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Gr-1 Compare Two Off Angle Normalization, Emily Ehrlich
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 …
Gr-34 Defensive Neural Network, Hongkyu Lee
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 …
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 …
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-50 Predicting Users' Engagement During Interviews With Biofeedback, Voice, And Supervised Machine Learning, Thaide Huichapa
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 …
Gr-53 An Investigation On Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset And Its Effectiveness, Md Jobair Hossain Faruk
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 …
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-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-20 Analyzing Concentration Levels In Online Education Using Machine Learning, Gray Daugherty, Rachel W Lawson, Kyle C. Ensley, Michael Chann, Tobi Adams
Uc-20 Analyzing Concentration Levels In Online Education Using Machine Learning, Gray Daugherty, Rachel W Lawson, Kyle C. Ensley, Michael Chann, Tobi Adams
C-Day Computing Showcase
These past few years have introduced the most important time in history to study new faucets of online learning. Due to COVID's impact, online learning became a staple in millions of homes across the country. Guided by the research question, “Can a machine learning model be created and trained to detect student concentration level based on eye and facial data?”, we set out to contribute to society’s understanding of online learning under the guidance of Dr. Ying Xie and Dr. Linh Le. Our process involved recording ourselves participating in online classes to garnish eye and facial data. Each student recorded …
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-30 Malware Analysis Using Reverse Engineering, William K Pharr, Kelton Reid, Icyss M Strong, Michael R Lewis
Uc-30 Malware Analysis Using Reverse Engineering, William K Pharr, Kelton Reid, Icyss M Strong, Michael R Lewis
C-Day Computing Showcase
Cybercrimes are a billion-dollar industry that is rapidly growing by the day. One of the biggest threats faced by companies is the infection of malware. New forms of malware are created daily and ever evolving to evade detection methods. Understanding how malware infects your system and how it eludes detection is crucial to keeping a company's network and devices safe. During this project we will be using reverse engineering methods to better understand the functionality of malware, as well as how it eludes detection. We will be using IDAPro and WiDbg to perform the reverse engineering. Using this knowledge, we …
Gr-38 Energy Cost And Efficiency On Edge Computing: Challenges And Vision, Kousalya Banka
Gr-38 Energy Cost And Efficiency On Edge Computing: Challenges And Vision, Kousalya Banka
C-Day Computing Showcase
The Internet of Things (IoT) has been the key for many advancements in next-generation technologies for the past few years. With a conceptual grouping of ecosystem elements such as sensors, actuators, and smart objects connected to perform complex operations to perform environmental monitoring, intelligent transport system, smart building, smart cities, and endless other possibilities. Edge computing helps the IoT’s reach even further and be more robust by connecting multiple censored devices through the internet and forming powerful computational capabilities. Unfortunately, this computation level comes at a cost as the devices are constantly being used to communicate and perform specific actions. …
Uc-57 Cultiva- The Plant Companion, Travis R Hescox, Kat Branham, Ahsan Jamal, Joseph Henggeler, Erick Reyes, Andy Alcaraz, Momodou Mbye
Uc-57 Cultiva- The Plant Companion, Travis R Hescox, Kat Branham, Ahsan Jamal, Joseph Henggeler, Erick Reyes, Andy Alcaraz, Momodou Mbye
C-Day Computing Showcase
The goal of this project is to improve the lives of gardeners or everyday people with a green thumb by providing them with a planter that will not only hold their plant of choice, but also give them information about the health and growth of their plant without them having to interact with it directly. This project will provide the user with a planter containing sensors that communicate with an application from which the user can monitor the environment of the plant. This project can serve a wide range of people from first-time gardeners to seasoned veterans. Users will no …
Uc-59 Analyzing Concentration Levels In Online Learning With Facial Values, Elliott J Witherell, Jakeira Askew, Jonathan R Dicks, Steven C Mcguire, Jacob A Walton
Uc-59 Analyzing Concentration Levels In Online Learning With Facial Values, Elliott J Witherell, Jakeira Askew, Jonathan R Dicks, Steven C Mcguire, Jacob A Walton
C-Day Computing Showcase
Can deep learning models accurately predict whether an individual is focused or distracted on a task in order to improve learning efficiency? In the context of online learning with the use of a webcam, this project is aimed at detecting concentration levels of students to potentially assist with improving learning efficiency. Machine learning technologies have been utilized to evaluate students’ facial expression and eye movements to identify whether a student is focused or distracted. The machine learning branch that is employed is a supervised learning model. This supervised learning model makes predictions based on given input features. A total of …
Uc-6 Covid-19 Data Analysis - Regression, Noah Druss
Uc-6 Covid-19 Data Analysis - Regression, Noah Druss
C-Day Computing Showcase
Covid-19 has been arguably the most impactful event in the past century. SARS-Cov-2 is a viral respiratory illness discovered in late 2019 that has spread to almost every country in the world. It has directly or indirectly affected just about everybody in the world greatly, causing over 117 million cases and 2.59 million deaths as of March 2021. This project has focused on the use of different types of linear regression to both analyze and predict Covid-19 infection data based on different features. First, simple linear regression was used to predict total deaths based on infections both globally and by …
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
Uc-69 Team 10b Bchain, Jonathan D Lashgari, Carlos A Diaz, Jeffery Erhunse, Caleb T Goff, Giang T Nguyen
Uc-69 Team 10b Bchain, Jonathan D Lashgari, Carlos A Diaz, Jeffery Erhunse, Caleb T Goff, Giang T Nguyen
C-Day Computing Showcase
BChain is a new P2P file sharing system that is fully private, anonymous, globally self-verifying, and utilizes an automatic peer-maintained network of trust in data, accomplished through new methods of routing content over the whole network, encrypted, rather than per torrent download. Verification is done by adding file metadata to a blockchain giving the network consistent knowledge of each file it can transfer, and how to verify file received against the network. This enables a policy of zero trust against peers. This system is implemented by an app that interfaces with the network using the protocol, using it for upload, …
Ur-41 The Accessibility Of The Mobile Gaming Platform For The Visually Impaired, Christian Thomas Jansen
Ur-41 The Accessibility Of The Mobile Gaming Platform For The Visually Impaired, Christian Thomas Jansen
C-Day Computing Showcase
The motivation for this project is to research mobile gaming interfaces with the goal of conceptualizing practices in game design that would create more accessible interfaces for the visual impairment community. Thus far, the project has focused on practices that mobile game designers can use to make their games more accessible to the visually impaired. These includes the use of plain text rather than graphics to be scannable by screen readers, the inclusion of audio-oriented support and instruction, the use of contrasting colors to make options more recognizable to those with partial visual impairments, and the implementation of game mechanics …
Ur-46 Breastnet;, Cora L Meador, Ryan Deem
Ur-46 Breastnet;, Cora L Meador, Ryan Deem
C-Day Computing Showcase
In the United states, 13% of women are diagnosed with breast cancer in their lifetime, and it is the second leading cause of death by cancer in women. Early detection and screening can result in an increase of life expectancy by 10 years on average. Unfortunately, breast cancer can be challenging to detect, since it can appear anywhere in the breast. Cancer that is detected in its early stages can give patients more options and save thousands of dollars in medical costs. Some of the most recent developments in computer science and machine learning are in the biomedical field, especially …
Gc-54 Covid-19 Mortality Prediction Using Machine Learning Techniques, Lindsay Schirato, Kennedy Makina, Dwayne Flanders
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 …
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 …
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. …
Gr-23 Machine Learning Techniques For Malware Network Traffic Detection, Jermaine Cameron
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 …
Uc-16 Understanding The Drivers Of Medication Nonadherence In The United States, Roman A Schwieterman, Austin Poole, Austin Kay, Muhammad Usman Mustafa, Issifou Ali
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 …
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-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-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