Understanding, quantifying, and tracking atmospheric methane and emissions is essential for addressing concerns and informing decisions that affect the climate, economy, and human health and safety. Atmospheric methane is a potent greenhouse gas (GHG) that contributes to global warming. While carbon dioxide is by far the dominant cause of the rise in global average temperatures, methane also plays a significant role because it absorbs more energy per unit mass than carbon dioxide does, giving it a disproportionately large effect on global radiative forcing. In addition to contributing to climate change, methane also affects human health as a precursor to ozone pollution in the lower atmosphere. Improving Characterization of Anthropogenic Methane Emissions in the United States summarizes the current state of understanding of methane emissions sources and the measurement approaches and evaluates opportunities for methodological and inventory development improvements. This report will inform future research agendas of various U.S. agencies, including NOAA, the EPA, the DOE, NASA, the U.S. Department of Agriculture (USDA), and the National Science Foundation (NSF).

This book presents the main methods and techniques for measuring and monitoring the accuracy of geometrical parameters of precision Computer Numerically Controlled (CNC) and automated machines, including modern coordinate measuring machines (CMMs). Highlights include: • Standard methods and means of testing, together with methods newly developed and tested by the authors; • Various parameters, such as straightness, perpendicularity, flatness, pitch, yaw, and roll, as well as the principal processes for measurement of these parameters; • Lists and tables of geometrical accuracy parameters, together with diagrams of arrangements for their control and evaluation of measurement results; • Special methods and some original new devices for measurement and monitoring, information measuring systems (consisting of laser interferometers, photoelectric raster encoders or scales, etc.), and methods for the measurement and testing of circular scales, length scales, and encoders; • Methods for measuring small lengths, gaps, and distances between two surfaces; • Examples showing the suitability of mechatronic methods for high accuracy correction of machines; and • Particular attention is given to the analysis of ISO written standards of accuracy control, terms and definitions, and methods for evaluation of the measurement results during performance verification.

Phasor Measurement Units and Wide Area Monitoring Systems presents complete coverage of phasor measurement units (PMUs), bringing together a rigorous academic approach and practical considerations on the implementation of PMUs to the power system. In addition, it includes a complete theory and practice of PMU technology development and implementation in power systems. - Presents complete coverage of the topic from the measurement to the system, bringing together a rigorous academic approach and practical considerations on the implementation of PMUs to the power system - Includes a complete proposal of implementation for a PMU platform that could be replicated in every laboratory - Covers PMU software compiled for National Instrument HW, a compiled monitoring platform to be used to monitor PMU data and developed custom solutions, and a compiled National Instrument schematic to be executed within a SmartPhone app

The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use

This is the digital version of the printed book (Copyright © 1996). Based on an award-winning doctoral thesis at Carnegie Mellon University, Measuring and Managing Performance in Organizations presents a captivating analysis of the perils of performance measurement systems. In the book’s foreword, Peopleware authors Tom DeMarco and Timothy Lister rave, “We believe this is a book that needs to be on the desk of just about anyone who manages anything.” Because people often react with unanticipated sophistication when they are being measured, measurement-based management systems can become dysfunctional, interfering with achievement of intended results. Fortunately, as the author shows, measurement dysfunction follows a pattern that can be identified and avoided. The author’s findings are bolstered by interviews with eight recognized experts in the use of measurement to manage computer software development: David N. Card, of Software Productivity Solutions; Tom DeMarco, of the Atlantic Systems Guild; Capers Jones, of Software Productivity Research; John Musa, of AT&T Bell Laboratories; Daniel J. Paulish, of Siemens Corporate Research; Lawrence H. Putnam, of Quantitative Software Management; E. O. Tilford, Sr., of Fissure; plus the anonymous Expert X. A practical model for analyzing measurement projects solidifies the text–don’t start without it!

This volume, developed by the Observatory together with OECD, provides an overall conceptual framework for understanding and applying strategies aimed at improving quality of care. Crucially, it summarizes available evidence on different quality strategies and provides recommendations for their implementation. This book is intended to help policy-makers to understand concepts of quality and to support them to evaluate single strategies and combinations of strategies.

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You'll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You'll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. - Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges - Enables discussions between business and IT with a non-technical vocabulary for data quality measurement - Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

Spectacular security failures continue to dominate the headlines despite huge increases in security budgets and ever-more draconian regulations. The 20/20 hindsight of audits is no longer an effective solution to security weaknesses, and the necessity for real-time strategic metrics has never been more critical. Information Security Management Metr

'The M4P approach fosters understanding of the functions and players within market systems and how these can be strengthened in order to better serve the needs of the poor.' Alan Gibson. This collection, all inspired in some way by Gibson's teachings, is essential reading for practitioners, funders, consultants, academics, and policymakers.

Structural health monitoring (SHM) is a new engineering field with a growing tendency, based on technology development focused on data acquisition and analysis, to prevent possible damage in man-made structures and land's natural faults. The data are obtained from sensors and monitoring systems that allow detecting damages on structures, space vehicles, and land natural faults, to model their behavior under adverse scenarios, in order to search the detection of anomalies. Currently, there are many SHM systems with sensors based on different technologies like optical fiber, video cameras, optical scanners, wireless networks, and piezoelectric transducers, among others. In this context, the present book includes selected chapters with theoretical models and applications, to preserve infrastructure and prevent loss of human lives.