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Articles 61 - 90 of 217
Full-Text Articles in Physical Sciences and Mathematics
Sleep Patterns, Urinary Levels Of Melatonin And Subsequent Weight Change In The Women’S Health Initiative Observational Study, Nicole M. Barron
Sleep Patterns, Urinary Levels Of Melatonin And Subsequent Weight Change In The Women’S Health Initiative Observational Study, Nicole M. Barron
Masters Theses
Results from prospective studies examining associations between sleep duration and weight gain have been mixed. Melatonin has been hypothesized to mediate the association between sleep duration and weight/body composition. In cross-sectional studies, aMT6s has been shown to be inversely associated with weight/body fat percentage. We examined associations between baseline sleep duration, insomnia status, aMT6s levels with weight/body fat percentage through 6 years, utilizing a subset 690 women who participated in a breast cancer case-control study nested within the WHI-OS. Multi-variable and mixed-effects regression was used to calculate beta-coefficients and 95% confidence intervals. Cross-sectional analyses showed urinary aMT6s levels were inversely …
Who Is Like Whom? Reclassification And Performance Patterns For Different Groupings Of English Learners, Molly M. Faulkner-Bond
Who Is Like Whom? Reclassification And Performance Patterns For Different Groupings Of English Learners, Molly M. Faulkner-Bond
Doctoral Dissertations
Approximately 10 percent of the US K-12 population consists of English learners (ELs), or students who are learning English in addition to academic content in areas like English language arts (ELA) and mathematics. In addition to meeting the same academic content and performance standards set for all students, it is also a goal for ELs to be reclassified – i.e., to master English so that they can shed the EL label and participate in academic settings where English is used without needing special support. Working with a longitudinal cohort of ~28,000 ELs in grades 3 through 8 from one state, …
Joint Analysis Of Zero-Heavy Longitudinal Outcomes: Models And Comparison Of Study Designs, Erin R. Lundy
Joint Analysis Of Zero-Heavy Longitudinal Outcomes: Models And Comparison Of Study Designs, Erin R. Lundy
Electronic Thesis and Dissertation Repository
Understanding the patterns and mechanisms of the process of desistance from criminal activity is imperative for the development of effective sanctions and legal policy. Methodological challenges in the analysis of longitudinal criminal behaviour data include the need to develop methods for multivariate longitudinal discrete data, incorporating modulating exposure variables and several possible sources of zero-inflation. We develop new tools for zero-heavy joint outcome analysis which address these challenges and provide novel insights on processes related to offending patterns. Comparisons with existing approaches demonstrate the benefits of utilizing modeling frameworks which incorporate distinct sources of zeros. An additional concern in this …
Computational Modeling Of Facial Response For Detecting Differential Traits In Autism Spectrum Disorders, Manar D. Samad
Computational Modeling Of Facial Response For Detecting Differential Traits In Autism Spectrum Disorders, Manar D. Samad
Electrical & Computer Engineering Theses & Dissertations
This dissertation proposes novel computational modeling and computer vision methods for the analysis and discovery of differential traits in subjects with Autism Spectrum Disorders (ASD) using video and three-dimensional (3D) images of face and facial expressions. ASD is a neurodevelopmental disorder that impairs an individual’s nonverbal communication skills. This work studies ASD from the pathophysiology of facial expressions which may manifest atypical responses in the face. State-of-the-art psychophysical studies mostly employ na¨ıve human raters to visually score atypical facial responses of individuals with ASD, which may be subjective, tedious, and error prone. A few quantitative studies use intrusive sensors on …
Analysis Off Dependent Discrete Choices Using Gaussian Copula, Arjun Poddar
Analysis Off Dependent Discrete Choices Using Gaussian Copula, Arjun Poddar
Mathematics & Statistics Theses & Dissertations
A popular tool for analyzing product choices of consumers is the well-known conditional logit discrete choice model. Originally publicized by McFadden (1974), this model assumes that the random components of the underlying latent utility functions of the consumers follow independent Gumbel distributions. However, in practice the independence assumption may be violated and a more reasonable model should account for the dependence of the utilities. In this dissertation we use the Gaussian copula with compound symmetric and autoregressive of order one correlation matrices to construct a general multivariate model for the joint distribution of the utilities. The induced correlations on the …
Novel Methods For Analyzing Longitudinal Data With Measurement Error In The Time Variable, Caroline Munindi Mulatya
Novel Methods For Analyzing Longitudinal Data With Measurement Error In The Time Variable, Caroline Munindi Mulatya
Theses and Dissertations
In some longitudinal studies, the observed time points are often confounded with measurement error due to the sampling conditions, resulting into data with measurement error in the time variable. This type of data occurs mainly in observational studies when the onset of a longitudinal process is unknown or in clinical trials when individual visits do not take place as specified by the study protocol, but are often rounded to coincide with the study protocol. Methodological and inferential implications of error in time varying covariates for both linear and nonlinear models have been studied widely. In this dissertation, we shift attention …
Bayesian Nonparametric Approaches To Multiple Testing, Density Estimation, And Supervised Learning, William Cipolli Iii
Bayesian Nonparametric Approaches To Multiple Testing, Density Estimation, And Supervised Learning, William Cipolli Iii
Theses and Dissertations
This dissertation presents methods for several applications of Polya tree models. These novel nonparametric approaches to the problems of multiple testing, density estimation and supervised learning provide an alternative to other parametric and nonparametric models. In Chapter 2, the proposed approximate finite Polya tree multiple testing procedure is very successful in correctly classifying the observations with non-zero mean in a computationally efficient manner; this holds even when the non-zero means are simulated from a mean-zero distribution. Further, the model is capable of this for “interestingly different” observations in the cases where that is of interest. Chapter 3 proposes discrete, and …
Development And Application Of Bayesian Semiparametric Models For Dependent Data, Junshu Bao
Development And Application Of Bayesian Semiparametric Models For Dependent Data, Junshu Bao
Theses and Dissertations
Dependent data are very common in many research fields, such as medicine (repeated measures), finance (time series), traffic (clustered), etc. Effective control/modeling of the dependency among data can enhance the performance of the models and result in better prediction. In many cases, the correlation itself may be of great interest. In this dissertation, we develop novel Bayesian semi-/nonparametric regression models to analyze data with various dependence structures. In Chapter 2, a Bayesian non- parametric multivariate ordinal regression model is proposed to fit drinking behavior survey data from DWI offenders. The responses are two-dimensional ordinal data, drinking frequency and drinking quantity …
The Effects Of Age And Gender On Pedestrian Traffic Injuries: A Random Parameters And Latent Class Analysis, Tatok Raharjo Raharjo
The Effects Of Age And Gender On Pedestrian Traffic Injuries: A Random Parameters And Latent Class Analysis, Tatok Raharjo Raharjo
USF Tampa Graduate Theses and Dissertations
Pedestrians are vulnerable road users because they do not have any protection while they walk. They are unlike cyclists and motorcyclists who often have at least helmet protection and sometimes additional body protection (in the case of motorcyclists with body-armored jackets and pants). In the US, pedestrian fatalities are increasing and becoming an ever larger proportion of overall roadway fatalities (NHTSA, 2016), thus underscoring the need to study factors that influence pedestrian-injury severity and potentially develop appropriate countermeasures. One of the critical elements in the study of pedestrian-injury severities is to understand how injuries vary across age and gender ‒ …
Joint Modelling In Liver Transplantation, Elizabeth M. Renouf
Joint Modelling In Liver Transplantation, Elizabeth M. Renouf
Electronic Thesis and Dissertation Repository
In the setting of liver transplantation, clinical trials and transplant registries regularly collect repeated measurements of clinical biomarkers which may be strongly associated with a time-to-event such as graft failure or disease recurrence. Multiple time-to-event outcomes are routinely collected. However, joint models are rarely used. This thesis will describe important considerations for joint modelling in the setting of liver transplantation. We will focus on transplant registry data from the United States. We develop a new tool for joint modelling in the context where a critical health event can be tracked in the longitudinal biomarker and often presents as a non-linear …
Statistical Analysis And Modeling Health Data: A Longitudinal Study, Bhikhari Prasad Tharu
Statistical Analysis And Modeling Health Data: A Longitudinal Study, Bhikhari Prasad Tharu
USF Tampa Graduate Theses and Dissertations
Lung cancer has been considered one of the leading causes of deaths while cancer re- mains the second most common cause of deaths in the USA. Understanding the behavior of a disease over time could yield important information to make decisions about the disease. Statistical models could provide crucial clues and help to make a decision about the dis- ease, budget allocation, evaluation, and implement prevention. Longitudinal trend analysis of the diseases helps to understand long term effects and nature. Cholesterol level is one of the most contributing risk factors for Coronary Heart Disease. Studying cholesterol statistically helps to know …
Stochastic Processes And Their Applications To Change Point Detection Problems, Heng Yang
Stochastic Processes And Their Applications To Change Point Detection Problems, Heng Yang
Dissertations, Theses, and Capstone Projects
This dissertation addresses the change point detection problem when either the post-change distribution has uncertainty or the post-change distribution is time inhomogeneous. In the case of post-change distribution uncertainty, attention is drawn to the construction of a family of composite stopping times. It is shown that the proposed composite stopping time has third order optimality in the detection problem with Wiener observations and also provides information to distinguish the different values of post-change drift. In the case of post-change distribution uncertainty, a computationally efficient decision rule with low-complexity based on Cumulative Sum (CUSUM) algorithm is also introduced. In the time …
Statistical Modeling Of Carbon Dioxide And Cluster Analysis Of Time Dependent Information: Lag Target Time Series Clustering, Multi-Factor Time Series Clustering, And Multi-Level Time Series Clustering, Doo Young Kim
USF Tampa Graduate Theses and Dissertations
The current study consists of three major parts. Statistical modeling, the connection between statistical modeling and cluster analysis, and proposing new methods to cluster time dependent information.
First, we perform a statistical modeling of the Carbon Dioxide (CO2) emission in South Korea in order to identify the attributable variables including interaction effects. One of the hot issues in the earth in 21st century is Global warming which is caused by the marriage between atmospheric temperature and CO2 in the atmosphere. When we confront this global problem, we first need to verify what causes the problem then we …
Computing The (Un)Computable: A Computationally-Augmented Perspective On The Yasukuni Shrine Controversy, Ryan Muther
Computing The (Un)Computable: A Computationally-Augmented Perspective On The Yasukuni Shrine Controversy, Ryan Muther
Honors Theses
Computational methods have been used with increasing frequency in the social sciences and humanities, due to the availability of digital sources and computing power to study everything from changes in the meanings of words in Latin texts to how knowledge was categorized in eighteen century encyclopedias. Recent trends in the fields of digital humanities and computational social science include statistical methods like machine learning, requiring large pre-tagged and annotated sets of documents which in turn necessitates a great deal of prior work to create data to use with such methods. This reliance on large corpora of annotated data limits the …
Thinking Poker Through Game Theory, Damian Palafox
Thinking Poker Through Game Theory, Damian Palafox
Electronic Theses, Projects, and Dissertations
Poker is a complex game to analyze. In this project we will use the mathematics of game theory to solve some simplified variations of the game. Probability is the building block behind game theory. We must understand a few concepts from probability such as distributions, expected value, variance, and enumeration methods to aid us in studying game theory. We will solve and analyze games through game theory by using different decision methods, decision trees, and the process of domination and simplification. Poker models, with and without cards, will be provided to illustrate optimal strategies. Extensions to those models will be …
Metals Additive Manufacturing Powder Aging Characterization, Thomas Russell Lovejoy, Nicholas Karl Muetterties, David Takeo Otsu
Metals Additive Manufacturing Powder Aging Characterization, Thomas Russell Lovejoy, Nicholas Karl Muetterties, David Takeo Otsu
Mechanical Engineering
The metallic additive manufacturing process known as selective laser melting requires highly spherical, normally distributed powder with diameters in the range of 10 to 50 microns. Previous observations have shown a degradation in powder quality over time, resulting in unwanted characteristics in the final printed parts. 21-6-9 stainless steel powder was used to fabricate test parts, with leftover powder recycled back into the machine. Powder samples and test specimens were characterized to observe changes across build cycles. Few changes were observed in the physical and mechanical properties of the specimens, however, there were indications of chemical changes across cycles. Potential …
Statistical Methodology For Data With Multiple Limits Of Detection, Robert M. Flikkema
Statistical Methodology For Data With Multiple Limits Of Detection, Robert M. Flikkema
Dissertations
Limitations of instruments used to collect continuous data sometimes lead to obtaining observations lower than a limit of detection. These observations are known as nondetects. They could be zeroes, or positive numbers, but they are too small to be recorded by a measuring device. Nondetects frequently occur in environmental data. Trace amounts of chemicals can exist in soil or groundwater and are undetectable by a machine reading. These observations pose a problem to researchers since the true values are unknown.
Simulations in the literature have led to inconsistent conclusions regarding what estimation technique to use with nondetect data when estimating …
Time Dependent Kernel Density Estimation: A New Parameter Estimation Algorithm, Applications In Time Series Classification And Clustering, Xing Wang
USF Tampa Graduate Theses and Dissertations
The Time Dependent Kernel Density Estimation (TDKDE) developed by Harvey & Oryshchenko (2012) is a kernel density estimation adjusted by the Exponentially Weighted Moving Average (EWMA) weighting scheme. The Maximum Likelihood Estimation (MLE) procedure for estimating the parameters proposed by Harvey & Oryshchenko (2012) is easy to apply but has two inherent problems. In this study, we evaluate the performances of the probability density estimation in terms of the uniformity of Probability Integral Transforms (PITs) on various kernel functions combined with different preset numbers. Furthermore, we develop a new estimation algorithm which can be conducted using Artificial Neural Networks to …
Elements Of The Mathematical Formulation Of Quantum Mechanics, Keunjae Go
Elements Of The Mathematical Formulation Of Quantum Mechanics, Keunjae Go
Senior Honors Papers / Undergraduate Theses
In this paper, we will explore some of the basic elements of the mathematical formulation of quantum mechanics. In the first section, I will list the motivations for introducing a probability model that is quite different from that of the classical probability theory, but still shares quite a few significant commonalities. Later in the paper, I will discuss the quantum probability theory in detail, while paying a brief attention to some of the axioms (by Birkhoff and von Neumann) that illustrate both the commonalities and differences between classical mechanics and quantum mechanics. This paper will end with a presentation of …
Quantifying Transit Access In New York City: Formulating An Accessibility Index For Analyzing Spatial And Social Patterns Of Public Transportation, Maxwell S. Siegel
Quantifying Transit Access In New York City: Formulating An Accessibility Index For Analyzing Spatial And Social Patterns Of Public Transportation, Maxwell S. Siegel
Theses and Dissertations
This paper aims to analyze accessibility within New York City’s transportation system through creating unique accessibility indices. Indices are detailed and implemented using GIS, analyzing the distribution of transit need and access. Regression analyses are performed highlighting relationships between demographics and accessibility and recommendations for transit expansion are presented.
Genetic Imputation: Accuracy To Application, Shelina Raynell Ramnarine
Genetic Imputation: Accuracy To Application, Shelina Raynell Ramnarine
Arts & Sciences Electronic Theses and Dissertations
Genotype imputation, the process of inferring genotypes for untyped variants, is used to identify and refine genetic association findings. This body of work focuses on assessing imputation accuracy and uses imputed data to identify genetic contributors to mentholated cigarette preference.
Inaccuracies in imputed data can distort the observed association between variants and a disease. Many statistics are used to assess accuracy; some compare imputed to genotyped data and others are calculated without reference to true genotypes. Prior work has shown that the Imputation Quality Score (IQS), which is based on Cohens kappa statistic and compares imputed genotype probabilities to true …
Market Effect: The Impact Of For-Profit Charter Schools On Racial And Socioeconomic Segregation, William Brett Robertson
Market Effect: The Impact Of For-Profit Charter Schools On Racial And Socioeconomic Segregation, William Brett Robertson
Arts & Sciences Electronic Theses and Dissertations
For-profit charter schools are a controversial new development in public education. They combine a structural imperative to maximize profit for private shareholders with the social good of providing public education. This dissertation describes two analyses of for-profit charter schools designed to explore their impact on racial and socioeconomic segregation. The analyses utilize geographic information systems, multilevel modeling, and logistic regression to determine whether and how for-profit charter schools are likely to locate in demographically different neighborhoods, and/or educate demographically different student populations from other types of public schools. The results indicate that for-profit charter schools are less likely than other …
Distributed Target Tracking And Synchronization In Wireless Sensor Networks, Jichuan Li
Distributed Target Tracking And Synchronization In Wireless Sensor Networks, Jichuan Li
McKelvey School of Engineering Theses & Dissertations
Wireless sensor networks provide useful information for various applications but pose challenges in scalable information processing and network maintenance. This dissertation focuses on statistical methods for distributed information fusion and sensor synchronization for target tracking in wireless sensor networks.
We perform target tracking using particle filtering. For scalability, we extend centralized particle filtering to distributed particle filtering via distributed fusion of local estimates provided by individual sensors. We derive a distributed fusion rule from Bayes' theorem and implement it via average consensus. We approximate each local estimate as a Gaussian mixture and develop a sampling-based approach to the nonlinear fusion …
Examining Cost Functionality And Optimization: A Case Study On Testing The Reasonableness Of New Aircraft Using Historical Aircraft Data, Katherine Jozefiak
Examining Cost Functionality And Optimization: A Case Study On Testing The Reasonableness Of New Aircraft Using Historical Aircraft Data, Katherine Jozefiak
Arts & Sciences Electronic Theses and Dissertations
When pursuing business by competing for government contracts, proving the submitted price is reasonable is often required. This proof is called a test of reasonableness. This study analyzes data from historical aircraft programs in relation of a new aircraft program in order to demonstrate the estimated cost of the new program is reasonable. The purpose of this study is to investigate three questions. Is the new program cost reasonable using current industry and government parameters? Is it better to look at programs from a total cost perspective or break the total cost into subcategory levels? Finally, this study applies a …
Spot Volatility Estimation Of Ito Semimartingales Using Delta Sequences, Weixuan Gao
Spot Volatility Estimation Of Ito Semimartingales Using Delta Sequences, Weixuan Gao
Arts & Sciences Electronic Theses and Dissertations
This thesis studies a unifying class of nonparametric spot volatility estimators proposed by Mancini et. al.(2013). This method is based on delta sequences and is conceived to include many of the existing estimators in the field as special cases. The thesis first surveys the asymptotic theory of the proposed estimators under an infill asymptotic scheme and fixed time horizon, when the state variable follows a Brownian semimartingale. Then, some extensions to include jumps and financial microstructure noise in the observed price process are also presented. The main goal of the thesis is to assess the suitability of the proposed methods …
Lead Poisoning In United States Children, Zeren Zhou
Lead Poisoning In United States Children, Zeren Zhou
Arts & Sciences Electronic Theses and Dissertations
We investigate factors related to blood lead levels of children ages 1 to 5 in the United States for the years 2007-2014. We use data from the National Health and Nutrition Examination Survey (NHANES). The goal is to explore predictors of lead in childrens' blood and to develop a multivariate model using as many predictors as possible. The analysis is conducted using SAS survey regression procedures that account for weighting, stratification, and clustering of the data.
Classification Trees And Rule-Based Modeling Using The C5.0 Algorithm For Self-Image Across Sex And Race In St. Louis, Rohan Shirali
Classification Trees And Rule-Based Modeling Using The C5.0 Algorithm For Self-Image Across Sex And Race In St. Louis, Rohan Shirali
Arts & Sciences Electronic Theses and Dissertations
The study population comprised children, adolescents, and adults who were residents of the city of St. Louis at the time of data collection in 2015. The data collected includes sex, age, race, measured height and weight, self-reported height and weight, zip code, educational background, exercise and diet habits, and descriptions and strategies of participants' weight (i.e. overweight and trying to lose weight, respectively). I use the C5.0 algorithm to create classification trees and rule-based models to analyze this population. Specifically, I model a binary self-image variable as a function of sex, age, race, zip code, and a ratio of reported …
Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, Jason A. Teichman
Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, Jason A. Teichman
University of New Orleans Theses and Dissertations
Sea state is a subjective quantity whose accuracy depends on an observer’s ability to translate local wind waves into numerical scales. It provides an analytical tool for estimating the impact of the sea on data quality and operational safety. Tasks dependent on the characteristics of local sea surface conditions often require accurate and immediate assessment. An attempt to automate sea state classification using eleven years of ship motion and sea state observation data is made using parametric modeling of distribution-based confidence and tolerance intervals and a probabilistic model using sea state frequencies. Models utilizing distribution intervals are not able to …
Population Projection And Habitat Preference Modeling Of The Endangered James Spinymussel (Pleurobema Collina), Marisa Draper
Population Projection And Habitat Preference Modeling Of The Endangered James Spinymussel (Pleurobema Collina), Marisa Draper
Senior Honors Projects, 2010-2019
The James Spinymussel (Pleurobema collina) is an endangered mussel species at the top of Virginia’s conservation list. The James Spinymussel plays a critical role in the environment by filtering and cleaning stream water while providing shelter and food for macroinvertebrates; however, conservation efforts are complicated by the mussels’ burrowing behavior, camouflage, and complex life cycle. The goals of the research conducted were to estimate detection probabilities that could be used to predict species presence and facilitate field work, and to track individually marked mussels to test for habitat preferences. Using existing literature and mark-recapture field data, these goals were accomplished …
The Relationship Between Time Of Day, Mood, And Electroencephalography (Eeg) Asymmetry, Morgan Tantillo
The Relationship Between Time Of Day, Mood, And Electroencephalography (Eeg) Asymmetry, Morgan Tantillo
Honors Projects
Previous researchers have had success in finding a correlation between exercise and an increase in positive mood. Researchers have also found a correlation between time of day and mood. The current study will explore the relationship between time of day, mood, and electroencephalography (EEG) asymmetry. The study utilized a convenient sample of ten undergraduate students at Bowling Green State University. Participants had baseline EEG recordings taken, and then participated in moderate exercise, followed by another EEG recording. Participants’ mood was assessed through a self-reported mood questionnaire before the condition as well as immediately after. Due to multiple statistical tests, the …