This book provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with a broad range of real-world applications. The book will be useful as a textbook for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.
This book provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with a broad range of real-world applications. The book will be useful as a textbook for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.
This volume contains original, refereed contributions by researchers from institutions and laboratories across the world that are involved in metrology and testing. They were adapted from presentations made at the eleventh edition of the Advanced Mathematical and Computational Tools in Metrology and Testing conference held at the University of Strathclyde, Glasgow, in September 2017, organized by IMEKO Technical Committee 21, the National Physical Laboratory, UK, and the University of Strathclyde. The papers present new modeling approaches, algorithms and computational methods for analyzing data from metrology systems and for evaluation of the measurement uncertainty, and describe their applications in a wide range of measurement areas.This volume is useful to all researchers, engineers and practitioners who need to characterize the capabilities of measurement systems and evaluate measurement data. Through the papers written by experts working in leading institutions, it covers the latest computational approaches and describes applications to current measurement challenges in engineering, environment and life sciences.
Metrology is the science of measurements. As such, it deals with the problem of obtaining knowledge of physical reality through its quantifiable properties. The problems of measurement and of measurement accuracy are central to all natural and technical sciences. Now in its second edition, this monograph conveys the fundamental theory of measurement and provides some algorithms for result testing and validation.
The book focuses on the extension of quality-assured measurement and metrology into psychological and social domains. This is not only feasible and achievable, but also a pressing concern. Significant progress in developing a common conceptual system for measurement across the sciences has been made in recent collaborations between metrologists and psychometricians, as reported in the chapters of this book. Modeling, estimation, and interpretation of objectively reproducible unit quantities that support both general comparability and adaptation to unique local circumstances are demonstrated in fields as diverse as artificial intelligence, justice, and beauty perception.
Measurement plays a fundamental role both in physical and behavioral sciences, as well as in engineering and technology: it is the link between abstract models and empirical reality and is a privileged method of gathering information from the real world. Is it possible to develop a single theory of measurement for the various domains of science and technology in which measurement is involved? This book takes the challenge by addressing the following main issues: What is the meaning of measurement? How do we measure? What can be measured? A theoretical framework that could truly be shared by scientists in different fields, ranging from physics and engineering to psychology is developed. The future in fact will require greater collaboration between science and technology and between different sciences. Measurement, which played a key role in the birth of modern science, can act as an essential interdisciplinary tool and language for this new scenario. A sound theoretical basis for addressing key problems in measurement is provided. These include perceptual measurement, the evaluation of uncertainty, the evaluation of inter-comparisons, the analysis of risks in decision-making and the characterization of dynamical measurement. Currently, increasing attention is paid to these issues due to their scientific, technical, economic and social impact. The book proposes a unified probabilistic approach to them which may allow more rational and effective solutions to be reached. Great care was taken to make the text as accessible as possible in several ways. Firstly, by giving preference to as interdisciplinary a terminology as possible; secondly, by carefully defining and discussing all key terms. This ensures that a wide readership, including people from different mathematical backgrounds and different understandings of measurement can all benefit from this work. Concerning mathematics, all the main results are preceded by intuitive discussions and illustrated by simple examples. Moreover, precise proofs are always included in order to enable the more demanding readers to make conscious and creative use of these ideas, and also to develop new ones. The book demonstrates that measurement, which is commonly understood to be a merely experimental matter, poses theoretical questions which are no less challenging than those arising in other, apparently more theoretical, disciplines.
This book presents a general and comprehensive framework for the assurance of quality in measurements. Written by a foremost expert in the field, the text reflects an on-going international effort to extend traditional quality assured measurement, rooted in fundamental physics and the SI, to include non-physical areas such as person-centred care and the social sciences more generally. Chapter by chapter, the book follows the measurement quality assurance loop, based on Deming’s work. The author enhances this quality assurance cycle with insights from recent research, including work on the politics and philosophy of metrology, the new SI, quantitative and qualitative scales and entropy, decision risks and uncertainty when addressing human challenges, Man as a Measurement Instrument, and Psychometry and Person-centred care. Quality Assured Measurement: Unification across Social and Physical Sciences provides students and researchers in physics, chemistry, engineering, medicine and the social sciences with practical guidance on designing, implementing and applying a quality-assured measurement while engaging readers in the most novel and expansive areas of contemporary measurement research.
