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A Programmatic Geographic Information Systems Analysis Of Plant Hardiness Zones, Andrew Bowen May 2023

A Programmatic Geographic Information Systems Analysis Of Plant Hardiness Zones, Andrew Bowen

Electronic Theses and Dissertations

The Plant Hardiness Zone Map consists of thirteen geographical zones that describe whether a plant can survive based on average annual minimal temperatures. As climate change progresses, minimum temperatures in all regions are expected to change. This work programmatically evaluates predicted future climate projection data and converts it to United States Department of Agriculture-defined hardiness zones. Through the next 80 years, hardiness zones are projected to move poleward; in effect, colder zones will lose area and warmer zones will gain area globally. Some implications include changes in crop growing degree days, which could alter crop productivity, migration and settlement of …


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 …


Data Discovery Analysis On Complex Time Series Data, Peter Lawrence Severynen Dec 2022

Data Discovery Analysis On Complex Time Series Data, Peter Lawrence Severynen

Computer Science and Engineering Theses

Complex time series are a ubiquitous form of data in the modern world. They have wide application across many different fields of scientific inquiry and business endeavor. Time series are used to understand and forecast weather patterns, voting patterns, computer network traffic, population health outcomes, demographic changes, the results of scientific experiments, and the performance of stocks and mutual funds. But time series can be difficult to analyze by conventional methods when the data is multivariate, incomplete, or in different formats. To address these issues, an investigation of several multivariate time series datasets was performed using the methods of automatic …


Obstacles In Learning Algorithm Run-Time Complexity Analysis, Bailey Licht Dec 2022

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.


Evaluating Similarity Of Cross-Architecture Basic Blocks, Elijah L. Meyer Jan 2022

Evaluating Similarity Of Cross-Architecture Basic Blocks, Elijah L. Meyer

Browse all Theses and Dissertations

Vulnerabilities in source code can be compiled for multiple processor architectures and make their way into several different devices. Security researchers frequently have no way to obtain this source code to analyze for vulnerabilities. Therefore, the ability to effectively analyze binary code is essential. Similarity detection is one facet of binary code analysis. Because source code can be compiled for different architectures, the need can arise for detecting code similarity across architectures. This need is especially apparent when analyzing firmware from embedded computing environments such as Internet of Things devices, where the processor architecture is dependent on the product and …


Using Deep Learning For Children Brain Image Analysis, Rafael Toche Pizano May 2021

Using Deep Learning For Children Brain Image Analysis, Rafael Toche Pizano

Computer Science and Computer Engineering Undergraduate Honors Theses

Analyzing the correlation between brain volumetric/morphometry features and cognition/behavior in children is important in the field of pediatrics as identifying such relationships can help identify children who may be at risk for illnesses. Understanding these relationships can not only help identify children who may be at risk of illnesses, but it can also help evaluate strategies that promote brain development in children. Currently, one way to do this is to use traditional statistical methods such as a correlation analysis, but such an approach does not make it easy to generalize and predict how brain volumetric/morphometry will impact cognition/behavior. One of …


Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), Samantha O'Rourke May 2021

Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), Samantha O'Rourke

Theses/Capstones/Creative Projects

Within the United States Air Force, there are repeated patterns of differences observed during exercises. After an exercise is completed, forms are filled out detailing observations, successes, and recommendations seen throughout the exercise. At the most, no two reports are identical and must be analyzed by personnel and then categorized based on common themes observed. Developing a computer application will greatly reduce the time and resources used to analyze each After Action Report. This application can visually represent these observations and optimize the effectiveness of these exercises. The visualization is done through graphs displaying the frequency of observations and recommendations. …


Image Analysis Of Charged Bimodal Colloidal Systems In Microgravity., Adam J. Cecil May 2021

Image Analysis Of Charged Bimodal Colloidal Systems In Microgravity., Adam J. Cecil

Electronic Theses and Dissertations

Colloids are suspensions of two or more phases and have been topics of research for advanced, tunable materials for decades. Stabilization of colloids is typically attributed to thermodynamic mechanisms; however, recent studies have identified transport or entropic mechanisms that can potentially stabilize a thermodynamically unstable colloidal system. In this study, suspensions of silsesquioxane microparticles and zirconia nanoparticles were dispersed in a nitric acid solution and allowed to aggregate for 8-12 days in microgravity aboard the International Space Station. The suspensions were subsequently imaged periodically at 2.5x magnification. Due to the inadequacy of existing image analysis programs, the python package “Colloidspy” …


An Introduction To Federated Learning And Its Analysis, Manjari Ganapathy May 2021

An Introduction To Federated Learning And Its Analysis, Manjari Ganapathy

UNLV Theses, Dissertations, Professional Papers, and Capstones

With the onset of the digital era, data privacy is one of the most predominant issues. Decentralized learning is becoming popular as the data can remain within local entities by maintaining privacy. Federated Learning is a decentralized machine learning approach, where multiple clients collaboratively learn a model, without sharing raw data. There are many practical challenges in solving Federated Learning, which include communication set up, data heterogeneity and computational capacity of clients. In this thesis, I explore recent methods of Federated Learning with various settings, such as data distributions and data variability, used in several applications. In addition, I, specifically, …


Using Grids As Password Entry Devices, Karol Lejmbach Apr 2021

Using Grids As Password Entry Devices, Karol Lejmbach

Master's Theses (2009 -)

The classic text-based password has been around for a very long time. A lot of security research has been conducted on it. A set of best practices has been available for many years stressing the use of longer and more complex passwords. The issue with this approach is that humans have a hard time recalling long complex sequences of characters. Worse, the more complex the string of characters the more prone it is to being written down which is the most detrimental security threat. The goal of this paper is to introduce and provide an introductory analysis of a grid-based …


Big Data In Single Player Games, Mohammad Khaldoun Farhan Aldaboubi May 2020

Big Data In Single Player Games, Mohammad Khaldoun Farhan Aldaboubi

Computer Science and Engineering Theses

Improving video games can be exponentially more efficient by utilizing big data. Big data plays a big part in modern gaming, especially for multiplayer games like poker, first person shooter games. Utilizing the data gathered from video games can be used in ways that will improve the player experience massively and can be eye-opening to find issues, player pattern, and improve the game in ways that will be hard to pin point without gathering data of how the players are playing the game. However, while big data is being utilized in multiplayer games, it’s not utilized as much in single …


Detection Of Snps Associated With Bone Loss Rate By Using Machine Learning Approaches, Avinash Yaganapu May 2020

Detection Of Snps Associated With Bone Loss Rate By Using Machine Learning Approaches, Avinash Yaganapu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Osteoporosis is one of the most common diseases seen in postmenopausal women, it decreases the bone density and quality, and later causes bone loss. Generally, bone loss occurs when bone losses its content and become porous: a sponge like substance. In most Genome Wide Association Studies (GWAS), researchers perform experiments with genomic data that contains some millions of numbers of single nucleotide polymorphisms (SNPs) and checks their association with the trait or disease. In this thesis, we performed two separate analyses with 2207 (of bone loss and bone gain) and 645 (of bone loss) instances separately. For predicting the SNPs …


Extracting Information From Subroutines Using Static Analysis Semantics, Luke A. Burnett Jan 2020

Extracting Information From Subroutines Using Static Analysis Semantics, Luke A. Burnett

Browse all Theses and Dissertations

Understanding how a system component can interact with other services can take an immeasurable amount of time. Reverse engineering embedded and large systems can rely on understanding how components interact with one another. This process is time consuming and can sometimes be generalized through certain behavior.We will be explaining two such complicated systems and highlighting similarities between them. We will show that through static analysis you can capture compiler behavior and apply it to the understanding of a function, reducing the total time required to understand a component of whichever system you are learning.


Phylogenetic Reconstruction Analysis On Gene Order And Copy Number Variation, Ruofan Xia Oct 2019

Phylogenetic Reconstruction Analysis On Gene Order And Copy Number Variation, Ruofan Xia

Theses and Dissertations

Genome rearrangement is known as one of the main evolutionary mechanisms on the genomic level. Phylogenetic analysis based on rearrangement played a crucial role in biological research in the past decades, especially with the increasing avail- ability of fully sequenced genomes. In general, phylogenetic analysis aims to solve two problems: Small Parsimony Problem (SPP) and Big Parsimony Problem (BPP). Maximum parsimony is a popular approach for SPP and BPP which relies on itera- tively solving a NP-hard problem, the median problem. As a result, current median solvers and phylogenetic inference methods based on the median problem all face se- rious …


Krylov Subspace Spectral Methods With Non-Homogenous Boundary Conditions, Abbie Hendley Aug 2019

Krylov Subspace Spectral Methods With Non-Homogenous Boundary Conditions, Abbie Hendley

Master's Theses

For this thesis, Krylov Subspace Spectral (KSS) methods, developed by Dr. James Lambers, will be used to solve a one-dimensional, heat equation with non-homogenous boundary conditions. While current methods such as Finite Difference are able to carry out these computations efficiently, their accuracy and scalability can be improved. We will solve the heat equation in one-dimension with two cases to observe the behaviors of the errors using KSS methods. The first case will implement KSS methods with trigonometric initial conditions, then another case where the initial conditions are polynomial functions. We will also look at both the time-independent and time-dependent …


An Instruction Embedding Model For Binary Code Analysis, Kimberly Michelle Redmond Apr 2019

An Instruction Embedding Model For Binary Code Analysis, Kimberly Michelle Redmond

Theses and Dissertations

Binary code analysis is important for understanding programs without access to the original source code, which is common with proprietary software. Analyzing binaries can be challenging given their high variability: due to growth in tech manufactur- ers, source code is now frequently compiled for multiple instruction set architectures (ISAs); however, there is no formal dictionary that translates between their assem- bly languages. The difficulty of analysis is further compounded by different compiler optimizations and obfuscated malware signatures. Such minutiae means that some vulnerabilities may only be detectable on a fine-grained level. Recent strides in ma- chine learning—particularly in Natural Language …


An Instructional Designer Competency Framework For Complex Learning Designs, David Alan Schubert Jan 2019

An Instructional Designer Competency Framework For Complex Learning Designs, David Alan Schubert

CCE Theses and Dissertations

Learning design competency frameworks published by professional organizations, exist for typical instructional design efforts. However, a review of literature revealed a lack of frameworks available for the creation of complex learning designs (CLDs). The goal of this research was to develop a competency framework for the creation of CLDs. Quantitative and qualitative methods were employed in the four phases of the design and development research approach In phase one, a survey based on the Educational Technology Multimedia Competency Survey (ETMCS) was sent to instructional designers who self-reported as having experience creating CLDs. The purpose of phase one was to identify …


Microarray Data Analysis And Classification Of Cancers, Grant Gates Jan 2019

Microarray Data Analysis And Classification Of Cancers, Grant Gates

Williams Honors College, Honors Research Projects

When it comes to cancer, there is no standardized approach for identifying new cancer classes nor is there a standardized approach for assigning cancer tumors to existing classes. These two ideas are known as class discovery and class prediction. For a cancer patient to receive proper treatment, it is important that the type of cancer be accurately identified. For my Senior Honors Project, I would like to use this opportunity to research a topic in bioinformatics. Bioinformatics incorporates a few different subjects into one including biology, computer science and statistics. An intricate method for class discovery and class prediction is …


Health Monitoring Of Atlas Data Center Clusters And Failure Analysis, Meenakshi Balasubramanian Dec 2018

Health Monitoring Of Atlas Data Center Clusters And Failure Analysis, Meenakshi Balasubramanian

Computer Science and Engineering Theses

Monitoring the health of data center clusters is an integral part of any industrial facility. ATLAS is one of the High Energy Physics experiments at the Large Hadron Collider (LHC) at CERN. ATLAS DDM (Distributed Data Management) is a system that manages data transfer, staging, deletions and experimental data on the LHC grid. Currently, the DDM system relies on Rucio software, with Cloud based object storage and No-SQL solutions. It is a cumbersome process in the current system, to fetch and analyze the transfer, staging and deletion metrics of a specific site for any regional center. In this thesis, a …


Towards Automated Domain-Oriented Lexicon Construction And Dimension Reduction For Arabic Sentiment Analysis, Hasan A. Alshahrani Dec 2018

Towards Automated Domain-Oriented Lexicon Construction And Dimension Reduction For Arabic Sentiment Analysis, Hasan A. Alshahrani

Dissertations

Sentiment analysis is a type of text mining that uses Natural Language Processing (NLP) tools to identify and label opinionated text. There are two main approaches of sentiment analysis: lexicon-based, and statistical approach. In our research, we use the lexicon-based approach because the lexicon contains sentiment words and phrases which are the main linguistic units to express sentiments. More specifically, we work with domain-oriented lexicons as they are more efficient than general ones because the polarity is heavily driven by domains.

Arabic language has a degree of uniqueness that makes it hard to be processed with the available cross-language tools …


Techniques For Spatio-Temporal Analysis Of Trajectory Data, Praveen Kumar Tripathi Aug 2016

Techniques For Spatio-Temporal Analysis Of Trajectory Data, Praveen Kumar Tripathi

Computer Science and Engineering Dissertations

The goal of this thesis is to develop novel techniques for the analysis of spatio-temporal trajectory data. Recent advances in tracking devices such as Global Positioning System (GPS) and mobile phones have resulted in an abundance of spatio-temporal trajectory data. Because of the importance of both the space and time dimensions in trajectory data, different analysis techniques are needed. The analysis techniques explored in this thesis involve two variations: point based analysis and trajectory based analysis. Point based analysis has been done to identify the hot spots in the trajectory dataset (hurricane data). Here we consider the trajectory data as …


Analysis Of Artificial Neural Networks In The Diagnosing Of Breast Cancer Using Fine Needle Aspirates, Janette Vazquez Aug 2016

Analysis Of Artificial Neural Networks In The Diagnosing Of Breast Cancer Using Fine Needle Aspirates, Janette Vazquez

Theses and Dissertations

This thesis examines how Artificial Neural Networks can be used to classify a set of samples from a fine needle aspirate dataset. The dataset is composed of various different attributes, each of which are used to come to the conclusion as to whether a sample is benign or malignant. To automate the process of analyzing the various attributes and coming to a correct prediction, a neural network was implemented. First, a Feedforward Neural Network was trained with the dataset using a Backpropagation training method and an activation sigmoid function with one hidden layer in the architecture of the network. After …


Comparative Analysis: Successes And Failures Of St. Louis, Stephen Anane-Boakye Jan 2016

Comparative Analysis: Successes And Failures Of St. Louis, Stephen Anane-Boakye

Walden Dissertations and Doctoral Studies

The St. Louis School District (SLSD) provided its students with a virtual education program (VEP) but abandoned it following a cut in federal funding, omitting an alternative pathway for students to complete their education. The problem addressed in this study was the effect of technology and management's decision to discontinue the VEP. The purpose of this qualitative study was to determine management's role and the effect of the technology in discontinuing the VEP. Dewey's theory of education and Koskela and Howell's theory of management established the theoretical foundation for the study. A purposeful sampling selection approach was used to recruit …


Detecting Php-Based Cross-Site Scripting Vulnerabilities Using Static Program Analysis, Steven M. Kelbley Jan 2016

Detecting Php-Based Cross-Site Scripting Vulnerabilities Using Static Program Analysis, Steven M. Kelbley

Browse all Theses and Dissertations

With the widespread adoption of dynamic web applications in recent years, a number of threats to the security of these applications have emerged as significant challenges for application developers. The security of developed applications has become a higher priority for both developers and their employers as cyber attacks become increasingly more prevalent and damaging. Some of the most used web application frameworks are written in PHP and have become major targets due to the large number of servers running these applications worldwide. A number of tools exist to evaluate PHP code for issues, however most of these applications are not …


Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus Jan 2016

Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus

Dissertations, Master's Theses and Master's Reports

The representation of nonuniform, multi-modal, time-limited time series data is complex and explored through the use of discrete representation, dimensionality reduction with segmentation based techniques, and with behavioral representation approaches. These explorations are done with a focus on an outpatient oncology setting with the classification and regression analysis being used for length of survival prognosis. Each decision of representation and analysis is not independent, with implications of each decision in method for how the data is represented and then which analysis technique is used. One unique aspect of the work is the use of outpatient clinical data for patients, which …


Study Of Feasability For Phase Difference Extraction Using Software Defined Radio In Location Analysis, Paul Miller Aug 2013

Study Of Feasability For Phase Difference Extraction Using Software Defined Radio In Location Analysis, Paul Miller

Masters Theses

Here is a method for using the phase of an HF radio signal for use in location analysis. This computation is implemented in a software defined radio processing block in the GNU Radio environment. The signals analyzed are received by an Ettus Research USRP SDR. We created a phase analysis system called WMU Rootsync, which compares the roots of a received signal to the roots of a generated reference signal for the phase analysis. This research describes a prototype method for phase analysis only. Future projects may use these ideas differently than presented here. We intend for future projects to …


Simulation And Analysis Of Insider Attacks, Christopher Blake Clark May 2013

Simulation And Analysis Of Insider Attacks, Christopher Blake Clark

UNLV Theses, Dissertations, Professional Papers, and Capstones

An insider is an individual (usually an employee, contractor, or business partner) that has been trusted with access to an organization's systems and sensitive data for legitimate purposes. A malicious insider abuses this access in a way that negatively impacts the company, such as exposing, modifying, or defacing software and data.

Many algorithms, strategies, and analyses have been developed with the intent of detecting and/or preventing insider attacks. In an academic setting, these tools and approaches show great promise. To be sure of their effectiveness, however, these analyses need to be tested. While real data is available on insider attacks …


Robotic Swarming Without Inter-Agent Communication, Daniel Jonathan Standish Jan 2013

Robotic Swarming Without Inter-Agent Communication, Daniel Jonathan Standish

USF Tampa Graduate Theses and Dissertations

Many physical and algorithmic swarms utilize inter-agent communication to achieve advanced swarming behaviors. These swarms are inspired by biological swarms that can be seen throughout nature and include bee swarms, ant colonies, fish schools, and bird flocks. These biological swarms do not utilize inter-agent communication like their physical and algorithmic counterparts. Instead, organisms in nature rely on a local awareness of other swarm members that facilitates proper swarm motion and behavior. This research aims to pursue an effective swarm algorithm using only line-of-sight proximity information and no inter-agent communication. It is expected that the swarm performance will be lower than …


Generation And Analysis Of Verbal Route Directions For Blind Navigation, John Nicholson May 2010

Generation And Analysis Of Verbal Route Directions For Blind Navigation, John Nicholson

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

According to the National Federation of the Blind, there are an estimated 10 million people in the United States who are visually impaired. Of these, 1.3 million are legally blind. Many people with extreme vision loss receive orientation and mobility training in order to help them learn skills that allow them to travel and navigate multiple types of indoor and outdoor environments. Even with this training, a fundamental problem these people face is learning new routes, especially in environments with which they are not familiar. Although the research community has developed a number of localization and navigation aids that are …


Security And Performance Analysis For Rfid Protocols, Bing Liang Jan 2010

Security And Performance Analysis For Rfid Protocols, Bing Liang

Dissertations and Theses Collection (Open Access)

Radio Frequency Identification (RFID) is an advanced object identification technology that has already been applied in various industries. However, the insecure nature of the communication channel between readers and tags makes RFID systems vulnerable to various kinds of attacks. In recent years, many new methods have been proposed to improve the security of RFID systems, such as disabling tags, agent management and establishing cryptographic protocols. Among them, we focus on the last approach, which is more economic and convenient in certain cases. The first part of our work is to categorize typical existing RFID protocols according to their security levels. …