Physical Sciences and Mathematics Commons^™

Markov Chain Model Of Three-Dimensional Daphnia Magna Movement, Helen L. Kafka

Theses and Dissertations

Daphnia magna make turns through an antennae-whipping action. This action occursevery few seconds, hence, during the intervening time, the animal either remains in place or continues movement roughly along its current course. We view their movement in three dimensions. We divide the movement in the three dimensions into the movement on a two-dimensional lattice and the movement between the different planes. For the movement on the lattice, we construct a second-order Markov chain model to make predictions about which region of the lattice the animal moves to based on where it was at the last two time points. The movement …

Computation Of Risk Measures In Finance And Parallel Real-Time Scheduling, Yajuan Li

Dissertations

Many application areas employ various risk measures, such as a quantile, to assess risks. For example, in finance, risk managers employ a quantile to help determine appropriate levels of capital needed to be able to absorb (with high probability) large unexpected losses in credit portfolios comprising loans, bonds, and other financial instruments subject to default. This dissertation discusses the computation of risk measures in finance and parallel real-time scheduling.

Firstly, two estimation approaches are compared for one risk measure, a quantile, via randomized quasi-Monte Carlo (RQMC) in an asymptotic setting where the number of randomizations for RQMC grows large, but …

Machine Learning Model Comparison And Arma Simulation Of Exhaled Breath Signals Classifying Covid-19 Patients, Aaron Christopher Segura

Mathematics & Statistics ETDs

This study compared the performance of machine learning models in classifying COVID-19 patients using exhaled breath signals and simulated datasets. Ground truth classification was determined by the gold standard Polymerase Chain Reaction (PCR) test results. A residual bootstrapped method generated the simulated datasets by fitting signal data to Autoregressive Moving Average (ARMA) models. Classification models included neural networks, k-nearest neighbors, naïve Bayes, random forest, and support vector machines. A Recursive Feature Elimination (RFE) study was performed to determine if reducing signal features would improve the classification models performance using Gini Importance scoring for the two classes. The top 25% of …

Efficient Handover Mechanisms For Heterogeneous Networks., Shankar Kumar Ghosh Dr.

Doctoral Theses

In this thesis, some analytical frameworks have been developed to analyze the effect of different system parameters on handover performances in heterogeneous network (HetNet) and based on such frameworks, some efficient handover algorithms have been proposed. The study starts with an analytical framework to investigate the effect of resource allocation mechanisms, upper layer mobility management protocols (MMPs) and handover decision metrics on user perceived throughput. This analysis reveals that among other factors, handover decision metric plays a crucial role in determining user perceived throughput in HetNet. Subsequently, we develop two handover decision metrics for ultra dense networks (UDN) and unlicensed …

Wildfire Simulation Using Agent Based Modeling: Expanding Controlled Burn Season, Morgan C. Kromer

Senior Independent Study Theses

The United States is home to many different and unique forests. Prior to the 21st century, the United States Forests Service assumed that the best way to protect these forests was to put all efforts to keeping them alive. An enemy to these efforts were wildfires, thus the US adopted a complete fire suppression approach. At the turn of the century, the US realized that wildfires are a necessary part of a forest ecosystem, as they help return nutrients to the soil and reduce ground fuels. However, after suppressing all fires for over 100 years, the forests evolved into a …

A Brief Treatise On Bayesian Inverse Regression., Debashis Chatterjee Dr.

Doctoral Theses

Inverse problems, where in a broad sense the task is to learn from the noisy response about some unknown function, usually represented as the argument of some known functional form, has received wide attention in the general scientific disciplines. However, apart from the class of traditional inverse problems, there exists another class of inverse problems, which qualify as more authentic class of inverse problems, but unfortunately did not receive as much attention.In a nutshell, the other class of inverse problems can be described as the problem of predicting the covariates corresponding to given responses and the rest of the data. …

Some Nonparametric Hybrid Predictive Models : Asymptotic Properties And Applications., Tanujit Chakraborty Dr.

Doctoral Theses

Prediction problems like classification, regression, and time series forecasting have always attracted both the statisticians and computer scientists worldwide to take up the challenges of data science and implementation of complicated models using modern computing facilities. But most traditional statistical and machine learning models assume the available data to be well-behaved in terms of the presence of a full set of essential features, equal size of classes, and stationary data structures in all data instances, etc. Practical data sets from the domain of business analytics, process and quality control, software reliability, and macroeconomics, to name a few, suffer from various …

Applying Deep Learning To The Ice Cream Vendor Problem: An Extension Of The Newsvendor Problem, Gaffar Solihu

Electronic Theses and Dissertations

The Newsvendor problem is a classical supply chain problem used to develop strategies for inventory optimization. The goal of the newsvendor problem is to predict the optimal order quantity of a product to meet an uncertain demand in the future, given that the demand distribution itself is known. The Ice Cream Vendor Problem extends the classical newsvendor problem to an uncertain demand with unknown distribution, albeit a distribution that is known to depend on exogenous features. The goal is thus to estimate the order quantity that minimizes the total cost when demand does not follow any known statistical distribution. The …

Planar Motion Control Of A Cube Satellite Using Cold Gas Thrusters, Christian Lozoya

Open Access Theses & Dissertations

This Thesis presents a mathematical model developed for the computational simulation ofCubeSat movement using four thrusters that permit uniaxial translation and rotation. Arbitrary functions are fit to boundary conditions to simulate the force, acceleration, velocity, and displacement of the CubeSat along a plane. The model is used to derive a motion control algorithm assuming constant pressure and mass. A single model describes both translation and rotation. This Thesis also explores the relationship between propellant consumption and the time required to complete a displacement implied by the model.

Exploring The Variance Of The Sample Variance Through Estimation And Simulation, Christina Stradwick

Theses, Dissertations and Capstones

In this thesis, we examine properties of the variance of the sample variance, which we will denote V (S ² ). We derive a formula for this variance and show that it only depends on the sample size, variance, and kurtosis of the underlying distribution. We also derive the maximum likelihood estimators for this parameter, V^ˆ (S ² ), under the normal, exponential, Bernoulli, and Poisson distributions and end the thesis with simulations demonstrating the distributions of these estimators.

Optimal Layout For A Component Grid, Michael W. Ebert

Computer Science and Software Engineering

Several puzzle games include a specific type of optimization problem: given components that produce and consume different resources and a grid of squares, find the optimal way to place the components to maximize output. I developed a method to evaluate potential solutions quickly and automated the solving of the problem using a genetic algorithm.

The Loewner Equation And Weierstrass' Function, Gavin Ainsley Glenn

Chancellor’s Honors Program Projects

No abstract provided.

Neural Network Predictions Of A Simulation-Based Statistical And Graph Theoretic Study Of The Board Game Risk, Jacob Munson

Murray State Theses and Dissertations

We translate the RISK board into a graph which undergoes updates as the game advances. The dissection of the game into a network model in discrete time is a novel approach to examining RISK. A review of the existing statistical findings of skirmishes in RISK is provided. The graphical changes are accompanied by an examination of the statistical properties of RISK. The game is modeled as a discrete time dynamic network graph, with the various features of the game modeled as properties of the network at a given time. As the network is computationally intensive to implement, results are produced …

Numerical Simulation Of Hydrogen Absorption/Desorption Processes In Cylindrical Metal-Hydrogen Reactors For Hydrogen Storage, Fei Han

Doctoral Dissertations

Hydrogen is one of the best fuels because of its high calorific value and environmental friendliness. However, because of its low density, it has storage problems such as high pressure, large volume requirements, heavy weight and safely risks; this quality prevents its wide usage and commercialization.

Researchers have found that some metal/inter-metallic compounds/alloys, such as Mg, La, LaNi5, ZrV2, Mg2Ni and Ti 2Ni, can react with hydrogen and attain relatively large amounts of hydrogen at a relatively low pressure and near normal temperature. Under certain conditions, hydride can desorb hydrogen quickly. Thus, the metal- hydrogen reaction could be a practical …

American Spread Option Models And Valuation, Yu Hu

Theses and Dissertations

Spread options are derivative securities, which are written on the difference between the values of two underlying market variables. They are very important tools to hedge the correlation risk. American style spread options allow the holder to exercise the option at any time up to and including maturity. Although they are widely used to hedge and speculate in financial market, the valuation of the American spread option is very challenging. Because even under the classic assumptions that the underlying assets follow the log-normal distribution, the resulting spread doesn't have a distribution with a simple closed formula. In this dissertation, we …

Traffic Modeling In Lagrangian Coordinates Using Smartphone Apps, Sergio Contreras

UNLV Theses, Dissertations, Professional Papers, and Capstones

Traditionally, one of the ways traffic flow has been studied is by using the kinematic wave model. This model is derived in the Eulerian framework by using conservation of the number of vehicles. Recently, the kinematic wave model has been transformed into Lagrangian coordinates. In this framework, the independent variables are unique

vehicles and time. The detailed change in framework, and the properties of the model in the changed framework are reviewed. Numerical results from different traffic cases are explained. Since vehicle trajectory data can be easily collected from smartphones,

a smartphone application is developed for this purpose. This data …

Data Combination From Multiple Sources Under Measurement Error, Hugo Gasca-Aragon

Open Access Dissertations

Regulatory Agencies are responsible for monitoring the performance of particular measurement communities. In order to achieve their objectives, they sponsor Intercomparison exercises between the members of these communities. The Intercomparison Exercise Program for Organic Contaminants in the Marine Environment is an ongoing NIST/NOAA program. It was started in 1986 and there have been 19 studies to date. Using this data as a motivation we review the theory and practices applied to its analysis.

It is a common practice to apply some kind of filter to the comparison study data. These filters go from outliers detection and exclusion to exclusion of …

On Decision Making: Bayesian And Stochastic Optimization Approaches, Yang Shen

Masters Theses

Decision analysis provides a framework for searching an optimal solution under uncertainties and potential risks. This thesis focuses on two problems arising in transportation engineering and computer sciences, respectively.

First, it is considered a centralized controller which imposes actions on a number of interacting subsystems. Employing an appropriate Markov Decision Process framework, we establish that the Pareto optimal solution of each subsystem will be optimal for the entire system. Synthetic data have been taken into account for verifying this claim.

Next, we focus on a supercomputing problem utilizing a hierarchical Bayesian model. We estimate an optimal solution in order to …

Statistical Properties Of A Convoluted Beta-Weibull Distribution, Jianan Sun

Theses, Dissertations and Capstones

A new class of distributions recently developed involves the logit of the beta distribution. Among this class of distributions are the beta-normal (Eugene et.al. (2002)); beta-Gumbel (Nadarajah and Kotz (2004)); beta-exponential (Nadarajah and Kotz (2006)); beta-Weibull (Famoye et al. (2005)); beta-Rayleigh (Akinsete and Lowe (2008)); beta-Laplace (Kozubowski and Nadarajah (2008)); and beta-Pareto (Akinsete et al. (2008)), among a few others. Many useful statistical properties arising from these distributions and their applications to real life data have been discussed in the literature. One approach by which a new statistical distribution is generated is by the transformation of random variables having known …

Comparing Cognitive Decision Models Of Iowa Gambling Task In Indivituals Following Temporal Lobectomy, Jenny Vennukkah Jeyarajah

Mathematics Theses

This study examined the theoretical basis for decision making behavior of patients with right or left temporal lobectomy and a control group when they participated in the Iowa Gambling Task. Two cognitive decision models, Expectancy Valence Model and Strategy Switching Heuristic Choice Model, were compared for best fit. The best fitting model was then chosen to provide the basis for parameter estimation (sources of decision making, i.e. cognitive, motivational, and response processes) and interpretation. Both models outperformed the baseline model. However comparison of G2 means between the two cognitive decision models showed the expectancy valence model having a higher mean …

Simulation, Kriging, And Visualization Of Circular-Spatial Data, William James Morphet

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The circular dataimage is defined by displaying direction as the color at the same direction in a color wheel composed of a sequence of two-color gradients with color continuity between gradients. The resulting image of circular-spatial data is continuous with high resolution. Examples include ocean wind direction, Earth's main magnetic field, and rocket nozzle internal combustion flow. The cosineogram is defined as the mean cosine of the angle between random components of direction as a function of distance between observation locations. It expresses the spatial correlation of circular-spatial data. A circular kriging solution is developed based on a model fitted …

Simulation Study Of Estimation And Inference In Factor Analysis: Normal And Non-Normal Noise Distributions, Ping Zhang

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Objective: To study the estimation and inference m factor analyses when the data have normal or non-normal noise distributions.

Methods: Population data were created in package R with a specified number of factors, factor structure and observable variables with known loadings. Then, repeated simple random samples (SRS's) were taken from the population, independently. The maximum likelihood method with varimax rotation was used to perform factor analysis and inference on each sampled dataset. Factor loadings were estimated to determine if the estimation of the loadings was (approximately) unbiased and/or efficient for each specified population and chi-square x2-statistics were obtained to test …

Computer Simulation And Homogenization In Heating Design Optimization, Daniel K. Balls

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The ability to ensure uniformity of temperature within a given finite physical region is an essential element in the success of many scientific processes, especially those that involve extreme fluctuation in temperature. Such a process is performed in an instrument called the LightTyper developed by Idaho Technology, Inc. of Salt Lake City Utah. This paper details the development and results of a scheme intended to obtain a heating design that ensures a high degree of temperature uniformity within the Idaho Technology instrument. Due to the experiments performed during this project, we were able to answer many questions that concerned finding …

Numerical Simulation Of Saturated Flow With Fractal Analysis Of The Hydraulic Conductivity Distribution, Joan Leilani Oana

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The purpose of this report is to investigate the behavior of a nonreactive contaminant in a perfectly stratified aquifer under uniform, steady-state flow. The design and the implementation of a solute transport model which characterizes the heterogeneities of the aquifer properties in a stochastic framework is reviewed. The model closely examines the advection and dispersion of the plume. The advection is the process by which the plume is transported in the aquifer by the bulk average motion of the groundwater whereas the dispersion refers to the spreading of the plume about its mean displacement position. The relationship between the fractally …

Monte Carlo Simulation Of The Game Of Twenty-One, Douglas E. Loer

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The purpose of this paper is to demonstrate the application of computer simulation to the game of Twenty-One to predict a player's expected return from the game. Twenty-One has traditionally been one of the most popular casino games and has attracted much effort to accurately estimate the house's true advantage. Probability theory has been tried, but the thousands of different combinations of cards possible in all hands throughout the entire pack make it practically impossible to apply probability theory without overlooking some possibilities. For this reason, Twenty-One is a perfect candidate for simulation. By blocking several simulations, normal theory can …

A Logistic System Simulation Model Encompassing Poisson Processes And Normal Or Weibull Life, Willard A. Hansen

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This thesis describes a computer simulation model for determining effective spares stock levels for recoverable items at Air Force bases and depots. The simulation model is based on the following fundamental inventory theory; whenever a demand arises, it is satisfied from stock on hand, and the quantity equal to that demand is recorded immediately; when a demand exceeds stock on hand, the excess demand is backordered immediately and when item life expires procurement action is initiated at depot level. The resulting product of the model cam be used as a guide for the optimum distribution of available spares or as …