Digital Commons Network^™

Using Deep Neural Networks To Analyze Precision Agriculture Data, Stephanie Liebl

Electronic Theses and Dissertations

As the population of the Earth increases, there is a growing need for food to feed the inhabitants. Precision agriculture offers techniques and tools that can be used to help accommodate the growing population. One specific precision agriculture tool is remote sensing data, which can be used to image fields as an effort to better predict or understand the crops. In this thesis, deep neural networks are used to evaluate various spatial, spectral, and temporal resolutions of three different satellite images to determine which best predicts corn yield. The main metrics we used to evaluate the models were R-squared (R2), …

The Effect Of Initial Conditions On The Weather Research And Forecasting Model, Aaron D. Baker

Electronic Theses and Dissertations

Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to …

Evaluation Of The Effect Of The Clinical-Decision-Support Systems On Diabetes Management: A Multivariate Meta-Analysis Comparison With Univariate Meta-Analysis, Abdelfattah Elbarsha

Electronic Theses and Dissertations

The advantage of using meta-analysis lies in its ability in providing a quantitative summary of the findings from multiple studies. The aim of this dissertation was first to conduct a simulation study in order to understand what factors (sample size, between-study correlation, and percent of missing data) have a significant effect on meta-analysis estimates and whether using univariate or multivariate meta-analysis would produce different estimates.

The second goal of this study was to evaluate the effect of clinical decision support systems CDSS on diabetes care management by conducting three separate univariate meta-analyses and one multivariate meta-analysis. CDSS are health information …

The Combined Impact Of Continuous And Ordinal Auxiliary Variables On Missing Data Imputation In Sem, Salina Wu Whitaker

Electronic Theses and Dissertations

“Modern” methods of addressing missing data using full-information maximum-likelihood (FIML) have become mainstays in SEM analyses. FIML allows the inclusion of auxiliary variables which carry information that is related to missing values and can reduce bias in parameter estimates. Past research has illustrated the benefits of auxiliary variable inclusion under different missingness conditions (MCAR and MNAR; e.g., Enders, 2008), missingness proportions (e.g., Collins et al., 2001), and although limited, missingness patterns (e.g., Yoo, 2009) in FIML analyses. While past studies have focused on the effects of either continuous or ordinal auxiliary variables, no study has included both types in their …

Is Corequisite Developmental Math Effective At East Tennessee State University?, Christine Padden

Electronic Theses and Dissertations

This thesis looks at the corequisite developmental math program at East Tennessee State University (ETSU) and compares the effectiveness to the previous developmental math program by comparing the student outcomes in MATH 1530. MATH 1530 is a non-calculus based statistic and probability course that satisfies most majors’ general education math requirements. ETSU sees approximately 1,000 students a year pass through MATH 1530 which is around 6.7% of the total enrollment at ETSU[9]. We are interested in the last five years of the developmental math program before it was changed to corequisite developmental math and the first five years of corequisite …

Cramer Type Moderate Deviations For Random Fields And Mutual Information Estimation For Mixed-Pair Random Variables, Aleksandr Beknazaryan

Electronic Theses and Dissertations

In this dissertation we first study Cramer type moderate deviation for partial sums of random fields by applying the conjugate method. In 1938 Cramer published his results on large deviations of sums of i.i.d. random variables after which a lot of research has been done on establishing Cramer type moderate and large deviation theorems for different types of random variables and for various statistics. In particular results have been obtained for independent non-identically distributed random variables for the sum of independent random to estimate the mutual information between two random variables. The estimates enjoy a central limit theorem under some …

Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor

Electronic Theses and Dissertations

Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …

Fm Radio Signal Propagation Evaluation And Creating Statistical Models For Signal Strength Prediction In Differing Topographic Environments, Timothy Land

Electronic Theses and Dissertations

Radio wave signal strength and associated propagation models are rarely analyzed across individual geographic provinces. This study evaluates the effectiveness of the Radio Mobile model to predict radio wave signal strength in the Blue Ridge and Valley and Ridge physiographic provinces. A spectrum analyzer was used on 19 FM transmitters to determine model accuracy. Statistical analysis determined the significance between different terrain factors and signal strength. Field signal strength was found to be related to test site elevation, transmitter azimuth, elevation angle, transmitter elevation, path loss, and distance. Using 76 signal strength receiver sites, Ordinary Least Square regression models predicted …

Quasi-Random Action Selection In Markov Decision Processes, Samuel D. Walker

Electronic Theses and Dissertations

In Markov decision processes an operator exploits known data regarding the environment it inhabits. The information exploited is learned from random exploration of the state-action space. This paper proposes to optimize exploration through the implementation of quasi-random sequences in both discrete and continuous state-action spaces. For the discrete case a permutation is applied to the indices of the action space to avoid repetitive behavior. In the continuous case sequences of low discrepancy, such as Halton sequences, are utilized to disperse the actions more uniformly.

A Multi-Indexed Logistic Model For Time Series, Xiang Liu

Electronic Theses and Dissertations

In this thesis, we explore a multi-indexed logistic regression (MILR) model, with particular emphasis given to its application to time series. MILR includes simple logistic regression (SLR) as a special case, and the hope is that it will in some instances also produce significantly better results. To motivate the development of MILR, we consider its application to the analysis of both simulated sine wave data and stock data. We looked at well-studied SLR and its application in the analysis of time series data. Using a more sophisticated representation of sequential data, we then detail the implementation of MILR. We compare …

Mahalanobis Kernel-Based Support Vector Data Description For Detection Of Large Shifts In Mean Vector, Vu Nguyen

Electronic Theses and Dissertations

Statistical process control (SPC) applies the science of statistics to various process control in order to provide higher-quality products and better services. The K chart is one among the many important tools that SPC offers. Creation of the K chart is based on Support Vector Data Description (SVDD), a popular data classifier method inspired by Support Vector Machine (SVM). As any methods associated with SVM, SVDD benefits from a wide variety of choices of kernel, which determines the effectiveness of the whole model. Among the most popular choices is the Euclidean distance-based Gaussian kernel, which enables SVDD to obtain a …

Modeling User Transportation Patterns Using Mobile Devices, Erfan Davami

Electronic Theses and Dissertations

Participatory sensing frameworks use humans and their computing devices as a large mobile sensing network. Dramatic accessibility and affordability have turned mobile devices (smartphone and tablet computers) into the most popular computational machines in the world, exceeding laptops. By the end of 2013, more than 1.5 billion people on earth will have a smartphone. Increased coverage and higher speeds of cellular networks have given these devices the power to constantly stream large amounts of data. Most mobile devices are equipped with advanced sensors such as GPS, cameras, and microphones. This expansion of smartphone numbers and power has created a sensing …

Three-Dimensional Modeling Of The Human Jaw/Teeth Using Optics And Statistics., Aly Saber Abdelrahim

Electronic Theses and Dissertations

Object modeling is a fundamental problem in engineering, involving talents from computer-aided design, computational geometry, computer vision and advanced manufacturing. The process of object modeling takes three stages: sensing, representation, and analysis. Various sensors may be used to capture information about objects; optical cameras and laser scanners are common with rigid objects, while X-ray, CT and MRI are common with biological organs. These sensors may provide a direct or an indirect inference about the object, requiring a geometric representation in the computer that is suitable for subsequent usage. Geometric representations that are compact, i.e., capture the main features of the …

Applications Of Transit Signal Priority Technology For Transit Service, Frank Anthony Consoli

Electronic Theses and Dissertations

This research demonstrated the effectiveness of Transit Signal Priority (TSP) in improving bus corridor travel time in a simulated environment using real world data. TSP is a technology that provides preferential treatment to buses at signalized intersections. By considering different scenarios of activating bus signal priority when a bus is 3 or 5 minutes behind schedule, it was demonstrated that bus travel times improved significantly while there is little effect on delays for crossing street traffic. The case of providing signal priority for buses unconditionally resulted in significant crossing street delays for some signalized intersections with only minor improvement to …

A Statistical Analysis Of The Beneficial Effects Of Ferrous Chloride At The T. E. Maxson Treatment Plant, Bjorn Carlsson

Electronic Theses and Dissertations

Addition of ferrous chloride can improve wastewater treatment plant process outcomes. In the study, a municipal wastewater treatment plant ceased adding ferrous chloride to its anaerobic lagoon and belt filter press filtrate return streams. Total suspended solids (TSS) and five-day biochemical oxygen demand (BOD5) effluent concentrations and percent removals, primary clarifier BOD5 and TSS effluent concentration and percent removals, sludge volume index (SVI), sludge polymer feed demand, and H2S concentration in biogas on days with ferrous chloride addition were all compared using non-parametric randomization statistical techniques to days without ferrous chloride addition. It was found that plant performance on days …

Absolute Penalty And Shrinkage Estimation Strategies In Linear And Partially Linear Models With Correlated Errors, Saber Fallahpour

Electronic Theses and Dissertations

In this dissertation we propose shrinkage estimators and absolute penalty estimators (APEs) in linear models, partially linear models (PLM) and quasi-likelihood models. We study the asymptotic properties of shrinkage estimators both analytically and through simulation studies, and compare their performance with APEs. In Chapter 2, we propose shrinkage estimators for a multiple linear regression with first order random coefficient autoregressive (RCAR(1)) error term. We also present two APEs for this models which are modified versions of lasso and adaptive lasso estimators. We compare the performance of shrinkage estimators and APEs through the mean squared error criterion. Monte Carlo studies were …

Revising Common Core Georgia Performance Standards Statistics Lesson Plans To Better Align With Statistical Practice, Rachel Bonilla

Electronic Theses and Dissertations

In this thesis, lesson plans provided by the Georgia Department of Education are revised to give students better exposure and practice working with real-life data. Three learning tasks and a performance task are presented covering a unit lesson on statistical regression. The development of Georgia statistics curriculum standards are reviewed and presented.

Acute Myocardial Infarction Patient Data To Assess Healthcare Utilization And Treatments., Pedro Ramos

Electronic Theses and Dissertations

The goal of this study is to use a data mining framework to assess the three main treatments for acute myocardial infarction: thrombolytic therapy, percutaneous coronary intervention (percutaneous angioplasty), and coronary artery bypass surgery. The need for a data mining framework in this study arises because of the use of real world data rather than highly clean and homogenous data found in most clinical trials and epidemiological studies. The assessment is based on determining a profile of patients undergoing an episode of acute myocardial infarction, determine resource utilization by treatment, and creating a model that predicts each treatment resource utilization …

Marginal Nonparametric Inference For Waiting Times In Multistage Models : Hypothesis Testing And Regression., Douglas J. Lorenz

Electronic Theses and Dissertations

Marginal inference for waiting times in multi-stage time-to-event models is complicated by right censoring of observations as well as the prior history of events in the model. In general, complications arise due to the evolution of the censoring process in so called "calendar time", contrasted with the evolution of the waiting time process conditional upon entry into a given stage. Developments in inference for survival data under dependent censoring have been extended to the multi-stage framework, and non parametric estimators for the cumulative hazard function and survival function for waiting times analogous of the classical Nelson-Aalen and Kaplan-Meier estimators for …

Time Series Analysis Of Stock Prices Using The Box-Jenkins Approach, Shakira Green

Electronic Theses and Dissertations

A time series is a sequence of data points, typically measured at uniform time intervals. Examples occur in a variety of fields ranging from economics to engineering, and methods of analyzing time series constitute an important part of Statistics. Time series analysis comprises methods for analyzing time series data in order to extract meaningful characteristics of the data and forecast future values. The Autoregressive Integrated Moving Average (ARIMA) models, or Box-Jenkins methodology, are a class of linear models that are capable of representing stationary as well as nonstationary time series. ARIMA models rely heavily on autocorrelation patterns. This paper will …

A Comparative Study Between The Standards Of Learning And In-Class Grades., Randetta Lynn Fuller

Electronic Theses and Dissertations

We examined the Standards of Learning mathematics scores and in-class grades for a rural Virginia county public school system. We looked at third, fourth, fifth, sixth, and seventh grades as well as Algebra I, Algebra II, and Geometry classes. The purpose of this was to determine whether or not there is a strong correlation between the Standards of Learning and the students' in-class grades. Had a strong enough correlation between the Standards of Learning and in-class grades been found we would have used only the in-class grades to predict the Standard of Learning test scores. However, we found that the …

Generalized Inference In Linear Regression Models, Quazi Ibrahim

Electronic Theses and Dissertations

In this thesis, we consider inference problems in linear regression under both homoscedasticity and heteroscedasticity of the error noise. Namely, we construct generalized confidence regions and generalized confidence intervals for regression coefficients of linear regression models. Regressor variables are considered non-stochastic. Independent normal errors with zero mean and constant or varying dispersion are considered. The regression data from two different regimes are considered. In testing the equality of the regression coefficients in the two regimes under heteroscedasticity, we develop the generalized pivotal quantities of their differences and the generalized p-values. Generalized methods of inference are especially useful in multiparameter cases …

Comparison Of Career Statistics And Season Statistics In Major League Baseball, Mark Joseph Ammons

Electronic Theses and Dissertations

This is a comparison of statistics for some of the best seasons and careers of players from Major League Baseball; using data collected on batting average, at bat to homerun ratio, and earned run average. Two teams were created, composed of season leaders and career leaders, chosen for their outstanding offensive and pitching abilities, and were pitted against one another to determine superiority. These two teams also compared against a team from each era of major league baseball. The season and career leaders challenged, the 1918 Boston Red Sox, 1927 New York Yankees, 1955 Brooklyn Dodgers, 1961 New York Yankees, …

Probability And Statistics For Third Through Fifth Grade Classrooms., Melissa Taylor Mckinnon

Electronic Theses and Dissertations

This document contains a variety of lesson plans that can be readily used by a teacher of intermediate students. This thesis contains two units in Probability and one unit in Statistics. Any educator can supplement this document with any curriculum to teach lessons from vocabulary to concept.

Teaching Probability And Statistics To English Language Learners In Grade Five., Mary Jo Johnson Neal

Electronic Theses and Dissertations

An increasing number of English Language Learners enrolling in the Washington County Virginia Public School System during the past several years prompted the idea of this thesis. These students are currently mainstreamed in the regular academic classroom. Adapting to their needs is a new challenge in education for teachers in Southwest Virginia. This thesis offers an opportunity for teachers to prepare for a multicultural classroom setting providing English Language Learners with learning strategies necessary to gain confidence in their mathematical ability and academic success in the areas of probability and statistics. Lesson plans have been specifically designed emphasizing teaching strategies, …

Modeling And Characterizations Of New Notions In Life Testing With Statistical Applications, Mohammad Sepehrifar

Electronic Theses and Dissertations

Knowing the class to which a life distribution belongs gives us an idea about the aging of the device or system the life distribution represents, and enables us to compare the aging properties of different systems. This research intends to establish several new nonparametric classes of life distributions defined by the concept of inactivity time of a unit with a guaranteed minimum life length. These classes play an important role in the study of reliability theory, survival analysis, maintenance policies, economics, actuarial sciences and many other applied areas.

Performance Of Bootstrap Confidence Intervals For L-Moments And Ratios Of L-Moments., Suzanne Glass

Electronic Theses and Dissertations

L-moments are defined as linear combinations of expected values of order statistics of a variable.(Hosking 1990) L-moments are estimated from samples using functions of weighted means of order statistics. The advantages of L-moments over classical moments are: able to characterize a wider range of distributions; L-moments are more robust to the presence of outliers in the data when estimated from a sample; and L-moments are less subject to bias in estimation and approximate their asymptotic normal distribution more closely.

Hosking (1990) obtained an asymptotic result specifying the sample L-moments have a multivariate normal distribution as n approaches infinity. The standard …