Alistair B. Forbes – författare

The aim of this book is to provide, ?rstly, an introduction to probability and statistics especially directed to the metrology and testing ?elds and secondly, a comprehensive, newer set of modelling methods for data and uncertainty analysis that are generally not considered yet within mainstream methods. The book brings, for the ?rst time, a coherent account of these newer me- ods and their computational implementation. They are potentially important because they address problems in application ?elds where the usual hypot- ses that are at the basis of most of the traditional statistical and probabilistic methods, for example, relating to normality of the probability distributions, are frequently not ful?lled to such an extent that an accurate treatment of the calibration or test data using standard approaches is not possible. Additi- ally, the methods can represent alternative ways of data analysis, allowing a deeper understanding of complex situations in measurement. The book lends itself as a possible textbook for undergraduate or postgraduate study in an area where existing texts focus mainly on the most common and well-known methods that do not encompass modern approaches to calibration and testing problems. The book is structured in such a way to guide readers with only a g- eral interest in measurement issues through a series of review papers, from an initial introduction to modelling principles in metrology and testing, to the basic principles of probability in metrology and statistical approaches to - certainty assessment.

The aim of this book is to provide, ?rstly, an introduction to probability and statistics especially directed to the metrology and testing ?elds and secondly, a comprehensive, newer set of modelling methods for data and uncertainty analysis that are generally not considered yet within mainstream methods. The book brings, for the ?rst time, a coherent account of these newer me- ods and their computational implementation. They are potentially important because they address problems in application ?elds where the usual hypot- ses that are at the basis of most of the traditional statistical and probabilistic methods, for example, relating to normality of the probability distributions, are frequently not ful?lled to such an extent that an accurate treatment of the calibration or test data using standard approaches is not possible. Additi- ally, the methods can represent alternative ways of data analysis, allowing a deeper understanding of complex situations in measurement. The book lends itself as a possible textbook for undergraduate or postgraduate study in an area where existing texts focus mainly on the most common and well-known methods that do not encompass modern approaches to calibration and testing problems. The book is structured in such a way to guide readers with only a g- eral interest in measurement issues through a series of review papers, from an initial introduction to modelling principles in metrology and testing, to the basic principles of probability in metrology and statistical approaches to - certainty assessment.

This volume contains original, refereed contributions by researchers from national metrology institutes, universities and laboratories across the world involved in metrology and testing. The volume has been produced by the International Measurement Confederation Technical Committee 21, Mathematical Tools for Measurements and is the twelfth in the series. The papers cover topics in numerical analysis and computational tools, statistical inference, regression, calibration and metrological traceability, computer science and data provenance, and describe applications in a wide range of application domains. This volume is useful to all researchers, engineers and practitioners who need to characterize the capabilities of measurement systems and evaluate measurement data. It will also be of interest to scientists and engineers concerned with the reliability, trustworthiness and reproducibility of data and data analytics in data-driven systems in engineering, environmental and life sciences.

The main theme of the AMCTM 2008 conference, reinforced by the establishment of IMEKO TC21, was to provide a central opportunity for the metrology and testing community worldwide to engage with applied mathematicians, statisticians and software engineers working in the relevant fields.This review volume consists of reviewed papers prepared on the basis of the oral and poster presentations of the Conference participants. It covers all the general matters of advanced statistical modeling (e.g. uncertainty evaluation, experimental design, optimization, data analysis and applications, multiple measurands, correlation, etc.), metrology software (e.g. engineering aspects, requirements or specification, risk assessment, software development, software examination, software tools for data analysis, visualization, experiment control, best practice, standards, etc.), numerical methods (e.g. numerical data analysis, numerical simulations, inverse problems, uncertainty evaluation of numerical algorithms, applications, etc.), and data fusion techniques and design and analysis of inter-laboratory comparisons.

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.

This volume contains original, refereed worldwide contributions. They were prompted by presentations made at the ninth AMCTM Conference held in Göteborg (Sweden) in June 2011 on the theme of advanced mathematical and computational tools in metrology and also, in the title of this book series, in testing.The themes in this volume reflect the importance of the mathematical, statistical and numerical tools and techniques in metrology and testing and, also in keeping the challenge promoted by the Metre Convention, to access a mutual recognition for the measurement standards.

This volume contains original and refereed contributions from the tenth AMCTM Conference (www.nviim.ru/AMCTM2014) held in St. Petersburg (Russia) in September 2014 on the theme of advanced mathematical and computational tools in metrology and testing.The themes in this volume reflect the importance of the mathematical, statistical and numerical tools and techniques in metrology and testing and, also keeping the challenge promoted by the Metre Convention, to access a mutual recognition for the measurement standards.

This volume contains original, refereed contributions by researchers from national metrology institutes, universities and laboratories across the world involved in metrology and testing. The volume has been produced by the International Measurement Confederation (IMEKO) Technical Committee 21, Mathematical Tools for Measurements, in association with IMEKO Technical Committee 6, Digitalisation, and the European Network for Mathematics and Statistics for Metrology, following presentations made at the Advanced Mathematical and Computational Tools in Metrology online conference, hosted by the Institute of Metrology of Bosnia and Herzegovina, Sarajevo, in September 2023. The volume covers the application of novel mathematical and statistical modelling techniques and data analysis and machine learning approaches to metrology and measurement science, uncertainty quantification, and knowledge representation and reasoning to enable the digitalization of metrological services.This volume is of interest to all researchers, data scientists, engineers and practitioners who need to characterize the capabilities of measurement systems, evaluate measurement data, quantify uncertainties and make inferences and decisions based on models and data. It will also be of interest to those working in the quality infrastructure concerned with the reliability, transparency, trustworthiness and reproducibility of data, data analytics, machine learning and AI, in engineering, physical, environmental and the life sciences.

Advances in metrology depend on improvements in scientific and technical knowledge and in instrumentation quality, as well as better use of advanced mathematical tools and development of new ones. In this volume, scientists from both the mathematical and the metrological fields exchange their experiences. Industrial sectors, such as instrumentation and software, are likely to benefit from this exchange, since metrology has a high impact on the overall quality of industrial products, and applied mathematics is becoming more and more important in industrial processes.This book is of interest to people in universities, research centers and industries who are involved in measurements and need advanced mathematical tools to solve their problems, and to those developing such mathematical tools.