Advanced Mathematical and Computational Tools in Metrology and Testing VIII (Series on Advances in Mathematics for Applied 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.

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.