Computer Sciences Commons^™

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 …

Uc-37 Interactive Pdf File Editing For Online Classes, David J Hall, Chris J Stubbs, Justin Masters, Dalton G Parker, Rosendo Lopez

C-Day Computing Showcase

This system aims to create an interactive environment for teachers to view/grade/edit student submission in virtual classes. Objectives for this project are to create independent component or logic model that includes the following functions. This component should be integrated with a .net core application easily. -Upload pdf files to the system and save files to the server; -Record audio online and save audio to the system; also, the audio can be played online; -Upload and play video or video link (YouTube); -Split file. When uploading a PDF file, the system will allow to split or crop the file (partial file …

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

Uc-56 Rendeview, James C Noltimier, Gyasi Igyan, Barrett Rose, Niyi Adekunle, Ashley Lowe

C-Day Computing Showcase

Rendeview is a mobile application designed to allow users to find a physical meeting location equitable for 3+ people, taking into account drive time and traffic conditions.Advisors(s): Dr. Reza PariziTopic(s): Software EngineeringSWE 4724

Uc-7 Software Engineer – Clarity Llc, Amy Mullins

C-Day Computing Showcase

Clarity makes an app called CaptionMate that does closed captions for phone calls.. During the internship, a website was made to visualize metrics that are collected on users such as calls made, minutes used, time active, region, age, theme, font, and platform used. Bar charts are used to show minutes and calls used on days of the week. 100% bar charts are used to show how much a day contributes to the usage of the app; a user contributes to minutes, calls and platform usage; and show calls incoming vs. outgoing. Line graphs were created to show growth in app …

Ur-48 Using Semantic Segmentation In A Convoluted Neural Network For Vocal Localization In Music, Trevor E Stanca, Trinite, Noah

C-Day Computing Showcase

I. PROJECT OVERVIEW A. Research Question In this project, the question was asked: ”Is there an easier way to extract vocals from music?” Many other works are able to extract vocals with Deep Neural Networks using Multitask Learning, which are large and take a long time to train. To rival this, we wish to present a method to identify vocals with a Convolutional U-Network (U-Net) for Semantic Segmentation of audio files. B. Project Description This project differs from other works by identifying vocal locations by converting audio files in Short Time Fourier Transforms(STFT), and treating them as images in the …

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

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-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

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 …

Wellstar Health Systems Internship- Cse 4983, Joyce Anderson, Project Advisor: Dawn Tatum

C-Day Computing Showcase

I interned at Wellstar Health Systems in there IT department. Staring from months 1 - 6 I rotated throughout the the IT Service Desk, Field Services, IT Service Management, IT Security, and IT Applications departments. Towards months 7 - 12 I worked in the IT Service management depart in the Knowledge based composing and editing knowledge articles for WellStar employees that had ITIL access to view and for instruction on how to work WellStar applications.

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.

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.

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

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 And Technology Intern, Adp- Cs 7995, Deeksha Koya, Project Advisor: Dawn Tatum

C-Day Computing Showcase

Migrating the legacy surveys to on platform Salesforce Surveys.

Global Product And Technology Intern- Cs 7995, Krushita Patel, Project Advisor: Dawn Tatum

C-Day Computing Showcase

My project is about the experience that I have had and I have been currently having working as an intern at ADP working full time. I have also included my work description and what I am looking forward to for my rest of internship.

It Deployment And Fulfillment Co-Op- Cs 4983, Sam Wilson, Project Advisor: Dawn Tatum

C-Day Computing Showcase

No abstract provided.

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.

Using Artificial Intelligence To Prescribe Medicine- Cs 4732, Xander Bush, Louis Livingston, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

With the current advancements being made in the Machine Learning field, utilizing Artificial Intelligence and Deep Learning techniques to analyze complex information such as genome information has become possible. By creating and building up a database of such data as well as compatible medicines, we suspect it is possible to prescribe personalized medicines to treat patients with a high percentage of success while also being able to take into account various other health conditions and pre-dispositions. This possibility depends heavily on the ability of the Neural Network or various other Machine Learning structure to correctly interpret the information from a …

Tracking High-Speed Chase Vehicles With Machine Learning​- Cs 4732, Louis Livingston, Dylan Sirna, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

From law enforcement officers, to fleeing suspects, to the general public, lengthy police pursuits poses a risk to all involved. With modern advances in machine vision, pursuits caught on camera can be analyzed with machine learning techniques. These techniques can then be used to produce datasets for future researchers to use in machine learning algorithms. This paper explores ways to produce those datasets using OpenCV, a machine vision library for Python, as well as GOTURN, a object tracker for OpenCV.

Service Industry Sentience- Cs 4267, Charles Peery, Project Advisor: Mohammed Aledhari

C-Day Computing Showcase

Since Amazon GO opened its' doors to employees in late 2016, businesses have been watching closely to see if a store without checkout can succeed in the current market.

While self-checkout stations have been in use since 1986, businesses are looking for ways to enhance the convenience of shoppers. From online ordering, contactless payments, and same day pickup, to drone delivery, leaving packages inside your home, and now checkout free stores.

In this presentation I explore the possibility of using YOLO and OpenCV to produce a checkout system based on object recognition which makes a system that is cheaper and …

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.