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2022

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Articles 511 - 540 of 18298

Full-Text Articles in Physical Sciences and Mathematics

Gc-244 Msit Capstone Project Fall 2022, Megen Cochran, Skylar Story, Tatiana Brown, Simisola Babatunde Dec 2022

Gc-244 Msit Capstone Project Fall 2022, Megen Cochran, Skylar Story, Tatiana Brown, Simisola Babatunde

C-Day Computing Showcase

Computer network system administrators need to inspect and analyze network traffic and detect malicious communications, monitor system performance, and provide operational services. However, identifying threats contained within encrypted network traffic, which has become increasingly prevalent, poses a unique set of challenges. It is imperative to monitor this traffic or threats and malware but do so in a way that maintains privacy. This project aims to develop a machine learning-based system that can accurately detect malware communication in this setting.

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Gc-258 Heart Disease Prediction Using Machine Learning, Devin Jackson, Richard Stupka, Trinadh Chigurupati, Demontae Moore Dec 2022

Gc-258 Heart Disease Prediction Using Machine Learning, Devin Jackson, Richard Stupka, Trinadh Chigurupati, Demontae Moore

C-Day Computing Showcase

Research has shown that the early detection of Heart Disease is critical to treating and understanding the causes. Through the use of advanced machine learning models and com- prehensive data sets collected on patients of varying backgrounds and health statuses, this research shows the listed correlations between attributes of data points and positive identification of the disease. This research uses 1026 unique records and 14 attributes including the classifier of Heart Disease. These attributes range from simple (cholesterol level) to more complex and subjective (chest pain type) but each attribute presents an opportunity to improve each of the analyzed models …

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Gc-308 Heart Disease Prediction And Analysis By Machine Learning, Venkata Sabarinath Nekkalapu, Venkata Anusha Yammada, Mrinal Kapoor, Sai Sindhu Ponugoti, Suman Pudota Dec 2022

Gc-308 Heart Disease Prediction And Analysis By Machine Learning, Venkata Sabarinath Nekkalapu, Venkata Anusha Yammada, Mrinal Kapoor, Sai Sindhu Ponugoti, Suman Pudota

C-Day Computing Showcase

The heart is the most crucial part of the Human body. The organ circulates blood out of the circulatory system’s blood vessels. Any disease or failure of this organ causes death. Heart disease is one of the primary sources of death in the cutting-edge world. There are 2,380 deaths from heart disease each day, based on 2018 data. Also, heart disease causes the highest number of deaths globally, with approximately 18 million people dying yearly, meaning around 31This prediction can be made using Machine Learning techniques. With machine learning. Combining a prediction model with machine learning correctly classified results for …

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Gr-241 On Training Explainable Neurons, Lance Kennedy Dec 2022

Gr-241 On Training Explainable Neurons, Lance Kennedy

C-Day Computing Showcase

Neural networks have become increasingly powerful and commonplace tools for guiding decision-making. However, due to the black-box nature of many of these networks, it is often difficult to understand exactly what guides them to a certain prediction, making them dangerous to use for sensitive decision making, and making it difficult to ensure confidence in their output. For instance, a network which classifies images of dogs and cats may turn out to be flawed with little consequence, but a neural network that diagnoses the presence of diseases should be assured to make sound predictions. By understanding why a network makes the …

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Gr-283 Chatbot, Vamsi Krishna Dhulipalla Dec 2022

Gr-283 Chatbot, Vamsi Krishna Dhulipalla

C-Day Computing Showcase

Mental health issue are the most common issue facing in human society. These issues are mostly in impact negatively on working peoples, on the individual, his/her family, workplace, community, and the economy. Our project is based on mental health chat bot of natural language processing with deep learning models .We have a structure data set of Mental Health. In the data set we have nine columns. We use neural networks to create our models .We use another method call scratch in which we create a model by our self and use it so our project we create a layer with …

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Gr-288 Comparative Performance Analysis Of Hybrid Quantum Machine Learning Algorithm To Assess Post Stroke Rehabilitation Exercises, Manohar Murikipudi, Abm. Adnan Azmee Dec 2022

Gr-288 Comparative Performance Analysis Of Hybrid Quantum Machine Learning Algorithm To Assess Post Stroke Rehabilitation Exercises, Manohar Murikipudi, Abm. Adnan Azmee

C-Day Computing Showcase

Due to the advancements in technology, data is growing exponentially. With this increased dataset size, the computation to process the generated information is rising sequentially. And the currently available classical computational tools and learning algorithms will not work due to the limitations of Moore's law. To overcome the computational issues, we have to switch to Quantum Computing which works based on the laws of Quantum Mechanics. Quantum Machine Learning (QML), a subset of Quantum Computing, is faster and more capable of doing complex calculations that a classical computer can't. Classical Computers work on bits - 0 or 1, whereas a …

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Gr-307 Eeg Classification Using Neural Network – An Application Of Machine Learning In Classification Of Attention Deficiency, To Measure The Effect Of Chakramarmakosha Meditation-Ii, Sreekanth Gopi Dec 2022

Gr-307 Eeg Classification Using Neural Network – An Application Of Machine Learning In Classification Of Attention Deficiency, To Measure The Effect Of Chakramarmakosha Meditation-Ii, Sreekanth Gopi

C-Day Computing Showcase

Stress reduces attention span and is a common problem that impacts students’ academic performance as well as their self-efficacy in handling challenging situations. Meditation techniques have been proven to help manage stress levels. In the previous research, the author used Heart Coherence as the metric to show the impact of ChakraMarmaKosha Meditation (CM), a meditation on human energy centers, on reducing the stress level. In this research we apply a new version of CM which is CM-II as a guided psychotherapy and cognitive therapy meditation, to analyze its impact on reducing attention deficiency among students. This study uses Electroencephalography (EEG) …

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Uc-296 Cybersecurity Park, Neil E. Weingarten, Jadante Hendrick, Kylie Nowokunski, Tyler Crawford Dec 2022

Uc-296 Cybersecurity Park, Neil E. Weingarten, Jadante Hendrick, Kylie Nowokunski, Tyler Crawford

C-Day Computing Showcase

Cybersecurity Park is an educational VR game intended for middle-school-age children that aims to demonstrate a wide range of cybersecurity concepts to the players. Such concepts include hacking ethics and types of hackers, cryptography, Trojan Horse / ransomware viruses, and authentication and authorization. These concepts are split into various mini-games that the player can freely navigate to from the hub they spawn in. For example, in the mini-game showcasing the Trojan Horse concept, players play as a knight defending a castle from evildoers. Visitors will approach the castle and ask access into the castle, and, based on the actions by …

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Ur-285 Operation Enduring Freedom: Improving Mission Effectiveness By Identifying Trends In Successful Terrorism, Dalton A. Shaver Dec 2022

Ur-285 Operation Enduring Freedom: Improving Mission Effectiveness By Identifying Trends In Successful Terrorism, Dalton A. Shaver

C-Day Computing Showcase

This research examines how the characteristics of terrorist attacks predict the chance of an attack succeeding, where an attack is defined as successful if the intended attack type is carried out. Data was analyzed across three geographical missions within Operation Enduring Freedom: Trans-Sahara, Horn of Africa, and the Philippines. Using predicted probabilities of success obtained from logistic regression models, the medians were plotted to compare the characteristics of terrorist attacks across missions. By determining the specific features of attacks that produce the highest probabilities of success, the effectiveness of Operation Enduring Freedom can be improved by focusing counter-terrorism training and …

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Gr-252 Solving Multiple Traveling Salesman Problem Using K Means Clustering And Mixed Integer Programming - An Integrated Approach, Navneet Verma Dec 2022

Gr-252 Solving Multiple Traveling Salesman Problem Using K Means Clustering And Mixed Integer Programming - An Integrated Approach, Navneet Verma

C-Day Computing Showcase

In this research paper, we explore an efficient algorithm for multiple Traveling Salesman Problem (m-TSP) using an approach which combines K Means clustering algorithm and Mixed Integer Programming (MIP). The Traveling Salesman problem is an NP hard problem which relates to generation of minimum cost round trip tours for multiple salesmen visiting several cities in their territory. Our novel approach has the promise of reaching closer to the optimal solution as compared to heuristics-based approaches such as genetic algorithms.

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Uc-246 Spudify, Nathanial R. Bintliff, Jimmy V. Nguyen, Tyler Holmes, Alex M. Tawara, Addison Christian Dec 2022

Uc-246 Spudify, Nathanial R. Bintliff, Jimmy V. Nguyen, Tyler Holmes, Alex M. Tawara, Addison Christian

C-Day Computing Showcase

Spotify’s yearly wrapped report is extremely popular amongst its users. Unfortunately users must wait a year from every report to view statistics about their listening habits. Our app will allow users to generate reports displaying their top songs and artists whenever they want. Additionally, our app will allow users to generate recommendations for new music based on their favorite songs/artists. Users will also be able to generate advanced recommendations by inputting custom artists/genres/songs and customizing a variety of parameters such as the recommended song’s tempo, loudness, and danceability. Our app will give Spotify users the freedom to view statistics regarding …

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Uc-257 Gtri: Analysis Of Alternatives, Jake D. Pham, Zayda Huballah, Evans Jones, Roshni Modi, Salimata Bado Dec 2022

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 …

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Uc-261 Grocery Application, Quin’Dariu A. Lyles-Woods, Adam Maksymczuk, Aidan Le-Beard, Jeetu Sharma, Danny Sor Dec 2022

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 …

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Uc-272 Defunct To Funct: Expanding The Functionality Of Forgotten Robots, Thomas E. Stockdale, Khoa Ho, Johnny Huynh, Marcel Youri Nguiagaing Seuga Dec 2022

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 …

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Ur-295 Data Collection In Parkinson's Vr, Neil E. Weingarten, Ian Mcconnell Dec 2022

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.

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Gc-250 Object Detection And Tracking: Deep Learning-Based Framework With Euclidean Distance, Iou, And Hungarian Algorithm, Md Jobair Hossain Faruk Dec 2022

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 …

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Gr-273 Building A Chatbot, Varun Gottam, Sathwik Chepyala, Sai Mohit Saimpu, Venkata Sai Krishna Yalavarthi, Nikhil Sai Buddiga Dec 2022

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.

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Gr-287 Natural Disaster Prediction, Sravya Sabbu, Aishwarya Turlapati, Suryapraveen Adivi Dec 2022

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 …

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Gr-300 Azure Security Kql Query Builder, Navyapravalika Sabbula, Jeevana Kalipindi Dec 2022

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 …

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Gr-306 Improving Wildfire Propagation Simulations Using Cellular Automata To Help Emergency Management, Madeline Frank, Lokesh Meesala, Yagnasree Bollineni, Amrutha Venkatesh, Mujahid Shaheed Shaik Dec 2022

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 …

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Uc-266 Indy-5 Compchores, Myers Berry, Ian Snyder Dec 2022

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 …

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Uc-274 Restful Robots, Jack I. Young, Derek M. Comella, Sarah Thomas, Andrew Loveless Dec 2022

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 …

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Ur-269 Towards Bounding The Behavior Of Deep Neural Networks, Richard Borowski Dec 2022

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 …

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Ur-302 Using Quantum Computing To Determine The Optimal Path On Cascading Graphs, Michael B. Swann, Ethan K. Hunt Dec 2022

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 …

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On The Spatial Modelling Of Biological Invasions, Tedi Ramaj Dec 2022

On The Spatial Modelling Of Biological Invasions, Tedi Ramaj

Electronic Thesis and Dissertation Repository

We investigate problems of biological spatial invasion through the use of spatial modelling. We begin by examining the spread of an invasive weed plant species through a forest by developing a system of partial differential equations (PDEs) involving an invasive weed and a competing native plant species. We find that extinction of the native plant species may be achieved by increasing the carrying capacity of the forest as well as the competition coefficient between the species. We also find that the boundary conditions exert long-term control on the biomass of the invasive weed and hence should be considered when implementing …

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The North Platte River Valley: The Intersectionality Between Water Quality And People, Anni Poetzl Dec 2022

The North Platte River Valley: The Intersectionality Between Water Quality And People, Anni Poetzl

School of Natural Resources: Dissertations, Theses, and Student Research

The North Platte River (NPR) Valley of western Nebraska is a semi-arid watershed with row crop production, livestock production, and urban land use activity and has a population of diverse stakeholders. These land use activities contribute to the enrichment of surface waters, such as streams, which can affect human and ecosystem health, as well as economic development and recreational activities. The project objectives are to: (1) quantify the movement of dissolved inorganic nutrients from the land within the NPR Valley to the NPR via tributaries and canals, (2) identify spatiotemporal variability of nutrient limitation of periphyton growth within the NPR, …

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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 Dec 2022

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.

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Predicting Publication Of Clinical Trials Using Structured And Unstructured Data: Model Development And Validation Study, Siyang Wang, Simon Šuster, Timothy Baldwin, Karin Verspoor Dec 2022

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 …

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Core-Collapse Supernova Simulations With Spectral Two-Moment Neutrino Transport, Ran Chu Dec 2022

Core-Collapse Supernova Simulations With Spectral Two-Moment Neutrino Transport, Ran Chu

Doctoral Dissertations

The primary focus of this dissertation is to develop a next-generation, state-of-the-art neutrino kinetics capability that will be used in the context of the next-generation, state-of-the-art core-collapse supernova (CCSN) simulation frameworks \thornado\ and \FLASH.\index{CCSN} \thornado\ is a \textbf{t}oolkit for \textbf{h}igh-\textbf{or}der \textbf{n}eutrino-r\textbf{ad}iation hydr\textbf{o}dynamics, which is a collection of modules that can be incorporated into a simulation code/framework, such as \FLASH, together with a nuclear equation of state (EOS)\index{EOS} library, such as the \WeakLib\ EOS tables. The first part of this work extends the \WeakLib\ code to compute neutrino interaction rates from~\cite{Bruenn_1985} and produce corresponding opacity tables.\index{Bruenn 1985} The processes of emission, …

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Constrained Collective Movement In Human-Robot Teams, Joshua Fagan Dec 2022

Constrained Collective Movement In Human-Robot Teams, Joshua Fagan

Doctoral Dissertations

This research focuses on improving human-robot co-navigation for teams of robots and humans navigating together as a unit while accomplishing a desired task. Frequently, the team’s co-navigation is strongly influenced by a predefined Standard Operating Procedure (SOP), which acts as a high-level guide for where agents should go and what they should do. In this work, I introduce the concept of Constrained Collective Movement (CCM) of a team to describe how members of the team perform inter-team and intra-team navigation to execute a joint task while balancing environmental and application-specific constraints. This work advances robots’ abilities to participate along side …

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