Physical Sciences and Mathematics Commons^™

Better Understanding Genomic Architecture With The Use Of Applied Statistics And Explainable Artificial Intelligence, Jonathon C. Romero

Doctoral Dissertations

With the continuous improvements in biological data collection, new techniques are needed to better understand the complex relationships in genomic and other biological data sets. Explainable Artificial Intelligence (X-AI) techniques like Iterative Random Forest (iRF) excel at finding interactions within data, such as genomic epistasis. Here, the introduction of new methods to mine for these complex interactions is shown in a variety of scenarios. The application of iRF as a method for Genomic Wide Epistasis Studies shows that the method is robust in finding interacting sets of features in synthetic data, without requiring the exponentially increasing computation time of many …

Sparse Model Selection Using Information Complexity, Yaojin Sun

Doctoral Dissertations

This dissertation studies and uses the application of information complexity to statistical model selection through three different projects. Specifically, we design statistical models that incorporate sparsity features to make the models more explanatory and computationally efficient.

In the first project, we propose a Sparse Bridge Regression model for variable selection when the number of variables is much greater than the number of observations if model misspecification occurs. The model is demonstrated to have excellent explanatory power in high-dimensional data analysis through numerical simulations and real-world data analysis.

The second project proposes a novel hybrid modeling method that utilizes a mixture …

Motor Control-Based Assessment Of Therapy Effects In Individuals Post-Stroke: Implications For Prediction Of Response And Subject-Specific Modifications, Ashley Rice

Doctoral Dissertations

Producing a coordinated motion such as walking is, at its root, the result of healthy communication pathways between the central nervous system and the musculoskeletal system. The central nervous system produces an electrical signal responsible for the excitation of a muscle, and the musculoskeletal system contains the necessary equipment for producing a movement-driving force to achieve a desired motion. Motor control refers to the ability an individual has to produce a desired motion, and the complexity of motor control is a mathematical concept stemming from how the electrical signals from the central nervous system translate to muscle activations. Exercising a …

Spatio-Temporal Modeling Of Crime In Chicago, Illinois, Shelby Scott

Doctoral Dissertations

Gun crime is a major public health concern in the United States. In Chicago, Illinois, gun crime incurs a significant cost of life along with monetary costs and community unrest. Due to past legislation, there is limited research applying quantitative methods to gun crime in Chicago. The overall purpose of this work is to create a cellular automata model to observe and project the epidemic spread of gun crime in Chicago. To create that model, t-test analyses of temporal patterns, a Bayesian point process model, a negative binomial Bayesian subset selection, and a k-selection algorithm are used. The cellular automata …

Association Between Stream Impairment By Mercury And Superfund Sites In The Conterminous Usa, Karessa L. Manning

Masters Theses

Mercury is a natural element that can cause harm to the brain, heart, kidneys, lungs, and immune system, especially to fetuses developing in the womb. Many natural and anthropogenic factors contribute to mercury in the environment, such as geologic deposits, landfills, gold and silver mining operations, cement production, and atmospheric deposition. Mercury has been identified as a contaminant of concern at many National Priority List (NPL) sites, however, studies on contamination at NPL sites are often only conducted on a local level. This study was to analyze the potential connection between mercury-contaminated NPL sites and the presence of mercury impaired …

Root Stage Distributions And Their Importance In Plant-Soil Feedback Models, Tyler Poppenwimer

Doctoral Dissertations

Roots are fundamental to PSFs, being a key mediator of these feedbacks by interacting with and affecting the soil environment and soil microbial communities. However, most PSF models aggregate roots into a homogeneous component or only implicitly simulate roots via functions. Roots are not homogeneous and root traits (nutrient and water uptake, turnover rate, respiration rate, mycorrhizal colonization, etc.) vary with age, branch order, and diameter. Trait differences among a plant’s roots lead to variation in root function and roots can be disaggregated according to their function. The impact on plant growth and resource cycling of changes in the distribution …

Bayesian Topological Machine Learning, Christopher A. Oballe

Doctoral Dissertations

Topological data analysis encompasses a broad set of ideas and techniques that address 1) how to rigorously define and summarize the shape of data, and 2) use these constructs for inference. This dissertation addresses the second problem by developing new inferential tools for topological data analysis and applying them to solve real-world data problems. First, a Bayesian framework to approximate probability distributions of persistence diagrams is established. The key insight underpinning this framework is that persistence diagrams may be viewed as Poisson point processes with prior intensities. With this assumption in hand, one may compute posterior intensities by adopting techniques …

Modelling Cash Crop Growth In Tn, Spencer Weston

Chancellor’s Honors Program Projects

No abstract provided.

Development And Validation Of The Statistics Assessment Of Graduate Students, Dammika Lakmal Walpitage

Doctoral Dissertations

This study developed the Statistics Assessment of Graduate Students (SAGS) instrument, and established its preliminary item characteristics, reliability, and validity evidence. Even though there are limited number of assessments available for measuring different aspects of statistical cognition, these previously available assessments have numerous limitations. The SAGS instrument was developed using Rasch modeling approach to create a new measure of statistical research methodology knowledge of graduate students in education and other behavioral and social sciences. Thirty-five multiple-choice questions were written with stems representing applied research situations and response options distinguishing between appropriate use of various statistical tests or procedures. A focus …

Variable Selection Via Penalized Regression And The Genetic Algorithm Using Information Complexity, With Applications For High-Dimensional -Omics Data, Tyler J. Massaro

Doctoral Dissertations

This dissertation is a collection of examples, algorithms, and techniques for researchers interested in selecting influential variables from statistical regression models. Chapters 1, 2, and 3 provide background information that will be used throughout the remaining chapters, on topics including but not limited to information complexity, model selection, covariance estimation, stepwise variable selection, penalized regression, and especially the genetic algorithm (GA) approach to variable subsetting.

In chapter 4, we fully develop the framework for performing GA subset selection in logistic regression models. We present advantages of this approach against stepwise and elastic net regularized regression in selecting variables from a …

Advanced Sequential Monte Carlo Methods And Their Applications To Sparse Sensor Network For Detection And Estimation, Kai Kang

Doctoral Dissertations

The general state space models present a flexible framework for modeling dynamic systems and therefore have vast applications in many disciplines such as engineering, economics, biology, etc. However, optimal estimation problems of non-linear non-Gaussian state space models are analytically intractable in general. Sequential Monte Carlo (SMC) methods become a very popular class of simulation-based methods for the solution of optimal estimation problems. The advantages of SMC methods in comparison with classical filtering methods such as Kalman Filter and Extended Kalman Filter are that they are able to handle non-linear non-Gaussian scenarios without relying on any local linearization techniques. In this …

Effects Of Bullying And Victimization On Friendship Selection, Reciprocation, And Maintenance In Elementary School Children, Marisa Lynn Whitley

Masters Theses

This study examined the effects of elementary school children’s bullying and victimization experiences on their friendships over time. The majority of children experience acts of aggression or bullying before the end of elementary school, and bullying and peer victimization is associated with academic, social, behavioral, and psychological difficulties. This study used social networks analysis (R SIENA 4.0) to examine whether peer reports of forms of bullying and victimization (i.e., overt and relational) affect the likelihood of friendship selection, reciprocation, and maintenance in 2^nd-4^th grade children. Children (N = 143) from the Midwestern region of the United …

Evaluating The Effects Of Standardized Patient Care Pathways On Clinical Outcomes, Anna V. Romanova

Doctoral Dissertations

The main focus of this study is to create a standardized approach to evaluating the impact of the patient care pathways across all major disease categories and key outcome measures in a hospital setting when randomized clinical trials are not feasible. Toward this goal I identify statistical methods, control factors, and adjustments that can correct for potential confounding in observational studies. I investigate the efficiency of existing bias correction methods under varying conditions of imbalanced samples through a Monte Carlo simulation. The simulation results are then utilized in a case study for one of the largest primary diagnosis areas, chronic …

Predicting High-Stakes Tests Of Math Achievement Using A Group-Administered Rti Instrument: Validating Skills Measured By The Monitoring Instructional Responsiveness: Math, Jeremy Thomas Coles

Doctoral Dissertations

Three universal screeners and nine progress monitoring probes from the Monitoring Instructional Responsiveness: Math (MIR:M), a silent, group-administered math assessment designed for implementation with an RTI Model, were administered to 223 fifth-grade students. The growth parameters of the overall MIR:M composite and two global composites (math calculation and math reasoning) identified significant variation in student growth, within significant linear and quadratic trajectories. However, there were significant differences in the nature of the growth trajectories that have applied educational implications. In addition, growth parameters across the three composites provided significant predictive potential when using the Tennessee Comprehensive Assessment Program (TCAP) Achievement …

Impacts Of Climate Change On The Evolution Of The Electrical Grid, Melissa Ree Allen

Doctoral Dissertations

Maintaining interdependent infrastructures exposed to a changing climate requires understanding 1) the local impact on power assets; 2) how the infrastructure will evolve as the demand for infrastructure changes location and volume and; 3) what vulnerabilities are introduced by these changing infrastructure topologies. This dissertation attempts to develop a methodology that will a) downscale the climate direct effect on the infrastructure; b) allow population to redistribute in response to increasing extreme events that will increase under climate impacts; and c) project new distributions of electricity demand in the mid-21^st century.

The research was structured in three parts. The first …

Comparison Of Triangle And Tetrad Discrimination Methodology In Applied, Industrial Manner, Sara Lyn Carlisle

Masters Theses

The triangle method has been widely used in the food industry for many years when conducting sensory discrimination testing. Recently, however, another discrimination testing method, the tetrad, has begun to gain popularity. Based on currently published research, the tetrad method possesses statistical advantages over the triangle and would require fewer panelists, reduce testing time, and use less sample material. More testing is needed to confirm these advantages in an applied, industrial approach on a wider range of products. Over thirty triangles and thirty tetrads with untrained panelists have been completed in order to compare the two methods. Products tested ranged …

Experimental And Statistical Techniques To Probe Extraordinary Electronic Properties Of Molecules, Byron Hager Smith

Doctoral Dissertations

The existence of an additional electron or hole in the presence of an electric monopole is a well understood physical system, but this ideality is far from the true physical properties of many molecules. Examples of such irregular electronic states include the attachment of an excess charge to a molecule's dipole moment, electronic correlation spanning a molecule, or attachment of multiple excess charges. Current theoretical and experimental interpretations widely vary for these states and further elucidation of the nature of irregular electronic structure may provide solutions to unexplained observations and the impetus for industrial application. For example, in the case …

Geographic And Temporal Epidemiology Of Campylobacteriosis, Jennifer Weisent

Doctoral Dissertations

Campylobacteriosis is a leading cause of gastroenteritis in the United States. The focus of this research was to (i) analyze and predict spatial and temporal patterns and associations for campylobacteriosis risk and (ii) compare the utility of advanced modeling methods. Laboratory-confirmed Campylobacter case data, obtained from the Foodborne Diseases Active Surveillance Network were used in all investigations.

We compared the accuracy of forecasting techniques for campylobacteriosis risk in Minnesota, Oregon and Georgia and found that time series regression, decomposition, and Box-Jenkins Autoregressive Integrated Moving Averages reliably predict monthly risk of infection for campylobacteriosis. Decomposition provided the fastest, most accurate, user-friendly …

Automating Large-Scale Simulation Calibration To Real-World Sensor Data, Richard Everett Edwards

Doctoral Dissertations

Many key decisions and design policies are made using sophisticated computer simulations. However, these sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. This dissertation's goal is to address these simulation deficiencies by presenting a general automated process for tuning simulation inputs such that simulation output matches real world measured data. The automated process involves the following key components -- 1) Identify a model that accurately estimates the real world simulation calibration target from measured sensor data; 2) Identify …

A Geospatial Based Decision Framework For Extending Marssim Regulatory Principles Into The Subsurface, Robert Nathan Stewart

Doctoral Dissertations

The Multi-Agency Radiological Site Survey Investigation Manual (MARSSIM) is a regulatory guidance document regarding compliance evaluation of radiologically contaminated soils and buildings (USNRC, 2000). Compliance is determined by comparing radiological measurements to established limits using a combination of hypothesis testing and scanning measurements. Scanning allows investigators to identify localized pockets of contamination missed during sampling and allows investigators to assess radiological exposure at different spatial scales. Scale is important in radiological dose assessment as regulatory limits can vary with the size of the contaminated area and sites are often evaluated at more than one scale (USNRC, 2000). Unfortunately, scanning is …

An Analysis Of Boosted Regression Trees To Predict The Strength Properties Of Wood Composites, Dillon Matthew Carty

Masters Theses

The forest products industry is a significant contributor to the U.S. economy contributing six percent of the total U.S. manufacturing gross domestic product (GDP), placing it on par with the U.S. automotive and plastics industries. Sustaining business competitiveness by reducing costs and maintaining product quality will be essential in the long term for this industry. Improved production efficiency and business competitiveness is the primary rationale for this work. A challenge facing this industry is to develop better knowledge of the complex nature of process variables and their relationship with final product quality attributes. Quantifying better the relationships between process variables …

Exploring The Effectiveness Of Environmentally Sustainable Practices In Municipal Government: A Case Study Of The City Of Knoxville’S Department Of Parks And Recreation, Anthony Michael Brown

Masters Theses

Sustainability practices produce programs and services that meet current needs while preserving the environment and natural resources for the future. City parks and recreation departments are facing budget shortfalls and increasing expectations from customers. Governments are now embracing sustainability practices to create financial savings while also fostering relations with customers.

The purpose of this single case study was twofold: (1) to examine the effectiveness of one city department’s strategies in outsourcing its environmental sustainability program through a performance contract with Ameresco; and (2) to examine the perceptions of key department employees about the effectiveness of the sustainability initiative. A …

A Study Of Missing Data Imputation And Predictive Modeling Of Strength Properties Of Wood Composites, Yan Zeng

Masters Theses

Problem: Real-time process and destructive test data were collected from a wood composite manufacturer in the U.S. to develop real-time predictive models of two key strength properties (Modulus of Rupture (MOR) and Internal Bound (IB)) of a wood composite manufacturing process. Sensor malfunction and data “send/retrieval” problems lead to null fields in the company’s data warehouse which resulted in information loss. Many manufacturers attempt to build accurate predictive models excluding entire records with null fields or using summary statistics such as mean or median in place of the null field. However, predictive model errors in validation may be higher …

Bayesian Logistic Regression Model For Siting Biomass-Using Facilities, Xia Huang

Masters Theses

Key sources of oil for western markets are located in complex geopolitical environments that increase economic and social risk. The amalgamation of economic, environmental, social and national security concerns for petroleum-based economies have created a renewed emphasis on alternative sources of energy which include biomass. The stability of sustainable biomass markets hinges on improved methods to predict and visualize business risk and cost to the supply chain.

This thesis develops Bayesian logistic regression models, with comparisons of classical maximum likelihood models, to quantify significant factors that influence the siting of biomass-using facilities and predict potential locations in the 13-state Southeastern …

Mixture Of Factor Analyzers With Information Criteria And The Genetic Algorithm, Esra Turan

Doctoral Dissertations

In this dissertation, we have developed and combined several statistical techniques in Bayesian factor analysis (BAYFA) and mixture of factor analyzers (MFA) to overcome the shortcoming of these existing methods. Information Criteria are brought into the context of the BAYFA model as a decision rule for choosing the number of factors m along with the Press and Shigemasu method, Gibbs Sampling and Iterated Conditional Modes deterministic optimization. Because of sensitivity of BAYFA on the prior information of the factor pattern structure, the prior factor pattern structure is learned directly from the given sample observations data adaptively using Sparse Root algorithm. …

A New Screening Methodology For Mixture Experiments, Maria Weese

Doctoral Dissertations

Many materials we use in daily life are comprised of a mixture; plastics, gasoline, food, medicine, etc. Mixture experiments, where factors are proportions of components and the response depends only on the relative proportions of the components, are an integral part of product development and improvement. However, when the number of components is large and there are complex constraints, experimentation can be a daunting task. We study screening methods in a mixture setting using the framework of the Cox mixture model [1]. We exploit the easy interpretation of the parameters in the Cox mixture model and develop methods for screening …

A Statistical Analysis Of Key Factors Influencing The Location Of Biomass-Using Facilities, Xu Liu

Masters Theses

Bioenergy and biofuels are emerging industries in the U.S. economy that will require statistical and economical analyses of woody biomass resources, supply chains, and other key factors that influence the siting of industrial facilities. This thesis develops models using logistic regression to improve the understanding of the key factors that influence the locations of existing wood-using bioenergy and biofuels plants, and other wood-using plants. The scope of the study is 13 Southeastern states.¹ Logistic regression models are developed at the state and regional levels. The resolution of the study is the ZIP Code tabulation area (ZCTA). There are 9,416 …

Analyzing The Effects Of Coupons And Promotion In The Grocery Retail Sector, Milena Hanna Chotard

Masters Theses

Modern scanner technology is pervasive throughout the retailing sector of the economy and is almost universal in the food retail industry. Along with loyalty programs, it has led to the development of massive databases which accurately and proficiently track the purchasing habits of customers. Making use of this information is one of the most important efforts in the management of this sector to further increase profitability.

This thesis explores the application of several statistical techniques to extract specific information from two large databases of customer purchasing behavior at a major US grocery chain. In particular, we first focus on the …

Secrets Of A Mississippi Riverboat Gambler, Harlan D. Mills

The Harlan D. Mills Collection

No abstract provided.

Player Win Averages: A Complete Guide To Winning Baseball Players, Eldon G. Mills, Harlan D. Mills

The Harlan D. Mills Collection

No abstract provided.