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

Numerical Analysis and Scientific Computing Commons

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

1,375 Full-Text Articles 2,127 Authors 383,711 Downloads 109 Institutions

All Articles in Numerical Analysis and Scientific Computing

Faceted Search

1,375 full-text articles. Page 1 of 54.

Integrating Mathematics And Biology In The Classroom: A Compendium Of Case Studies And Labs, Becky Sanft, Anne Walter 2019 University of North Carolina at Asheville

Integrating Mathematics And Biology In The Classroom: A Compendium Of Case Studies And Labs, Becky Sanft, Anne Walter

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.


Quantifying Pollen Traits To Build A Mathematical Model Of Pollen Competition - A Mathematician's Perspective, Montana Ferita, Julie Fucarino, Alex Capaldi, Charlotte Beckford 2019 Westminster College

Quantifying Pollen Traits To Build A Mathematical Model Of Pollen Competition - A Mathematician's Perspective, Montana Ferita, Julie Fucarino, Alex Capaldi, Charlotte Beckford

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.


Period Drift In A Neutrally Stable Stochastic Oscillator, Kevin Sanft 2019 Illinois State University

Period Drift In A Neutrally Stable Stochastic Oscillator, Kevin Sanft

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.


An Agent-Based Model Of An Endangered Florida Tillansia Utriculata Population, Erin N. Bodine, Alexandra Campbell, Anna C. Kula 2019 Rhodes College

An Agent-Based Model Of An Endangered Florida Tillansia Utriculata Population, Erin N. Bodine, Alexandra Campbell, Anna C. Kula

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.


A Machine Learning Model For Clustering Securities, Vanessa Torres, Travis Deason, Michael Landrum, Nibhrat Lohria 2019 Southern Methodist University

A Machine Learning Model For Clustering Securities, Vanessa Torres, Travis Deason, Michael Landrum, Nibhrat Lohria

SMU Data Science Review

In this paper, we evaluate the self-declared industry classifications and industry relationships between companies listed on either the Nasdaq or the New York Stock Exchange (NYSE) markets. Large corporations typically operate in multiple industries simultaneously; however, for investment purposes they are classified as belonging to a single industry. This simple classification obscures the actual industries within which a company operates, and, therefore, the investment risks of that company.
By using Natural Language Processing (NLP) techniques on Security and Exchange Commission (SEC) filings, we obtained self-defined industry classifications per company. Using clustering techniques such as Hierarchical Agglomerative and k-means clustering we ...


A Tale Of Two Bays: The Development And Applications Of The Saco And Casco Modeling Project, Stephen M. Moore 2019 University of Maine

A Tale Of Two Bays: The Development And Applications Of The Saco And Casco Modeling Project, Stephen M. Moore

Electronic Theses and Dissertations

This thesis details the development and application of a finite-volume, hydrodynamic model of Saco and Casco Bays. The primary study conducted herein focused on coupling storm simulations with sea level rise (SLR) to identify vulnerabilities of the two bays. The February 1978 Northeaster and an April freshwater discharge event in 2007 following the Patriot’s Day Storm were modeled by utilizing the Finite-Volume Coastal Ocean Model (FVCOM). Both events were repeatedly simulated under SLR scenarios ranging from 0 to 7 ft. Modeled storm responses were identified from the 1978 blizzard simulations and were tracked across SLR scenarios. By comparing changes ...


Hpc: Hierarchical Phylogeny Construction, Anindya Das, Xiaoqiu Huang 2019 Iowa State University

Hpc: Hierarchical Phylogeny Construction, Anindya Das, Xiaoqiu Huang

Computer Science Publications

Rapid improvements in DNA sequencing technology have resulted in long genome sequences for a large number of similar isolates with a wide range of single nucleotide polymorphism (SNP) rates, where some isolates can have thousands of times lower SNP rates than others. Genome sequences of this kind are a challenge to existing methods for construction of phylogenetic trees. We address the issues by developing a hierarchical approach to phylogeny construction. In this method, the construction is performed at multiple levels, where at each level, groups of isolates with similar levels of similarity are identified and their phylogenetic trees are constructed ...


Bottom-Up Estimation And Top-Down Prediction: Solar Energy Prediction Combining Information From Multiple Sources, Youngdeok Hwang, Siyuan Lu, Jae Kwang Kim 2019 Sungkyunkwan University

Bottom-Up Estimation And Top-Down Prediction: Solar Energy Prediction Combining Information From Multiple Sources, Youngdeok Hwang, Siyuan Lu, Jae Kwang Kim

Jae Kwang Kim

Accurately forecasting solar power using the data from multiple sources is an important but challenging problem. Our goal is to combine two different physics model forecasting outputs with real measurements from an automated monitoring network so as to better predict solar power in a timely manner. To this end, we propose a new approach of analyzing large-scale multilevel models with great computational efficiency requiring minimum monitoring and intervention. This approach features a division of the large scale data set into smaller ones with manageable sizes, based on their physical locations, and fit a local model in each area. The local ...


Longitudinal Analysis With Modes Of Operation For Aes, Dana Geislinger, Cory Thigpen, Daniel W. Engels 2019 Southern Methodist University

Longitudinal Analysis With Modes Of Operation For Aes, Dana Geislinger, Cory Thigpen, Daniel W. Engels

SMU Data Science Review

In this paper, we present an empirical evaluation of the randomness of the ciphertext blocks generated by the Advanced Encryption Standard (AES) cipher in Counter (CTR) mode and in Cipher Block Chaining (CBC) mode. Vulnerabilities have been found in the AES cipher that may lead to a reduction in the randomness of the generated ciphertext blocks that can result in a practical attack on the cipher. We evaluate the randomness of the AES ciphertext using the standard key length and NIST randomness tests. We evaluate the randomness through a longitudinal analysis on 200 billion ciphertext blocks using logistic regression and ...


Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr. 2019 Iowa State University

Seasonal Warranty Prediction Based On Recurrent Event Data, Qianqian Shan, Yili Hong, William Q. Meeker Jr.

William Q Meeker

Warranty return data from repairable systems, such as vehicles, usually result in recurrent event data. The non-homogeneous Poisson process (NHPP) model is used widely to describe such data. Seasonality in the repair frequencies and other variabilities, however, complicate the modeling of recurrent event data. Not much work has been done to address the seasonality, and this paper provides a general approach for the application of NHPP models with dynamic covariates to predict seasonal warranty returns. A hierarchical clustering method is used to stratify the population into groups that are more homogeneous than the than the overall population. The stratification facilitates ...


Predicting Switch-Like Behavior In Proteins Using Logistic Regression On Sequence-Based Descriptors, Benjamin Strauss 2019 San Jose State University

Predicting Switch-Like Behavior In Proteins Using Logistic Regression On Sequence-Based Descriptors, Benjamin Strauss

Master's Projects

Ligands can bind at specific protein locations, inducing conformational changes such as those involving secondary structure. Identifying these possible switches from sequence, including homology, is an important ongoing area of research. We attempt to predict possible secondary structure switches from sequence in proteins using machine learning, specifically a logistic regression approach with 48 N-acetyltransferases as our learning set and 5 sirtuins as our test set. Validated residue binary assignments of 0 (no change in secondary structure) and 1 (change in secondary structure) were determined (DSSP) from 3D X-ray structures for sets of virtually identical chains crystallized under different conditions. Our ...


Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg 2019 Loyola University Chicago

Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

This paper points students towards ideas they can use towards developing a convenient library for robot navigation, with examples based on Botball primitives, and points educators towards mathematics and programming exercises they can suggest to students, especially advanced high school students.


Matrix Shanks Transformations, Claude Brezinski, Michela Redivo-Zaglia 2019 University of Lille, France

Matrix Shanks Transformations, Claude Brezinski, Michela Redivo-Zaglia

Electronic Journal of Linear Algebra

Shanks' transformation is a well know sequence transformation for accelerating the convergence of scalar sequences. It has been extended to the case of sequences of vectors and sequences of square matrices satisfying a linear difference equation with scalar coefficients. In this paper, a more general extension to the matrix case where the matrices can be rectangular and satisfy a difference equation with matrix coefficients is proposed and studied. In the particular case of square matrices, the new transformation can be recursively implemented by the matrix $\varepsilon$-algorithm of Wynn. Then, the transformation is related to matrix Pad\'{e}-type and ...


Krylov Subspace Spectral Methods With Non-Homogenous Boundary Conditions, Abbie Hendley 2019 The University of Southern Mississippi

Krylov Subspace Spectral Methods With Non-Homogenous Boundary Conditions, Abbie Hendley

Master's Theses

For this thesis, Krylov Subspace Spectral (KSS) methods, developed by Dr. James Lambers, will be used to solve a one-dimensional, heat equation with non-homogenous boundary conditions. While current methods such as Finite Difference are able to carry out these computations efficiently, their accuracy and scalability can be improved. We will solve the heat equation in one-dimension with two cases to observe the behaviors of the errors using KSS methods. The first case will implement KSS methods with trigonometric initial conditions, then another case where the initial conditions are polynomial functions. We will also look at both the time-independent and time-dependent ...


Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm 2019 California Polytechnic State University, San Luis Obispo

Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm

Master's Theses and Project Reports

Machine learning has been gaining popularity over the past few decades as computers have become more advanced. On a fundamental level, machine learning consists of the use of computerized statistical methods to analyze data and discover trends that may not have been obvious or otherwise observable previously. These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new material discovery has been of high interest ...


Simulating Epidemics And Interventions On High Resolution Social Networks, Christopher E. Siu 2019 California Polytechnic State University, San Luis Obispo

Simulating Epidemics And Interventions On High Resolution Social Networks, Christopher E. Siu

Master's Theses and Project Reports

Mathematical models of disease spreading are a key factor of ensuring that we are prepared to deal with the next epidemic. They allow us to predict how an infection will spread throughout a population, thereby allowing us to make intelligent choices when attempting to contain the disease. Whether due to a lack of empirical data, a lack of computational power, a lack of biological understanding, or some combination thereof, traditional models must make sweeping assumptions about the behavior of a population during an epidemic.

In this thesis, we implement granular epidemic simulations using a rich social network constructed from real-world ...


Block Glt Sequences: Matrix Functions And Engineering Application, Carlo Garoni, Stefano Serra-Capizzano 2019 University of Insubria

Block Glt Sequences: Matrix Functions And Engineering Application, Carlo Garoni, Stefano Serra-Capizzano

Electronic Journal of Linear Algebra

The theory of block generalized locally Toeplitz (GLT) sequences is a powerful apparatus for computing the spectral distribution of block-structured matrices arising from the discretization of differential problems, with a special reference to systems of differential equations (DEs) and to the higher-order finite element or discontinuous Galerkin approximation of both scalar and vectorial DEs. In the present paper, the theory of block GLT sequences is extended by proving that $\{f(A_n)\}_n$ is a block GLT sequence as long as $f$ is continuous and $\{A_n\}_n$ is a block GLT sequence formed by Hermitian matrices. It is also provided a ...


Classifying Challenging Behaviors In Autism Spectrum Disorder With Neural Document Embeddings, Abigail Atchison 2019 Chapman University

Classifying Challenging Behaviors In Autism Spectrum Disorder With Neural Document Embeddings, Abigail Atchison

Computational and Data Sciences (MS) Theses

The understanding and treatment of challenging behaviors in individuals with Autism Spectrum Disorder is paramount to enabling the success of behavioral therapy; an essential step in this process being the labeling of challenging behaviors demonstrated in therapy sessions. These manifestations differ across individuals and within individuals over time and thus, the appropriate classification of a challenging behavior when considering purely qualitative factors can be unclear. In this thesis we seek to add quantitative depth to this otherwise qualitative task of challenging behavior classification. We do so through the application of natural language processing techniques to behavioral descriptions extracted from the ...


Real-Time Rfi Mitigation In Radio Astronomy, Emily Ramey, Nick Joslyn, Richard Prestage, Michael Lam, Luke Hawkins, Tim Blattner, Mark Whitehead 2019 Washington University in St. Louis

Real-Time Rfi Mitigation In Radio Astronomy, Emily Ramey, Nick Joslyn, Richard Prestage, Michael Lam, Luke Hawkins, Tim Blattner, Mark Whitehead

Senior Honors Papers / Undergraduate Theses

As the use of wireless technology has increased around the world, Radio Frequency Interference (RFI) has become more and more of a problem for radio astronomers. Preventative measures exist to limit the presence of RFI, and programs exist to remove it from saved data, but the use of algorithms to detect and remove RFI as an observation is occurring is much less common. Such a method would be incredibly useful for observations in which the data must undergo several rounds of processing before being saved, as in pulsar timing studies. Strategies for real-time mitigation have been discussed and tested with ...


Arecibo Message, Joshua P. Tan 2019 CUNY La Guardia Community College

Arecibo Message, Joshua P. Tan

Open Educational Resources

This two week assignment asks students to interpret and analyze the 1974 Arecibo Message sent by Drake and Sagan. Week 1 introduces the concepts behind the construction of the message and engages with a critical analysis of the architecture and the contents of the message. Week 2 asks students to develop software in a Jupyter Notebook (available for free from the Anaconda Python Distribution) to interpret messages that were similar to those produced by Drake and Sagan.


Digital Commons powered by bepress