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Articles 546301 - 546330 of 5160178
Full-Text Articles in Entire DC Network
Uc-344 Wisewallet, Sagar Patel, Shpetim Berdyna, Ethan R Nuqui, Sebastian Curca
Uc-344 Wisewallet, Sagar Patel, Shpetim Berdyna, Ethan R Nuqui, Sebastian Curca
C-Day Computing Showcase
WiseWallet is designed to help users manage their finances in a simple and intuitive way. The app provides an easy-to-use interface for tracking income, expenses, and savings, allowing users to set goals and monitor their progress towards achieving them. The app also features customizable categories and budgets, enabling users to tailor their budgeting approach to their individual needs and preferences. In addition, the app provides visual aids such as charts and graphs to help users better understand their spending patterns and make informed financial decisions. With its user-friendly interface and powerful features, the Flutter mobile app for budgeting is an …
Uc-364 Step Up, Liam K Hardage, Sami Iqbal, Emely P Guerrero Bengoa, Zachary Okwuosa
Uc-364 Step Up, Liam K Hardage, Sami Iqbal, Emely P Guerrero Bengoa, Zachary Okwuosa
C-Day Computing Showcase
Step Up is a website designed to let users enter their information and calculate a step count to aid them in losing weight. Each user creates an account to store their data. This information will include necessary variables to calculate their step count using their target weight loss. The step count provided by Step Up considers the number of steps a user between the ages of 19 to 40 must make over three months to reach their goal. Step Up allows users to receive email reminders to keep their information up to date. Administrators of Step Up have the option …
Uc-349 Virtual Reality Robots, Ian C Bryenton, Vincent P Giordano, George L Larumbe, Kazhan M Sofy
Uc-349 Virtual Reality Robots, Ian C Bryenton, Vincent P Giordano, George L Larumbe, Kazhan M Sofy
C-Day Computing Showcase
The UXA-90 Robots, that were in the possession of KSU since 2016, were first brought up to date by the previous group. Through their creation of a REST API, they were able to issue commands and increase the accessibility of the robots. The robots would once again be revived as our team opted to expand on their capabilities. Using the Unity Engine with C#, a Meta Quest 2 Virtual Reality (VR) device, and a Raspberry Pi, our team was able to both see and act through the robot. By default, the robot can: move, walk, see (through a webcam), hear …
Uc-377 Litter Scramble: Encouraging Conservation Through Play, Andrew C Hinson, Tony Ogden, Don Luong, Harrison G Brown
Uc-377 Litter Scramble: Encouraging Conservation Through Play, Andrew C Hinson, Tony Ogden, Don Luong, Harrison G Brown
C-Day Computing Showcase
Litter Scramble is a quick-play video gaming experience that delivers a nostalgic low-res combination of 2d assets in a 3d environment to produce an informative and entertaining session that will leave the player better informed on the impact that pollution and littering have on the natural world around us. Featuring a cast of simply animated 2d animals appropriate for a Georgia state park, the player will control a ranger through two different levels, each reflecting a different park environment, in a race against time and the animals to capture as much litter as possible. The development team was eager to …
Uc-373 Terrasim, Anna Alquisiras, Jadante Hendrick, Selene Espinosa, Jake Dunkley
Uc-373 Terrasim, Anna Alquisiras, Jadante Hendrick, Selene Espinosa, Jake Dunkley
C-Day Computing Showcase
This is an AI project utilizing FNN and OpenGL to simulate a more complex and practical version of John Conway's Game of Life, incorporating real world data for increased accuracy and relevance
Uc-385 Health-E-Patient (Web Application), Kishan Mistry, Blesson Amram Tenson, Faith N Leach, Jiten Patel
Uc-385 Health-E-Patient (Web Application), Kishan Mistry, Blesson Amram Tenson, Faith N Leach, Jiten Patel
C-Day Computing Showcase
Health-E-Patient is a web application that allows communication between hospitals, doctors and their patients. The product aims to provide a secure way of informing patients about appointments and medications while also allowing doctors to keep track of their patients. This application will also make it easier to communicate with your doctors and other care providers. We used Next.JS, a React-based web development framework with server-side rendering. We used MaterialUI for user interface and Firebase for Authentication and Database.
Uc-388 Quantum Computing In Cybersecurity Related Data Analysis : A Comparative Analysis Of Classical And Quantum Machine Learning Models On Various Security Threats, Ryan Lowhorn, Zac Cardwell
Uc-388 Quantum Computing In Cybersecurity Related Data Analysis : A Comparative Analysis Of Classical And Quantum Machine Learning Models On Various Security Threats, Ryan Lowhorn, Zac Cardwell
C-Day Computing Showcase
Financial fraud has become an increasingly prevalent and sophisticated issue in the modern world, causing significant losses for individuals, businesses, and economies alike. The exponential growth of digital transactions has only accelerated the need for effective and efficient fraud detection systems to safeguard these financial ecosystems. Traditional machine learning techniques, such as Neural Networks (NNs), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), have played a crucial role in mitigating the impact of fraud by employing advanced algorithms to identify and prevent fraudulent transactions. With the recent advent of quantum computing and its potential to revolutionize the field of machine …
Uc-383 Pantrypilot, Zarek F Syed, April Breedlove, Thuy Dong, Sanjay Bhadra
Uc-383 Pantrypilot, Zarek F Syed, April Breedlove, Thuy Dong, Sanjay Bhadra
C-Day Computing Showcase
Our team has developed an intuitive food pantry management system that streamlines the guest check-in process, optimizes time management, and enhances data reporting. The app is built with Next.js, TypeScript, and Firebase to create a platform-independent progressive web application. PantryPilot functions on both mobile devices and desktop devices.
Ur-331 Read-Talkback Assisted Platform For Aphasia, Michael J Clayton, Maxwell P Dixon, Navonte Riggin
Ur-331 Read-Talkback Assisted Platform For Aphasia, Michael J Clayton, Maxwell P Dixon, Navonte Riggin
C-Day Computing Showcase
Every year, there are lots of people who are affected with brain or other traumatic injuries that lead to some form of speech impairment. One of these conditions is Aphasia, which can cause a loss of word-finding or word-substitution, agrammatism, and apraxia. The team will be developing a Flutter app with a focus on Android systems that will track the user’s eye movements and read out the word that is being focused on. The goal of this app is to assist in improving the speech production and day-to-day activities of people with Aphasia or a similar disorder.
Ur-390 Bactifind: A Novel Cnn-Based Framework To Classify Bacterial Species, Lowhorn Ryan, Cardwell Zac
Ur-390 Bactifind: A Novel Cnn-Based Framework To Classify Bacterial Species, Lowhorn Ryan, Cardwell Zac
C-Day Computing Showcase
Abstract—Bacterial species identification is an essential step in diagnosing diseases caused by bacterial attacks. Effective prescription to cure these diseases depends on accurate bacterial species identification. Faster identification along with accuracy is essential because some bacteria grow fast in the human body. However, bacterial species classification using a laboratory environment through traditional approaches is time-consuming, and it depends on human expertise, which is not immune to human error. Well-trained and experienced microbiologists demonstrate the probability of preparing bacterial species identification reports with lower error rates. However, hiring experienced microbiologists is expensive. Convolutional Neural Network (CNN)-based automatic bacterial species classification system …
Ur-363 Quantum Machine Learning Applied To Cybersecurity, Adam M Waugh, Anna Destito, Joseph D Ragsdale
Ur-363 Quantum Machine Learning Applied To Cybersecurity, Adam M Waugh, Anna Destito, Joseph D Ragsdale
C-Day Computing Showcase
We propose the development of a system that uses the TensorFlow Quantum and PennyLane packages and applies quantum machine learning (QML) algorithms to process various security and malicious data sets and compares the performance with classical machine learning (CML) algorithms. One of the most important applications of QML is for cybersecurity. This project will begin with research of quantum computing and machine learning, then followed by the development of a system that uses the TensorFlow Quantum and PennyLane packages and applies quantum machine learning (QML) algorithms to process various security and malicious data sets and compares the performance with classical …
Ur-347 Blockchain In Ethereum, Savvy Lovell, Joshua Priest, Cameron D Cooper
Ur-347 Blockchain In Ethereum, Savvy Lovell, Joshua Priest, Cameron D Cooper
C-Day Computing Showcase
Earthereum is a cryptocurrency token built on the Ethereum blockchain utilizing an ERC-20 contract and implemented with Solidity in Remix and deploying using MetaMask. The mission of Earthereum is developing an ecologically-friendly utility for cryptocurrencies.
Ur-350 Quantum Game Theory, Christian Thomassy, Sean J Curtis, Cody A Lacey
Ur-350 Quantum Game Theory, Christian Thomassy, Sean J Curtis, Cody A Lacey
C-Day Computing Showcase
Quantum computing is a computing paradigm that utilizes the properties of quantum mechanics such as superposition, interface and entanglement for data processing and other tasks. Quantum computing can be used to work on the same problems existing supercomputers do but in a much more efficient manner. Classical game theory is a process of modeling that is widely used in AI applications. The extension of this theory to the quantum field is known as quantum game theory. It can be a promising tool for overcoming critical problems in quantum communication and the implementation of quantum artificial intelligence. Quantum game theory allows …
Ur-379 Combatting Data Heterogeneity In Federated Learning, Andrew J Hutchison, Justin C Bull, Aaron Cummings
Ur-379 Combatting Data Heterogeneity In Federated Learning, Andrew J Hutchison, Justin C Bull, Aaron Cummings
C-Day Computing Showcase
The growing concern in data privacy has led to new paradigms in Machine Learning primarily focused around keep data safe and secure. In our research project, we studied Federated Learning, specifically utilizing knowledge distillation and an autoencoder in an attempt to create a sustainable model that could be used in a field such as Heathcare. We propose a Federated Model using the Flower framework, trained on the MedMNIST2D dataset (Organ(A/C/S)MNIST), using Knowledge Distillation as a method of sharing the global model, and a Variational Autoencoder to deal with the problem of Data Heterogeneity that can arise on a distributed network. …
Gc-332 Website Seo Analysis Pfc Nyc, Corey Phillips, Travis Hutto, Ashraf Saaka, Tomisin Garuba
Gc-332 Website Seo Analysis Pfc Nyc, Corey Phillips, Travis Hutto, Ashraf Saaka, Tomisin Garuba
C-Day Computing Showcase
A website's rating and visibility in search engine results pages are improved through search engine optimization (SEO). Businesses benefit from SEO to increase website traffic, leads, and sales. This summary reviews SEO, its advantages, and the main tactics and strategies applied to Paddle for a Cure NYC. It also emphasizes the significance of technical optimization, link development, keyword research, and content for Paddle for a Cure NYC. This abstract underlines the need for constant optimization and monitoring to maintain Paddle for a Cure NYC's website visibility and competitiveness in search results.
Gc-333 Analysis Of Alternatives Of Workstation Deployment Solutions, Tyler L Tilton, Jesus Moscosa, Kameron Singleton, Kimberly Pitts
Gc-333 Analysis Of Alternatives Of Workstation Deployment Solutions, Tyler L Tilton, Jesus Moscosa, Kameron Singleton, Kimberly Pitts
C-Day Computing Showcase
In searching for a new workstation deployment solution, GTRI identified 15 ranked characteristics which an acceptable solution should possess. These 15 characteristics were used as the basis for this Analysis of Alternatives. This process consisted of a research phase and testing phase. During the research phase, team members compiled a list of potential solutions and gathered basic information about each. This list was eventually pruned to ten products which were further researched and scored based on their reported ability to meet the supplied requirements. As a result of this research, Ivanti DSM and Theopenem were selected for testing in a …
Gc-337 Analysis Of Alternatives For Workstation Deployment For Gtri, Josh Freeman, Kevin Glaze, Doug Curtis, Kayla Dougal
Gc-337 Analysis Of Alternatives For Workstation Deployment For Gtri, Josh Freeman, Kevin Glaze, Doug Curtis, Kayla Dougal
C-Day Computing Showcase
Georgia Tech Research Institute is requesting an analysis of alternatives of workstation deployment solution that can deploy an operating system to a workstation. This deployment solution must at least be able to deploy Windows 10, Windows 11, Red Hat Enterprise Linux 8 and 9; support multiple users simultaneously, support various models, and run custom scripts. The objective of the analysis of alternatives is to provide Georgia Tech Research Institute with one deployment solution that can replace their current software that facilitates this process. There are inefficiencies to resolve in their current environment such as deploying various operating systems and applying …
Gc-340 Ai For Quantitative Trading, Kiran Ponakaladinne, Sai Charan Binigari, Mayuri Jawale, Gowthami Petakamsetti
Gc-340 Ai For Quantitative Trading, Kiran Ponakaladinne, Sai Charan Binigari, Mayuri Jawale, Gowthami Petakamsetti
C-Day Computing Showcase
AI for quantitative trading involves using machine learning and other AI techniques to analyze financial data and make informed trading decisions. By automating the trading process and leveraging the power of AI, traders can potentially improve their performance and generate better returns. The goal is to identify and capitalize on available trading opportunities by using computer algorithms and programs based on simple or complex mathematical models. Stock market indicators are statistical measures that provide insights into the behavior of the stock market as a whole or of individual stocks. These indicators are used by investors, traders, and analysts to evaluate …
Gc-367 A Comparative Study Of Virtual Network Architectures For Cloud Computing Environments, Suvidha Sreeramoju, Susmitha Maddukuri
Gc-367 A Comparative Study Of Virtual Network Architectures For Cloud Computing Environments, Suvidha Sreeramoju, Susmitha Maddukuri
C-Day Computing Showcase
Virtual networks have emerged as a promising solution for creating customized network topologies that can meet the specific needs of different cloud environments. In this project, we present a comparative study of three different virtual network architectures for cloud computing environments. We compare these architectures based on a set of criteria, including performance, scalability, flexibility, and security. Our evaluation shows that all three virtual network architectures have their advantages and disadvantages. The choice of virtual network architecture depends on the specific needs and requirements of the cloud environment. Our evaluation provides insights into the trade-offs between different virtual network architectures …
Gc-380 Dinengo Application, Sai Sushanth Reddy Jonnalagadda, Sahith Vardhan Reddy Vancha, Subramanya Rahul Annavajhula
Gc-380 Dinengo Application, Sai Sushanth Reddy Jonnalagadda, Sahith Vardhan Reddy Vancha, Subramanya Rahul Annavajhula
C-Day Computing Showcase
This project aims to upgrade the DineNGo application, a software tool for restaurant management, with new features specified by the client, The Driven Software Solutions. The upgraded version includes enhancements to users' roles, such as implementing Role-Based Access Control (RBAC), and adding a payment required feature before order placement. Additionally, the new features aim to improve payment processing, reduce trips back and forth to the POS terminal, and provide a secure payment experience for customers. This document provides an overview of the project's scope, objectives, and system overview, along with the operational policies and constraints.
Gr-314 Reinforcement Learning Based Offloading Scheme Computation To Optimize Latency-Energy In Collaborative Cloud Networks, Jui Mhatre
C-Day Computing Showcase
Growing technologies like virtualization and artificial intelligence have become more popular on mobile devices. But lack of resources faced for processing these applications is still a major hurdle. Collaborative edge and cloud computing are one of the solutions to this problem. Remote servers have enough resources to support computation-heavy tasks and compute the results faster. But transmission time and energy are involved while offloading the computation to remote servers such as cloud and edge devices. There is a need to find an optimal offloading ratio for cloud as well as edge servers such that entire computation on remote as well …
Gr-358 Impact Of Avatar's Behavioral Change With Quantity On Human Perception In Immersive Experiences, Nicholas L Wile
Gr-358 Impact Of Avatar's Behavioral Change With Quantity On Human Perception In Immersive Experiences, Nicholas L Wile
C-Day Computing Showcase
As virtual reality technology evolves, researchers have found that the characteristics of virtual avatars including appearance, representation, and proximity, can significantly influence the immersive experience of the user. This project investigates the impact of the number of avatars and their behavioral influence on the user in a simulated learning environment. We developed a virtual reality classroom system with Unity designed to elicit, track, and record the user’s behavioral changes including eye gaze, head, and hand movement using HTC VIVE Pro Eye and physiological signals including Heart Rate (HR) and Galvanic Skin Response (GSR), while the user delivers presentations to classrooms …
Gr-362 Scale-Sim Extension To Support Gnn Inputs And Cnn Back Propagation, Rutul Desai, Phani Akshaya Sri Pasupuleti, Bobin Deng, Guangchi Liu
Gr-362 Scale-Sim Extension To Support Gnn Inputs And Cnn Back Propagation, Rutul Desai, Phani Akshaya Sri Pasupuleti, Bobin Deng, Guangchi Liu
C-Day Computing Showcase
In recent years, CNNs (Convolutional neural Network) and GNNs (Graph Neural Network) have gained a lot of attention and popularity in various fields such as computer vision, natural language processing, and social network analysis. Training large scale CNN and GNN models may take up to several months or sometimes years to complete. SCALE-Sim is a CNN accelerator with systolic array and SRAMs. However, SCALE-Sim only support CNN inference and not back propagation. To evaluate the CNN training, in this work we extend the SCALE-Sim to support CNN back propagation. Because the importance of the GNN applications and their training bottlenecks, …
Gr-384 Benchmarking Network Service Performance Using The Powder Wireless Testbed, Dillon J Horton, Manh V Nguyen, Sri Sesha Sailaja Lakshmi Tulasi Khandavilli, Thinh Van Le
Gr-384 Benchmarking Network Service Performance Using The Powder Wireless Testbed, Dillon J Horton, Manh V Nguyen, Sri Sesha Sailaja Lakshmi Tulasi Khandavilli, Thinh Van Le
C-Day Computing Showcase
5G RAN slicing provides a way to split network infrastructure into self-contained slices which can have various virtual network functions (VNFs) mapped onto them. Much work has gone into creating robust mapping and resource allocation algorithms in order to efficiently embed VNFs onto the available nodes in a slice. However, in order to most efficiently embed these VNFs we need to understand the resource and bandwidth needs of the services we are trying to embed. This project seeks to provide an accurate assessment of the needs of three commonly used network services. We do this by testing each network service …
Gr-391 Insight Into Current Covid-19 Variants And Data Science Applications, Ravi Potlapalli, Thanusha Sai Ande
Gr-391 Insight Into Current Covid-19 Variants And Data Science Applications, Ravi Potlapalli, Thanusha Sai Ande
C-Day Computing Showcase
COVID-19 has undergone several mutations resulting in the emergence of new variants such as Alpha, Beta, Gamma, Delta, and Omicron. Data science plays a vital role in understanding the spread of COVID-19 and its variants. The emergence of new COVID-19 variants has raised concerns about the effectiveness of existing vaccines and treatments. This poster provides insights into the current COVID-19 variants and the data science applications used to monitor and understand their spread. We will showcase the use of SQL to manage and analyze genomic data of SARS-CoV-2 variants, Power BI for visualization and tracking of COVID-19 cases and deaths, …
Gr-342 Integration Of Blockchain In Computer Networking: Overview, Applications, And Future Perspectives For Software-Defined Networking (Sdn), Network Security And Protocols, Md Jobair Hossain Faruk
Gr-342 Integration Of Blockchain In Computer Networking: Overview, Applications, And Future Perspectives For Software-Defined Networking (Sdn), Network Security And Protocols, Md Jobair Hossain Faruk
C-Day Computing Showcase
The rapid advancement and increasing complexity of computer networks have created a need for robust, secure, and scalable solutions to manage and protect network resources. Blockchain, an emerging distributed ledger technology, offers enhanced security, transparency, and privacy preservation, making it a promising solution for addressing networking challenges. This paper presents a comprehensive survey of blockchain integration in computer networking, focusing on its potential applications, benefits, and future perspectives in Software-defined Networking (SDN), network security, and networking protocols. We identify that blockchain's tamper-proof nature could significantly improve network security by mitigating risks associated with centralized control and single points of failure. …
Ec-371 Planit Crm - Refactoring For The Future, Justin Hall, Oluwaseyi Falaiye, Thomas Anderson, Sai Krupa Bariki Vidura, Samet Yekta Guclu, Ahmet Bugra Dogan
Ec-371 Planit Crm - Refactoring For The Future, Justin Hall, Oluwaseyi Falaiye, Thomas Anderson, Sai Krupa Bariki Vidura, Samet Yekta Guclu, Ahmet Bugra Dogan
C-Day Computing Showcase
Planit CRM is a Customer Relationship Management (CRM) software that helps in managing and tracking projects, tasks, invoices, quotes, leads, customers, transactions and much more. This software allows anyone to manage leads, create invoices, and start collecting payments seamlessly. The system was developed by Driven Software Solutions under the guidance of Shahzib Sarfraz in 2018. The software has since been used by business owners to allow for easier management of the income and expenses of their operation. It is supported by a team of around fifty developers who maintain the PlanIT CRM software off the site https://planitcrm.com, which can be …
Gc-345 Brainnet: Using Deep Learning To Classify Brain Tumors, Ryan Deem
Gc-345 Brainnet: Using Deep Learning To Classify Brain Tumors, Ryan Deem
C-Day Computing Showcase
Brain tumors are a common type of cancer, and they do not discriminate based on gender, age, or ethnicity. That said, the severity and type of tumor vary among the diagnosed individual, cancerous or benign. The three most common types for diagnosed individuals are glioma, meningioma, and pituitary. Even so, identifying the type of tumor can be an arduous process for both the doctor and the patient, but one technique known as Convolutional Neural Network (CNN) has been particularly effective in expediently and reliably determining the type of brain tumor. A CNN is a type of neural network that can …
Gc-382 Artificial Intelligence(Ai) For Quantitative Trading, Winifred Akpan, Emmanuel Ayo, Jason Kennedy, Malek Browning
Gc-382 Artificial Intelligence(Ai) For Quantitative Trading, Winifred Akpan, Emmanuel Ayo, Jason Kennedy, Malek Browning
C-Day Computing Showcase
This project involves the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques in quantitative trading and stock market analysis for educational purposes. The goal of this project is to predict stock market movement to help investors mitigate risks associated with trading and to provide higher returns. It involves the use, implementation, and refinement of basic python framework codes, sklearn library (pandas and numpy), in addition to the development and application of a Linear Regression labeling strategy to predict future daily stock trends, and the utilization of a Supervised Learning AI model. The techniques developed and utilized during this …
Gr-334 Comparative Evaluation Of Embed Dataset For Mammogram Classification Using Deep Learning Techniques, Nalla Vineela
Gr-334 Comparative Evaluation Of Embed Dataset For Mammogram Classification Using Deep Learning Techniques, Nalla Vineela
C-Day Computing Showcase
Breast cancer is a global health concern for women. The detection of breast cancer in its early stages is crucial, and screening mammography serves as a vital leading-edge tool for achieving this goal. In this study, we evaluated the performance of centralized versions of Resnet 50v2 and Resnet 152v2 models for classification of mammograms using different datasets, which were divided by location number extracted from the EMBED dataset. The datasets were preprocessed and used various techniques to improve the performance of the models. The models are trained and evaluated using metrics such as accuracy, area under the curve (AUC), F1 …