Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 12 of 12
Full-Text Articles in Physical Sciences and Mathematics
Reconstructing Historical Earthquake-Induced Tsunamis: Case Study Of 1820 Event Near South Sulawesi, Indonesia, Taylor Jole Paskett
Reconstructing Historical Earthquake-Induced Tsunamis: Case Study Of 1820 Event Near South Sulawesi, Indonesia, Taylor Jole Paskett
Theses and Dissertations
We build on the method introduced by Ringer, et al., applying it to an 1820 event that happened near South Sulawesi, Indonesia. We utilize other statistical models to aid our Metropolis-Hastings sampler, including a Gaussian process which informs the prior. We apply the method to multiple possible fault zones to determine which fault is the most likely source of the earthquake and tsunami. After collecting nearly 80,000 samples, we find that between the two most likely fault zones, the Walanae fault zone matches the anecdotal accounts much better than Flores. However, to support the anecdotal data, both samplers tend toward …
Exploring Improvements To The Convergence Of Reconstructing Historical Destructive Earthquakes, Kameron Lightheart
Exploring Improvements To The Convergence Of Reconstructing Historical Destructive Earthquakes, Kameron Lightheart
Theses and Dissertations
Determining risk to human populations due to natural disasters has been a topic of interest in the STEM fields for centuries. Earthquakes and the tsunamis they cause are of particular interest due to their repetition cycles. These cycles can last hundreds of years but we have only had modern measuring instruments for the last century or so which makes analysis difficult. In this document, we explore ways to improve upon an existing method for reconstructing earthquakes from historical accounts of tsunamis. This method was designed and implemented by Jared P Whitehead's research group over the last 5 years. The issue …
An Actuarial Approach To Personal Injury Protection Severity, Jason Colgrove
An Actuarial Approach To Personal Injury Protection Severity, Jason Colgrove
Undergraduate Honors Theses
Insurance companies examine the risk of financial losses for their policyholders as a way to accurately price insurance policies. Within the automobile insurance sector, the frequency of crashes and the associated liabilities started to increase in late 2013 when it had been on the decline for close to a decade. The purpose of this research focuses on the possible correlated variables that could lead to a better understanding of this change. To embark on this task, we teamed up with the Society of Actuaries, Casualty Actuarial Society, and the American Property Casualty Insurance Association to obtain data regarding frequency, severity, …
Using Machine Learning To Accurately Predict Ambient Soundscapes From Limited Data Sets, Katrina Lynn Pedersen
Using Machine Learning To Accurately Predict Ambient Soundscapes From Limited Data Sets, Katrina Lynn Pedersen
Theses and Dissertations
The ability to accurately characterize the soundscape, or combination of sounds, of diverse geographic areas has many practical implications. Interested parties include the United States military and the National Park Service, but applications also exist in areas such as public health, ecology, community and social justice noise analyses, and real estate. I use an ensemble of machine learning models to predict ambient sound levels throughout the contiguous United States. Our data set consists of 607 training sites, where various acoustic metrics, such as overall daytime L50 levels and one-third octave frequency band levels, have been obtained. I have data for …
A Bayesian Decision Theoretical Approach To Supervised Learning, Selective Sampling, And Empirical Function Optimization, James Lamond Carroll
A Bayesian Decision Theoretical Approach To Supervised Learning, Selective Sampling, And Empirical Function Optimization, James Lamond Carroll
Theses and Dissertations
Many have used the principles of statistics and Bayesian decision theory to model specific learning problems. It is less common to see models of the processes of learning in general. One exception is the model of the supervised learning process known as the "Extended Bayesian Formalism" or EBF. This model is descriptive, in that it can describe and compare learning algorithms. Thus the EBF is capable of modeling both effective and ineffective learning algorithms. We extend the EBF to model un-supervised learning, semi-supervised learning, supervised learning, and empirical function optimization. We also generalize the utility model of the EBF to …
Modeling Temperature Reduction In Tendons Using Gaussian Processes Within A Dynamic Linear Model, Richard David Wyss
Modeling Temperature Reduction In Tendons Using Gaussian Processes Within A Dynamic Linear Model, Richard David Wyss
Theses and Dissertations
The time it takes an athlete to recover from an injury can be highly influenced by training procedures as well as the medical care and physical therapy received. When an injury occurs to the muscles or tendons of an athlete, it is desirable to cool the muscles and tendons within the body to reduce inflammation, thereby reducing the recovery time. Consequently, finding a method of treatment that is effective in reducing tendon temperatures is beneficial to increasing the speed at which the athlete is able to recover. In this project, Bayesian inference with Gaussian processes will be used to model …
Sensitivity To Distributional Assumptions In Estimation Of The Odp Thresholding Function, Wendy Jill Bunn
Sensitivity To Distributional Assumptions In Estimation Of The Odp Thresholding Function, Wendy Jill Bunn
Theses and Dissertations
Recent technological advances in fields like medicine and genomics have produced high-dimensional data sets and a challenge to correctly interpret experimental results. The Optimal Discovery Procedure (ODP) (Storey 2005) builds on the framework of Neyman-Pearson hypothesis testing to optimally test thousands of hypotheses simultaneously. The method relies on the assumption of normally distributed data; however, many applications of this method will violate this assumption. This thesis investigates the sensitivity of this method to detection of significant but nonnormal data. Overall, estimation of the ODP with the method described in this thesis is satisfactory, except when the nonnormal alternative distribution has …
A Simulation-Based Approach For Evaluating Gene Expression Analyses, Carly Ruth Pendleton
A Simulation-Based Approach For Evaluating Gene Expression Analyses, Carly Ruth Pendleton
Theses and Dissertations
Microarrays enable biologists to measure differences in gene expression in thousands of genes simultaneously. The data produced by microarrays present a statistical challenge, one which has been met both by new modifications of existing methods and by completely new approaches. One of the difficulties with a new approach to microarray analysis is validating the method's power and sensitivity. A simulation study could provide such validation by simulating gene expression data and investigating the method's response to changes in the data; however, due to the complex dependencies and interactions found in gene expression data, such a simulation would be complicated and …
A Comparison Of Microarray Analyses: A Mixed Models Approach Versus The Significance Analysis Of Microarrays, Nathan Wallace Stephens
A Comparison Of Microarray Analyses: A Mixed Models Approach Versus The Significance Analysis Of Microarrays, Nathan Wallace Stephens
Theses and Dissertations
DNA microarrays are a relatively new technology for assessing the expression levels of thousands of genes simultaneously. Researchers hope to find genes that are differentially expressed by hybridizing cDNA from known treatment sources with various genes spotted on the microarrays. The large number of tests involved in analyzing microarrays has raised new questions in multiple testing. Several approaches for identifying differentially expressed genes have been proposed. This paper considers two: (1) a mixed models approach, and (2) the Signiffcance Analysis of Microarrays.
A Logistic Regression Analysis Of Utah Colleges Exit Poll Response Rates Using Sas Software, Clint W. Stevenson
A Logistic Regression Analysis Of Utah Colleges Exit Poll Response Rates Using Sas Software, Clint W. Stevenson
Theses and Dissertations
In this study I examine voter response at an interview level using a dataset of 7562 voter contacts (including responses and nonresponses) in the 2004 Utah Colleges Exit Poll. In 2004, 4908 of the 7562 voters approached responded to the exit poll for an overall response rate of 65 percent. Logistic regression is used to estimate factors that contribute to a success or failure of each interview attempt. This logistic regression model uses interviewer characteristics, voter characteristics (both respondents and nonrespondents), and exogenous factors as independent variables. Voter characteristics such as race, gender, and age are strongly associated with response. …
Bayesian And Positive Matrix Factorization Approaches To Pollution Source Apportionment, Jeff William Lingwall
Bayesian And Positive Matrix Factorization Approaches To Pollution Source Apportionment, Jeff William Lingwall
Theses and Dissertations
The use of Positive Matrix Factorization (PMF) in pollution source apportionment (PSA) is examined and illustrated. A study of its settings is conducted in order to optimize them in the context of PSA. The use of a priori information in PMF is examined, in the form of target factor profiles and pulling profile elements to zero. A Bayesian model using lognormal prior distributions for source profiles and source contributions is fit and examined.
Development Of Commercial Applications For Recycled Plastics Using Finite Element Analysis, Nanjunda Narasimhamurthy
Development Of Commercial Applications For Recycled Plastics Using Finite Element Analysis, Nanjunda Narasimhamurthy
Theses and Dissertations
This thesis investigates the suitability of thermo-kinetically recycled plastics for use in commercial product applications using finite element analysis and statistics. Different recycled material blends were tested and evaluated for their use in commercial product applications. There are six different blends of thermo-kinetically recycled plastics used for testing and CATIA is used for finite element analysis. The different types of thermo-kinetically recycled plastics blends are: pop bottles made of PolyethyleneTeraphthalate (PET), milk jugs made of High-Density Polyethylene (HDPE), Vinyl seats made of Poly Vinyl Chloride (PVC) and small amount of Polypropylene (PP) and Urethane, electronic scrap made of engineering resins …