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Full-Text Articles in Physical Sciences and Mathematics

Gr-434 Phase Estimation’S Application In Qram, Ethan K Hunt Nov 2023

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

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Gr-453 Medical Records Summarization Using Prompt-Based Nlp, Rawan Masadeh, Nicholas S Servies Nov 2023

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 …

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Egr-490 Importance Of Food Recognition On Blood Glucose Monitoring, Afnan Crystal Nov 2023

Egr-490 Importance Of Food Recognition On Blood Glucose Monitoring, Afnan Crystal

C-Day Computing Showcase

Maintaining blood sugar under control requires eating a healthy and balanced diet, exercising, and adhering to medications. Dietary consumption must be under strict control for diabetic patients’ general health. Traditional techniques for monitoring dietary consumption include recollection and manual record-keeping, which can be tedious and prone to mistakes. However, automated technologies for maintaining records that make use of computer vision, such as food image recognition systems, can streamline chronic health management for diabetics. These solutions seek to efficiently track daily food intake and consequential calories to facilitate and encourage lifestyle improvements. With this goal in mind, we design a Machine …

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Gr-496 Cardiac Arrest Prediction Model, Vineeth Amsham, Sai Reddy Balaiah, Tamilkumar Subbarayakgounder Nov 2023

Gr-496 Cardiac Arrest Prediction Model, Vineeth Amsham, Sai Reddy Balaiah, Tamilkumar Subbarayakgounder

C-Day Computing Showcase

The "Cardiac arrest prediction model" project melds machine learning with healthcare to tackle heart disease. It aims to surpass current diagnostic tools that fail to catch early signs of cardiac events, often leading to high mortality. By developing an ML model that identifies early predictors of cardiac arrest, the project seeks to enable early interventions. Using supervised learning for its pattern recognition strength, the goal is to predict heart attacks accurately and thus, revolutionize preventative care and outcomes. This effort marks a leap in medical diagnostics and moves towards personalized healthcare, potentially saving countless lives and pioneering a new direction …

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Gc-444 It Course Profile Website, Manikanta Voruganti Nov 2023

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.

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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 Nov 2023

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 …

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Gc-511 Predicting Stock Prices Using Different Machine Learning And Deep Learning Models, Afnan Crystal, Rohith Sundar Jonnalagadda, Hrithik Singh Chandel Nov 2023

Gc-511 Predicting Stock Prices Using Different Machine Learning And Deep Learning Models, Afnan Crystal, Rohith Sundar Jonnalagadda, Hrithik Singh Chandel

C-Day Computing Showcase

Our project focuses on the challenge of predicting the daily closing prices and stock movements of Amazon, one of the world's largest and most dynamic corporations. Amazon's stock prices are known for their unpredictability and are influenced by a multitude of intricate factors. Our project aims to provide accurate and reliable forecasts for Amazon's stock prices, going beyond mere predictions. The analysis employs a comprehensive approach, comparing the performance of three distinct machine learning and deep learning models: Linear Regression, Support Vector Machine (SVM), and Multi-Layered Perceptron (MLP) for financial time series data. The dataset we used spans from January …

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Gr-469 A Simulation Model Of The Traffic Signal System Using Java, Lingtao Chen Nov 2023

Gr-469 A Simulation Model Of The Traffic Signal System Using Java, Lingtao Chen

C-Day Computing Showcase

A traffic signal controls the flow of traffic at the intersection of two or more roadways. The first system of traffic signals was installed in London, England, in 1868. In this project, I will develop a simulation model for the traffic signal system using Java. The model will simulate the traffic signal system at a single four-way intersection. Also, I will compare the system performance with different input parameters, such as the number of vehicles and the cycle length, using various performance metrics, such as average waiting time and average sojourn time.

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Euc-472 Biomimetic Remote-Controlled Vehicle, Jonathan Ridley, Kian Brown Nov 2023

Euc-472 Biomimetic Remote-Controlled Vehicle, Jonathan Ridley, Kian Brown

C-Day Computing Showcase

The goal of this project is smoothly integrating instinctual concepts of control into devices beyond the body. It is essentially an attempt to extend the body without any complex prior training. To do this, we have developed a both a Bluetooth connection between hand movements and the motors of a multifaceted vehicle. Furthermore, the hand movements will be tracked using both an accelerometer and gyroscope found in the common hobbyist tool Arduino nano. Logging this data and processing it through the Bluetooth communication system, the intention is to provide real-time updates to the vehicle’s motors that ultimately sync the intentions …

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Uc-491 Spectrum Analysis Cli Tool, Vitor B. Santos, Trey Redden, Sam Corella, Christopher Flores Santos, Jonathan Glennon Nov 2023

Uc-491 Spectrum Analysis Cli Tool, Vitor B. Santos, Trey Redden, Sam Corella, Christopher Flores Santos, Jonathan Glennon

C-Day Computing Showcase

The Spectrum Analysis CLI Tool takes in .mp4 recordings of a Spectrum Analyzer, converts them programmatically into values the application can understand and outputs this data into a .csv file. This file can be parsed/filtered by the user with commands during upload of the .mp4 recording, or anytime after the recording has been processed.

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Ur-510 Exploring The Impact Of Wavelength In Non-Invasive Blood Glucose Monitoring, John E. Oakley, Tahsin Kazi Nov 2023

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 …

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Gc-417 It Curriculum Success Portal, Alexander Thacker, Cedric Boakye-Danquah, Damola Adeyemo, Abdoulaye Ndiaye, Lydia Asante Nov 2023

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 …

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Gr-515 Developing A Conversational Chatbot Using Seq2seq Model With Tensorflow, Drashtee Parmar, Ruthvik R. Anugu Nov 2023

Gr-515 Developing A Conversational Chatbot Using Seq2seq Model With Tensorflow, Drashtee Parmar, Ruthvik R. Anugu

C-Day Computing Showcase

Sequence-to-Sequence (Seq2Seq) modeling, when paired with Long-Short-Term Memory (LSTM) units, has demonstrated significant potential in developing conversational chatbot capable of participating in text-based conversation and providing human-like responses.The Cornell Movie-Dialogs Corpus will be used to extract dialogues, preprocess the data, and then use the output to train the Seq2Seq model. Our contributions include exploring the application of LSTM for Natural Language Generation (NLG) and creating a comprehensive chatbot system. According to the results of the experiment, our method works well for coming up with thoughtful answers during a conversation.

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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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