A robust data reconciliation strategy provides unbiased variable estimates in the presence of a moderate quantity of atypical measurements. However, estimates get worse if systematic measurement errors that persist in time ...

Robust Data Reconciliation enhances the quality of variable estimates when the data set contains a moderate proportion of atypical observations. But if systematic errors that persist in time, i.e. biases and drifts, are ...

Product quality can be understood as inversely proportional to the variability in its production process. The control chart is a well-established statistical tool for quantifying and analyzing this process' variability ...

Large-scale application of Quantitative Sensory Tests (QST) is impaired by lacking standardized testing protocols. One unclear methodological aspect is the number of records needed to minimize measurement error. Traditionally, ...

Phase-shifting Moire interferometry is a whole-field optical technique used to measure displacements. Because of its high sensitivity, its results are affected by even small environmental perturbations. In this paper, the ...

Robust Data Reconciliation strategies provide unbiasedvariable estimates in the presence of a moderate quantity of measurement grosserrors. Systematic errors which persist in time, as biases or drifts, overcome thisquantity ...

Society has been increasingly concerned about the impact of pain on farm animal welfare. This systematic review aims to provide evidence relating to the measurement properties (i.e. reliability, validity, and sensitivity) ...