Sentence examples for reduction analyses from inspiring English sources

Data reduction analyses revealed preference categories and associated dimensions of preference, i.e. aesthetically relevant attributes.

Item reduction analyses identified an 18-item short form of the PBQ (PBQ-SF) that exhibited psychometric properties similar to the original measure.

Data reduction analyses have been applied to tackle the problem of highly correlated indices, but valid landscape predictors for fine scale Mediterranean forest-mosaics are still missing.

Reliability and data reduction analyses were conducted to validate the construction of composite 'creativity' variables for the basis of further comparisons.

The synthesized samples were characterized by X-ray diffraction (XRD), nitrogen adsorption-desorption isotherms, UV vis diffuse reflection spectrum (UV vis DRS), H2-temperature-programmed reduction analyses (H2-TPR) and transmission electron microscopy (TEM).

Under these culture conditions the cells quickly used up most of the available dissolved oxygen, as reflected by resazurin dye reduction analyses.

Data-reduction analyses revealed the cognitive structure of wetland perception, a framework of categories and constructs that underpin wetland meaning.

Cost-reduction analyses are also promising: Wassmer anticipated reductions in cost even when partially based on modeling estimates [ 31]; two other studies showed the effects of clinical case management on hospital services and its cost effectiveness [ 12, 29].

Redox cycles were performed, involving temperature programmed reduction (TPR) analyses separated by an oxidation treatment (TPO).

Temperature-programmed reduction (TPR) analyses were carried out under continuous H2 flow (5% H2 in He) in a quartz cell at 10 K min−1 using a Quantachrome ChemBET 3000 (Quantachrome Instruments, Boynton Beach, FL, USA) coupled with a Hiden Analytical HPR 20 QIC mass spectrometry detector (Hiden Analytical, Warrington, UK).

In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria.