Foundations for Industrial Machines

Foundations for Industrial Machines
Author: K.G. Bhatia
Publisher: CRC Press
Total Pages: 0
Release: 2009-10-12
Genre: Technology & Engineering
ISBN: 9788190603201

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.

Handbook of Machine Foundations

Handbook of Machine Foundations
Author: P. Srinivasulu
Publisher: Tata McGraw-Hill Education
Total Pages: 0
Release: 1976
Genre: Foundations
ISBN: 9780070966116

Imperfect designing of machine foundations based on empirical formulations has led to the problem of troublesome vibrations in the existing foundations. Recent developments in the field of structural and soil dynamics have helped establish basic design principles for various types of machine foundations. In order to achieve efficiency and economy in the design, it is imperative that the designer have an in depth knowledge of various aspects of analysis, design and construction of machine foundations

Foundations of Data Science

Foundations of Data Science
Author: Avrim Blum
Publisher: Cambridge University Press
Total Pages: 433
Release: 2020-01-23
Genre: Computers
ISBN: 1108617360

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.

Mathematics for Machine Learning

Mathematics for Machine Learning
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
Total Pages: 392
Release: 2020-04-23
Genre: Computers
ISBN: 1108569323

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.

Foundations of Mechanical Accuracy

Foundations of Mechanical Accuracy
Author: Wayne
Publisher:
Total Pages: 353
Release: 1971-05-15
Genre:
ISBN: 9780262130806

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.

Foundations of Statistical Natural Language Processing

Foundations of Statistical Natural Language Processing
Author: Christopher Manning
Publisher: MIT Press
Total Pages: 719
Release: 1999-05-28
Genre: Language Arts & Disciplines
ISBN: 0262303795

Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

Handbook of Research on Foundations and Applications of Intelligent Business Analytics

Handbook of Research on Foundations and Applications of Intelligent Business Analytics
Author: Zhaohao Sun
Publisher: Business Science Reference
Total Pages: 450
Release: 2021
Genre: Big data
ISBN: 9781799890164

"This book addresses research issues by investigating into foundations, technologies, and applications of intelligent business analytics, offering theoretical foundations, technologies, methodologies, and applications of intelligent business analytics in an integrated way"--

Handbook of Machine and Computer Vision

Handbook of Machine and Computer Vision
Author: Alexander Hornberg
Publisher: John Wiley & Sons
Total Pages: 868
Release: 2017-06-19
Genre: Computers
ISBN: 3527413391

The second edition of this accepted reference work has been updated to reflect the rapid developments in the field and now covers both 2D and 3D imaging. Written by expert practitioners from leading companies operating in machine vision, this one-stop handbook guides readers through all aspects of image acquisition and image processing, including optics, electronics and software. The authors approach the subject in terms of industrial applications, elucidating such topics as illumination and camera calibration. Initial chapters concentrate on the latest hardware aspects, ranging from lenses and camera systems to camera-computer interfaces, with the software necessary discussed to an equal depth in later sections. These include digital image basics as well as image analysis and image processing. The book concludes with extended coverage of industrial applications in optics and electronics, backed by case studies and design strategies for the conception of complete machine vision systems. As a result, readers are not only able to understand the latest systems, but also to plan and evaluate this technology. With more than 500 images and tables to illustrate relevant principles and steps.