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Positive Definite Functions And Dual Pairs Of Locally Convex Spaces, Daniel Alpay, Saak Gabriyelyan 2018 Chapman University

Positive Definite Functions And Dual Pairs Of Locally Convex Spaces, Daniel Alpay, Saak Gabriyelyan

Mathematics, Physics, and Computer Science Faculty Articles and Research

Using pairs of locally convex topological vector spaces in duality and topologies defined by directed families of sets bounded with respect to the duality, we prove general factorization theorems and general dilation theorems for operator-valued positive definite functions.


Copula Theory And Regression Analysis, Mayooran Thevaraja 2018 Minnesota State University, Mankato

Copula Theory And Regression Analysis, Mayooran Thevaraja

All Graduate Theses, Dissertations, and Other Capstone Projects

Researchers are often interested to study in the relationships between one variable and several other variables. Regression analysis is the statistical method for investigating such relationship and it is one of the most commonly used statistical Methods in many scientific fields such as financial data analysis, medicine, biology, agriculture, economics, engineering, sociology, geology, etc. But basic form of the regression analysis, ordinary least squares is not suitable for actuarial applications because the relationships are often nonlinear and the probability distribution of the response variable may be non-Gaussian distribution. One of the method that has been successful in overcoming these challenges …


Effect Of Neuromodulation Of Short-Term Plasticity On Information Processing In Hippocampal Interneuron Synapses, Elham Bayat Mokhtari 2018 University of Montana

Effect Of Neuromodulation Of Short-Term Plasticity On Information Processing In Hippocampal Interneuron Synapses, Elham Bayat Mokhtari

Graduate Student Theses, Dissertations, & Professional Papers

Neurons convey information about the complex dynamic environment in the form of signals. Computational neuroscience provides a theoretical foundation toward enhancing our understanding of nervous system. The aim of this dissertation is to present techniques to study the brain and how it processes information in particular neurons in hippocampus.

We begin with a brief review of the history of neuroscience and biological background of basic neurons. To appreciate the importance of information theory, familiarity with the information theoretic basics is required, these basics are presented in Chapter 2. In Chapter 3, we use information theory to estimate the amount of …


Multiclass Classification Using Support Vector Machines, Duleep Prasanna W. Rathgamage Don 2018 Georgia Southern University

Multiclass Classification Using Support Vector Machines, Duleep Prasanna W. Rathgamage Don

College of Graduate Studies: Theses & Dissertations

In this thesis, we discuss different SVM methods for multiclass classification and introduce the Divide and Conquer Support Vector Machine (DCSVM) algorithm which relies on data sparsity in high dimensional space and performs a smart partitioning of the whole training data set into disjoint subsets that are easily separable. A single prediction performed between two partitions eliminates one or more classes in a single partition, leaving only a reduced number of candidate classes for subsequent steps. The algorithm continues recursively, reducing the number of classes at each step until a final binary decision is made between the last two classes …


Mathematical Formulation Of Fusion Energy Magnetohydrodynamics, Nikolaos I. Xiros 2017 University of New Orleans, Department of Mathematics

Mathematical Formulation Of Fusion Energy Magnetohydrodynamics, Nikolaos I. Xiros

LSU New Orleans Theses and Dissertations

Chapter 1 presents the basic principles of Controlled Thermonuclear Fusion, and the approaches to achieve nuclear fusion on Earth. Furthermore, the basic components of the Tokamak, the reactor which will house the fusion reaction, are analyzed. Finally, the chapter ends with a discussion on how the present thesis is related to the Controlled Thermonuclear Fusion. Chapter 2 introduces briefly the basic concepts of the Electromagnetic and Magnetohydrodynamic theories as well as MHD turbulence. Chapter 3 presents a first glance in OpenFOAM CFD library. Chapter 4 introduces the Orszag-Tang vortex flow, which is a benchmark test case for MHD numerical models. …


Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr 2017 University of New Orleans, New Orleans

Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr

LSU New Orleans Theses and Dissertations

This project started early in the summer of 2016 when it became evident there was a need for an effective and efficient signal analysis toolkit for the Littoral Acoustic Demonstration Center Gulf Ecological Monitoring and Modeling (LADC-GEMM) Research Consortium. LADC-GEMM collected underwater acoustic data in the northern Gulf of Mexico during the summer of 2015 using Environmental Acoustic Recording Systems (EARS) buoys. Much of the visualization of data was handled through short scripts and executed through terminal commands, each time requiring the data to be loaded into memory and parameters to be fed through arguments. The vision was to develop …


A Statistical Study Of Student Success In The Bgsu Honors College, Sarah Hercules 2017 Bowling Green State University

A Statistical Study Of Student Success In The Bgsu Honors College, Sarah Hercules

Honors Projects

Higher education has long tried to find the best measures to predict student success. Different colleges often have different guidelines, requiring different criteria to be evaluated. The BGSU Honors College has struggled with retention and recruitment of underrepresented students with their current admission criteria. This analysis studies different measures of student success such as BGSU GPA and number of completed Honors credits for high-achieving BGSU students who enrolled from Fall 2013 through Fall 2016 to find the best predictors of student success through regression analysis. Throughout this paper, the impact of ethnicity, gender, the college of a student’s program, high …


Homogenization Techniques For Population Dynamics In Strongly Heterogeneous Landscapes, Brian P. Yurk, Christina A. Cobbold 2017 Hope College

Homogenization Techniques For Population Dynamics In Strongly Heterogeneous Landscapes, Brian P. Yurk, Christina A. Cobbold

Faculty Publications

An important problem in spatial ecology is to understand how population-scale patterns emerge from individual-level birth, death, and movement processes. These processes, which depend on local landscape characteristics, vary spatially and may exhibit sharp transitions through behavioural responses to habitat edges, leading to discontinuous population densities. Such systems can be modelled using reaction–diffusion equations with interface conditions that capture local behaviour at patch boundaries. In this work we develop a novel homogenization technique to approximate the large-scale dynamics of the system. We illustrate our approach, which also generalizes to multiple species, with an example of logistic growth within a periodic …


Flow Anisotropy Due To Thread-Like Nanoparticle Agglomerations In Dilute Ferrofluids, Alexander Cali, Wah-Keat Lee, A. David Trubatch, Philip Yecko 2017 Montclair State University

Flow Anisotropy Due To Thread-Like Nanoparticle Agglomerations In Dilute Ferrofluids, Alexander Cali, Wah-Keat Lee, A. David Trubatch, Philip Yecko

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Improved knowledge of the magnetic field dependent flow properties of nanoparticle-based magnetic fluids is critical to the design of biomedical applications, including drug delivery and cell sorting. To probe the rheology of ferrofluid on a sub-millimeter scale, we examine the paths of 550 μm diameter glass spheres falling due to gravity in dilute ferrofluid, imposing a uniform magnetic field at an angle with respect to the vertical. Visualization of the spheres’ trajectories is achieved using high resolution X-ray phase-contrast imaging, allowing measurement of a terminal velocity while simultaneously revealing the formation of an array of long thread-like accumulations of magnetic …


Making Models With Bayes, Pilar Olid 2017 California State University, San Bernardino

Making Models With Bayes, Pilar Olid

Electronic Theses, Projects, and Dissertations

Bayesian statistics is an important approach to modern statistical analyses. It allows us to use our prior knowledge of the unknown parameters to construct a model for our data set. The foundation of Bayesian analysis is Bayes' Rule, which in its proportional form indicates that the posterior is proportional to the prior times the likelihood. We will demonstrate how we can apply Bayesian statistical techniques to fit a linear regression model and a hierarchical linear regression model to a data set. We will show how to apply different distributions to Bayesian analyses and how the use of a prior affects …


Infinite-Dimensional Measure Spaces And Frame Analysis, Palle Jorgensen, Myung-Sin Song 2017 The University of Iowa

Infinite-Dimensional Measure Spaces And Frame Analysis, Palle Jorgensen, Myung-Sin Song

SIUE Faculty Research, Scholarship, and Creative Activity

We study certain infinite-dimensional probability measures in connection with frame analysis. Earlier work on frame-measures has so far focused on the case of finite-dimensional frames. We point out that there are good reasons for a sharp distinction between stochastic analysis involving frames in finite vs. infinite dimensions. For the case of infinite-dimensional Hilbert space ℋ, we study three cases of measures. We first show that, for ℋ infinite dimensional, one must resort to infinite dimensional measure spaces which properly contain ℋ. The three cases we consider are: (i) Gaussian frame measures, (ii) Markov path-space measures, and (iii) determinantal measures.


Modeling Aggregation Of Proliferating Microglia In Response To Amyloid-Beta In Dementia, Adrienne C. Kinney, Ellen R. Swanson 2017 Centre College

Modeling Aggregation Of Proliferating Microglia In Response To Amyloid-Beta In Dementia, Adrienne C. Kinney, Ellen R. Swanson

Spora: A Journal of Biomathematics

Amyloid-beta plaques are prominent biological markers in dementia brains. In response to plaque formation, the brain's immune cells, microglia, become reactive. Microglia are measurable cells that surround amyloid-beta plaques, indicating their location. A system of partial differential equations describes the concentration of microglia in dementia brains by incorporating chemotactic signaling. However, this system fails to incorporate increasing numbers of reactive microglia cells in response to amyloid-beta aggregation. A system of ordinary differential equations describing the number of significant cells and proteins in the brain suggests the amount of reactive microglia increases significantly during the progression of dementia. We couple these …


Lessons And Perspectives From The Data Science Industry, Elsa Schaefer 2017 Illinois State University

Lessons And Perspectives From The Data Science Industry, Elsa Schaefer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Mathematically Modeling The Impact Of Invasive Crayfish Removal On Oncorhynchus Mykiss Population Dynamics In Topanga Creek, Madison Cox, Courtney Davis PhD, Rosi Dagit 2017 Pepperdine University

Mathematically Modeling The Impact Of Invasive Crayfish Removal On Oncorhynchus Mykiss Population Dynamics In Topanga Creek, Madison Cox, Courtney Davis Phd, Rosi Dagit

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Mathematical Modeling Of Tumor Immune Interactions: A Closer Look At The Role Of A Pd-L1 Inhibitor In Cancer Immunotherapy, Timothy Woods II 2017 Pomona College

Mathematical Modeling Of Tumor Immune Interactions: A Closer Look At The Role Of A Pd-L1 Inhibitor In Cancer Immunotherapy, Timothy Woods Ii

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


A Method For Sensitivity Analysis And Parameter Estimation Applied To A Large Reaction-Diffusion Model Of Cell Polarization, Marissa Renardy, Tau-Mu Yi, Dongbin Xiu, Ching-Shan Chou 2017 The Ohio State University

A Method For Sensitivity Analysis And Parameter Estimation Applied To A Large Reaction-Diffusion Model Of Cell Polarization, Marissa Renardy, Tau-Mu Yi, Dongbin Xiu, Ching-Shan Chou

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Drawbacks Of Utilizing The Logit Link In Propensity Score Weighting Adjustment, Evrim Oral 2017 LSUHSC, School of Public Health, Biostatistics Program

Drawbacks Of Utilizing The Logit Link In Propensity Score Weighting Adjustment, Evrim Oral

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Handguns And Hotspots: Spatio- Temporal Models For Gun Violence In Chicago,Il, Shelby Scott 2017 University of Tennessee, Knoxville

Handguns And Hotspots: Spatio- Temporal Models For Gun Violence In Chicago,Il, Shelby Scott

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Development Of Epithelial Tissues: How Are Cleavage Planes Chosen?, Ying Xin 2017 Ohio University - Main Campus

Development Of Epithelial Tissues: How Are Cleavage Planes Chosen?, Ying Xin

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


Mathematical Medicine: Modeling Disease And Treatment, Lisette dePillis 2017 Illinois State University

Mathematical Medicine: Modeling Disease And Treatment, Lisette Depillis

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.


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