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2022

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Using Materialized Views For Answering Graph Pattern Queries, Michael Lan Dec 2022

Using Materialized Views For Answering Graph Pattern Queries, Michael Lan

Dissertations

Discovering patterns in graphs by evaluating graph pattern queries involving direct (edge-to-edge mapping) and reachability (edge-to-path mapping) relationships under homomorphisms on data graphs has been extensively studied. Previous studies have aimed to reduce the evaluation time of graph pattern queries due to the potentially numerous matches on large data graphs.

In this work, the concept of the summary graph is developed to improve the evaluation of tree pattern queries and graph pattern queries. The summary graph first filters out candidate matches which violate certain reachability constraints, and then finds local matches of query edges. This reduces redundancy in the representation …


Android Security: Analysis And Applications, Raina Samuel Dec 2022

Android Security: Analysis And Applications, Raina Samuel

Dissertations

The Android mobile system is home to millions of apps that offer a wide range of functionalities. Users rely on Android apps in various facets of daily life, including critical, e.g., medical, settings. Generally, users trust that apps perform their stated purpose safely and accurately. However, despite the platform’s efforts to maintain a safe environment, apps routinely manage to evade scrutiny. This dissertation analyzes Android app behavior and has revealed several weakness: lapses in device authentication schemes, deceptive practices such as apps covering their traces, as well as behavioral and descriptive inaccuracies in medical apps. Examining a large corpus of …


Machine Learning-Based Data Analytics For Understanding Space Weather And Climate, Yasser Abduallah Dec 2022

Machine Learning-Based Data Analytics For Understanding Space Weather And Climate, Yasser Abduallah

Dissertations

This dissertation addresses multiple crucial problems in space weather and climate, presenting new machine learning-based data analytics algorithms and models for tackling the problems.

First, the dissertation presents two new approaches to predicting solar flares. One approach, called DeepSun, predicts solar flares by utilizing a machine-learning-as-a-service (MLaaS) platform. The DeepSun system provides a friendly interface for Web users and an application programming interface (API) for remote programming users. It adopts an ensemble learning method that employs several machine learning algorithms to perform multiclass flare prediction. The other approach, named SolarFlareNet, forecasts the occurrence of solar flares within the next 24 …


A Neural Analysis-Synthesis Approach To Learning Procedural Audio Models, Danzel Serrano Dec 2022

A Neural Analysis-Synthesis Approach To Learning Procedural Audio Models, Danzel Serrano

Theses

The effective sound design of environmental sounds is crucial to demonstrating an immersive experience. Classical Procedural Audio (PA) models have been developed to give the sound designer a fast way to synthesize a specific class of environmental sounds in a physically accurate and computationally efficient manner. These models are controllable due to the choice of parameters from analyzing a class of sound. However, the resulting synthesis lacks the fidelity for the preferred immersive experience; thus, the sound designer would rather search through an extensive database for real recordings of a target sound class. This thesis proposes the Procedural audio Variational …


Design Framework Of Uav-Based Environment Sensing, Localization, And Imaging System, Yue Sun Dec 2022

Design Framework Of Uav-Based Environment Sensing, Localization, And Imaging System, Yue Sun

Graduate Doctoral Dissertations

In this dissertation research, we develop a framework for designing an Unmanned Aerial Vehicle or UAV-based environment sensing, localization, and imaging system for challenging environments with no GPS signals and low visibility. The UAV system relies on the various sensors that it carries to conduct accurate sensing and localization of the objects in an environment, and further to reconstruct the 3D shapes of those objects. The system can be very useful when exploring an unknown or dangerous environment, e.g., a disaster site, which is not convenient or not accessible for humans. In addition, the system can be used for monitoring …


Methods For Drone Trajectory Analysis Of Bottlenose Dolphins (Tursiops Truncatus), Jillian D. Bliss Dec 2022

Methods For Drone Trajectory Analysis Of Bottlenose Dolphins (Tursiops Truncatus), Jillian D. Bliss

Theses and Dissertations

With the increase in the use of UAS (Unmanned Aerial Systems) for marine mammal research, there is a need for the development of methods of analysis to transform UAS high resolution video into quantitative data. This study sought to develop a preliminary method of analysis that would quantify and present a way to visualize the dynamics and relative spatial distribution and changes in distribution of bottlenose dolphins (Tursiops truncatus) in the waters of Turneffe Atoll, Belize. This approach employs a previously developed video tracking program ‘Keypoint Tracking’ that enables manual tracking of individual dolphins and the creation of …


Towards Parking Lot Occupancy Assessment Using Aerial Imagery And Computer Vision, John Jewell Dec 2022

Towards Parking Lot Occupancy Assessment Using Aerial Imagery And Computer Vision, John Jewell

Electronic Thesis and Dissertation Repository

Advances in Computer Vision and Aerial Imaging have enabled countless downstream applications. To this end, aerial imagery could be leveraged to analyze the usage of parking lots. This would enable retail centres to allocate space better and eliminate the parking oversupply problem. With this use case in mind, the proposed research introduces a novel framework for parking lot occupancy assessments. The framework consists of a pipeline of components that map a sequence of image sets spanning a parking lot at different time intervals to a parking lot turnover heatmap that encodes the frequency each parking stall was used. The pipeline …


Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn Dec 2022

Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn

Culminating Experience Projects

This project applied software specification gathering, architecture, work planning, and development to a real-world development effort for a local business. This project began with a feasibility meeting with the owner of Zeal Aerial Fitness. After feasibility was assessed the intended users, needed functionality, and expected user restrictions were identified with the stakeholders. A hybrid software lifecycle was selected to allow a focus on base functionality up front followed by an iterative development of expectations of the stakeholders. I was able to create various specification diagrams that express the end projects goals to both developers and non-tech individuals using a standard …


Folk Theories, Recommender Systems, And Human-Centered Explainable Artificial Intelligence (Hcxai), Michael Ridley Dec 2022

Folk Theories, Recommender Systems, And Human-Centered Explainable Artificial Intelligence (Hcxai), Michael Ridley

Electronic Thesis and Dissertation Repository

This study uses folk theories to enhance human-centered “explainable AI” (HCXAI). The complexity and opacity of machine learning has compelled the need for explainability. Consumer services like Amazon, Facebook, TikTok, and Spotify have resulted in machine learning becoming ubiquitous in the everyday lives of the non-expert, lay public. The following research questions inform this study: What are the folk theories of users that explain how a recommender system works? Is there a relationship between the folk theories of users and the principles of HCXAI that would facilitate the development of more transparent and explainable recommender systems? Using the Spotify music …


Advances In The Automatic Detection Of Optimization Opportunities In Computer Programs, Delaram Talaashrafi Dec 2022

Advances In The Automatic Detection Of Optimization Opportunities In Computer Programs, Delaram Talaashrafi

Electronic Thesis and Dissertation Repository

Massively parallel and heterogeneous systems together with their APIs have been used for various applications. To achieve high-performance software, the programmer should develop optimized algorithms to maximize the system’s resource utilization. However, designing such algorithms is challenging and time-consuming. Therefore, optimizing compilers are developed to take part in the programmer’s optimization burden. Developing effective optimizing compilers is an active area of research. Specifically, because loop nests are usually the hot spots in a program, their optimization has been the main subject of many optimization algorithms. This thesis aims to improve the scope and applicability of performance optimization algorithms used in …


Interpretable Network Representations, Shengmin Jin Dec 2022

Interpretable Network Representations, Shengmin Jin

Dissertations - ALL

Networks (or interchangeably graphs) have been ubiquitous across the globe and within science and engineering: social networks, collaboration networks, protein-protein interaction networks, infrastructure networks, among many others. Machine learning on graphs, especially network representation learning, has shown remarkable performance in network-based applications, such as node/graph classification, graph clustering, and link prediction. Like performance, it is equally crucial for individuals to understand the behavior of machine learning models and be able to explain how these models arrive at a certain decision. Such needs have motivated many studies on interpretability in machine learning. For example, for social network analysis, we may need …


Big Data Analytics Of Medical Data, Ashwin Rajasankar Dec 2022

Big Data Analytics Of Medical Data, Ashwin Rajasankar

Culminating Experience Projects

Data has become a huge part of modern decision making. With the improvements in computing performance and storage in the past two decades, storing large amounts of data has become much easier. Analyzing large amounts of data and creating data models with them can help organizations obtain insights and information which helps their decision making. Big data analytics has become an integral part of many fields such as retail, real estate, education, and medicine. In the project, the goal is to understand the working of Apache Spark and its different storage methods and create a data warehouse to analyze data. …


Exploring Coral Reefs With Interactive Geospatial Visualizations, David Nicolas Tonning Dec 2022

Exploring Coral Reefs With Interactive Geospatial Visualizations, David Nicolas Tonning

Culminating Experience Projects

This project uses geospatial data to generate custom polygons in an interactive setting to represent the size and location of coral reefs to extract insights from coral reef-centered data sets. Historically, the data used by the Reef Restoration Group Bonaire exists in disparate sources, making it difficult to track and analyze the outcomes of their restoration work. Additionally, this information is not available in a digestible format for other audiences who would be interested in this data, such as citizen scientists seeking coral reef health statistics, the general public wanting to better understand the coral reefs surrounding Bonaire or recreational …


Travel Dashboard, Naveen Kumar Lalam Dec 2022

Travel Dashboard, Naveen Kumar Lalam

Culminating Experience Projects

Travel Dashboard is a one stop solution for all the travel needs of travelers and tourists visiting a new place. In today’s world travel has become a part of everyone’s life and we love to travel whenever there is a holiday or long a weekend. Earlier, the travel industry was mostly dictated by tour operators who used to plan and organize tours with standard itinerary, while tourists had very limited choices and needed to pick one of the itineraries given by operator as there was no other option left for them. Time have changed now as travelers love to plan …


Low-Resource Machine Learning Techniques For The Analysis Of Online Social Media Textual Data, Toktam Amanzadeh Oghaz Dec 2022

Low-Resource Machine Learning Techniques For The Analysis Of Online Social Media Textual Data, Toktam Amanzadeh Oghaz

Electronic Theses and Dissertations, 2020-

Low-resource and label-efficient machine learning methods can be described as the family of statistical and machine learning techniques that can achieve high performance without needing a substantial amount of labeled data. These methods include both unsupervised learning techniques, such as LDA, and supervised methods, such as active learning, each providing different benefits. Thus, this dissertation is devoted to the design and analysis of unsupervised and supervised techniques to provide solutions for the following problems: Unsupervised narrative summary extraction for social media content, Social media text classification with Active Learning (AL), Investigating restrictions and benefits of using Curriculum Learning (CL) for …


Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn Dec 2022

Hybrid Life Cycles In Software Development, Eric Vincent Schoenborn

Culminating Experience Projects

This project applied software specification gathering, architecture, work planning, and development to a real-world development effort for a local business. This project began with a feasibility meeting with the owner of Zeal Aerial Fitness. After feasibility was assessed the intended users, needed functionality, and expected user restrictions were identified with the stakeholders. A hybrid software lifecycle was selected to allow a focus on base functionality up front followed by an iterative development of expectations of the stakeholders. I was able to create various specification diagrams that express the end projects goals to both developers and non-tech individuals using a standard …


Building A Deep Model For Multi-Class Coral Species Discrimination, Hyeong Gyu Jang Dec 2022

Building A Deep Model For Multi-Class Coral Species Discrimination, Hyeong Gyu Jang

Culminating Experience Projects

The goal of this qualitative research project is to develop and optimize a multi-class discrimination model to identify different species of coral based on their digital images. Currently, there are artificial intelligence (AI) models that can distinguish between coral and other undersea objects such as sand or rocks, but to our knowledge the problem of multi-species classification has not yet been addressed. Given that coral reefs are a good indicator of overall ocean health, it is important to develop models that can classify the presence of different species in underwater images as a way to monitor the effects of climate …


Covid-19 Prediction Using Machine Learning, Parashuram Singaraveni Dec 2022

Covid-19 Prediction Using Machine Learning, Parashuram Singaraveni

Culminating Experience Projects

All around the globe, humankind faces a disastrous situation that witnessed COVID-19 outbreak. The COVID-19 pandemic caused severe loss of human life across the world. Most of the countries had been socially and economically weakened. The health sector faced lots of challenges in diagnosing the COVID patients, vaccinating the people, identifying the people who are infected by the virus. At the earlier stage, it has been difficult to identify the symptoms in infected person that is caused by the virus. Months later, symptoms were identified and, disease detecting machines were invented. But still, time taking for the results from the …


College Job Portal, Harikrishna Gonuguntla Dec 2022

College Job Portal, Harikrishna Gonuguntla

Culminating Experience Projects

Through this project, I am producing a portal called "College Job Portal" that will make life easier for students, colleges, and the companies who hire the students by handling the hiring process. On-campus job placements are a crucial component in contemporary educational institutions. By entering information about their educational history, grades, technological abilities, and CV, students would register with the portal. Like students, companies would sign up with the site by supplying basic details like their address and contact information for human resources. The college would be the portal's administrator. Companies can advertise job openings using this site by including …


Notebooks Web Application, Vivekananda Marellali Dec 2022

Notebooks Web Application, Vivekananda Marellali

Culminating Experience Projects

In our day-to-day activities we often need to make quick short notes related to our work, study, or other activities. Later, those notes should be easy to access, modify, delete, share with others, or create PDF documents as and when required. It is ideal if the note content is rich text format such as HTML, as it provides many text formatting options and provide better view and readability. The Notes are better organized if they are grouped into notebooks where each notebook consists of related topic note pages and multiple users can create such notebooks and share with other users …


Full-Text Search Using Elasticsearch, Akash Shrestha Dec 2022

Full-Text Search Using Elasticsearch, Akash Shrestha

Culminating Experience Projects

Search engines have changed the way we use the internet. They can search or filter out relevant and valuable content of interest to the users. But many of the applications we use today lack search or are just poor. So how can we leverage the same power of search engines in our applications? This project aims to look at “Full-Text Search” which allows us to do a text-based search in text-intensive data. The search will be performed by matching any, or all words of the query exactly or with some relevancy against the indexes created by the searching tool. The …


Muse: A Genetic Algorithm For Musical Chord Progression Generation, Griffin Going Dec 2022

Muse: A Genetic Algorithm For Musical Chord Progression Generation, Griffin Going

Culminating Experience Projects

Foundational to our understanding and enjoyment of music is the intersection of harmony and movement. This intersection manifests as chord progressions which themselves underscore the rhythm and melody of a piece. In musical compositions, these progressions often follow a set of rules and patterns which are themselves frequently broken for the sake of novelty. In this work, we developed a genetic algorithm which learns these rules and patterns (and how to break them) from a dataset of 890 songs from various periods of the Billboard Top 100 rankings. The algorithm learned to generate increasingly valid, yet interesting chord progressions via …


Devops: Course Development, James Lee Vanderzouwen Dec 2022

Devops: Course Development, James Lee Vanderzouwen

Culminating Experience Projects

DevOps has become somewhat of a buzzword amongst software engineers in the industry. Often developers do not have a dedicated DevOps engineer let alone a DevOps team. Developers benefit when they know what happens between ‘works on my machine’ and production. Making sure those steps make sense and are safe benefits the operations team. From compliance to code review to regression testing, understanding the full SDLC, employing DevOps concepts, and minimizing overhead from dependencies is quickly becoming a pre-requisite for the modern software engineer. This project attempts to bridge the gap between buzzword and best practice by developing a college-level …


Malware Detection And Analysis, Namratha Suraneni Dec 2022

Malware Detection And Analysis, Namratha Suraneni

Culminating Experience Projects

Malicious software poses a serious threat to the cybersecurity of network infrastructures and is a global pandemic in the form of computer viruses, Trojan horses, and Internet worms. Studies imply that the effects of malware are deteriorating. The main defense against malware is malware detectors. The methods that such a detector employ define its level of quality. Therefore, it is crucial that we research malware detection methods and comprehend their advantages and disadvantages. Attackers are creating malware that is polymorphic and metamorphic and has the capacity to modify their source code as they spread. Furthermore, existing defenses, which often utilize …


Curriculum Development In Technical Education For Boys And Girls Club, Damanpreet Singh Dec 2022

Curriculum Development In Technical Education For Boys And Girls Club, Damanpreet Singh

Culminating Experience Projects

Technical education has been and will continue to be more and more important to succeed in the future. The Boys and Girls Club, founded in 1860, is a national organization of local chapters which provide voluntary after-school programs for young individuals. The Boys and Girls Club have life-changing programs that prepare the young individuals in the club for their future whether it’s for college, career, or life. The perfect way to prepare best prepare these kids for the future is to develop their technical education. Unfortunately, the boys and girls club of Muskegon has a lack of educational resources for …


Docker Container Image – Vulnerability Scanning, Joseph U. Ohaeche Dec 2022

Docker Container Image – Vulnerability Scanning, Joseph U. Ohaeche

Culminating Experience Projects

The technology landscape for container adoption has greatly evolved over the years from the first known Unix U7 container concept introduced in 1979 to the most utilized docker container concept which emerged in 2013. Docker container image is essentially a lightweight, standalone executable software package with capabilities to run an application. It is important to know that container images become containers when deployed, and simultaneously docker container images become docker containers when deployed on Docker Engine. This project paper aims, evaluates, and presents a methodology useful in vulnerability scanning of docker container images and suggests possible fixes based on OWASP …


Cloud Container Security’ Next Move, Vishakha Sadhwani Dec 2022

Cloud Container Security’ Next Move, Vishakha Sadhwani

Dissertations and Theses

In the last few years, it is apparent to cybersecurity experts everywhere that the proverbial container tech genie is out of the bottle, and has been widely embraced across multiple organizations. To achieve the flexibility of building and deploying applications anywhere and everywhere, cloud native environments have gained great momentum and made the development lifecycle simpler than ever. However, container environments brings with them a range of cybersecurity issues that includes images, containers, hosts, runtimes, registries, and orchestration platforms, which needs the necessity to focus on investing in securing your container stack.

According to this report[1], released by cloud-native …


Algorithmic Improvements In Deep Reinforcement Learning, Norman L. Tasfi Dec 2022

Algorithmic Improvements In Deep Reinforcement Learning, Norman L. Tasfi

Electronic Thesis and Dissertation Repository

Reinforcement Learning (RL) has seen exponential performance improvements over the past decade, achieving super-human performance across many domains. Deep Reinforcement Learning (DRL), the combination of RL methods with deep neural networks (DNN) as function approximators, has unlocked much of this progress. The path to generalized artificial intelligence (GAI) will depend on deep learning (DL) and RL. However, much work is required before the technology reaches anything resembling GAI. Therefore, this thesis focuses on a subset of areas within RL that require additional research to advance the field, specifically: sample efficiency, planning, and task transfer. The first area, sample efficiency, refers …


Fairness And Privacy In Machine Learning Algorithms, Neha Bhargava Dec 2022

Fairness And Privacy In Machine Learning Algorithms, Neha Bhargava

Master of Science in Computer Science Theses

Roughly 2.5 quintillion bytes of data is generated daily in this digital era. Manual processing of such huge amounts of data to extract useful information is nearly impossible but with the widespread use of machine learning algorithms and their ability to process enormous data in a fast, cost-effective, and scalable way has proven to be a preferred choice to glean useful insights and solve business problems in many domains. With this widespread use of machine learning algorithms there has always been concerns about the ethical issues that may arise from the use of this modern technology. While achieving high accuracies, …


Lawrence County Archives Website, Brianna Hawkins, Areeb Mohammed, David Niederweis, Mary-Kate Rynders Dec 2022

Lawrence County Archives Website, Brianna Hawkins, Areeb Mohammed, David Niederweis, Mary-Kate Rynders

Honors Capstone Projects and Theses

No abstract provided.