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Articles 1 - 10 of 10
Full-Text Articles in Physical Sciences and Mathematics
Joint Asymptotics For Smoothing Spline Semiparametric Nonlinear Models, Jiahui Yu
Joint Asymptotics For Smoothing Spline Semiparametric Nonlinear Models, Jiahui Yu
Doctoral Dissertations
We study the joint asymptotics of general smoothing spline semiparametric models in the settings of density estimation and regression. We provide a systematic framework which incorporates many existing models as special cases, and further allows for nonlinear relationships between the finite-dimensional Euclidean parameter and the infinite-dimensional functional parameter. For both density estimation and regression, we establish the local existence and uniqueness of the penalized likelihood estimators for our proposed models. In the density estimation setting, we prove joint consistency and obtain the rates of convergence of the joint estimator in an appropriate norm. The convergence rate of the parametric component …
Characterization Of The Anomalous Ph Of Aqueous Nanoemulsions, Kieran P. Ramos
Characterization Of The Anomalous Ph Of Aqueous Nanoemulsions, Kieran P. Ramos
Doctoral Dissertations
Aqueous water-in-oil nanoemulsions have emerged as a versatile tool for use in microfluidics, drug delivery, single-molecule measurements, and other research. Nanoemulsions are often prepared with perfluorocarbons which are remarkably biocompatbile due to their stability, low surface tension, lipophobicity, and hydrophobicity. Therefore it is often assumed that droplet contents are unperturbed by the perfluorinated surface. However, in microemulsions, which are similar to nanoemulsions, it is known that either the pH of the aqueous phase or the ionization constants of encapsulated molecules are different from bulk solution. There is also recent evidence of low pH in perfluorinated aqueous nanoemulsions. The current underlying …
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Doctoral Dissertations
Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …
Model-Form Uncertainty Quantification For Predictive Probabilistic Graphical Models, Jinchao Feng
Model-Form Uncertainty Quantification For Predictive Probabilistic Graphical Models, Jinchao Feng
Doctoral Dissertations
In this thesis, we focus on Uncertainty Quantification and Sensitivity Analysis, which can provide performance guarantees for predictive models built with both aleatoric and epistemic uncertainties, as well as data, and identify which components in a model have the most influence on predictions of our quantities of interest. In the first part (Chapter 2), we propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, …
Adaptive Feature Engineering Modeling For Ultrasound Image Classification For Decision Support, Hatwib Mugasa
Adaptive Feature Engineering Modeling For Ultrasound Image Classification For Decision Support, Hatwib Mugasa
Doctoral Dissertations
Ultrasonography is considered a relatively safe option for the diagnosis of benign and malignant cancer lesions due to the low-energy sound waves used. However, the visual interpretation of the ultrasound images is time-consuming and usually has high false alerts due to speckle noise. Improved methods of collection image-based data have been proposed to reduce noise in the images; however, this has proved not to solve the problem due to the complex nature of images and the exponential growth of biomedical datasets. Secondly, the target class in real-world biomedical datasets, that is the focus of interest of a biopsy, is usually …
Allocative Poisson Factorization For Computational Social Science, Aaron Schein
Allocative Poisson Factorization For Computational Social Science, Aaron Schein
Doctoral Dissertations
Social science data often comes in the form of high-dimensional discrete data such as categorical survey responses, social interaction records, or text. These data sets exhibit high degrees of sparsity, missingness, overdispersion, and burstiness, all of which present challenges to traditional statistical modeling techniques. The framework of Poisson factorization (PF) has emerged in recent years as a natural way to model high-dimensional discrete data sets. This framework assumes that each observed count in a data set is a Poisson random variable $y ~ Pois(\mu)$ whose rate parameter $\mu$ is a function of shared model parameters. This thesis examines a specific …
Methods For Making Policy-Relevant Forecasts Of Infectious Disease Incidence, Stephen A. Lauer
Methods For Making Policy-Relevant Forecasts Of Infectious Disease Incidence, Stephen A. Lauer
Doctoral Dissertations
Infectious diseases place an enormous burden on the people of the developing world and their governments. When, where, and how to allocate resources in order to slow the spread of a virus or deal with the aftermath of an outbreak is often the responsibility of local public health officials. In this thesis, we develop statistical methods for forecasting future incidence of infectious diseases and estimating the effects of interventions designed to reduce future incidence, bearing in mind the needs and concerns of those public health officials. While most infectious disease forecasting models focus on short-term horizons (i.e. weeks or …
Population Viability And Connectivity Of The Federally Threatened Eastern Indigo Snake In Central Peninsular Florida, Javan Bauder
Population Viability And Connectivity Of The Federally Threatened Eastern Indigo Snake In Central Peninsular Florida, Javan Bauder
Doctoral Dissertations
Understanding the factors influencing the likelihood of persistence of real-world populations requires both an accurate understanding of the traits and behaviors of individuals within those populations (e.g., movement, habitat selection, survival, fecundity, dispersal) but also an understanding of how those traits and behaviors are influenced by landscape features. The federally threatened eastern indigo snake (EIS, Drymarchon couperi) has declined throughout its range primarily due to anthropogenically-induced habitat loss and fragmentation making spatially-explicit assessments of population viability and connectivity essential for understanding its current status and directing future conservation efforts. The primary goal of my dissertation was to understand how …
Reliability Analysis For Systems With Outsourced Components, Zhengwei Hu
Reliability Analysis For Systems With Outsourced Components, Zhengwei Hu
Doctoral Dissertations
"The current business model for many industrial firms is to function as system integrators, depending on numerous outsourced components from outside component suppliers. This practice has resulted in tremendous cost savings; it makes system reliability analysis, however, more challenging due to the limited component information available to system designers. The component information is often proprietary to component suppliers. Motivated by the need of system reliability prediction with outsourced components, this work aims to explore feasible ways to accurately predict the system reliability during the system design stage. Four methods are proposed. The first method reconstructs component reliability functions using limited …
Novel Statistical Modeling Of Sleep Patterns In Drosophila Melanogaster, Luyang Wang
Novel Statistical Modeling Of Sleep Patterns In Drosophila Melanogaster, Luyang Wang
Doctoral Dissertations
”Sleep is one of the most important behaviors in animals, yet many aspects of sleep are not well understood. In humans, sleep has been shown to impact different aspects of health and cognitive performance. The fruit fly, Drosophila melanogaster, can be used as a model organism to investigate sleep patterns over an entire lifespan. The sleep-wake status can be recorded every minute over the life of individual flies, resulting in a wealth of data for identifying meaningful aspects of sleep. In this work, a framework based on statistical modeling methods is developed for sleep data collected on fruit flies …