In the more than 15 years since the second edition of Fundamentals of Machining and Machine Tools was published, the industry has seen many changes. Students must keep up with developments in analytical modeling of machining processes, modern cutting tool materials, and how these changes affect the economics of machining. With coverage reflecting state-of-the-art industry practice, Fundamentals of Machining and Machine Tools, Third Edition emphasizes underlying concepts, analytical methods, and economic considerations, requiring only basic mathematics and physics.
Supplying abundant examples, illustrations, and homework problems, Fundamentals of Machining and Machine Tools, Third Edition is an ideal textbook for senior undergraduate and graduate students studying metal cutting, machining, machine tool technology, machining applications, and manufacturing processes.
This is a short, easy to read manual on dowsing. Dowsing is known around the world by different names like divining, witching, radiesthesia and many others. It has been used since ancient times to locate water wells, find a variety of things or get answers to questions about almost any topic. Dowsing is an easy way to access universal information with the use of a simple mechanical tool. It doesn't take any special ability so anyone can to do it. Many are surprised at how easy it is. The purpose of Dowsing as a Daily Tool is to provide a practical 'how-to' for this time-proven skill. You can read it in a few hours and have a good idea of how to use dowsing in your life right away. Instead of a mystery, you get an easy-to-follow procedure. As well as many basic and advanced techniques, this edition has more information about the different instruments used for dowsing. It now includes responses for the bobber, Y-rod and L-rods in addition to those for the pendulum. This short book is for anyone who wants to step beyond conventional thinking and be more self-empowered. Dowsing as a Daily Tool is your every-day guide to 'intuition on demand.'
Semiotics as a Tool for Learning Mathematics is a collection of ten theoretical and empirical chapters, from researchers all over the world, who are interested in semiotic notions and their practical uses in mathematics classrooms. Collectively, they present a semiotic contribution to enhance pedagogical aspects both for the teaching of school mathematics and for the preparation of pre-service teachers. This enhancement involves the use of diagrams to visualize implicit or explicit mathematical relations and the use of mathematical discourse to facilitate the emergence of inferential reasoning in the process of argumentation. It will also facilitate the construction of proofs and solutions of mathematical problems as well as the progressive construction of mathematical conceptions that, eventually, will approximate the concept(s) encoded in mathematical symbols. These symbols hinge not only of mental operations but also on indexical and iconic aspects; aspects which often are not taken into account when working on the meaning of mathematical symbols. For such an enhancement to happen, it is necessary to transform basic notions of semiotic theories to make them usable for mathematics education. In addition, it is also necessary to back theoretical claims with empirical data. This anthology attempts to deal with such a conjunction. Overall, this book can be used as a theoretical basis for further semiotic considerations as well as for the design of different ways of teaching mathematical concepts.
Google Keywords and Search Results tell an interesting tale about our private and public lives. The results tell us as a society where we place our priorities in America. Are we in alignment? Read and find out.
Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.
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