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Operator transformations are presented that allow matrix operators for collocated variables to be transformed into matrix operators for staggered variables while preserving symmetries.

The performances of MW-PSNR for different wavelet transformations are presented in the upper part of Table 3.

Because of this, the results on acoustic model adaptation and feature transformations are presented only for the detector topology (similar choice has been done, e.g., in [4]).

Figure 3 shows examples of the Oxford dataset, where six image transformations are presented, including blur (Figures 3(a) and 3(b)), viewpoint change (Figures 3(c) and 3(d)), scale and rotation changes (Figures 3 e) and 3(f)), illumination change (Figure 3(g)), and JPEG compression (Figure 3(h)).

The λ-values from the Box-Cox transformations are presented.> -wrap-foot>> -wrap-foot>> -wrap-foot>> -wrap-foot>> -wrap-foot> aRBC = red blood cell count; MCV = mean corpuscular volume; MCHC = mean corpuscular haemoglobin concentration; WBC = white blood cell count; Segm.neutroph.neutroph

All these transformations are presented in detail in Additional file 1. Eliminated variables – only variables with all missing values have been eliminated, that is, those variables whose information was not collected by doctors and nurses.

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A Monte Carlo (MC) simulation technique which is well suited for studying diffusional phase transformations is presented.

A structured approach for matching requirements to visual form based on work domain analysis, task analysis, scale matching, and data transformations is presented.

A detailed analysis of those constructions that seem to be essential for students understanding of this topic including linear transformations is presented.

A band-to-band alignment procedure based on the first- and second-order polynomial transformations was presented to further align the four band images.

A schematic view of these transformations is presented below.

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