The Finite Element Method (FEM) has become an indispensable technology for the modelling and simulation of engineering systems. Written for engineers and students alike, the aim of the book is to provide the necessary theories and techniques of the FEM for readers to be able to use a commercial FEM package to solve primarily linear problems...

Now in its third edition, Strategic Thinking, takes you step by step through the questions to ask, in order to formulate strategies and write clear and concise strategic plans. Based on three core actions - creating knowledge, innovating ideas and implementing change -...

Trading Options in Turbulent Markets, Second Edition skillfully explains the intricacies of options volatility and shows you how to use options to cope, and profit from, market turbulence. Throughout this new...

Starting from a basic knowledge of mathematics and mechanics gained in standard foundation classes, Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave takes the reader conceptually through from the fundamental mechanics of lift  to the stage of actually being able to make practical calculations and...

Industrial Prognostics predicts an industrial system's lifespan using probability measurements to determine the way a machine operates. Prognostics are essential in determining being able to predict and stop failures before they occur. Therefore the development of dependable prognostic procedures for engineering systems is important to...

Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop...

What do people learn when they do not know that they are learning? Until recently all of the work in the area of implicit learning focused on empirical questions and methods. In this book, Axel Cleeremans explores unintentional learning from an information-processing perspective. He introduces a theoretical framework that unifies existing...

• Explore the different types of classification algorithms available in Apache Mahout
• Create and evaluate your own ready-to-use classification models using real world datasets
• A practical guide to...

We weigh every significant decision based on how it will affect our future. But when it comes to figuring that out, we mostly make the process up as we go along. While financial professional Peter Neuwirth can't help you actually predict the future, he can offer...

Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You’ll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a...