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Digital
System Dynamics for Mechanical Engineers
Authors: ---
ISBN: 9781461492931 9781461492924 9781461492948 9781493953844 Year: 2015 Publisher: New York, NY Springer

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Abstract

This textbook is ideal for mechanical engineering students preparing to enter the workforce during a time of rapidly accelerating technology, where they will be challenged to join interdisciplinary teams. It explains system dynamics using analogies familiar to the mechanical engineer while introducing new content in an intuitive fashion. The fundamentals provided in this book prepare the mechanical engineer to adapt to continuous technological advances with topics outside traditional mechanical engineering curricula by preparing them to apply basic principles and established approaches to new problems. This book also: · Reinforces the connection between the subject matter and engineering reality · Includes an instructor pack with the online publication that describes in-class experiments with minimal preparation requirements · Provides content dedicated to the modeling of modern interdisciplinary technological subjects, including opto-mechanical systems, high-speed manufacturing equipment, and measurement systems · Incorporates MATLAB® programming examples throughout the text · Incorporates MATLAB® examples that animate the dynamics of systems.


Digital
Bioinformatics for Immunomics
Authors: --- ---
ISBN: 9781441905406 9781441905413 9781441905390 9781461424857 Year: 2010 Publisher: New York, NY Springer

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Abstract

The field of Immunomics has developed within the post-genomic era as a response to the massive amount of biological and immunological data now available to researchers. Immunomics crosses the disciplines of immunology, genomics, proteomics and computational biology and address some fundamental problems in biological and medical research. This book covers some of the rich sources of immunological data that are currently available and describes the various bioinformatics techniques that have been utilized to aid our understanding of the immune system. It also describes the nature of the self/non-self distinction that forms the basis of immunological theory and how computational modeling can help to clarify our understanding of how the immune system works.

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