr-519 Meditation As An Intervention To Improve Student Attention An Eeg Study Based On Machine Learning Prediction And Spectral Ratio Analysis, Sreekanth Gopi Nov 2023

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 …

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Ur-407 Illusion Of Weight: The Use Of Tactile Glove For Muscle Exercise For Elders In Virtual Gym Experience, Johnathon R. Autry Nov 2023

Ur-407 Illusion Of Weight: The Use Of Tactile Glove For Muscle Exercise For Elders In Virtual Gym Experience, Johnathon R. Autry

C-Day Computing Showcase

This pilot study aims to investigate the potential creation of the perception of weight through a blend of visual and tactile feedback. Utilizing a tactile glove with varying vibration intensities and virtual dumbbell sizes, the experiment explores multiple conditions. These include tactile intensity (small, medium, large), virtual dumbbell sizes (small, medium, large), and diverse visualizations—ranging from no virtual dumbbell with or without tactile feedback to scenarios including both virtual dumbbells and tactile feedback. The study evaluates the virtual reality exercise experience and real performance using EMG sensors to measure muscle response, Heart Rate (HR), Galvanic Skin Response (GSR), and hand …

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Ur-445 Symphony Of Silicon: Rethinking Music Creation Through Deep Learning Models, Gabriel T. Gillott Nov 2023

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.

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Eur-525 Ai-Based Quiz Generation: The Role Of Llms In Digital Education, Devananda Sreekanth Nov 2023

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 …

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Uc-394 Ai Limitations, Maria Hurtado Garcia, Syed S. Ahmed, Tuan T. Tran, Michael A. Ramcharan, Kristina Tuzova Nov 2023

Uc-394 Ai Limitations, Maria Hurtado Garcia, Syed S. Ahmed, Tuan T. Tran, Michael A. Ramcharan, Kristina Tuzova

C-Day Computing Showcase

Our project, "AI Limitations," explores the application of AI, in our case ChatGPT, in creating an online auction website. It investigates the boundaries of ChatGPT's capabilities and highlights its potential, while recognizing limitations in generating precise guidance for completing complex tasks. The project combines research, programming, and documentation, providing valuable insights into AI's role in project development.

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Uc-401 Website Hardening And Ethical Hacking, Alex L Liu, Samrat H Pandya, Kennedy A Sanchez, Kenny M Frontin, Komlan I Wogomebu Nov 2023

Uc-401 Website Hardening And Ethical Hacking, Alex L Liu, Samrat H Pandya, Kennedy A Sanchez, Kenny M Frontin, Komlan I Wogomebu

C-Day Computing Showcase

This project is to showcase a real life scenario of securing a theoretical business website on Red Hat Linux, Apache, MariaDB, and PHP hosted in a virtual machine. The project objective is for a team to research ways to secure the theoretical business website, develop and implement security policies, and perform a red/blue team exercise. This project is a way for a team to exercise ethical hacking in a closed environment to obtain experience.

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Uc-408 Web Hardening, Christopher Brown, Spencer J Jackson, Lynder Kigo, Gabrielle Hooper Nov 2023

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.

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Uc-423 Developing Support For Dicom Medical Images, Cassidie G. Grogan Nov 2023

Uc-423 Developing Support For Dicom Medical Images, Cassidie G. Grogan

C-Day Computing Showcase

DICOM (Digital Imaging and Communications in Medicine) is the standard for storing and sharing medical image information. GIMP (GNU Image Manipulation Program) is the leading open-source program for processing professional and scientific images; however, it is currently unable to open many modern DICOM images. The project goal is to update GIMP's DICOM import plugin with code to support all types of DICOM images. After creating a C++ wrapper to incorporate the GDCM (Grassroots DICOM) library into the existing software, GIMP could import images that previously caused errors. The updated plugin has been submitted as a merge request and is currently …

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Uc-424 Ai Limitations For Web Devlopment, Jacob J. Lalicata, Josh Garske, Thomas Rowlinson, Matthew Madrigal, Muyiwa E. Adewumi Nov 2023

Uc-424 Ai Limitations For Web Devlopment, Jacob J. Lalicata, Josh Garske, Thomas Rowlinson, Matthew Madrigal, Muyiwa E. Adewumi

C-Day Computing Showcase

This research project delves into the exploratory journey of using an AI (Artificial Intelligence), specifically ChatGPT, to assist in developing an auction website. Highlighting the iterative process of problem identification, solution finding, and implementation during development, this project aims to furnish insights into leveraging AI capabilities while addressing its limitations. Through this, developers and AI enthusiasts can gain a comprehensive understanding of effective collaboration with AI, addressing common pitfalls, and devising solutions during software development.

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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 Nov 2023

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 …

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Uc-492 Lotspotter, Julian Yankah, Henry Pham, Tripp Greene, Jonathan Perry, Ghislain Dongbou Nov 2023

Uc-492 Lotspotter, Julian Yankah, Henry Pham, Tripp Greene, Jonathan Perry, Ghislain Dongbou

C-Day Computing Showcase

The parking issue has quietly become the cause of a lot of stress for travelers and other regular users. It's nothing new that some people miss their flight and/or get late to other important meetings and appointments because they couldn’t locate an available parking lot. Not because there isn't available parking but because they don’t know where it is! What if there was some way to solve that? Introducing LotSpotter! An application built to detect and navigate to vacant parking spaces across the United States. It will leverage various technologies, including image processing, sensors, AI and mobile app development, to …

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Uc-502 Chess App With Ai, Connor Handley, John Paul Cohran, Cole Smith, Paul Russell, Eric Tsai Nov 2023

Uc-502 Chess App With Ai, Connor Handley, John Paul Cohran, Cole Smith, Paul Russell, Eric Tsai

C-Day Computing Showcase

The objective of this project is to create a website that contains a virtual chess game, where the user can play against an opponent powered by an artificial intelligence model. This chess platform will be a widely accessible and user-friendly way to become more familiar with and practice the game of chess.

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Uc-506 Underock Arena, Bryanna N Walker Nov 2023

Uc-506 Underock Arena, Bryanna N Walker

C-Day Computing Showcase

The game I developed was meant to highlight the ways that game developers can utilize our mobile devices to create a casual game. Breaking down complex parts of an RPG battling game, I devised the most casual and mobile-friendly way for the player to battle with unique bugs against an AI enemy using only 3 simple buttons: attack, heal, and ultimate. In addition, because of my areas of study at Kennesaw State University, I wanted to use my artistic abilities in my game. I thought it would be interesting to see how traditional art looks in a mobile game on …

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