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The equations of motion are first generated in the Cartesian coordinate system and then transformed into the relative coordinate system by using a velocity transformation.
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Eye velocity data were edited to remove saccades and any body movement artifacts using a velocity threshold.
Fixations were identified using a velocity-based algorithm with a velocity threshold of 6.58°/s (see Henderson, McClure, Pierce ,& Schrock, 1997).
Set 2: Normalized profiles (NP): The second data set is termed NP and is derived from the RP set using a homothetic transformation; all velocities are scaled by a factor of 800/V bedrock so that the bedrock velocity is equal to 800 m/s for each profile in this "normalized profile" set, while the thickness of each layer is also scaled with the same factor to maintain an unchanged transfer function.
TG levels were transformed using a logarithmic transformation (see Supplementary Material for a power transformation approach).
The model was constructed by using a Fourier transformation technique for the Helmholtz equation and the velocity boundary conditions at the duct's wall.
Velocity was measured using a linear velocity displacement transducer.
In essence, PCA rotates data by using a linear transformation.
Height phenotypic measurements were approximately normalized using a log10 transformation.
With a sample volume (2.5 or 3.0 mm wide) positioned on the color signal in the LAD, Doppler spectral tracings of flow velocity in the LAD were recorded using a fast Fourier transformation.
We model the transformation between a similarity model and a distance function using a transformation function.
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