Mathematical Methods for Scientists and Engineers (Donald A. McQuarrie)

Data Analysis: Statistical and Computational Methods for Scientists and Engineers

Spend your few moment to read a book even only few pages. Reading book is not obligation and force for everybody. When you don't want to read, you can get punishment from the publisher. Read a book becomes a choice of your different characteristics. Many people with reading habit will always be enjoyable to read, or on the contrary. For some reasons, this data analysis statistical and computati...

Parallel Numerical Methods Course for Future Scientists and Engineers

The rise of computational science has facilitated rapid progress in many areas of science and technology over the last decade. There is a growing demand in computational scientists and engineers capable of efficient collaboration in interdisciplinary groups. Training such specialists includes courses on numerical analysis and parallel computing. In this paper we present a new Master’s course Pa...

Python for Scientists and Engineers

D uring the past decade, Python (an interpreted, high-level programming language) has arguably become the de facto standard for exploratory, interactive, and computation-driven scientific research. This issue discusses Python’s advantages for scientific research and presents several of the core Python libraries and tools used in this domain. Although the issue’s articles are selfcontained, they...

Scientists and Engineers

A Unified Approach to Mathematical Optimization and Lagrange Multiplier Theory for Scientists and Engineers

It should be no surprise that the differentiation of functionals (real valued functions) defined on abstract spaces plays a fundamental role in continuous optimization theory and applications. Differential tools were the major part of the early calculus of variations and actually it was their use that motivated the terminology calculus of variations. The tools that we develop that allow us to w...