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COLT
Patented in 1836, the Colt pistol with its revolving cylinder was the first practical firearm that could shoot more than one bullet without reloading. Its most immediate impact was on the expansionism of the American west, where white emigrants and US soldiers came to depend on it, and where Native Americans came to dread it. In making the revolver, Colt also changed American manufacturing, and revolutionized industry in the United States. Rasenberger brings the brazenly ambitious and profoundly innovative industrialist and leader Samuel Colt to vivid life. During an age of promise and progress, and also of slavery, corruption, and unbridled greed, Colt not only helped to create this America, he completely embodied it.-- adapted from info provided
This book is tailored for students and professionals as well as novices from other fields to mass spectrometry. It will guide them from the basics to the successful application of mass spectrometry in their daily research. Starting from the very principles of gas-phase ion chemistry and isotopic properties, it leads through the design of mass analyzers and ionization methods in use to mass spectral interpretation and coupling techniques. Step by step the readers will learn how mass spectrometry works and what it can do as a powerful tool in their hands. The book comprises a balanced mixture of practice-oriented information and theoretical background. The clear layout, a wealth of high-quality figures and a database of exercises and solutions, accessible via the publisher's web site, support teaching and learning.
This volume presents the proceedings of the Second European Conference on Computational Learning Theory (EuroCOLT '95), held in Barcelona, Spain in March 1995. The book contains full versions of the 28 papers accepted for presentation at the conference as well as three invited papers. All relevant topics in fundamental studies of computational aspects of artificial and natural learning systems and machine learning are covered; in particular artificial and biological neural networks, genetic and evolutionary algorithms, robotics, pattern recognition, inductive logic programming, decision theory, Bayesian/MDL estimation, statistical physics, and cryptography are addressed.
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.