The University of Western Ontario
AAR Aerospace Consulting, LLC
University of Nevada, Las Vegas
University of New Hampshire, Durham
University of Nebraska-Lincoln
The University of New Orleans
Foundations Of Wave Phenomena: Complete Version,
2016
Department of Physics, Utah State University
Foundations Of Wave Phenomena: Complete Version, Charles G. Torre
Foundations of Wave Phenomena
This is the complete version of Foundations of Wave Phenomena. Version 8.2.
Please click here to explore the components of this work.
How Steep Is Steep? Learning Curves In Training Undergraduates To Do Fluid-Structure Interaction Modeling,
2016
University of North Carolina at Chapel Hill
How Steep Is Steep? Learning Curves In Training Undergraduates To Do Fluid-Structure Interaction Modeling, Nicholas A. Battista
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Interplay Of Quantum Size Effect, Anisotropy And Surface Stress Shapes The Instability Of Thin Metal Films,
2016
Western Kentucky University
Interplay Of Quantum Size Effect, Anisotropy And Surface Stress Shapes The Instability Of Thin Metal Films, Mikhail Khenner
Mikhail Khenner
Krylov Subspace Spectral Method With Multigrid For A Time-Dependent, Variable-Coefficient Partial Differential Equation,
2016
The University of Southern Mississippi
Krylov Subspace Spectral Method With Multigrid For A Time-Dependent, Variable-Coefficient Partial Differential Equation, Haley Renee Dozier
Master's Theses
Krylov Subspace Spectral (KSS) methods are traditionally used to solve time-dependent, variable-coefficient PDEs. They are high-order accurate, component-wise methods that are efficient with variable input sizes.
This thesis will demonstrate how one can make KSS methods even more efficient by using a Multigrid-like approach for low-frequency components. The essential ingredients of Multigrid, such as restriction, residual correction, and prolongation, are adapted to the timedependent case. Then a comparison of KSS, KSS with Multigrid, KSS-EPI and standard Krylov projection methods will be demonstrated.
An Algorithm For The Machine Calculation Of Minimal Paths,
2016
East Tennessee State University
An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger
Electronic Theses and Dissertations
Problems involving the minimization of functionals date back to antiquity. The mathematics of the calculus of variations has provided a framework for the analytical solution of a limited class of such problems. This paper describes a numerical approximation technique for obtaining machine solutions to minimal path problems. It is shown that this technique is applicable not only to the common case of finding geodesics on parameterized surfaces in R3, but also to the general case of finding minimal functionals on hypersurfaces in Rn associated with an arbitrary metric.
Mathematical Hybrid Models For Image Segmentation.,
2016
University of Louisville
Mathematical Hybrid Models For Image Segmentation., Carlos M. Paniagua Mejia
UofL Electronic Theses and Dissertations
Two hybrid image segmentation models that are able to process a wide variety of images are proposed. The models take advantage of global (region) and local (edge) data of the image to be segmented. The first one is a region-based PDE model that incorporates a combination of global and local statistics. The influence of each statistic is controlled using weights obtained via an asymptotically stable exponential function. Through incorporation of edge information, the second model extends the capabilities of a strictly region-based variational formulation, making it able to process more general images. Several examples are provided showing the improvements of ...
An Averaging Method For Advection-Diffusion Equations,
2016
Graduate Center, City University of New York
An Averaging Method For Advection-Diffusion Equations, Nicholas Spizzirri
All Graduate Works by Year: Dissertations, Theses, and Capstone Projects
Many models for physical systems have dynamics that happen over various different time scales. For example, contrast the everyday waves in the ocean with the larger, slowly moving global currents. The method of multiple scales is an approach for approximating the solutions of differential equations by separating out the dynamics at slower and faster time scales. In this work, we apply the method of multiple scales to generic advection-diffusion equations (both linear and non-linear, and in arbitrary spatial dimensions) and develop a method for 'averaging out' the faster scale phenomena, giving us an 'effective' solution for the slower scale dynamics ...
Mathematical Models Of Biofilm For Antimicrobial Persistence,
2016
University of North Carolina at Chapel Hill
Mathematical Models Of Biofilm For Antimicrobial Persistence, Jia Zhao
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modelling The Polarization, Migration And Neuromast Deposition In The Zebrafish Posterior Lateral Line System,
2016
University of British Columbia
Modelling The Polarization, Migration And Neuromast Deposition In The Zebrafish Posterior Lateral Line System, Hildur Knutsdottir
Biology and Medicine Through Mathematics Conference
No abstract provided.
Spatial Patterning In The York River Tidal Marshes Through The Interaction Of Cordgrass, Mussels And Sediment,
2016
College of William and Mary
Spatial Patterning In The York River Tidal Marshes Through The Interaction Of Cordgrass, Mussels And Sediment, Sofya Zaytseva, Leah Shaw, Rom Lipcius, Junping Shi
Biology and Medicine Through Mathematics Conference
No abstract provided.
Low Energy Defibrillation By Synchronization; 90 % Less Energy Compared To One Shock.,
2016
Georgia Institute of Technology
Low Energy Defibrillation By Synchronization; 90 % Less Energy Compared To One Shock., Flavio H. Fenton, Yanyan Ji, Ilija Uzelac, Niels Otani, Elizabeth M. Cherry
Biology and Medicine Through Mathematics Conference
No abstract provided.
Explicitly Separating Growth And Motility In A Glioblastoma Tumor Model,
2016
Arizona State University
Explicitly Separating Growth And Motility In A Glioblastoma Tumor Model, Tracy Stepien, Erica Rutter, Meng Fan, Yang Kuang
Biology and Medicine Through Mathematics Conference
No abstract provided.
Force Generation And Contraction Of Random Actomyosin Bundles.,
2016
Courant Institute (NYU)
Force Generation And Contraction Of Random Actomyosin Bundles., Dietmar B. Oelz
Biology and Medicine Through Mathematics Conference
No abstract provided.
General Existence Results For Abstract Mckean-Vlasov Stochastic Equations With Variable Delay,
2016
West Chester University of Pennsylvania
General Existence Results For Abstract Mckean-Vlasov Stochastic Equations With Variable Delay, Mark A. Mckibben
Mathematics
Results concerning the global existence and uniqueness of mild solutions for a class of first-order abstract stochastic integro-differential equations with variable delay in a real separable Hilbert space in which we allow the nonlinearities at a given time t to depend not only on the state of the solution at time t, but also on the corresponding probability distribution at time t are established. The classical Lipschitz is replaced by a weaker so-called Caratheodory condition under which we still maintain uniqueness. The time-dependent case is discussed, as well as an extension of the theory to the case of a nonlocal ...
Non-Compact Solutions To Inverse Mean Curvature Flow In Hyperbolic Space,
2016
University of Tennessee - Knoxville
Non-Compact Solutions To Inverse Mean Curvature Flow In Hyperbolic Space, Brian Daniel Allen
Doctoral Dissertations
We investigate Inverse Mean Curvature Flow (IMCF) of non-compact hypersurfaces in hyperbolic space. Specifically, we look at bounded graphs over horospheres in Hyperbolic space and show long time existence of the flow as well as asymptotic convergence to horospheres. Along the way many important local estimates as well as global estimates are obtained. In addition, we develop a useful family of cutoff functions for IMCF as well as a non-compact ODE maximum principle at infinity which are integral tools used throughout the document.
Solution Techniques And Error Analysis Of General Classes Of Partial Differential Equations,
2016
Boise State University
Solution Techniques And Error Analysis Of General Classes Of Partial Differential Equations, Wijayasinghe Arachchige Waruni Nisansala Wijayasinghe
Boise State University Theses and Dissertations
While constructive insight for a multitude of phenomena appearing in the physical and biological sciences, medicine, engineering and economics can be gained through the analysis of mathematical models posed in terms of systems of ordinary and partial differential equations, it has been observed that a better description of the behavior of the investigated phenomena can be achieved through the use of functional differential equations (FDEs) or partial functional differential equations (PFDEs). PFDEs or functional equations with ordinary derivatives are subclasses of FDEs. FDEs form a general class of differential equations applied in a variety of disciplines and are characterized by ...
Procesy Cieplne I Aparaty (Lab),
2016
Wroclaw University of Technology
2. Population,
2016
Illinois Mathematics and Science Academy
2. Population, Ruth Dover
Differential Equations
Introduction to logistic population growth.
4. Dragging Along,
2016
Illinois Mathematics and Science Academy
3: Drugs And De's,
2016
Illinois Mathematics and Science Academy
3: Drugs And De's, Ruth Dover
Differential Equations
Making a connection between discrete recursion and differential equations.
