Foundations for Industrial Machines PDF Download
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Author: K.G. Bhatia
Publisher: CRC Press
ISBN: 9788190603201
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
The performance, safety and stability of machines depends largely on their design, manufacturing and interaction with environment. Machine foundations should be designed in such a way that the dynamic forces transmitted to the soil through the foundation, eliminating all potentially harmful forces. This handbook is designed primarily for the practising engineers engaged in design of machine foundations. It covers basic fundamentals for understanding and evaluating dynamic response of machine foundation systems with emphasis is on detailed dynamic analysis for response evaulation. Use of commercially available Finite Element packages, for analysis and design of the foundation, is recommended. Theory is supported by results from practice in the form of examples.
Author: K.G. Bhatia
Publisher: CRC Press
ISBN: 9788190603201
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
The performance, safety and stability of machines depends largely on their design, manufacturing and interaction with environment. Machine foundations should be designed in such a way that the dynamic forces transmitted to the soil through the foundation, eliminating all potentially harmful forces. This handbook is designed primarily for the practising engineers engaged in design of machine foundations. It covers basic fundamentals for understanding and evaluating dynamic response of machine foundation systems with emphasis is on detailed dynamic analysis for response evaulation. Use of commercially available Finite Element packages, for analysis and design of the foundation, is recommended. Theory is supported by results from practice in the form of examples.
Author: Shamsher Prakash
Publisher: Wiley-Interscience
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 680
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Book Description
Theory of vibrations. Wave propagation in an elastic medium. Dynamic soil properties. Unbalanced forces for design of machine foundations. Foundations for reciprocating machines. Foundations for impact machines. Foundations for high-speed rotary machines. Foundations for miscellaneous types of machines. Vibration absorption and isolation. Dynamic response of embedded block foundations. Machine foundations on piles. Case histories. Construction of machine foundations. Computer program for the design of a block foundation. Computer program for the design of a hammer foundation. Brief description of some available computer programs. Computation of moment of inertia. Conversion factors.
Author: Suresh C. Arya
Publisher: Gulf Publishing
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 216
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Book Description
This text brings together traditional and new concepts and procedures for analyzing and designing dynamically loaded structures.
Author: P. Srinivasulu
Publisher:
ISBN:
Category : MACHINERY
Languages : en
Pages : 264
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Book Description
Author: Mehryar Mohri
Publisher: MIT Press
ISBN: 0262351366
Category : Computers
Languages : en
Pages : 505
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Book Description
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.
Author: Wayne
Publisher:
ISBN: 9780262130806
Category :
Languages : en
Pages : 353
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Book Description
In his introduction to this book, George R. Harrison, Dean Emeritus of M.I.T.'s School of Science, writes as follows: "Basic to man's behavior is his ability to determine, modify, and adapt to his environment. This he has been able to do in proportion to his skill at making measurements, and fundamental to all other measuring operations is his ability to determine locations in the material world. Thus the science of mechanical measurements is a fundamental one. It is this science, and the art which accompanies and informs it, with which this book is concerned." This is the third book produced by the , Inc., of Bridgeport, Connecticut. Like all of its products, the book is marked by a clean precision of design and execution. The firm has built a worldwide reputation since 1924, both as a manufacturer of special tooling to extremely close accuracies and of machine tools that make possible a very high degree of precision. Wayne R. Moore has assembled in the 350 pages of Foundations of Mechanical Accuracythe company's intimate knowledge of and experience with mechanical accuracy, and how to achieve it. He has illustrated his text with over 500 original photographs and drawings. This book tells how to attain precision in manufacturing to millionths of an inch and how to control such precision by appropriate measuring techniques. The book is divided into four main sections: geometry, standards of length, dividing the circle, and roundness. A fifth section covers "Universal Measuring Machine Techniques and Applications." The book is printed in two colors throughout, and interspersed with full-page, full-color plates.
Author: Avrim Blum
Publisher: Cambridge University Press
ISBN: 1108617360
Category : Computers
Languages : en
Pages : 433
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Book Description
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author: Alexander Major
Publisher:
ISBN:
Category : Machinery
Languages : en
Pages : 840
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Book Description
Author: M.Z. Kolovsky
Publisher: Springer Science & Business Media
ISBN: 3540465162
Category : Science
Languages : en
Pages : 403
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Book Description
A new approach to the theory of mechanisms and machines, based on a lecture course for mechanical engineering students at the St. Petersburg State Technical University. The material differs from traditional textbooks due to its more profound elaboration of the methods of structural, geometric, kinematic and dynamic analysis. These established and novel methods take into account the needs of modern machine design as well as the potential of computers.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
