An efficiency curve obtained in a gamma-ray spectrometric system using a high purity germanium detector and radioactive standards of ¹³³Ba, ¹⁵²Eu and ^166mHo in an energy range of 50 to 1400 keV was established for metrological purposes. To do this, the efficiency response of the detector was used considering 29 different energies. This allowed calibrating various gammaemitter radioactive point sources, within of a 50 kBq to 550 MBq activity range, with expanded uncertainties below 2.5% at two-sigma confidence level (k=2). The obtained activity value for ²²Na was validated by sum-peak coincidence method.

Outside of the classical physical and chemical metrologies, there is a large field of measurement, which is called dimensionless or “soft “ metrology by analogy with hard and soft sciences.
The objective of this presentation is to provide an overview of this field, to analyze the methods used and their linkage to classical metrology.
The author will take 3 examples, an historical one, the measurement of human character, and two modern research fields, software usability and customer satisfaction.
He will also show the recent efforts from the European Commission, as part of the New Emerging Sciences and Technologies program (N.E.S.T.), to increase the objectivity of these measurements.

This paper presents the preliminary results of a research aimed to evaluate the effect of the measurement process on the effectiveness of control charting. To achieve this goal, the authors propose propagating the uncertainty of measurement through the control charting process using the Monte Carlo simulation technique (MCS).
Results are shown, evidencing that measurement uncertainty affects significantly the effectiveness of control charts an that the influence is different depending on the nature of the uncertainty contribution.

The ISO-GUM express that the standard deviation of the experimental standard deviation of the mean q obtained for ratio σ[s(q)]/σ(q) has a not negligible value for practical values of n, and therefore that Type A evaluations of the standard uncertainty are not necessarily more reliable than Type B evaluations. Although this correct comparison either, the assertion based on the value of the σ(q) is the not best, in way that this work to consider other relation as argument for this comparison.

Monitoring the physical or chemical conditions of the materials composing a monument can be achieved in a not invasive way by using trained neural networks. Soft sensors based on Elman neural networks have been developed to provide virtual measurements at locations of the monument surface using only the measurements acquired by an Air Ambient Monitor Station located nearby the monument. Here we improve the accuracy of the virtual measurements by using averaging techniques or mixture of such soft sensors. The accuracy of these virtual instruments is analyzed and compared from a metrological and statistical point of view.