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Full-Text Articles in Physical Sciences and Mathematics
Ur-65 Cnn Cifar Image Identification, Matteo L Staciarine
Ur-65 Cnn Cifar Image Identification, Matteo L Staciarine
C-Day Computing Showcase
Reducing the learning rate of a CNN can positively affect the validation accuracy of a machine learning model. Dropping out nodes from different layers can further delay overfitting from happening. Validation loss decreases over more epochs, but it must be cut when it reaches its minimum value.Advisors(s): Dr. Dan LoTopic(s): Artificial Intelligence
Uc-11 Information Recall For Kids With Autism, Alex J Bechke, Elizabeth Burnside, Haiden Gembinski, Ross Murphy, Ryan Taylor, Henok Demisse
Uc-11 Information Recall For Kids With Autism, Alex J Bechke, Elizabeth Burnside, Haiden Gembinski, Ross Murphy, Ryan Taylor, Henok Demisse
C-Day Computing Showcase
Description: Our project "Information Recall For Kids With Autism" also known as the product name given by the client "Safe Kid" is an app to help children with autism understand basic contact information such as phone numbers, addresses, and names. This app is being created for our client Spectrum Behavioral Associates who specialize in helping kids and young adults who have autism, learning development delays, or other behavioral challenges. Motivation: To teach kids who have autism basic contact information in case of an emergency. Materials and Methods: The app we are creating is a local based app made within Unity. …
Ur-60 Video-To-Video Synthesis With Semantically Segmented Video, Aydan Mufti, Jordan S Hasty
Ur-60 Video-To-Video Synthesis With Semantically Segmented Video, Aydan Mufti, Jordan S Hasty
C-Day Computing Showcase
Our project involves studying the usage of generative adversarial networks (GANs) to translate semantically segmented video to photo-realistic video in a process known as video-to-video synthesis. The model is able to learn a mapping from semantically segmented masks to real-life images which depict the corresponding semantic labels. To achieve this, we employ a conditional GAN-based learning method that produces output conditionally based on the source video to be translated. Our model is capable of synthesizing a translated video, given semantically labeled video, that resembles real video by accurately replicating low-frequency details from the source.Advisors(s): Dr. Mohammed AledhariTopic(s): Artificial IntelligenceCS 4732
Ur-63 Low Cost High Impact Fall Detection At The Edge, Dylan Sirna, Noah Sage
Ur-63 Low Cost High Impact Fall Detection At The Edge, Dylan Sirna, Noah Sage
C-Day Computing Showcase
ML models have become more accurate, powerful and portable in recent years, the purpose of this project is to explore how these advances can be applied towards fall detection for less cost than before possible. This project explores the application of micro controllers which have become cheaper and stronger along with emerging machine learning models that can be trained on a traditional computer with greater resources and then port the model to be interpreted on a micro-controller such as a raspberry pi. These two factors lead to the reason to revisit the problem of fall detection, a problem that plagues …
Ur-66 Image Segmentation With Machine Learning, Kedar A Johnson
Ur-66 Image Segmentation With Machine Learning, Kedar A Johnson
C-Day Computing Showcase
An experiment-based analysis of the performance of machine learning algorithms in image segmentation. The experiment is organized to test three experimental groups representing supervised, unsupervised and reinforcement machine learning. The three experimental groups are exposed to three datasets of images for training and testing. They’re performance results are recorded and compared for a statistically significant difference in mean performance values. These results are assumed to identify a trend in differences in performance if a statistically significant difference in performance statistics is discovered between any of the three groups. This experiment will follow a quasi-experimental design because of the absence of …
Gc-52 Ksu Spring Capstone - It Security Solution For Small Business – Group 1, William Simmons, Olajumoke Giwa, Beau Beard, Collin Peters
Gc-52 Ksu Spring Capstone - It Security Solution For Small Business – Group 1, William Simmons, Olajumoke Giwa, Beau Beard, Collin Peters
C-Day Computing Showcase
For this project, we decided to use the nopCommerce open-source eCommerce solution for our simulated small business. Leveraging the pre-configured web server provide to our group, we installed the nopCommerce solution package and built our security program around the web site. Our security program consists of nginx configured web server and load balancer, SSL certificate for encryption, firewall and a secure backend SQL server.Advisors(s): Project Sponsor: Dr. Lei Li Course Professor: Dr. Meng HanTopic(s): SecurityIT 7993
Gr-40 Design And Implementation Of A Microservices Web-Based Architecture For Code Deployment And Testing, Soin Abdoul Kassif Baba M Traore
Gr-40 Design And Implementation Of A Microservices Web-Based Architecture For Code Deployment And Testing, Soin Abdoul Kassif Baba M Traore
C-Day Computing Showcase
Many tech stars like Netflix, Amazon, PayPal, eBay, and Twitter are evolving from monolithic to a microservice architecture due to the benefits for Agile and DevOps teams. Microservices architecture can be applied to multiple industries, like IoT, using containerization. Virtual containers give an ideal environment for developing and testing IoT technologies. Since the IoT industry has exponential growth, it is the responsibility of universities to teach IoT with hands-on labs to minimize the gap between what the students learn and what is on-demand in the job market. That can be done by using containerization. There are many approaches in the …
Gr-44 An Efficient Intrusion Detection Framework Based On Federated Learning For Iot Networks., Osama Shahid
Gr-44 An Efficient Intrusion Detection Framework Based On Federated Learning For Iot Networks., Osama Shahid
C-Day Computing Showcase
There are abundant number of IoT devices that are connected on over multiple networks. These devices can be exposed to multiple different types of network threats. Though, these devices do have security and software that does act as a wall of protection we purpose a Federated Learning (FL) approach that would allow detection of threats of a network for IoT devices. Federated Learning can be best described as decentralized training. Adhering to the GDPR rules that prevent data from being distributed, FL addressed the challenge by bringing the ML model to the data rather than the traditional method where the …
Uc-26 Pose Extraction For Real-Time Workout Assist_Capstone Group_W01_Spring Semester, Royce Camp, Zach Christmas, Jonathon Segars, Amanda Mead, Cameron Page
Uc-26 Pose Extraction For Real-Time Workout Assist_Capstone Group_W01_Spring Semester, Royce Camp, Zach Christmas, Jonathon Segars, Amanda Mead, Cameron Page
C-Day Computing Showcase
Motion Intelligence Research Project We installed and tested many existing pose extraction technologies in many situations. We provided reports on the different software solutions and decided on a single solution that performed the best. We will extract key-points and track the movements across multiple dimensions. We will demonstrate the X and Y movements of everyone for our chosen software solution in a Business Intelligent tool (PowerBI). Given the current epidemic, we are not going to be able to compare against the professional KinaTrax software on campus. Although, Dr. Xie has given us other software packages to compare our given software …
Uc-35 Development Of An Automated Software Packaging Solution For Linux, Robert D Ryan, Sammi Figueroa, Dylan Parker, Blair Hill, Bishwo R Marhatta
Uc-35 Development Of An Automated Software Packaging Solution For Linux, Robert D Ryan, Sammi Figueroa, Dylan Parker, Blair Hill, Bishwo R Marhatta
C-Day Computing Showcase
The main problem with using Linux software in the science and Bioinformatics community is because Linux has a large number of distributions and dependencies. This hinders researches and science students with the problem of tracking down dependencies for software which could then further break the existing system dependencies. Our team looked to solve these problems by creating a BASH script that could quickly mass package AppImages and contain Linux software with all dependencies. Our team worked through the last ten weeks and researched all components of AppImage and discovered all means to more easily package and have a repeatable process …
Gr-67 Representation Learning For Motion Sequence, Saisangararamaleengam Alagapan, Alexandru Malos, Roshni Kishor, Venkateswara Reddy Mosali
Gr-67 Representation Learning For Motion Sequence, Saisangararamaleengam Alagapan, Alexandru Malos, Roshni Kishor, Venkateswara Reddy Mosali
C-Day Computing Showcase
This research project proposes a new deep learning architecture that is used to align human poses to be used in an exercise assistant system. In short, the assistant system takes a video feed of a user doing exercise, then provides visual feedback by comparing the user’s current pose to a professional trainer’s pose that is stored in the system. We design a new deep architecture to accomplish this task and show better accuracy and efficiency.Advisors(s): Project Sponsors - Dr. Ying Xie & Dr. Linh Le Project Advisor- Dr. Meng HanTopic(s): Data/Data AnalyticsIT 7993
Gr-70 Defending Data Reconstruction Through Adaptive Image Augmentation, Seunghyeon Shin
Gr-70 Defending Data Reconstruction Through Adaptive Image Augmentation, Seunghyeon Shin
C-Day Computing Showcase
In this paper, we introduce a data augmentation-based defense strategy for preventing the reconstruction of training data through the exploitation of stolen model gradient. The collection of training data to a centralized server has been required for the training of neural networks in traditional machine learning. However, as privacy becomes a significant concern, the concept of Federated learning is introduced. In federated learning, a centralized server shares the well-trained neural network and participating end-users send the gradient back to the server after training without sharing the sensitive data itself. As the concept of federated learning does not share the original …
Uc-36 Using Machine Learning Techniques To Predict Rt-Pcr Results For Covid-19 Patients., Bradley T Durden, Mathew Shulman, Andy Reynolds, Thomas A Phillips, Demontae Moore, Indya Andrews
Uc-36 Using Machine Learning Techniques To Predict Rt-Pcr Results For Covid-19 Patients., Bradley T Durden, Mathew Shulman, Andy Reynolds, Thomas A Phillips, Demontae Moore, Indya Andrews
C-Day Computing Showcase
With the COVID-19 pandemic still a threat, healthcare professionals and medical industries keep searching for better ways to mitigate the spread of COVID-19. While Machine Learning has been applied in many other domains, there is now a high demand for diagnosis systems that utilize Machine Learning techniques in the healthcare domain and in particular combating COVID-19. In this project, we explore the role of Machine Learning models in combating COVID-19, using WEKA as the main tool for analysis.Advisors(s): Dr. Ming Yang - IT 4983 Capstone Professor Dr. Seyedamin Pouriyeh - Project OwnerTopic(s): Data/Data AnalyticsIT 4983
Uc-39 Journalistic Integrity Vis Artifical Intelligence, Dylan Dalton, Ray Martin, Duy Nquyen, Yesse Quezada, Brian Dominguez
Uc-39 Journalistic Integrity Vis Artifical Intelligence, Dylan Dalton, Ray Martin, Duy Nquyen, Yesse Quezada, Brian Dominguez
C-Day Computing Showcase
We are developing a web app to recognize and rate political bias in online journalism using artificial intelligence. All human writing inherently contains bias ,however bias is less harmful if it is transparent to the reader because they can now make informed decisions about what they read. We've collected articles and and reactions to them from online sources, and then used Neural Networks trained for natural language processing to determine bias. The project can predict bias labels on a news articles with 82% accuracy.Advisors(s): Reza Meimandi Parizi - course instructor Asher Nuckolls - project ownerTopic(s): Artificial IntelligenceSWE4724
Gc-28 Modern Web Scraping, Kenny Randolph, Joselyn Giron, Denise Tucker, Justin B Bridges, Sandhya Bantu
Gc-28 Modern Web Scraping, Kenny Randolph, Joselyn Giron, Denise Tucker, Justin B Bridges, Sandhya Bantu
C-Day Computing Showcase
This project was developed for the IT7993 Capstone class in the May semester of 2021.The goal of the project is to scrape all names of key professionals of organizations in the open990.org website and insert that information into a structured database for query and analysis. The Key Professionals dataset aims to include global coverage of key investor and consultant professionals, beginning with US-based companies, involved in making an investment decision. The overarching aim of this project is to create a one-stop center for institutional asset management distribution intelligence; the one spot to go for mandates, documentation and profiles of consultants, …
Gc-47 Key Professional Dataset - Dataspider, Janell Westmoreland, Vy Duong, Nyong Nkereuwem, Kajal S Vaghani, Ritu Choudhary
Gc-47 Key Professional Dataset - Dataspider, Janell Westmoreland, Vy Duong, Nyong Nkereuwem, Kajal S Vaghani, Ritu Choudhary
C-Day Computing Showcase
The purpose of this project is to build a Web Crawler to extract personal information from a public website like Reddit and LinkedIn. We completed the Instagram crawling as a bonus for the project. The team will be using MySQL or any other open source relational database to organize the data and conduct a quantitative data analysis on it.Advisors(s): Dr. Han - Professor IT7993 Capstone Jing Wang -Project SponsorTopic(s): Data/Data AnalyticsIT7993
Gr-33 Efficient Yet Robust Privacy Preservation \\For Mpeg-Dash Based Video Streaming, Luke A Cranfill
Gr-33 Efficient Yet Robust Privacy Preservation \\For Mpeg-Dash Based Video Streaming, Luke A Cranfill
C-Day Computing Showcase
MPEG-DASH is a video streaming standard that outlines protocols for sending audio and video content from a server to a client over HTTP. However, it creates an opportunity for an adversary to invade users' privacy. While a user is watching a video, information is leaked in the form of meta-data, the size and time that the server sent data to the user. After a fingerprint of this data is created, the adversary can use this to identify whether a target user is watching the corresponding video. Only one defense strategy has been proposed to deal with this problem: differential privacy …
Gr-45 Framework For Collecting Data From Specialized Iot Devices., Md Saiful Islam
Gr-45 Framework For Collecting Data From Specialized Iot Devices., Md Saiful Islam
C-Day Computing Showcase
The Internet of Things (IoT) is the most significant and blooming technology in the 21st century. IoT has rapidly developed by covering hundreds of applications in the civil, health, military, and agriculture areas. IoT is based on the collection of sensor data through an embedded system, and this embedded system uploads the data on the internet. Devices and sensor technologies connected over a network can monitor and measure data in real-time. The main challenge is to collect data from IoT devices, transmit them to store in the Cloud, and later retrieve them at any time for visualization and data analysis. …
Gr-64 How Could Iot Assist Healthcare System During Covid-19 Or Future Pandemics?, Mohammad Nasajpour Esfahani
Gr-64 How Could Iot Assist Healthcare System During Covid-19 Or Future Pandemics?, Mohammad Nasajpour Esfahani
C-Day Computing Showcase
The Internet of Things (IoT), a technology built upon sensors and devices, has shown great applicability among various domains, especially healthcare. This pandemic has critically impacted all parts of society including people, health centers, businesses, authorities, etc. Researchers are attempting to adopt different technologies to mitigate this virus faster and save more lives. Regarding the great benefits that Internet of Things (IoT) has brought into different areas within the healthcare domain, this technology has been performing several main tasks including diagnosing, monitoring, tracing, disinfecting, and vaccinating to combat this virus. Our research is conducted of the possible IoT solutions to …
Uc-12 Comprehensive Security Solution For Small E-Commerce Business, Patrick Mccollums, Hristo Bakalov, Philinda Morse, Tyler Phillips, Watson Day
Uc-12 Comprehensive Security Solution For Small E-Commerce Business, Patrick Mccollums, Hristo Bakalov, Philinda Morse, Tyler Phillips, Watson Day
C-Day Computing Showcase
Project Description: Create an e-commerce server and a comprehensive security program to protect a web server for a simulated small business. This server will include security tools such as intrusion detection, firewall, and network monitoring. The installation and maintenance of this solution will be documented as part of the final documentation package. The server will be reviewed for exploitation from other teams while we attempt the exploitation of their server(s). Research/Motivation: How to research, install, configure, and integrate various open-source software packages for information security, e-commerce, web hosting, and database. Our motivation for this project was to create and secure …
Uc-15 Malware Analysis Using Reverse Engineering, Shamour Jones, Cynthia S Marcellus, Andy Pham, Nathan Rowe, Joshua Rowland
Uc-15 Malware Analysis Using Reverse Engineering, Shamour Jones, Cynthia S Marcellus, Andy Pham, Nathan Rowe, Joshua Rowland
C-Day Computing Showcase
The motivation for this project is driven by evaluation of the different tools on the market that allow for breaking down executables or binary files, and understanding what the malware is doing. By reverse-engineering the malware, we can understand its impact and how to protect against it. Our focus is to understand where different tools are stronger than others, as well as understand the evolving landscape of malware and security overall. For this capstone project, we utilized two different tools and many sample malware files. The methods used to debug the malware are detailed in our milestone two report and …
Uc-25 Woodline Interiors Project Planning Application, Beniamin Costea, Iram Nawaz, Natan Beraki, Daniel Lopez, Carter Richter, Yeonkuk Woo
Uc-25 Woodline Interiors Project Planning Application, Beniamin Costea, Iram Nawaz, Natan Beraki, Daniel Lopez, Carter Richter, Yeonkuk Woo
C-Day Computing Showcase
Meeting with the client regularly, we’ve established one of the many solutions to their requirements. The client, WoodLine Interiors, needs a well-designed system that can solve product management, client communication, and project management. The main issue that the company is facing is in the area of managing multiple projects and tracking project progress. Their issue is commonly addressed by a large number of companies that create software solutions, but it’s not personalized for their appropriate needs in the field of cabinetry. As a result our solution created the perfect stages and states of the project so there is no more …
Uc-31 An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes, Justin Duchatellier
Uc-31 An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes, Justin Duchatellier
C-Day Computing Showcase
Cloud-edge systems are vulnerable to thermal attacks as the increased energy consumption may remain undetected, while occurring alongside normal, CPU-intensive applications. The purpose of our research is to study thermal effects on modern edge systems. We also analyze how performance is affected from the increased heat and identify preventative measures. We speculate that due to the technology being a recent innovation, research on cloud-edge devices and thermal attacks is scarce. Other research focuses on server systems rather than edge platforms. In our paper, we use a Raspberry Pi 4 and a CPU-intensive application to represent thermal attacks on cloud-edge systems. …
Uc-62 Machine Learning: Twitter Bots In Disguise, Matthew Joseph Scheer, Nicolas Vasquez, James C Andersen, Joshua Tiangco, Justin Van, Cody R Walicek, Daniel Rimmel
Uc-62 Machine Learning: Twitter Bots In Disguise, Matthew Joseph Scheer, Nicolas Vasquez, James C Andersen, Joshua Tiangco, Justin Van, Cody R Walicek, Daniel Rimmel
C-Day Computing Showcase
This project was designed to help fight against misinformation spread by bots(computers), the goal assigned to us was to find and inform Twitter users of bots that follow and are being followed by the user.Advisors(s): Dr. Reza PariziTopic(s): Artificial IntelligenceSWE 4724
Web Developer Summer Intern At Keller Williams Realty- Cs 7995, Revatee Vaidya, Project Advisor: Dawn Tatum
Web Developer Summer Intern At Keller Williams Realty- Cs 7995, Revatee Vaidya, Project Advisor: Dawn Tatum
C-Day Computing Showcase
The purpose of this poster is to outline the duties of a Summer intern at Keller Williams Realty in Atlanta, Georgia as a Web Developer Intern. At Keller Williams, my aim was to develop and design websites for Blue Apple Real Estate School and Blue Apple Homes using WordPress and Learn Dash. The poster discusses my summer training, projects I was involved in, Technologies I used and my future goals.
Global Product And Technology Intern, Adp- Cs 7995, Keerthi Manchukonda, Project Advisor: Dawn Tatum
Global Product And Technology Intern, Adp- Cs 7995, Keerthi Manchukonda, Project Advisor: Dawn Tatum
C-Day Computing Showcase
I'm working on API for the PDF service generation of the Canadian Tax forms(Federal and Provinces) in specific. But it can be used for all countries and states.
Global & Product Technology Intern Adp- Cs 7995, Neha Gosavi, Project Advisor: Dawn Tatum
Global & Product Technology Intern Adp- Cs 7995, Neha Gosavi, Project Advisor: Dawn Tatum
C-Day Computing Showcase
I am Neha Gosavi. I am graduate student in Computer Science and currently doing summer internship as Global Product & Technology Intern at ADP. As intern I am part of SRE team(Site Reliability Engineer ).SRE team comprised of engineers taken from a diverse set of disciplines. This cross functional team was designed to support one of the key product offered by the company. I was involved with AWS cloud migration Poject and docker application, Splunk dashboard.
Second Language Education Website And App Design, Songqiao Yu, Project Advisor: Mohammed Aledhari
Second Language Education Website And App Design, Songqiao Yu, Project Advisor: Mohammed Aledhari
C-Day Computing Showcase
During the pandemic, schools are closed and it brought a great chance for JoJo Learning to expand and explore the new method of customer acquisition. With a combination method of educational robot and E-book, JoJo is providing his customers with a compound solution for summer second language learning for kids and toddlers. As part of the team, my main responsibility is to prototype and publish new UIUX design and using data analysis as a method to find the key channels of the business.
Facial Recognition And Object Detection-Based Smart Cashier System- Cs 4732, Timmy Duong, Project Advisor: Mohammed Aledhari
Facial Recognition And Object Detection-Based Smart Cashier System- Cs 4732, Timmy Duong, Project Advisor: Mohammed Aledhari
C-Day Computing Showcase
The topic of smart based cashier system. Professor Dr. Aledhari is the project advisor for CS4732 Machine Vision.
Improving Policy Making With Informed Covid-19 Case Prediction-Cs 4267, John Hurd, Project Advisor: Mohammed Aledhari
Improving Policy Making With Informed Covid-19 Case Prediction-Cs 4267, John Hurd, Project Advisor: Mohammed Aledhari
C-Day Computing Showcase
Covid-19 has necessitated many changes in the way life in the United States of America is lived. These include things such as new operational hours for retail and other service locations, mandatory and encouraged social distancing protocols on a state and federal level, and major changes to the way educational services are delivered in K-12 and higher education in both public and private contexts. The goal of this project is to produce a mathematical model with the express purpose of directly aiding pandemic response policy decision making by comparing predicted impacts of various logistical decisions and social distancing guidelines.