Volume Rendering Using Principal Component Analysis

Here the original Axelsson model and the Modified Stuhmiller model were in best agreement, which could indicate that chest wall velocity is a better injury parameter than

In the analysis of flow around an acoustic antenna, various tensors appear, for example the strain rate tensor, structural tensors and tensorial expressions involved in the

By multivariate analysis using Principal Component Analysis (PCA) and Partial Least Square (PLS) calibration, it can be concluded that the overt1ow water masses

Principal component analysis (PCA) applied to the spectra obtained from online fluorescence (a) and diffuse reflectance (b) hyperspectral imaging, and offline full range (400–2500

What is important with regards to sufficient variation on the dependent variable in a logistic regression is that the total sample is sufficiently high to include a high number

In addition, the literature overview revealed that multivariate techniques, especially principal component analysis (PCA), were the preferred data analysis approaches used in

We present a technique to extract regions from a volumetric dataset without introducing any aliasing so that the extracted volume can be explored using direct volume

One problem with cell-based PCA is that it results in subtle discontinuity artefacts at the cell boundaries in the reconstructed images.. Another problem with PCA based approaches