Parallel and Distributed Computing and Networks

This book looks at fundamentals, theoretical concepts, and how theory informs perspectives of thinking for distributed team cognition. The chapters yield a broad understanding of the nature of diverse

Computing and Coding in the Real World looks at applied coding and the computation hidden in the world that surrounds us. Readers will learn how things work, from scanners at supermarket checkouts to

Deep Neural Networks and Applications makes the readers aware about the various artificial neural networks (ANN) and the topologies related to main neural networks (MNN). The book throws light on the

Reveals the diverse ways that cognition was seen as spread over brain, body and world in the 9-17th centuriesThis collection brings together 14 essays by international specialists in Medieval and Rena

The two-volume set LNCS 11508 and 11509 constitutes the refereed proceedings of of the 18th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2019, held in Zakopane, Polan

This informative text/reference presents a detailed review of the state of the art in industrial sensor and control networks. The book examines a broad range of applications, along with their design o

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with

A comprehensive guide to Fog and Edge applications, architectures, and technologiesRecent years have seen the explosive growth of the Internet of Things (IoT): the internet-connected network of device

The science of networks represented a substantial change in the way we see natural and technological phenomena. Now we have a better understanding that networks are, in most cases, networks of network

This book constitutes the refereed proceedings of the Third International Conference on Smart Computing and Communications, SmartCom 2018, held in Tokyo, Japan, in December 2018. The 45 papers present

Arguably the strongest addition to numerical finance of the past decade, Algorithmic Adjoint Differentiation (AAD) is the technology implemented in modern financial software to produce thousands of accurate risk sensitivities, within seconds, on light hardware.AAD recently became a centerpiece of modern financial systems, and a key skill for all quantitative analysts, developers, risk professionals or anyone involved with derivatives. It is increasingly taught in Masters programs in finance.Wiley's Computational Finance books, written by some of the very people who wrote Danske Bank's award-winning systems, offer a unique insight into the modern implementation of financial models. The volumes combine financial modelling, mathematics and programming to resolve real life financial problems and produce effective derivatives software.This volume is a complete, self-contained learning reference for AAD, and its application in finance. AAD is explained in deep detail throughout chapters that

The proceedings covers advanced and multi-disciplinary research on design of smart computing and informatics. The theme of the book broadly focuses on various innovation paradigms in system knowledge,

Designed for professionals and students of networking and cryptography, this book covers key concepts and issues related to emerging technology, such as the Internet of Things, WiMax, mobile access, c