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Results of measurements and conclusions derived from them constitute much of the technical information produced by the National Institute of Standards and Technology (NIST). In July 1992 the Director of NIST appointed an Ad Hoc Committee on Uncertainty Statements and charged it with recommending a policy on this important topic. The Committee concluded that the CIPM approach could be used to provide quantitative expression of measurement that would satisfy NIST¿s customers¿ requirements. NIST initially published a Technical Note on this issue in Jan. 1993. This 1994 edition addresses the most important questions raised by recipients concerning some of the points it addressed and some it did not. Illustrations.
Research centering on blood flow in the heart continues to hold an important position, especially since a better understanding of the subject may help reduce the incidence of coronary arterial disease and heart attacks. This book summarizes recent advances in the field; it is the product of fruitful cooperation among international scientists who met in Japan in May, 1990 to discuss the regulation of coronary blood flow.
This book is a printed edition of the Special Issue "Sound and Music Computing" that was published in Applied Sciences
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.
This handbook offers the first comprehensive, state-of-the-field guide to past weather and climate and their role in human societies. Bringing together dozens of international specialists from the sciences and humanities, this volume describes the methods, sources, and major findings of historical climate reconstruction and impact research. Its chapters take the reader through each key source of past climate and weather information and each technique of analysis; through each historical period and region of the world; through the major topics of climate and history and core case studies; and finally through the history of climate ideas and science. Using clear, non-technical language, The Palgrave Handbook of Climate History serves as a textbook for students, a reference guide for specialists and an introduction to climate history for scholars and interested readers.
This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
The application of metal-oxide surge arresters to safeguard electric power equipment against the hazards of abnormally high voltage surges of various origins is covered. Step-by-step directions toward proper solutions of various applications are provided. In many cases, the prescribed steps are adequate. More complex and special solutions requiring study by experienced engineers are described, but specific solutions are not always given. The procedures are based on theoretical studies, test results, and experience.
An aging population, increasing obesity and more people with mobility impairments are bringing new challenges to the management of routine and emergency people movement in many countries. These population challenges, coupled with the innovative designs being suggested for both the built environment and other commonly used structures (e.g., transportation systems) and the increasingly complex incident scenarios of fire, terrorism, and large-scale community disasters, provide even greater challenges to population management and safety. Pedestrian and Evacuation Dynamics, an edited volume, is based on the Pedestrian and Evacuation Dynamics (PED) 5th International 2010 conference, March 8th-10th 2010, located at the National Institute of Standards and Technology, Gaithersburg, MD, USA. This volume addresses both pedestrian and evacuation dynamics and associated human behavior to provide answers for policy makers, designers, and emergency management to help solve real world problems in this rapidly developing field. Data collection, analysis, and model development of people movement and behavior during nonemergency and emergency situations will be covered as well.
Extreme Solar Particle Storms: The hostile Sun provides a consolidated review of our current understanding of extreme solar events, or black swans, that leave our technological society vulnerable. Written by experts at the forefront of the growing field of solar storms, this book will be of interest to students and researchers, as well as those curious about the threat that our Sun poses to the modern world.