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Articles 2131 - 2160 of 16633

Full-Text Articles in Physical Sciences and Mathematics

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-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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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-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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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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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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Uc-395 Ccse Reservation Application, Nicholas Kelley, Tykira Carreker, Keith Mutisya, Aaron Hyatt Nov 2023

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.

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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-426 Cybersecurity Park, Michael P. Leung, Kalil R. Masters, Robert Deason, Ian C. Skoonberg, Aiden D. Gohlke Nov 2023

Uc-426 Cybersecurity Park, Michael P. Leung, Kalil R. Masters, Robert Deason, Ian C. Skoonberg, Aiden D. Gohlke

C-Day Computing Showcase

We are presenting two additional modules to the Cyber Security Park, a long-running game project that is part of the realities lab. Whack-a-Malware is an arcade game where the player has to whack various malware, each with unique effects that mimic real-world malware. This includes Adware, Spyware, Ransomware, Computer Worms, and Trojan Horses. The player is equipped with two hammers that instantly destroy malware. But it goes on a three-second cooldown every time they destroy something. The player can reduce the cooldown by destroying adware as they are the main cause of slowing down the computer. Digital Footprints Private Investigator …

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Uc-432 Ccse Reservation Application, Brandon R. Bunn, Ryan Kafka, Dina Levieva, Alyn Ovell, Olivia C. Venuti Nov 2023

Uc-432 Ccse Reservation Application, Brandon R. Bunn, Ryan Kafka, Dina Levieva, Alyn Ovell, Olivia C. Venuti

C-Day Computing Showcase

This CCSE Reservation Application project is focused on creating a unified web application to simplify the reservation process for inventory devices and room time slots for faculty and staff at Kennesaw State University. This initiative combines two separate reservation systems into a single solution, encompassing a database, backend, and frontend. The database will store relevant information, the backend will handle data communication, and the frontend will provide a user-friendly interface for making reservations. Administrators will have access to an admin view for managing requests. The project has faced challenges, including resource constraints and team coordination issues. While the integration 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-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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Uc-508 Memories: Echoes Of Resilience, Ethan J Hester, Joshua Tyler Padgett, Katelyn R Freeman, Sarah Crosby, Keith W Rhymer Nov 2023

Uc-508 Memories: Echoes Of Resilience, Ethan J Hester, Joshua Tyler Padgett, Katelyn R Freeman, Sarah Crosby, Keith W Rhymer

C-Day Computing Showcase

Memories: Echoes of Resilience is a first-person narrative experience that takes players through different experiences of a boy with autism. The game aims to show how everyday interactions can be different to someone with autism. Experiences such as making friends in school, being in overstimulating environments, or managing adult life are experiences we want to simulate for the player. The player will be able to interact with the world around them but will also have to be aware of how their environment impacts them, so they don’t become overstimulated.

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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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Ur-484 Ai Detection – Chat Gpt, Wylder Everett, Daniel Mode, Paul Nguyen, Alfred Johnson, Bilal Khan Nov 2023

Ur-484 Ai Detection – Chat Gpt, Wylder Everett, Daniel Mode, Paul Nguyen, Alfred Johnson, Bilal Khan

C-Day Computing Showcase

With the emergence of large language models (LLM) and Artificial Intelligence (AI) assistants like ChatGPT, accompanying tremendous potentials are critical challenges. Indeed, these assistant systems can provide quality information with conveniences. However, the generated contents are highly problematic being seemingly indistinguishable from that of human. The implication of this issue is severe in science, education, and domains that value original contents. With such motivation, this project addresses the task of identifying ChatGPT-synthesized texts with a focus on education, specifically, in short-answer questions. The goal of the project is to develop an AI technology that identifies synthesized texts by comparing such …

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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-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-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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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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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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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-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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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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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-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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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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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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Gr-405 Boosting Clickbait Detection Through Semantic Insights And Attention-Driven Neural Network, Lokesh Meesala Nov 2023

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 …

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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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