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Search Publications by: Bonita V. Saunders (Fed)

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Displaying 1 - 25 of 48

Semantic Preserving Bijective Mappings of Mathematical Formulae between Word Processors and Computer Algebra Systems

June 28, 2017
Author(s)
Howard S. Cohl, Bonita V. Saunders, Marjorie A. McClain, Moritz Schubotz, Joon Bang, Juergen Gerhardt, Andre Greiner Petter
There are many different approaches to represent mathematical expressions on computers. Word processors like LaTeX offer the ability to render mathematical expressions as one would write these on paper. Using LaTeX, LaTeXML, and tools generated for use in

Digital Repository of Mathematical Formulae KLS Seeding Project

June 23, 2015
Author(s)
Howard S. Cohl, Marjorie A. McClain, Bonita V. Saunders, Moritz Schubotz, Cherry Y. Zou, Alex A. Danoff, Azeem S. Mohammed
One initial goal for the DRMF is to seed our digital compendium with fundamental orthogonal polynomial formulae. We have received permission from Springer-Verlag and the authors to use formulae from Chapters 1, 9, and 14 from the book "Hypergeometric

Dynamic 3D Visualizations of Complex Function Surfaces Using X3DOM and WebGL

June 1, 2015
Author(s)
Bonita V. Saunders, Brian Antonishek, Qiming Wang, Bruce R. Miller
In 1997 the National Institute of Standards and Technology (NIST) embarked on a huge project to replace one of the most cited resources for mathematical, physical and engineering scientists, the Handbook of Mathematical Functions with Formulas, Graphs, and

Digital Repository of Mathematical Formulae

October 17, 2014
Author(s)
Howard S. Cohl, Marjorie A. McClain, Bonita V. Saunders, Moritz Schubotz, Janelle Williams
The purpose of the NIST Digital Repository of Mathematical Formulae (DRMF) is to create a digital compendium of mathematical formulae for orthogonal polynomials and special functions (OPSF) and of associated mathematical data. The DRMF addresses needs of

Adaptive Composite B-Spline Grid Generation for Interactive 3D Visualizations

January 22, 2014
Author(s)
Bonita V. Saunders, Qiming Wang, Brian Antonishek
We describe an adaptive grid generation technique based on the composition of tensor product B-spline mappings, T and Phi, where Phi maps the unit square onto itself and T maps the unit square onto the desired physical domain. Variational methods are used