Catia V5 R17 For Designers


Sham Tickoo - 2005
    The textbook covers all-important workbenches of CATIA V5R17 with a thorough explanation of all commands, options, and their applications to create real-world products. About 55 mechanical engineering industry examples are used as tutorials and an additional 35 as exercises to ensure that the user can relate their knowledge and understand the design techniques used in the industry to design a product. After reading the textbook, the user will be able to create solid parts, assemblies, drawing views with bill of materials, surface models, and Sheet metal components. Also, the user will learn the editing techniques that are essential to make a successful design. In this book, the author emphasizes on the solid modeling techniques that improve the productivity and efficiency of the user. Salient Features of the Textbook Consists of 15 chapters that are organized in a pedagogical sequence. These chapters cover the Sketching, Modeling, Assembly, Drafting, Wireframe and Surface Design, and Generative Sheetmetal workbenches of CATIA V5R17. The first page of every chapter summarizes the topics that will be covered in it. Additional information is provided throughout the book in the form of tips and notes. Self-evaluation test and review questions are provided at the end of each chapter so that the users can assess their knowledge.Free Teaching and Learning Resources Online technical support by contacting techsupport@cadcim.com. All programs used in exercises and examples. Customizable PowerPoint presentations of all chapters in the textbook li>Instructor s Guide with solutions to all review questions and exercises in the textbook. Student projects to enhance the skills Class tests that can be used by faculty in the class To access these free teaching resources, please send your contact information to sales@cadcim.com, mentioning clearly your name, designation, university/college, street street address, city, state, zip, and country.

Research Methods in Language Learning


David Nunan - 1992
    This book is intended to help readers understand and critique research in language learning. It presents a balanced and objective view of a range of methods - including formal experiments, introspective methods, interaction and transcript analysis, ethnography, and case studies. The book is highly accessible and does not assume specialist or technical knowledge. This volume will be of interest to students of applied linguistics and educational researchers, in addition to classroom teachers and teachers-in-training. Throughout the book, theoretical issues are drawn from published studies and reports. The book emphasizes the professional and practical value of reading published research.

Satellite Communications


Timothy Pratt - 1986
    Includes chapters on orbital mechanics, spacecraft construction, satellite-path radio wave propagation, modulation techniques, multiple access, and a detailed analysis of the communications link.

Artificial Intelligence


Patrick Henry Winston - 1977
    From the book, you learn why the field is important, both as a branch of engineering and as a science. If you are a computer scientist or an engineer, you will enjoy the book, because it provides a cornucopia of new ideas for representing knowledge, using knowledge, and building practical systems. If you are a psychologist, biologist, linguist, or philosopher, you will enjoy the book because it provides an exciting computational perspective on the mystery of intelligence. The Knowledge You Need This completely rewritten and updated edition of Artificial Intelligence reflects the revolutionary progress made since the previous edition was published. Part I is about representing knowledge and about reasoning methods that make use of knowledge. The material covered includes the semantic-net family of representations, describe and match, generate and test, means-ends analysis, problem reduction, basic search, optimal search, adversarial search, rule chaining, the rete algorithm, frame inheritance, topological sorting, constraint propagation, logic, truth

Peter Norton's Introduction to Computers


Peter Norton - 1994
    It includes three entirely new chapters on the Internet, computer graphics, and multimedia. Thorough yet flexible, Introduction to Computers is appropriate for a full-semester course -- with or without a hands-on lab. The text is available with a student CD-ROM that contains interactive multimedia materials for each chapter. Also available are an Electronic Study Guide on CD-ROM, HyperGraphics package, and an Instructor's Productivity Center on CD-ROM.

Introduction to C Programming


Reema Thareja - 2013
    The aim of the book is to enable students to write effective C programs.The book starts with an introduction to programming in general followed by a detailed introduction to C programming. It then delves into a complete analysis of various constructs of C such as decision control and looping statements, functions, arrays, strings, pointers, structure and union, file management, and preprocessor directives. It also provides a separate chapter on linked list detailing the various kinds of linked lists and how they are used to allocate memory dynamically.A highly detailed pedagogical approach is followed throughout the book, which includes plenty of examples, figures, programming tips, keywords, and end-chapter exercises which make this book an ideal resource for students to master and fine-tune the art of writing C programs.

Data Structures and Algorithms Made Easy in Java: 700 Data Structure and Algorithmic Puzzles


Narasimha Karumanchi - 2011
    Success key books for: Programming puzzles for interviews Campus Preparation Degree/Masters Course Preparation Instructor's GATE Preparation Big job hunters: Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more Reference Manual for working people

Graph Theory With Applications To Engineering And Computer Science


Narsingh Deo - 2004
    GRAPH THEORY WITH APPLICATIONS TO ENGINEERING AND COMPUTER SCIENCE-PHI-DEO, NARSINGH-1979-EDN-1

A Textbook of English phonetics for Indian students


T. Balasubramanian - 1981
    Sufficient information about General Phonetics has been included in the book, with a view to facilitating the reader's understanding of the Phonetics of English. Plenty of examples are given from English, Tamil, Hindi and Urdu/Arabic to illustrate the points made. There are a number of diagrams throughout the book,illustrating the articulation of the sounds of English. The book also includes some information about General Phonology and the Phonology of English. A few sentences, dialogues and a popular tale have been given at the end of the book, both in orthography and in simple phonemic transcription. The book covers the Phonetics/Phonology syllabus of most Indian universities and ELT institutes

Data Structure Through C


Yashavant P. Kanetkar - 2003
    It adopts a novel approach, by using the programming language c to teach data structures. The book discusses concepts like arrays, algorithm analysis, strings, queues, trees and graphs. Well-designed animations related to these concepts are provided in the cd-rom which accompanies the book. This enables the reader to get a better understanding of the complex procedures described in the book through a visual demonstration of the same. Data structure through c is a comprehensive book which can be used as a reference book by students as well as computer professionals. It is written in a clear, easy-to-understood manner and it includes several programs and examples to explain clearly the complicated concepts related to data structures. The book was published by bpb publications in 2003 and is available in paperback. Key features: the book contains example programs that elucidate the concepts. It comes with a cd that visually demonstrates the theory presented in the book.

Study Package for NTSE Class X


McGraw-Hill Education - 2014
    This latest edition has included an english language test to stage 2 of the examination - as opposed to the previous edition that only covered scholastic aptitude and mental ability in part one and part two.study package for ntse class x is meant to provide a comprehensive coverage of all the topics that are prescribed in the most recent format of the prestigious ntse exam. Based around the syllabi of classes 9 and 10, it has been carefully framed to optimize the studying patterns of aspiring students who wish to write the exam.the book covers the necessary topics in each stage of the exam and is divided into sections that individually address all of these. It thus helps stimulate a real-world test environment. Some of the topics covered include the verbal test, non-verbal test and the assignments given in sections a, b and c in stage one (mental ability). Also included in stage 2 (scholastic aptitude) are subjects like physics, chemistry, biology, history, geography, economics, mathematics, political science, and, recently included after last year's examination - the english language test portion as well.the book was published in the year 2014 by tata mcgrawhill publication and is available in paperback.

Hands-On Machine Learning with Scikit-Learn and TensorFlow


Aurélien Géron - 2017
    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

Calculus Made Easy


Silvanus Phillips Thompson - 1910
    With a new introduction, three new chapters, modernized language and methods throughout, and an appendix of challenging and enjoyable practice problems, Calculus Made Easy has been thoroughly updated for the modern reader.

Data Smart: Using Data Science to Transform Information into Insight


John W. Foreman - 2013
    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction


Trevor Hastie - 2001
    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.