Libros de informática, página 7 de 1199

Empowering IoT with Big Data Analytics provides comprehensive coverage of major topics tools and techniques related to empowering IoT with big data technologies and big data analytics solutions thus allowing for better processing analysis protection distribution and visualization of data for the benefit of IoT applications and second a better deployment of IoT applications on the ground This book covers big data in the IoT era its application domains current state of the art in big data and IoT technologies standards platforms and solutions This book provides a holistic view of the big data value chain for IoT including storage processing protection distribution analytics and visualization Big data is a multi disciplinary topic involving handling intensive continuous and heterogeneous data retrieved from different sources including sensors social media and embedded systems The emergence of Internet of Things IoT and its application to many domains has led to the generation of huge amounts of both structured and unstructured data often referred to as big data

Cognitive Assistant Supported Human Robot Collaboration covers the design and development of cognitive assistants in the smart factory era its application domains challenges and current state of the art in assistance systems with collaborative robotics and IoT technologies standards platforms and solutions This book also provides a sociotechnical view of collaborative work in human robot teams investigating specific methods and techniques to analyze assistance systems This provides readers with a comprehensive overview of how cognitive assistants function and work in human robot teams

One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own.The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers.Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics.The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.

Quantum Computing for Healthcare Data Revolutionizing the Future of Medicine presents an advanced overview of the fundamentals of quantum computing from the transition of traditional to quantum computing to the challenges and opportunities encountered as various industries enter into the paradigm shift The book investigates how quantum AI quantum data processing and quantum data analysis can best be integrated into healthcare data systems The book also introduces a range of case studies which feature applications of quantum computing in connected medical devices medical simulations robotics medical diagnosis and drug discovery The book will be a valuable resource for researchers graduate students and professional programmers and computer engineers working in the areas of healthcare data management and analytics blockchain IoT and big data analytics

S is a high-level language for manipulating, analysing and displaying data. It forms the basis of two highly acclaimed and widely used data analysis software systems, the commercial S-PLUS and the OpenSource R. This book provides an in-depth guide to writing software in the S language under either or both of those systems. It is intended for readers who have some acquaintance with the S language and want to know how to use it more effectively, for example to build re-usable tools for streamlining routine data analysis or to implement new statistical methods.One of the outstanding strengths of the S language is the ease with which it can be extended by users. S is a functional language, and functions written by users are first-class objects treated in the same way as functions provided by the system. S code is eminently readable and so a good way to document precisely what algorithms were used, and as much of the implementations are themselves written in S, they can be studied as models and to understand their subtleties.The current implementations also provide easy ways for S functions to call compiled code written in C, Fortran and similar languages; this is documented here in depth.Increasingly S is being used for statistical or graphical analysis within larger software systems or for whole vertical-market applications.The interface facilities are most developed on windows and these are covered with worked examples. The authors have written the widely used "Modern Applied Statistics with S-PLUS", now in its third edition, and several software libraries that enhance S-PLUS and R; these and the examples used in both books are available on the Internet.Dr. W.N. Venables is a senior Statistician with the CSIRO/CMIS Environmetrics Project in Australia, having been at the Department of statistics, University of Adelaide for many years previously. Professor B.D. Ripley holds the Chair of Applied Statistics at the university of Oxford, and is the author of four other books on spatial statistics, simulation, pattern recognition and neural networks.Both authors are known and respected throughout the international S and R communities, for their books, workshops, short courses, freely available software and through their extensive contributions to the S-news and R mailing lists.

Esta obra comprende: Dos Tomos. Más de 1700 páginas Más de 2.500.000 palabras Léxico de más de 100.000 artículos y subartículos inglés-español Suplemento léxico de más de 1700 nuevos términos Definiciones en castellanoSinonimos ingleses y castellanos Remisiones y equivalencias español-ingles en contexto

This book addresses the topic of HR analytics focusing especially on demystifying analytics for HR managers from both statistical and computing points of view It presents the evolution and the importance of people analytics in today s workforce management and highlights the motivation for studying business analytics shows the different levels of analytic maturity and discusses real world success stories of business analytics in action through case studies The volume provides the readers with a step by step guide to analyze HR data and interpret the results for strategy formulation Each chapter of the book includes a vignette data driven exercises and real world case studies The authors also introduce the readers to data visualization software Microsoft Power BI as well as elaborates on how to use Tableau Desktop This book would be useful to the students of human resource management organizational behaviour applied psychology social work and sociology It would also serve as very good handbook for practicing business executives helping them to implement data analytics for effective decision making in all kinds of business situations around the world

Soft computing embraces methodologies for the development of intelligent systems that have been successfully applied to a large number of real-word problems. This collection of keynote papers, presented at the 7th On-line World Conference on Soft Computing in Engineering Design and Manufacturing, provides a comprehensive overview of recent advances in fuzzy, neural and evolutionary computing techniques and applications in engineering design and manufacturing. - New and highly advanced research results at the forefront of soft computing in engineering design and manufacturing. - Keynote papers by world-renowned researchers in the field. - A good overview of current soft computing research around the world. A collection of methodologies aimed at researchers and professional design and manufacturing engineers who develop and apply intelligent systems in computer engineering.

Computational Intelligence and Blockchain in Complex Systems System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI machine learning and computational intelligence in blockchain and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications This book examines the role of computational intelligence and machine learning in the development of algorithms to deploy blockchain technology across a number of applications including healthcare insurance smart grid smart contracts digital currency precision agriculture and supply chain The authors cover the unique and developing intersection between cyber security and blockchain in modern networks as well as in depth studies on cybersecurity challenges and multidisciplinary methods in modern blockchain networks Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods especially the complex algorithms involved in blockchain security aspects for hashing coding and decoding This book also provides readers with the most in depth technical guide to the intersection of computational intelligence and blockchain two of the most