The third edition of The Ecology and Silviculture of Oaks is an updated and expanded edition that explores oak forests as responsive ecosystems. New chapters emphasize the importance of fire in sustaining and managing oak forests, the effects of a changing climate, and advanced artificial regeneration techniques. This new edition expands on silvicultural methods for restoring and sustaining oak woodlands and savannahs, and on management of ecosystem services, including wildlife habitat. It...

There is increasing understanding that climate change will have profound, mostly harmful effects on human health. In this authoritative book, international experts examine long-recognized areas of health concern for populations vulnerable to climate change, describing effects that are both direct, such as heat waves, and indirect, such as via vector-borne diseases. Set in a broad international, economic, political and environmental context, this unique book expands these issues by reviving...

This brief introduces wireless communications ideas and techniques into the study of networked control systems. It focuses on state estimation problems in which sensor measurements (or related quantities) are transmitted over wireless links to a central observer.Wireless communications techniques are used for energy resource management in order to improve the performance of the estimator when transmission occurs over packet dropping links, taking energy use into account explicitly ...

The bible of all fundamental algorithms and the work that taught many of today's software developers most of what they know about computer programming.–Byte, September 1995I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up.–Charles LongIf you think y...

This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in m...

Introduction to Data Compression, Third Edition, is a concise and comprehensive guide to data compression. This book introduces the reader to the theory underlying today's compression techniques with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression, it covers lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quanti...

Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in netw...

This volume contains two types of papers—a selection of contributions from the “Second International Conference in Network Analysis” held in Nizhny Novgorod on May 7–9, 2012, and papers submitted to an "open call for papers" reflecting the activities of LATNA at the Higher School for Economics.This volume contains many new results in modeling and powerful algorithmic solutions applied to problems in• vehicle routing• single machine scheduling• modern financial...

This book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development...

Understand deep learning, the nuances of its different models, and where these models can be applied.The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R provides a theoretical and practical understanding of the models that perform these tasks by building upon the fundamentals of data science through machine learning...

Graphical models in their modern form have been around since the late 1970s and appear today in many areas of the sciences. Along with the ongoing developments of graphical models, a number of different graphical modeling software programs have been written over the years. In recent years many of these software developments have taken place within the R community, either in the form of new packages or by providing an R interface to existing software. This book attempts to give the reader a...

Steganography is the art of communicating a secret message, hiding the very existence of a secret message. This book is an introduction to steganalysis as part of the wider trend of multimedia forensics, as well as a practical tutorial on machine learning in this context. It looks at a wide range of feature vectors proposed for steganalysis with performance tests and comparisons. Python programs and algorithms are provided to allow readers to modify and reproduce outcomes discussed in the ...