Sentence examples for transformation measures from inspiring English sources

These expansion factors for IEEAF increased slightly between 1993 and 2002, which is a result of an increasing proportion of younger trees above coarse wood, e.g. through forest transformation measures.

Because of the transformations, measures of effects could be expressed as the relative change (percent) of the outcome variables for each doubling of the exposure.

In this setting, this paper addresses the following question: Can the maintainability of XSL transformations, measured in terms of code churn in the next revision of a transformation, be predicted using a combination of simple metrics?

New transformation of measures is studied and several examples are presented.

In particular, we adopt an explicit local linearization of the governing nonlinear SDEs and the resulting linearization errors in the estimates are corrected using Girsanov transformation of measures.

Indeed, the linearization scheme via transformation of measures provides a weak framework for computing moments and this fits in well with any stochastic filtering strategy wherein estimates are themselves statistical moments.

Following this, we suggest a novel procedure to weakly correct the SLTL-based strong solutions, which capture the analyticity and continuity of flow of a dynamical system, using Girsanov transformation of measures.

The significance is measured by scaling the correlation to the normal by a Fisher transformation and measuring the number of standard deviations from the mean.

The team applied a mathematical transformation that measured how much the time between beats fluctuated, a measure known as the wavelet coefficient, to sets of anywhere from two to more than 1000 heartbeat intervals.

The degree of β-SiC to α-SiC phase transformation was measured by means of quantitative XRD using internal standard technique.

Concentrations of the PFAs were transformed to log-molar units, and it was seen that after this transformation the measured exposures approximately follow a normal distribution.