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EBookClubs

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Book Advances in Feature Based Manufacturing

Download or read book Advances in Feature Based Manufacturing written by J.J. Shah and published by Elsevier. This book was released on 2013-10-22 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Well known researchers in all areas related to featured based manufacturing have contributed chapters to this book. Some of the chapters are surveys, while others review a specific technique. All contributions, including those from the editors, were thoroughly refereed. The goal of the book is to provide a comprehensive picture of the present stage of development of Features Technology from the point of view of applications in manufacturing. The book is aimed at several audiences. Firstly, it provides the research community with an overview of the present state-of-the-art features in manufacturing, along with references in the literature. Secondly, the book will be useful as supporting material for a graduate-level course on product modeling and realization. Finally, the book will also be valuable to industrial companies who are assessing the significance of features for their business.

Book Parametric and Feature Based CAD CAM

Download or read book Parametric and Feature Based CAD CAM written by Jami J. Shah and published by John Wiley & Sons. This book was released on 1995-11-03 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is the complete introduction and applications guide to this new technology. This book introduces the reader to features and gives an overview of geometric modeling techniques, discusses the conceptual development of features as modeling entities, illustrates the use of features for a variety of engineering design applications, and develops a set of broad functional requirements and addresses high level design issues.

Book Feature Representation and Learning Methods With Applications in Protein Secondary Structure

Download or read book Feature Representation and Learning Methods With Applications in Protein Secondary Structure written by Zhibin Lv and published by Frontiers Media SA. This book was released on 2021-10-25 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

Download or read book Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint written by Mark K. Hinders and published by Springer Nature. This book was released on 2020-07-01 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader’s area of interest, or read together to provide a comprehensive overview of the topic. Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.

Book Feature Engineering for Machine Learning and Data Analytics

Download or read book Feature Engineering for Machine Learning and Data Analytics written by Guozhu Dong and published by CRC Press. This book was released on 2018-03-14 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation. The book presents key concepts, methods, examples, and applications, as well as chapters on feature engineering for major data types such as texts, images, sequences, time series, graphs, streaming data, software engineering data, Twitter data, and social media data. It also contains generic feature generation approaches, as well as methods for generating tried-and-tested, hand-crafted, domain-specific features. The first chapter defines the concepts of features and feature engineering, offers an overview of the book, and provides pointers to topics not covered in this book. The next six chapters are devoted to feature engineering, including feature generation for specific data types. The subsequent four chapters cover generic approaches for feature engineering, namely feature selection, feature transformation based feature engineering, deep learning based feature engineering, and pattern based feature generation and engineering. The last three chapters discuss feature engineering for social bot detection, software management, and Twitter-based applications respectively. This book can be used as a reference for data analysts, big data scientists, data preprocessing workers, project managers, project developers, prediction modelers, professors, researchers, graduate students, and upper level undergraduate students. It can also be used as the primary text for courses on feature engineering, or as a supplement for courses on machine learning, data mining, and big data analytics.

Book Recent Advances in Ensembles for Feature Selection

Download or read book Recent Advances in Ensembles for Feature Selection written by Verónica Bolón-Canedo and published by Springer. This book was released on 2018-04-30 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance. With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative. The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges that researchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.

Book Unsupervised Feature Extraction Applied to Bioinformatics

Download or read book Unsupervised Feature Extraction Applied to Bioinformatics written by Y-h. Taguchi and published by Springer Nature. This book was released on 2019-08-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics. Allows readers to analyze data sets with small samples and many features; Provides a fast algorithm, based upon linear algebra, to analyze big data; Includes several applications to multi-view data analyses, with a focus on bioinformatics.

Book Feature Selection for High Dimensional Data

Download or read book Feature Selection for High Dimensional Data written by Verónica Bolón-Canedo and published by Springer. This book was released on 2015-10-05 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data. The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers. The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.

Book Advances in Feature Selection for Data and Pattern Recognition

Download or read book Advances in Feature Selection for Data and Pattern Recognition written by Urszula Stańczyk and published by Springer. This book was released on 2017-11-16 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved. Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners.

Book Python Feature Engineering Cookbook

Download or read book Python Feature Engineering Cookbook written by Soledad Galli and published by Packt Publishing Ltd. This book was released on 2022-10-31 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create end-to-end, reproducible feature engineering pipelines that can be deployed into production using open-source Python libraries Key Features Learn and implement feature engineering best practices Reinforce your learning with the help of multiple hands-on recipes Build end-to-end feature engineering pipelines that are performant and reproducible Book DescriptionFeature engineering, the process of transforming variables and creating features, albeit time-consuming, ensures that your machine learning models perform seamlessly. This second edition of Python Feature Engineering Cookbook will take the struggle out of feature engineering by showing you how to use open source Python libraries to accelerate the process via a plethora of practical, hands-on recipes. This updated edition begins by addressing fundamental data challenges such as missing data and categorical values, before moving on to strategies for dealing with skewed distributions and outliers. The concluding chapters show you how to develop new features from various types of data, including text, time series, and relational databases. With the help of numerous open source Python libraries, you'll learn how to implement each feature engineering method in a performant, reproducible, and elegant manner. By the end of this Python book, you will have the tools and expertise needed to confidently build end-to-end and reproducible feature engineering pipelines that can be deployed into production.What you will learn Impute missing data using various univariate and multivariate methods Encode categorical variables with one-hot, ordinal, and count encoding Handle highly cardinal categorical variables Transform, discretize, and scale your variables Create variables from date and time with pandas and Feature-engine Combine variables into new features Extract features from text as well as from transactional data with Featuretools Create features from time series data with tsfresh Who this book is for This book is for machine learning and data science students and professionals, as well as software engineers working on machine learning model deployment, who want to learn more about how to transform their data and create new features to train machine learning models in a better way.

Book Wh movement and the Theory of Feature checking

Download or read book Wh movement and the Theory of Feature checking written by Andrew Simpson and published by John Benjamins Publishing. This book was released on 2000-01-01 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wh-movement and the theory of feature-checking argues that cross-linguistic variation in wh-constructions reduces to the availability of different lexical instantiations of a +wh C0 both across languages and within a single language, and the way in which such lexical elements are syntactically identified, either via movement or base-generation. Evidence from a wide range of patterns including wh-expletive questions leads to the conclusion that wh-feature checking may sometimes be effected non-locally and 'at a distance' (long-distance wh-agreement), and that movement in general takes place for two related but discrete reasons: both to identify and activate an underspecified licensing head and in order for an element to occur in the checking domain projected by its relevant licensing head. Developing and generalizing the proposals beyond wh-phenomena, the study also goes on to argue for a Minimalist model of syntax in which feature-dependencies are in fact all licensed in the overt syntax and where there is no need for any further level of LF.

Book Emotion Recognition using Speech Features

Download or read book Emotion Recognition using Speech Features written by K. Sreenivasa Rao and published by Springer Science & Business Media. This book was released on 2012-11-07 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Emotion Recognition Using Speech Features” provides coverage of emotion-specific features present in speech. The author also discusses suitable models for capturing emotion-specific information for distinguishing different emotions. The content of this book is important for designing and developing natural and sophisticated speech systems. In this Brief, Drs. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models. Additionally, the authors provide information about exploiting multiple evidences derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Features includes discussion of: • Global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information; • Exploiting complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance; • Proposed multi-stage and hybrid models for improving the emotion recognition performance. This brief is for researchers working in areas related to speech-based products such as mobile phone manufacturing companies, automobile companies, and entertainment products as well as researchers involved in basic and applied speech processing research.

Book Method of classification of global machine conditions based on spectral features of infrared images and classifiers fusion

Download or read book Method of classification of global machine conditions based on spectral features of infrared images and classifiers fusion written by Marek Fidali and published by Infinite Study. This book was released on with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper describes an original method of global machine condition assessment for infrared condition monitoring and diagnostics systems. This method integrates two approaches: the first is processing and analysis of infrared images in the frequency domain by the use of 2D Fourier transform and a set of F-image features, the second uses fusion of classification results obtained independently for F-image features. To find the best condition assessment solution, the two different types of classifiers, k-nearest neighbours and support vector machine, as well as data fusion method based on Dezert–Smarandache theory have been investigated. This method has been verified using infrared images recorded during experiments performed on the laboratory model of rotating machinery. The results obtained during the research confirm that the method could be successfully used for the identification of operational conditions that are difficult to be recognised.

Book Phonetic Variation and Acoustic Distinctive Features

Download or read book Phonetic Variation and Acoustic Distinctive Features written by Clara N. Bush and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-03-22 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Phonetic Variation and Acoustic Distinctive Features".

Book JAVA 9 0 To 13 0 New Features

Download or read book JAVA 9 0 To 13 0 New Features written by JogA Mandar and published by BPB Publications. This book was released on 2019-09-20 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive guide to study the version updates from JDK9.0 to JDK13.0Key features Learn the journey of Java from its initial days till date. Learn how to implement modular programming in java9. Study the updates in different versions of Java from version 9.0 to 13.0. Understand the need and working of reactive programming. Learn to migrate the pre-existing Java code to new versions. Learn how to use jshell to test a new API before using in a project.DescriptionVersion release is one of the important phases of success of any programming language. Over the years, Java had made many improvements in its API to make to reliable and flexible to use. This book aims at providing you information related to all the updates from JDK9.0 to JDK13.0 in one place.This book starts with a brief history of Java. It covers how Java has evolved as a complete programming language over the years by launching different versions. You will learn the concept of module system and other important concepts introduced in JSE9 .0 and JSE10.0. Moving ahead, the book will take you through updates in JDK11.0. Concepts like Epsilon, ZGC, and Nest-Based access control have also been discussed.Though the version updates are good to learn, they create complexities in updating the existing code to make it compatible with the new version. This book talks in detail about how you can migrate your legacy code to match up with the new versions. It also covers how to use jshell, a tool used to test your code snippet without writing the complete application class, with numerous examples. Further, this book covers in detail the concept of reactive programming. Concepts like publisher, subscriber, subscription and back-pressure have been discussed with examples.At the end of the book, you will learn about the very recent updates which have been released by Java. The chapters talk about JDK12.0 and JDK13.0. They cover concepts like Shenondaoh, microbenchmark suit, modified switch expression from JDK12.0. Though, Java13 is still a hot-plated dish, this book gives you a fair idea about what are the new updates which have been proposed in this version.What will you learnBy the end of this book, you will be able to implement the updates provided in different versions of Java. This book has covered the updates from version 9.0 to 13.0. You will be able to work with the Java Module System. You will be able to test the new API using jshell. Along with this, you will be able to migrate your legacy code to match the recommendations of new versions of Java.Who this book is forThis book covers the new version updates in Java. So, prior knowledge of Java is recommended before reading this book. Though we are covering the versions from JSE9.0 onwards, it is not necessary that the reader should be expert in the earlier versions. If you are keen to know the recent developments in Java API, this is the perfect book for you.Table of contents1. Insights of Versioning2. What's new in Java93. Understanding JDK10 - Step towards JDK114. Dive in JDK115. Migrating the code6. Working with JShell7. Reactive Programming and Concurrency Updates8. What next in Java129. Introduction to Java13About the authorMandar Jog is a passionate Java Trainer with over 15 years of experience in retail and corporate training. He has global certifications like SCJP and SCWCD. His areas of expertise are Java, J2EE (Spring, Hibernate). He has delivered more than 500 training sessions on Core Java, Web Technologies, Hibernate, Spring Boot, Angular, etc.

Book Key Features and Parameters in Arabic Grammar

Download or read book Key Features and Parameters in Arabic Grammar written by Abdelkader Fassi Fehri and published by John Benjamins Publishing. This book was released on 2012-02-01 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: In light of recent generative minimalism, and comparative parametric theory of language variation, the book investigates key features and parameters of Arabic grammar. Part I addresses morpho-syntactic and semantic interfaces in temporality, aspectuality, and actionality, including the Past/Perfect/Perfective ambiguity akin to the very synthetic temporal morphology, collocating time adverb construal, and interpretability of verbal Number as pluractional. Part II is dedicated to nominal architecture, the behaviour of bare nouns as true indefinites, the count/mass dichotomy (re-examined in light of general, collective, and singulative DP properties), the mirror image ordering of serialized adjectives, and N-to-D Move in synthetic possession, proper names, and individuated vocatives. Part III examines the role of CP in time and space anchoring, double access reading (in a DAR language such as Arabic), sequence of tense (SOT), silent pronominal categories in consistent null subject languages (including referential and generic pro), and the interpretability of inflection. Semantic and formal parameters are set out, within a mixed macro/micro-parametric model of language variation. The book is of particular interest to students, researchers, and teachers of Arabic, Semitic, comparative, typological, or general linguistics.

Book VoIP  Voice Over Internet Protocol Architecture and Features

Download or read book VoIP Voice Over Internet Protocol Architecture and Features written by Abdul Sattar Mohmand and published by Lulu.com. This book was released on 2008-06-28 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: VoIP or Voice Over Internet Protocol is an emerging telecommunication technology that make use of IP network to carry voice just like PSTN (Public Switched Telephone Network) or traditional phones. There are several companies offering low cost and more flexible phones and packages of VoIP systems. Future belongs to VoIP because of its low cost and flexibility and more control.This innovative technology will change the life of people because the dream of video phone is just behind its bars. This book covers the basic architecture, usefulness, challenges and features of the VoIP Phones systems.