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Trust Management in the Internet of Vehicles

Trust Management in the Internet of Vehicles

The Internet of Vehicles (IoV) is referred to as an efficient and inevitable convergence of the Internet of Things intelligent transportation systems edge / fog and cloud computing and big data all of which could be intelligently harvested for the cooperative vehicular safety and non-safety applications as well as cooperative mobility management. A secure and low-latency communication is therefore indispensable to meet the stringent performance requirements of the safety-critical vehicular applications. Whilst the challenges surrounding low latency are being addressed by the researchers in both academia and industry it is the security of an IoV network which is of paramount importance as a single malicious message is perfectly capable enough of jeopardizing the entire networking infrastructure and can prove fatal for the vehicular passengers and the vulnerable pedestrians. This book thus investigates the promising notion of trust in a bid to strengthen the resilience of the IoV networks. It not only introduces trust categorically in the context of an IoV network i. e. in terms of its fundamentals and salient characteristics but further envisages state-of-the-art trust models and intelligent trust threshold mechanisms for segregating both malicious and non-malicious vehicles. Furthermore open research challenges and recommendations for addressing the same are discussed in the same too. | Trust Management in the Internet of Vehicles

GBP 48.99
1

Decision Support System and Automated Negotiations

The Biometric Computing Recognition and Registration

The Biometric Computing Recognition and Registration

The Biometric Computing: Recognition & Registration presents introduction of biometrics along with detailed analysis for identification and recognition methods. This book forms the required platform for understanding biometric computing and its implementation for securing target system. It also provides the comprehensive analysis on algorithms architectures and interdisciplinary connection of biometric computing along with detailed case-studies for newborns and resolution spaces. The strength of this book is its unique approach starting with how biometric computing works to research paradigms and gradually moves towards its advancement. This book is divided into three parts that comprises basic fundamentals and definitions algorithms and methodologies and futuristic research and case studies. Features: A clear view to the fundamentals of Biometric Computing Identification and recognition approach for different human characteristics Different methodologies and algorithms for human identification using biometrics traits such as face Iris fingerprint palm print voiceprint etc. Interdisciplinary connection of biometric computing with the fields like deep neural network artificial intelligence Internet of Biometric Things low resolution face recognition etc. This book is an edited volume by prominent invited researchers and practitioners around the globe in the field of biometrics describes the fundamental and recent advancement in biometric recognition and registration. This book is a perfect research handbook for young practitioners who are intending to carry out their research in the field of Biometric Computing and will be used by industry professionals graduate and researcher students in the field of computer science and engineering. | The Biometric Computing Recognition and Registration

GBP 140.00
1

Operating System Design The Xinu Approach Second Edition

Operating System Design The Xinu Approach Second Edition

An Update of the Most Practical A-to-Z Operating System BookWidely lauded for avoiding the typical black box approach found in other operating system textbooks the first edition of this bestselling book taught readers how an operating system works and explained how to build it from the ground up. Continuing to follow a logical pattern for system design Operating System Design: The Xinu Approach Second Edition removes the mystery from operating system design and consolidates the body of material into a systematic discipline. It presents a hierarchical design paradigm that organizes major operating system components in an orderly understandable manner. The book guides readers through the construction of a conventional process-based operating system using practical straightforward primitives. It gives the implementation details of one set of primitives usually the most popular set. Once readers understand how primitives can be implemented on conventional hardware they can then easily implement alternative versions. The text begins with a bare machine and proceeds step-by-step through the design and implementation of Xinu which is a small elegant operating system that supports dynamic process creation dynamic memory allocation network communication local and remote file systems a shell and device-independent I/O functions. The Xinu code runs on many hardware platforms. This second edition has been completely rewritten to contrast operating systems for RISC and CISC processors. Encouraging hands-on experimentation the book provides updated code throughout and examples for two low-cost experimenter boards: BeagleBone Black from ARM and Galileo from Intel. | Operating System Design The Xinu Approach Second Edition

GBP 39.99
1

Sample Size Calculations in Clinical Research

Sample Size Calculations in Clinical Research

Praise for the Second Edition:… this is a useful comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study. BiometricsThis impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative binary and time-to-event outcomes are covered comprehensively with separate sample size formulae for testing equality non-inferiority and equivalence. Many less familiar topics are also covered … – Journal of the Royal Statistical SocietySample Size Calculations in Clinical Research Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications this book includes a well-balanced summary of current and emerging clinical issues regulatory requirements and recently developed statistical methodologies for sample size calculation. Features:Compares the relative merits and disadvantages of statistical methods for sample size calculationsExplains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stagesPresents real-world examples from several therapeutic areas including cardiovascular medicine the central nervous system anti-infective medicine oncology and women’s healthProvides sample size calculations for dose response studies microarray studies and Bayesian approachesThis new edition is updated throughout includes many new sections and five new chapters on emerging topics: two stage seamless adaptive designs cluster randomized trial design zero-inflated Poisson distribution clinical trials with extremely low incidence rates and clinical trial simulation.

GBP 38.99
1

Hands-On Machine Learning with R

Hands-On Machine Learning with R

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R which includes using various R packages such as glmnet h2o ranger xgboost keras and others to effectively model and gain insight from their data. The book favors a hands-on approach providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book the reader will be exposed to the entire machine learning process including feature engineering resampling hyperparameter tuning model evaluation and interpretation. The reader will be exposed to powerful algorithms such as regularized regression random forests gradient boosting machines deep learning generalized low rank models and more! By favoring a hands-on approach and using real word data the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages understand when and how to tune the various hyperparameters and be able to interpret model results. By the end of this book the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering resampling deep learning and more. · Uses a hands-on approach and real world data.

GBP 82.99
1

Introduction to High-Dimensional Statistics

Introduction to High-Dimensional Statistics

Praise for the first edition: [This book] succeeds singularly at providing a structured introduction to this active field of research. … it is arguably the most accessible overview yet published of the mathematical ideas and principles that one needs to master to enter the field of high-dimensional statistics. … recommended to anyone interested in the main results of current research in high-dimensional statistics as well as anyone interested in acquiring the core mathematical skills to enter this area of research. —Journal of the American Statistical Association Introduction to High-Dimensional Statistics Second Edition preserves the philosophy of the first edition: to be a concise guide for students and researchers discovering the area and interested in the mathematics involved. The main concepts and ideas are presented in simple settings avoiding thereby unessential technicalities. High-dimensional statistics is a fast-evolving field and much progress has been made on a large variety of topics providing new insights and methods. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics this new edition: Offers revised chapters from the previous edition with the inclusion of many additional materials on some important topics including compress sensing estimation with convex constraints the slope estimator simultaneously low-rank and row-sparse linear regression or aggregation of a continuous set of estimators. Introduces three new chapters on iterative algorithms clustering and minimax lower bounds. Provides enhanced appendices minimax lower-bounds mainly with the addition of the Davis-Kahan perturbation bound and of two simple versions of the Hanson-Wright concentration inequality. Covers cutting-edge statistical methods including model selection sparsity and the Lasso iterative hard thresholding aggregation support vector machines and learning theory. Provides detailed exercises at the end of every chapter with collaborative solutions on a wiki site. Illustrates concepts with simple but clear practical examples.

GBP 74.99
1

Operating Systems Evolutionary Concepts and Modern Design Principles

Operating Systems Evolutionary Concepts and Modern Design Principles

This text demystifies the subject of operating systems by using a simple step-by-step approach from fundamentals to modern concepts of traditional uniprocessor operating systems in addition to advanced operating systems on various multiple-processor platforms and also real-time operating systems (RTOSs). While giving insight into the generic operating systems of today its primary objective is to integrate concepts techniques and case studies into cohesive chapters that provide a reasonable balance between theoretical design issues and practical implementation details. It addresses most of the issues that need to be resolved in the design and development of continuously evolving rich diversified modern operating systems and describes successful implementation approaches in the form of abstract models and algorithms. This book is primarily intended for use in undergraduate courses in any discipline and also for a substantial portion of postgraduate courses that include the subject of operating systems. It can also be used for self-study. Key Features • Exhaustive discussions on traditional uniprocessor-based generic operating systems with figures tables and also real-life implementations of Windows UNIX Linux and to some extent Sun Solaris. • Separate chapter on security and protection: a grand challenge in the domain of today’s operating systems describing many different issues including implementation in modern operating systems like UNIX Linux and Windows. • Separate chapter on advanced operating systems detailing major design issues and salient features of multiple-processor-based operating systems including distributed operating systems. Cluster architecture; a low-cost base substitute for true distributed systems is explained including its classification merits and drawbacks. • Separate chapter on real-time operating systems containing fundamental topics useful concepts and major issues as well as a few different types of real-life implementations. • Online Support Material is provided to negotiate acute page constraint which is exclusively a part and parcel of the text delivered in this book containing the chapter-wise/topic-wise detail explanation with representative figures of many important areas for the completeness of the narratives. | Operating Systems Evolutionary Concepts and Modern Design Principles

GBP 150.00
1

Advanced R Second Edition

Advanced R Second Edition

Advanced R helps you understand how R works at a fundamental level. It is designed for R programmers who want to deepen their understanding of the language and programmers experienced in other languages who want to understand what makes R different and special. This book will teach you the foundations of R; three fundamental programming paradigms (functional object-oriented and metaprogramming); and powerful techniques for debugging and optimisingyour code. By reading this book you will learn: The difference between an object and its name and why the distinction is important The important vector data structures how they fit together and how you can pull them apart using subsetting The fine details of functions and environments The condition system which powers messages warnings and errors The powerful functional programming paradigm which can replace many for loops The three most important OO systems: S3 S4 and R6 The tidy eval toolkit for metaprogramming which allows you to manipulate code and control evaluation Effective debugging techniques that you can deploy regardless of how your code is run How to find and remove performance bottlenecks The second edition is a comprehensive update: New foundational chapters: Names and values Control flow and Conditions comprehensive coverage of object oriented programming with chapters on S3 S4 R6 and how to choose between them Much deeper coverage of metaprogramming including the new tidy evaluation framework use of new package like rlang (http://rlang. r-lib. org) which provides a clean interface to low-level operations and purr (http://purrr. tidyverse. org/) for functional programming Use of color in code chunks and figuresHadley Wickham is Chief Scientist at RStudio an Adjunct Professor at Stanford University and the University of Auckland and a member of the R Foundation. He is the lead developer of the tidyverse a collection of R packages including ggplot2 and dplyr designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund) R Packages and ggplot2: Elegant Graphics for Data Analysis. | Advanced R Second Edition

GBP 48.99
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Sampling Design and Analysis

Sampling Design and Analysis

The level is appropriate for an upper-level undergraduate or graduate-level statistics major. Sampling: Design and Analysis (SDA) will also benefit a non-statistics major with a desire to understand the concepts of sampling from a finite population. A student with patience to delve into the rigor of survey statistics will gain even more from the content that SDA offers. The updates to SDA have potential to enrich traditional survey sampling classes at both the undergraduate and graduate levels. The new discussions of low response rates non-probability surveys and internet as a data collection mode hold particular value as these statistical issues have become increasingly important in survey practice in recent years… I would eagerly adopt the new edition of SDA as the required textbook. (Emily Berg Iowa State University) What is the unemployment rate? What is the total area of land planted with soybeans? How many persons have antibodies to the virus causing COVID-19? Sampling: Design and Analysis Third Edition shows you how to design and analyze surveys to answer these and other questions. This authoritative text used as a standard reference by numerous survey organizations teaches the principles of sampling with examples from social sciences public opinion research public health business agriculture and ecology. Readers should be familiar with concepts from an introductory statistics class including probability and linear regression; optional sections contain statistical theory for readers familiar with mathematical statistics. Key Features: Has been thoroughly revised to incorporate recent research and applications. Includes a new chapter on nonprobability samples and more than 200 new examples and exercises have been added. Teaches the principles of sampling with examples from social sciences public opinion research public health business agriculture and ecology. SDA’s companion website contains data sets computer code and links to two free downloadable supplementary books (also available in paperback) that provide step-by-step guides—with code annotated output and helpful tips—for working through the SDA examples. Instructors can use either R or SAS® software. SAS® Software Companion for Sampling: Design and Analysis Third Edition by Sharon L. Lohr (2022 CRC Press) R Companion for Sampling: Design and Analysis Third Edition by Yan Lu and Sharon L. Lohr (2022 CRC Press) | Sampling Design and Analysis

GBP 66.99
1