Open Access. Powered by Scholars. Published by Universities.®

Applied Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

6,611 Full-Text Articles 7,740 Authors 1,967,775 Downloads 226 Institutions

All Articles in Applied Mathematics

Faceted Search

6,611 full-text articles. Page 1 of 230.

Supplementary Files For "Creating A Universal Depth-To-Load Conversion Technique For The Conterminous United States Using Random Forests", Jesse Wheeler, Brennan Bean, Marc Maguire 2021 University of Michigan-Ann Arbor

Supplementary Files For "Creating A Universal Depth-To-Load Conversion Technique For The Conterminous United States Using Random Forests", Jesse Wheeler, Brennan Bean, Marc Maguire

Browse all Datasets

As part of an ongoing effort to update the ground snow load maps in the United States, this paper presents an investigation into snow densities for the purpose of predicting ground snow loads for structural engineering design with ASCE 7. Despite their importance, direct measurements of snow load are sparse when compared to measurements of snow depth. As a result, it is often necessary to estimate snow load using snow depth and other readily accessible climate variables. Existing depth-to-load conversion methods, each of varying complexity, are well suited for snow load estimation for a particular region or station network, but ...


Coevolution Of Hosts And Pathogens In The Presence Of Multiple Types Of Hosts, Evan J. Mitchell 2021 The University of Western Ontario

Coevolution Of Hosts And Pathogens In The Presence Of Multiple Types Of Hosts, Evan J. Mitchell

Electronic Thesis and Dissertation Repository

How will hosts and pathogens coevolve in response to multiple types of hosts? I study this question from three different perspectives. First, I model a scenario in which hosts are categorized as female or male. Hosts invest resources in maintaining their immune system at a cost to their reproductive success, while pathogens face a trade-off between transmission and duration of infection. Importantly, female hosts are also able to vertically transmit an infection to their newborn offspring. The main result is that as the rate of vertical transmission increases, female hosts will have a greater incentive to pay the cost to ...


Development Of A Low Field Mri-Based Approach For Observation Of Water Penetration Into Clay: Preliminary Results, Shivam Gupta 2021 Western University

Development Of A Low Field Mri-Based Approach For Observation Of Water Penetration Into Clay: Preliminary Results, Shivam Gupta

Undergraduate Student Research Internships Conference

Magnetic resonance imaging (MRI) are considered one of the most efficient and non-invasive methods of observing water content in permeable substances. MRI can visualize and quantify the movement of water in real time. In this study, MRI was used to observe the water penetration through clay. Furthermore, MRI can acquire three-dimensional data due to its radio-frequency signals from any orientation. The contrast of the images produced by MRI is a display of the fluid concentration. As such, any change in the contrast intensity is interpreted as a regional change in the concentration of fluid. This report summarizes the preliminary results ...


Symphas: A Modular Api For Phase-Field Modeling Using Compile-Time Symbolic Algebra, Steven A. Silber 2021 The University of Western Ontario

Symphas: A Modular Api For Phase-Field Modeling Using Compile-Time Symbolic Algebra, Steven A. Silber

Electronic Thesis and Dissertation Repository

The phase-field method is a common approach to qualitative analysis of phase transitions. It allows visualizing the time evolution of a phase transition, providing valuable insight into the underlying microstructure and the dynamical processes that take place. Although the approach is applied in a diverse range of fields, from metal-forming to cardiac modelling, there are a limited number of software tools available that allow simulating any phase-field problem and that are highly accessible. To address this, a new open source API and software package called SymPhas is developed for simulating phase-field and phase-field crystal in 1-, 2- and 3-dimensions. Phase-field ...


Ciculant Matrix And Fft, Thomas S. Devries 2021 Western University

Ciculant Matrix And Fft, Thomas S. Devries

Undergraduate Student Research Internships Conference

The goal was to produce all the eigen values for a BOHEMIAN matrices using coefficient set {0, 1, -1, i, -i} of a size 15 vector. There are 5^15 eigen values so it was attempted to be done in parrallel for parts of the algorithm that permitted.


An Upper Bound On The Spectral P-Norms Of Tensors And Matrix Permanent, Killian J. Hitsman, Vehbi E. Paksoy 2021 Nova Southeastern University

An Upper Bound On The Spectral P-Norms Of Tensors And Matrix Permanent, Killian J. Hitsman, Vehbi E. Paksoy

Mako: NSU Undergraduate Student Journal

No abstract provided.


Using An Analytical Approach Of The Kuramoto Model To Stimulate 3d Neural Activity Of The Stomach, Morteza Al Rabya 2021 Western University

Using An Analytical Approach Of The Kuramoto Model To Stimulate 3d Neural Activity Of The Stomach, Morteza Al Rabya

Undergraduate Student Research Internships Conference

No abstract provided.


Eigenvalue Problems On Atypical Domains - The Finite Element Method, Toufiic Ayoub 2021 Western University

Eigenvalue Problems On Atypical Domains - The Finite Element Method, Toufiic Ayoub

Undergraduate Student Research Internships Conference

Why do we care about eigenvalues and eigenvectors? What's the big deal? For many people enrolled in entry level linear algebra courses, these concepts seem like far fetched abstractions that become pointless exercises in computation. But in reality, these fundamental ideas are vital to how we live our lives every single day. But how?


Simulating Dislocation Densities With Finite Element Analysis, Ja'Nya Breeden, Dow Drake, Saurabh Puri 2021 Francis Marion University

Simulating Dislocation Densities With Finite Element Analysis, Ja'nya Breeden, Dow Drake, Saurabh Puri

REU Final Reports

A one-dimensional set of nonlinear time-dependent partial differential equations developed by Acharya (2010) is studied to observe how differing levels of applied strain affect dislocation walls. The framework of this model consists of a convective and diffusive term which is used to develop a linear system of equations to test two methods of the finite element method. The linear system of partial differential equations is used to determine whether the standard or Discontinuous Galerkin method will be used. The Discontinuous Galerkin method is implemented to discretize the continuum model and the results of simulations involving zero and non-zero applied strain ...


Optimal Information Design In Two-Sided Trade, Pradhi Aggarwal 2021 Yale University

Optimal Information Design In Two-Sided Trade, Pradhi Aggarwal

The Yale Undergraduate Research Journal

In a two-sided market with a broker, the broker can influence the buyer’s and seller’s optimal trading behaviour through strategic information design. We study the impact of information about waiting times on riders and drivers in a rideshare market. We consider three information regimes: the first in which no information about time is revealed, the second in which true waiting times are communicated, and finally an intermediate regime in which agents are only told whether their waiting time falls within a high or low category. We evaluate the optimality of each information regime by maximizing welfare and revenue ...


Applications Of Bayesian Inference For Modelling Dynamic Instability In Neuronal Dendrite Morphogenesis, Daniel Fridman 2021 Yale University

Applications Of Bayesian Inference For Modelling Dynamic Instability In Neuronal Dendrite Morphogenesis, Daniel Fridman

The Yale Undergraduate Research Journal

Neurons are complex biological systems which develop intricate morphologies and whose dendrites are essential in receiving and integrating input signals from neighboring neurons. While much research has been done on the role of dendrites in neuronal development, a further understanding of dendrite dynamics can provide insight into neural development and the cellular basis of neurological diseases such as schizophrenia, Down’s syndrome, and autism. The Jonathon Howard lab hypothesizes that microtubules are a primary driving force in dendrite dynamics. Since it is known that microtubules display dynamic instability, rapidly transitioning between growth, paused, and shrinking states, the Howard lab proposes ...


Credit Risk Measurement And Application Based On Bp Neural Networks, Jingshi Luo 2021 The University of Western Ontario

Credit Risk Measurement And Application Based On Bp Neural Networks, Jingshi Luo

Electronic Thesis and Dissertation Repository

The emergence of P2P(Peer-to-peer) lending has opened up a popular way for micro-finance, and the financial lending industry in many countries is growing rapidly. While it facilitates lending to individuals and small and medium-sized enterprises, improving the risk identification capability of the P2P platform is vitally necessary for the sustainable development of the platform. Especially the potential credit risk caused by information asymmetry, this may be fatal to this industry. In order to alleviate the adverse effects of this problem, this paper takes Lending Club’s real loan data as the empirical research object. The random forest is used ...


Modeling Weather Vulnerability Dynamically: Applications Of Multiple Linear Regression To Weather Index Microinsurance, Sophie Wu 2021 Western University

Modeling Weather Vulnerability Dynamically: Applications Of Multiple Linear Regression To Weather Index Microinsurance, Sophie Wu

Undergraduate Student Research Internships Conference

This paper offers a broad overview of the philanthropic goals of microinsurance — namely, to provide vulnerable populations with more self-sufficient and sustainable methods of coping with risk — and through this lens, analyses the applications of multiple linear regression in developing dynamic models for microinsurance. We explain the foundations of MLR (multiple linear regression), and then give two examples for how a simple multiple linear regression model can be adapted with a novel outcome variable (famine) and dependent variables (climate change related costs). Overall, a better understanding of MLR can lend to a better understanding of how microinsurance can scale its ...


Euler's Three-Body Problem, Sylvio R. Bistafa 2021 University of Sao Paulo

Euler's Three-Body Problem, Sylvio R. Bistafa

Euleriana

In physics and astronomy, Euler's three-body problem is to solve for the motion of a body that is acted upon by the gravitational field of two other bodies. This problem is named after Leonhard Euler (1707-1783), who discussed it in memoirs published in the 1760s. In these publications, Euler found that the parameter that controls the relative distances among three collinear bodies is given by a quintic equation. Later on, in 1772, Lagrange dealt with the same problem, and demonstrated that for any three masses with circular orbits, there are two special constant-pattern solutions, one where the three bodies ...


On The Application Of Principal Component Analysis To Classification Problems, Jianwei Zheng, Cyril Rakovski 2021 Chapman University

On The Application Of Principal Component Analysis To Classification Problems, Jianwei Zheng, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Principal Component Analysis (PCA) is a commonly used technique that uses the correlation structure of the original variables to reduce the dimensionality of the data. This reduction is achieved by considering only the first few principal components for a subsequent analysis. The usual inclusion criterion is defined by the proportion of the total variance of the principal components exceeding a predetermined threshold. We show that in certain classification problems, even extremely high inclusion threshold can negatively impact the classification accuracy. The omission of small variance principal components can severely diminish the performance of the models. We noticed this phenomenon in ...


Client Access Feature Engineering For The Homeless Community Of The City Of Portland, Oswaldo Ceballos Jr 2021 University of Texas at Austin

Client Access Feature Engineering For The Homeless Community Of The City Of Portland, Oswaldo Ceballos Jr

altREU Projects

Given the severity of homeless in many cities across the country, the project at hand attempts to assist a service provider organization called Central City Concern (CCC) with their mission of providing services to the community of Portland. These services include housing, recovery, health care, and jobs. With many different types of services available through the works of CCC, there exists an abundance of information and data pertaining to the individuals that interact with the CCC service system. The goal of this project is to perform an exploratory analysis and feature engineer the existing datasets CCC has collected over the ...


Empirical Fitting Of Periodically Repeating Environmental Data, Pavel Bělík, Andrew Hotchkiss, Brandon Perez, John Zobitz 2021 Augsburg University

Empirical Fitting Of Periodically Repeating Environmental Data, Pavel Bělík, Andrew Hotchkiss, Brandon Perez, John Zobitz

Spora: A Journal of Biomathematics

We extend and generalize an approach to conduct fitting models of periodically repeating data. Our method first detrends the data from a baseline function and then fits the data to a periodic (trigonometric, polynomial, or piecewise linear) function. The polynomial and piecewise linear functions are developed from assumptions of continuity and differentiability across each time period. We apply this approach to different datasets in the environmental sciences in addition to a synthetic dataset. Overall the polynomial and piecewise linear approaches developed here performed as good (or better) compared to the trigonometric approach when evaluated using statistical measures (R2 or ...


Growth-Profile Configuration For Specific Deformations Of Tubular Organs: A Study Of Growth-Induced Thinning And Dilation Of The Human Cervix, Kun Gou, Seungik Baek, Marvin M.F. Lutnesky, Hai-Chao Han 2021 Texas A&M University-San Antonio

Growth-Profile Configuration For Specific Deformations Of Tubular Organs: A Study Of Growth-Induced Thinning And Dilation Of The Human Cervix, Kun Gou, Seungik Baek, Marvin M.F. Lutnesky, Hai-Chao Han

Mathematics Faculty Publications

Growth is a significant factor that results in deformations of tubular organs, and particular deformations associated with growth enable tubular organs to perform certain physiological functions. Configuring growth profiles that achieve particular deformation patterns is critical for analyzing potential pathological conditions and for developing corresponding clinical treatments for tubular organ dysfunctions. However, deformation-targeted growth is rarely studied. In this article, the human cervix during pregnancy is studied as an example to show how cervical thinning and dilation are generated by growth. An advanced hyperelasticity theory called morphoelasticity is employed to model the deformations, and a growth tensor is used to ...


A Fast Method For Computing Volume Potentials In The Galerkin Boundary Element Method In 3d Geometries, Sasan Mohyaddin 2021 Southern Methodist University

A Fast Method For Computing Volume Potentials In The Galerkin Boundary Element Method In 3d Geometries, Sasan Mohyaddin

Mathematics Theses and Dissertations

We discuss how the Fast Multipole Method (FMM) applied to a boundary concentrated mesh can be used to evaluate volume potentials that arise in the boundary element method. If $h$ is the meshwidth near the boundary, then the algorithm can compute the potential in nearly $\Ord(h^{-2})$ operations while maintaining an $\Ord(h^p)$ convergence of the error. The effectiveness of the algorithms are demonstrated by solving boundary integral equations of the Poisson equation.


Fast Multipole Methods For Wave And Charge Source Interactions In Layered Media And Deep Neural Network Algorithms For High-Dimensional Pdes, Wenzhong Zhang 2021 Southern Methodist University

Fast Multipole Methods For Wave And Charge Source Interactions In Layered Media And Deep Neural Network Algorithms For High-Dimensional Pdes, Wenzhong Zhang

Mathematics Theses and Dissertations

In this dissertation, we develop fast algorithms for large scale numerical computations, including the fast multipole method (FMM) in layered media, and the forward-backward stochastic differential equation (FBSDE) based deep neural network (DNN) algorithms for high-dimensional parabolic partial differential equations (PDEs), addressing the issues of real-world challenging computational problems in various computation scenarios.

We develop the FMM in layered media, by first studying analytical and numerical properties of the Green's functions in layered media for the 2-D and 3-D Helmholtz equation, the linearized Poisson--Boltzmann equation, the Laplace's equation, and the tensor Green's functions for the time-harmonic Maxwell ...


Digital Commons powered by bepress