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Full-Text Articles in Computer Sciences

Uc-14 Teleclinic, Jay P Bhatt, Lucius Burch, Zekai Fei, Bijoy Shah, Hao Zhang Apr 2021

Uc-14 Teleclinic, Jay P Bhatt, Lucius Burch, Zekai Fei, Bijoy Shah, Hao Zhang

C-Day Computing Showcase

TeleClinic is a telemedicine web application that provides ease of access and a medium for interaction between patients and their respective doctors and administrators. In particular, this web portal includes a chat feature, an area for medical reports, an area for appointment requests, and an area for video recordings. Additionally, TeleClinic meets the requirements prescribed by the Health Insurance Portability and Accountability Act (H.I.P.A.A.) via upholding data privacy and safeguarding medical information. To maximize its overall utility, TeleClinic utilizes the React and React Redux libraries for its front-end and a NoSQL database in Google Firebase for its back-end.Advisors(s): Dr. Ken …

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Gr-64 How Could Iot Assist Healthcare System During Covid-19 Or Future Pandemics?, Mohammad Nasajpour Esfahani Apr 2021

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 …

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Gc-54 Covid-19 Mortality Prediction Using Machine Learning Techniques, Lindsay Schirato, Kennedy Makina, Dwayne Flanders Apr 2021

Gc-54 Covid-19 Mortality Prediction Using Machine Learning Techniques, Lindsay Schirato, Kennedy Makina, Dwayne Flanders

C-Day Computing Showcase

In late 2019, SARS-CoV2 also known as COVID-19 was first identified in the city of Wuhan, China. This virus can infect a person and without showing any signs of sickness, can spread of COVID-19 unknowingly. The World Health Organization declared it a global pandemic in March 2020 because of its far-reaching effects in every part of the world. Scientists have been working to leverage technology to prevent spread, detection and vaccine development. With machine learning, models can predict which patient will most likely have a higher mortality rate. Using WEKA, a machine learning tool and a data set based on …

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Gr-33 Efficient Yet Robust Privacy Preservation \\For Mpeg-Dash Based Video Streaming, Luke A Cranfill Apr 2021

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 …

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Uc-11 Information Recall For Kids With Autism, Alex J Bechke, Elizabeth Burnside, Haiden Gembinski, Ross Murphy, Ryan Taylor, Henok Demisse Apr 2021

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. …

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Gr-23 Machine Learning Techniques For Malware Network Traffic Detection, Jermaine Cameron Apr 2021

Gr-23 Machine Learning Techniques For Malware Network Traffic Detection, Jermaine Cameron

C-Day Computing Showcase

Persistent malware variants are a constant threat to computing infrastructure across all regions and business sectors. Traditional detection systems focus primarily on signature-based analysis but this approach cannot adequately keep pace with the velocity and volume of new malware variants that are continuously deployed onto the internet. Most network traffic detection techniques are focused on analyzing raw packets and have not deterred the surge of persistent malware. Therefore, it is important to develop new research techniques that are focused on optimized metadata from malware network traffic to effectively identify an ever-increasing expanse of malicious software. Recent research efforts by Letteri …

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Uc-16 Understanding The Drivers Of Medication Nonadherence In The United States, Roman A Schwieterman, Austin Poole, Austin Kay, Muhammad Usman Mustafa, Issifou Ali Apr 2021

Uc-16 Understanding The Drivers Of Medication Nonadherence In The United States, Roman A Schwieterman, Austin Poole, Austin Kay, Muhammad Usman Mustafa, Issifou Ali

C-Day Computing Showcase

Medication nonadherence is generally defined as a patient’s inability to take their medications correctly as prescribed by their doctors. Medication nonadherence adversely affects patient outcomes and increases healthcare costs. Prior research found that health system-, condition-, patient- (older age is one factor), therapy- and social/economic-related factors have been identified to show effect on non-adherence. Our goal is to analyze the NHIS data to understand the sociodemographic and health causes of medication nonadherence, as well as answer the following questions about our selected topic: What variables are the most relevant drivers of nonadherence? Does the direction and strength of the associations …

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Uc-26 Pose Extraction For Real-Time Workout Assist_Capstone Group_W01_Spring Semester, Royce Camp, Zach Christmas, Jonathon Segars, Amanda Mead, Cameron Page Apr 2021

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 …

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Uc-31 An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes, Justin Duchatellier Apr 2021

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. …

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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 Apr 2021

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

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Uc-35 Development Of An Automated Software Packaging Solution For Linux, Robert D Ryan, Sammi Figueroa, Dylan Parker, Blair Hill, Bishwo R Marhatta Apr 2021

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 …

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Uc-37 Interactive Pdf File Editing For Online Classes, David J Hall, Chris J Stubbs, Justin Masters, Dalton G Parker, Rosendo Lopez Apr 2021

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 …

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Uc-39 Journalistic Integrity Vis Artifical Intelligence, Dylan Dalton, Ray Martin, Duy Nquyen, Yesse Quezada, Brian Dominguez Apr 2021

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

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Uc-56 Rendeview, James C Noltimier, Gyasi Igyan, Barrett Rose, Niyi Adekunle, Ashley Lowe Apr 2021

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

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Uc-7 Software Engineer – Clarity Llc, Amy Mullins Apr 2021

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 …

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Ur-48 Using Semantic Segmentation In A Convoluted Neural Network For Vocal Localization In Music, Trevor E Stanca, Trinite, Noah Apr 2021

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 …

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Ur-60 Video-To-Video Synthesis With Semantically Segmented Video, Aydan Mufti, Jordan S Hasty Apr 2021

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

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Ur-63 Low Cost High Impact Fall Detection At The Edge, Dylan Sirna, Noah Sage Apr 2021

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 …

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Ur-65 Cnn Cifar Image Identification, Matteo L Staciarine Apr 2021

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

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Ur-66 Image Segmentation With Machine Learning, Kedar A Johnson Apr 2021

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 …

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Gc-28 Modern Web Scraping, Kenny Randolph, Joselyn Giron, Denise Tucker, Justin B Bridges, Sandhya Bantu Apr 2021

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, …

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Gc-47 Key Professional Dataset - Dataspider, Janell Westmoreland, Vy Duong, Nyong Nkereuwem, Kajal S Vaghani, Ritu Choudhary Apr 2021

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

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Gr-1 Compare Two Off Angle Normalization, Emily Ehrlich Apr 2021

Gr-1 Compare Two Off Angle Normalization, Emily Ehrlich

C-Day Computing Showcase

This work investigates different iris normalization techniques to compare their performance including elliptical normalization and circular normalization after frontal projection of off-angle iris recognition. Elliptical normalization samples the iris texture using elliptical segmentation parameters. For circular unwrapping, we first estimate the gaze deviation using ellipse parameters and the image will be projected back to frontal view using perspective transformation. Then, we segment the transformed image and normalize using circular parameters. We further investigate if: (i) elliptical normalization or circular unwrapping recognition performance is higher, and (ii) the two segmentations methods in circular unwrapping increase the recognition efficiency. Based on the …

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Gr-34 Defensive Neural Network, Hongkyu Lee Apr 2021

Gr-34 Defensive Neural Network, Hongkyu Lee

C-Day Computing Showcase

Machine learning (ML) algorithms require a massive amount of data. Firms such as Google and Facebook exploit user's data to deliver a more precise ML-based service. However, collecting users' data is a risky action because their private data can be leaked through the transmission. As a remedy, federated learning is introduced. In federated learning, a central server distributes a machine learning model to users. Each user trains the model to its data, and send the model back. Later the models are aggregated and distributed again. Federated learning is more secure in that it emancipates users from the risk of sending …

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Gr-40 Design And Implementation Of A Microservices Web-Based Architecture For Code Deployment And Testing, Soin Abdoul Kassif Baba M Traore Apr 2021

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 …

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Gr-44 An Efficient Intrusion Detection Framework Based On Federated Learning For Iot Networks., Osama Shahid Apr 2021

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 …

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Gr-45 Framework For Collecting Data From Specialized Iot Devices., Md Saiful Islam Apr 2021

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. …

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Gr-50 Predicting Users' Engagement During Interviews With Biofeedback, Voice, And Supervised Machine Learning, Thaide Huichapa Apr 2021

Gr-50 Predicting Users' Engagement During Interviews With Biofeedback, Voice, And Supervised Machine Learning, Thaide Huichapa

C-Day Computing Showcase

Studies show that the quality of the information collected during an elicitation interview, and consequently the quality of the software product that needs to be developed, highly depends on the interviewee's engagement. Because of social expectations, interviewees tend to hide if they are bored or not engaged. To overcome this problem and support the analyst during the interviews, this research uses biometric data and voice features, together with supervised machine learning algorithms, to predict the interviewee's engagement. We built our solution on an experiment consisted of interviewing 31 participants. We collected the data using an Empatica wristband and a default …

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Gr-53 An Investigation On Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset And Its Effectiveness, Md Jobair Hossain Faruk Apr 2021

Gr-53 An Investigation On Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset And Its Effectiveness, Md Jobair Hossain Faruk

C-Day Computing Showcase

Neurotechnology describes as one of the focal points of today’s research around the domain of Brain-Computer Interfaces (BCI). The primary attempts of BCI research are to decoding human speech from brain signals and controlling neuro-psychological patterns that would benefit people suffering from neurological disorders. In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches. First, we explore a decoding natural speech approach that is designed to decode human speech directly from the human brain onto a digital screen introduced by Facebook Reality Lab and University of California San Francisco. Then, we study a …

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Gr-67 Representation Learning For Motion Sequence, Saisangararamaleengam Alagapan, Alexandru Malos, Roshni Kishor, Venkateswara Reddy Mosali Apr 2021

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

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