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2021

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Articles 1981 - 2010 of 3476

Full-Text Articles in Computer Sciences

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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Gr-70 Defending Data Reconstruction Through Adaptive Image Augmentation, Seunghyeon Shin Apr 2021

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 …

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Uc-12 Comprehensive Security Solution For Small E-Commerce Business, Patrick Mccollums, Hristo Bakalov, Philinda Morse, Tyler Phillips, Watson Day Apr 2021

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 …

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Uc-15 Malware Analysis Using Reverse Engineering, Shamour Jones, Cynthia S Marcellus, Andy Pham, Nathan Rowe, Joshua Rowland Apr 2021

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 …

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Uc-20 Analyzing Concentration Levels In Online Education Using Machine Learning, Gray Daugherty, Rachel W Lawson, Kyle C. Ensley, Michael Chann, Tobi Adams Apr 2021

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 …

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Uc-25 Woodline Interiors Project Planning Application, Beniamin Costea, Iram Nawaz, Natan Beraki, Daniel Lopez, Carter Richter, Yeonkuk Woo Apr 2021

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 …

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Uc-30 Malware Analysis Using Reverse Engineering, William K Pharr, Kelton Reid, Icyss M Strong, Michael R Lewis Apr 2021

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 …

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Gr-38 Energy Cost And Efficiency On Edge Computing: Challenges And Vision, Kousalya Banka Apr 2021

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. …

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Uc-57 Cultiva- The Plant Companion, Travis R Hescox, Kat Branham, Ahsan Jamal, Joseph Henggeler, Erick Reyes, Andy Alcaraz, Momodou Mbye Apr 2021

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 …

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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 Apr 2021

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 …

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Uc-6 Covid-19 Data Analysis - Regression, Noah Druss Apr 2021

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 …

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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 Apr 2021

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

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Uc-69 Team 10b Bchain, Jonathan D Lashgari, Carlos A Diaz, Jeffery Erhunse, Caleb T Goff, Giang T Nguyen Apr 2021

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, …

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Ur-41 The Accessibility Of The Mobile Gaming Platform For The Visually Impaired, Christian Thomas Jansen Apr 2021

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 …

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Ur-46 Breastnet;, Cora L Meador, Ryan Deem Apr 2021

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 …

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Cognitive Radio Spectrum Sensing And Prediction Using Deep Reinforcement Learning, Syed Qaisar Jalil, Mubashir Husain Rehmani, Stephan Chalup Apr 2021

Cognitive Radio Spectrum Sensing And Prediction Using Deep Reinforcement Learning, Syed Qaisar Jalil, Mubashir Husain Rehmani, Stephan Chalup

Preprints

In this paper, we propose to use deep reinforcement learning (DRL) for the task of cooperative spectrum sensing (CSS) in a cognitive radio network. We selected a recently proposed offline DRL method called conservative Q-learning (CQL) due to its ability to learn complex data distributions efficiently. The task of CSS is performed as follows. Each secondary user (SU) performs local sensing and using CQL algorithm, determines the presence of licensed user for current and k-1 future timeslots. These results are forwarded to the fusion centre where another CQL algorithm is operating that generates a global decision for the current and …

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Comparative Study Of Virtual Reality Vs Augmented Reality For Training Oriented Applications, Ramiro Serrano Vergel Apr 2021

Comparative Study Of Virtual Reality Vs Augmented Reality For Training Oriented Applications, Ramiro Serrano Vergel

Theses and Dissertations

The usability of interactive applications based on virtual environments for training in 3D simulations needs to be reviewed and evaluated to identify which of these technologies fit better for a specific context. The study of these systems can be complex, considering that there are diverse characteristics in the applications proposed. Additionally, there are countless contexts in which these technologies could be applied. Therefore, this study provides a first approach to the analysis of the differences between AR and VR for the specific case of 3D object manipulation. This study is oriented on the analysis of the effects of latency, field …

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Control Over Skies: Survivability, Coverage, And Mobility Laws For Hierarchical Aerial Base Stations, Vishal Sharma, Navuday Sharma, Mubashir Husain Rehmani, Haris Pervaiz Apr 2021

Control Over Skies: Survivability, Coverage, And Mobility Laws For Hierarchical Aerial Base Stations, Vishal Sharma, Navuday Sharma, Mubashir Husain Rehmani, Haris Pervaiz

Publications

Aerial Base Stations (ABSs) have gained significant importance in the next generation of wireless networks for accommodating mobile ground users and flash crowds with high convenience and quality. However, to achieve an efficient ABS network, many factors pertaining to ABS flight, governing laws and information transmissions must be studied. In this article, multi-drone communications are studied in three major aspects, survivability, coverage, and mobility laws, which optimize the multitier ABS network to avoid issues related to inter-cell interference, deficient energy, frequent handovers, and lifetime. The article includes simulation results of hierarchical ABS allocations for handling a set of users over …

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