Uc-257 Gtri: Analysis Of Alternatives,
2022
Kennesaw State University
Uc-257 Gtri: Analysis Of Alternatives, Jake D. Pham, Zayda Huballah, Evans Jones, Roshni Modi, Salimata Bado
C-Day Computing Showcase
The Capstone project Analysis of Alternatives focuses on research and testing workstation deployment software and see if they can fulfill certain requirements that GTRI has requested. Planning and research was first conducted on ten different software that are available on the market where each software was evaluated on a point based system based on the requirements given to us by the company. After researching the ten software three are chosen that best fit the requirements from the company and are then moved to the testing phase. After testing the three chosen software the team will collectively decide which one to …
Uc-261 Grocery Application,
2022
Kennesaw State University
Uc-261 Grocery Application, Quin’Dariu A. Lyles-Woods, Adam Maksymczuk, Aidan Le-Beard, Jeetu Sharma, Danny Sor
C-Day Computing Showcase
This project is being completed for Kennesaw State University’s CS 4850 - Computer Science Senior Project undergraduate capstone course. This project as described is a dynamic grocery list mobile app that updates all members when items are added. The app then must contain groups that the user is able to join, have a list that is shared between that group, and have the ability for all users in the group to add and remove items from the list. To notify the users, push notifications are likely to be used. In addition to having a shared list, it makes sense that …
Uc-262 Gtri: It Web Management Project,
2022
Kennesaw State University
Uc-262 Gtri: It Web Management Project, Scott Duong, Vanessa Sunar, Firmin Ngappi, Meva Schmit, Stephan Mah
C-Day Computing Showcase
This project is meant to develop a baseline web application that will support development of future tools for managing an IT department (licensing, asset tracking, budget management, self-service software/configuration, issue management/tickets, etc.) As well as provide a free IT Management tool that an IT manager can easily access and use. Having an IT management tool to aid with different things such as tracking, budget management and more is very essential to efficiently run an IT department. There are various tools to assist with that which exist today. However, as pointed out by our client GTRI, a lot of them are …
Uc-263 It4983 Cybersecurity Capstone,
2022
Kennesaw State University
Uc-263 It4983 Cybersecurity Capstone, Jordan White, Stephen C. Woodman, Jenny Owens, Hector Gomez, Aaron Scott
C-Day Computing Showcase
For the Cybersecurity capstone project, our team was given a webserver and website for the company Akwaaba. We were tasked to fix all vulnerabilities, keep the server up to date, and help maintain the site with uptime being the priority. After the first two milestones were complete, we were to attempt to hack another team’s server while they attempted to do the same to us. When the attack phase began on Wednesday 10/26, our team discovered the other team had not changed any of their original passwords, so we took control within thirty minutes and took it down soon after. …
Uc-272 Defunct To Funct: Expanding The Functionality Of Forgotten Robots,
2022
Kennesaw State University
Uc-272 Defunct To Funct: Expanding The Functionality Of Forgotten Robots, Thomas E. Stockdale, Khoa Ho, Johnny Huynh, Marcel Youri Nguiagaing Seuga
C-Day Computing Showcase
The field of robotics is an expanding landscape, pushing the frontiers of engineering, machine vision, artificial intelligence and more. The robotics industry also has a foothold in many areas, such as consumer markets, scientific research, industrial and medical applications, and even exploration. With the growing interest in automated machines, individuals who can work with these machines are in demand, and providing a way to learn the skills to do so would be just as valuable. Kennesaw State University is currently in possession of two UXA-90 Humanoid robots; both of which have remained in storage for extended periods of time since …
Ur-295 Data Collection In Parkinson's Vr,
2022
Kennesaw State University
Ur-295 Data Collection In Parkinson's Vr, Neil E. Weingarten, Ian Mcconnell
C-Day Computing Showcase
This project is meant to show an addition to a Parkinson's simulation within VR where there are now different methods of data collection that are collected in-game. These data points are tracked and logged during gameplay, and are meant to allow researchers to make more effective use of the simulation as a tool for data collection. An example demo of the game and example files that were generated during gameplay are provided.
Gc-250 Object Detection And Tracking: Deep Learning-Based Framework With Euclidean Distance, Iou, And Hungarian Algorithm,
2022
Kennesaw State University
Gc-250 Object Detection And Tracking: Deep Learning-Based Framework With Euclidean Distance, Iou, And Hungarian Algorithm, Md Jobair Hossain Faruk
C-Day Computing Showcase
Object tracking is an important basis for the logistics industry where multiple packages are moved on conveyor belts at a time. Accurate datasets and efficient benchmarks are a few of the several problems for both object detection and tracking for training the deep learning-based framework. Preparing 100% accurate correspondence between objects throughout different frames by assigning human annotated unique_attributes to train framework efficiently over ground truth data. In this research, we develop an (i) OpenCV-based framework that allows the user to assign human-annotated identification between objects and (ii) a novel application for object detection and tracking. We utilize the assigned …
Gr-245 Parsimonics: Achieving High Classification Accuracy Even With High Dimensional Image Reduction,
2022
Kennesaw State University
Gr-245 Parsimonics: Achieving High Classification Accuracy Even With High Dimensional Image Reduction, Joshua Owens
C-Day Computing Showcase
The asl-alphabet dataset, hosted by Kaggle, is a collection of 87000 color images sized 200x200x3, grouped into 29 classes of 3000 images apiece (dataset A). The classes consist of the 26 English letters plus three classes for space, delete and nothing. As a proof of concept, the dataset was first truncated by deleting 2700 images from each class, leaving only the first 300 images per class and totaling 8700 images, or 10% of the original number of images (dataset B). Then, transfer learning was applied to dataset B using Alexnet with Imagenet weights. >99% accuracy with dataset B was readily …
Gr-273 Building A Chatbot,
2022
Kennesaw State University
Gr-273 Building A Chatbot, Varun Gottam, Sathwik Chepyala, Sai Mohit Saimpu, Venkata Sai Krishna Yalavarthi, Nikhil Sai Buddiga
C-Day Computing Showcase
A chatbot is now a part of many online applications like Health Care, Education, E-commerce, etc. It made the conversation between the customers and the service providers much more convenient as the chatbot can answer most of the queries without human intervention from the website side. This saves a lot of time and work.
Gr-284 Automated Vulnerability Detection In Source Code Using Deep Neural Networks,
2022
Kennesaw State University
Gr-284 Automated Vulnerability Detection In Source Code Using Deep Neural Networks, Mst Shapna Akter
C-Day Computing Showcase
One of the most important challenges in the field of a software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a large-scale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of open-source functions that point to potential exploits. We created an efficient and scalable vulnerability detection …
Gr-287 Natural Disaster Prediction,
2022
Kennesaw State University
Gr-287 Natural Disaster Prediction, Sravya Sabbu, Aishwarya Turlapati, Suryapraveen Adivi
C-Day Computing Showcase
Natural disasters are events that are difficult to avoid. There are several ways of reducing the risks of natural disasters. One of them is implementing disaster reduction programs. There are already several developed countries that apply the concept of disaster reduction. In addition to disaster reduction programs, there are several ways to predict or reducing the risks using artificial intelligence technology. One of them is machine learning. By utilizing this method at the moment, it facilitates tasks in visualizing, analysing, and predicting natural disaster. This project will focus on conducting a review process and understanding the purpose of Machine learning …
Gr-300 Azure Security Kql Query Builder,
2022
Kennesaw State University
Gr-300 Azure Security Kql Query Builder, Navyapravalika Sabbula, Jeevana Kalipindi
C-Day Computing Showcase
We produce and manage petabytes of data every day in today's culture when everything is digitally recorded, from our web surfing habits to our medical records. Big data will significantly alter all facets of existence. However, simply processing and interpreting data is insufficient; when data is presented visually, the human brain can identify patterns more quickly. In many different businesses, data analytics and visualization are essential decision-making tools. The visualization field is also opened up, displaying innovative thinking for visualizing the big-data dilemma. It is challenging to see such massive volumes of data in static or real-time formats. we explain …
Gr-306 Improving Wildfire Propagation Simulations Using Cellular Automata To Help Emergency Management,
2022
Kennesaw State University
Gr-306 Improving Wildfire Propagation Simulations Using Cellular Automata To Help Emergency Management, Madeline Frank, Lokesh Meesala, Yagnasree Bollineni, Amrutha Venkatesh, Mujahid Shaheed Shaik
C-Day Computing Showcase
Discrete computational models known as cellular automata (CA) utilize discrete spatial cells, each existing in one of a set of possible states at any given moment. Transition rules specify how a given cell’s state evolves in subsequent time steps and is dependent on the states of the given cell’s neighborhood of surrounding cells. A cellular automaton model can also account for the influence of other external or physical factors on the evolution of a given cell’s state. These capabilities afforded by CA models make it an ideal tool to simulate the propagation of wildfires. One specific study carried out by …
Uc-266 Indy-5 Compchores,
2022
Kennesaw State University
Uc-266 Indy-5 Compchores, Myers Berry, Ian Snyder
C-Day Computing Showcase
Getting anyone motivated to complete chores can be a chore itself! To solve this issue, our team is using Dart and Flutter to build a desktop application that pits roommates, family members, and siblings against one another to complete chores for points. The purpose of this program is to simulate competition between users in order to motivate users to complete tasks amongst the living space. To complete this task, our program will provide a place where users can create a family, create an account, join a family, create chores, complete chores, check chore history, view the family scoreboard, and view …
Uc-274 Restful Robots,
2022
Kennesaw State University
Uc-274 Restful Robots, Jack I. Young, Derek M. Comella, Sarah Thomas, Andrew Loveless
C-Day Computing Showcase
The UXA-90 Robots have been sitting idle at Kennesaw State University for years. The only documentation provided were factory manuals, and there was nothing additional found online. The first step was to conduct a risk assessment and report the results to Professor Perry and Dr. Pei. The objective of the risk assessment was to determine the viability of the robots and the feasibility of three different senior project teams using them for a project. Once the risk assessment was completed and reported it was determined that all three teams could proceed with their senior projects. However, it was recommended that …
Ur-269 Towards Bounding The Behavior Of Deep Neural Networks,
2022
Kennesaw State University
Ur-269 Towards Bounding The Behavior Of Deep Neural Networks, Richard Borowski
C-Day Computing Showcase
Advances in Artificial Intelligence (AI), particularly in the form of deep neural networks, have revolutionized a diverse range of fields. As neural networks become more pervasive, the need to understand the boundaries of their behavior is becoming increasingly important. For example, can we formally guarantee that an autonomous vehicle will not violate traffic laws, such as reaching excessive speeds? Towards the goal of bounding the behavior of a neural network, we propose how to bound the behavior of individual neurons by incrementally tightening formal bounds on it. We further provide a case study on classifying handwritten digits to illustrate the …
Ur-302 Using Quantum Computing To Determine The Optimal Path On Cascading Graphs,
2022
Kennesaw State University
Ur-302 Using Quantum Computing To Determine The Optimal Path On Cascading Graphs, Michael B. Swann, Ethan K. Hunt
C-Day Computing Showcase
Quantum computing has completely changed the computing paradigm. These special computers leverage the unique properties of quantum mechanics to solve problems that a classical computer cannot solve in polynomial time. Quantum mechanics such as superposition and entanglement are used to boost computational power exponentially in many problems . Many traditionally NP-complete problems, such as breaking the encryption of public-private key systems, are solvable with quantum computing in polynomial time. In this project, we will review quantum computing basics using real quantum computers and build on those basics to solve a subset of a graph optimization problems using both existing and …
Obstacles In Learning Algorithm Run-Time Complexity Analysis,
2022
University of Nebraska at Omaha
Obstacles In Learning Algorithm Run-Time Complexity Analysis, Bailey Licht
Theses/Capstones/Creative Projects
Algorithm run-time complexity analysis is an important topic in data structures and algorithms courses, but it is also a topic that many students struggle with. Commonly cited difficulties include the necessary mathematical background knowledge, the abstract nature of the topic, and the presentation style of the material. Analyzing the subject of algorithm analysis using multiple learning theories shows that course materials often leave out key steps in the learning process and neglect certain learning styles. Students can be more successful at learning algorithm run-time complexity analysis if these missing stages and learning styles are addressed.
An Ai-Based Framework For Studying Visual Diversity Of Urban Neighborhoods And Its Relationship With Socio-Demographic Variables,
2022
West Chester University of Pennsylvania
An Ai-Based Framework For Studying Visual Diversity Of Urban Neighborhoods And Its Relationship With Socio-Demographic Variables, Md Amiruzzaman, Ye Zhao, Stefanie Amiruzzaman, Aryn C. Karpinski, Tsung Heng Wu
Computer Science Faculty Publications
This study presents a framework to study quantitatively geographical visual diversities of urban neighborhood from a large collection of street-view images using an Artificial Intelligence (AI)-based image segmentation technique. A variety of diversity indices are computed from the extracted visual semantics. They are utilized to discover the relationships between urban visual appearance and socio-demographic variables. This study also validates the reliability of the method with human evaluators. The methodology and results obtained from this study can potentially be used to study urban features, locate houses, establish services, and better operate municipalities.
Predicting Publication Of Clinical Trials Using Structured And Unstructured Data: Model Development And Validation Study,
2022
The University of Melbourne
Predicting Publication Of Clinical Trials Using Structured And Unstructured Data: Model Development And Validation Study, Siyang Wang, Simon Šuster, Timothy Baldwin, Karin Verspoor
Natural Language Processing Faculty Publications
Background: Publication of registered clinical trials is a critical step in the timely dissemination of trial findings. However, a significant proportion of completed clinical trials are never published, motivating the need to analyze the factors behind success or failure to publish. This could inform study design, help regulatory decision-making, and improve resource allocation. It could also enhance our understanding of bias in the publication of trials and publication trends based on the research direction or strength of the findings. Although the publication of clinical trials has been addressed in several descriptive studies at an aggregate level, there is a lack …
