"This book by Lisa Tauxe and others is a marvelous tool for education and research in Paleomagnetism. Many students in the U.S. and around the world will welcome this publication, which was previously only available via the Internet. Professor Tauxe has performed a service for teaching and research that is utterly unique."—Neil D. Opdyke, University of Florida

For centuries, scientists have been fascinated by the role of the Sun in the Earth's climate system. Recent discoveries, outlined in this book, have gradually unveiled a complex picture, in which our variable Sun affects the climate variability via a number of subtle pathways, the implications of which are only now becoming clear. This handbook provides the scientifically curious, from undergraduate students to policy makers with a complete and accessible panorama of our present understanding of the Sun-climate connection. 61 experts from different communities have contributed to it, which reflects the highly multidisciplinary nature of this topic. The handbook is organised as a mosaic of short chapters, each of which addresses a specific aspect, and can be read independently. The reader will learn about the assumptions, the data, the models, and the unknowns behind each mechanism by which solar variability may impact climate variability. None of these mechanisms can adequately explain global warming observed since the 1950s. However, several of them do impact climate variability, in particular on a regional level. This handbook aims at addressing these issues in a factual way, and thereby challenge the reader to sharpen his/her critical thinking in a debate that is frequently distorted by unfounded claims.

This brief provides a review of the evolution of optical fiber sensing solutions and related applications. Unique production methods are presented and discussed, highlighting their evolution and analyzing their complexity. Under this scope, this brief presents the existing silica optical fiber sensors and polymer optical fiber sensors solutions, comparing its field of action (sensitivity, accuracy), complexity of manufacture and economic cost. Special attention is given to low-cost production methods. This brief evaluates the different existing techniques, assessing the accuracy and suitability of these sensors for possible Internet of Things (IoT) integration in different considered scenarios. Critical analytical techniques, also covered in this brief, are expected to play a key role in the world of IoT and the smart city of tomorrow.

Historical maps are fascinating documents and a valuable source of information for scientists of various disciplines. Many of these maps are available as scanned bitmap images, but in order to make them searchable in useful ways, a structured representation of the contained information is desirable. This book deals with the extraction of spatial information from historical maps. This cannot be expected to be solved fully automatically (since it involves difficult semantics), but is also too tedious to be done manually at scale. The methodology used in this book combines the strengths of both computers and humans: it describes efficient algorithms to largely automate information extraction tasks and pairs these algorithms with smart user interactions to handle what is not understood by the algorithm. The effectiveness of this approach is shown for various kinds of spatial documents from the 16th to the early 20th century.

This book constitutes the refereed proceedings of the 5th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2019, held in Trivandrum, India, in December 2019. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 63 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.

Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.

The main aims of power electronic converter systems (PECS) are to control, convert, and condition electrical power flow from one form to another through the use of solid state electronics. This book outlines current research into the scientific modeling, experimentation, and remedial measures for advancing the reliability, availability, system robustness, and maintainability of PECS at different levels of complexity.