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The 2-D space of the unknown velocity can be modeled as an N vx × N vy search space such that each point in the discretized space represents a hypothetical target velocity vector, where N vx and N vy denote the number of discrete points used to represent the entire target velocity space along the x-axis and y-axis, respectively.
This representation allows to include side-chain information without increasing the computational cost, because residues are still paired as single entities, i.e. the points used to represent them are not treated independently (see Methods).
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Different geometrical types can be described by vector data and basically there are three broad type categories; zero-dimensional points are used to represent points-of-interest, lines are used to represent linear features such as roads and topological lines, and polygons are used to represent particular areas such as lakes.
In this paper, we apply the AMA methods for image representation, in which a triangular mesh with fewer points is used to represent the original image f.
For discriminative and nonparametric approaches, lattice-type control points are used to represent the Bayes error gradient distribution in a nonparametric manner [44].
The average response of three data points was used to represent a single unknown sample.
A 10percentnt random sample of address points was used to represent the population distribution of Western Australia (165165 individuals), and postcode boundaries were used for summary purposes, as these are the spatial units used for disease reporting nationally in Australia.
Then a set of image patches Q 1 = { q(I 1, c1), q(I 1, c 2),..., q(I 1, c K)} centered at the salient points are used to represent the image appearance of the subject at the reference frame I 1.
One method for deducing the strength of an acoustic source distribution from measurement of the radiated field involves the inversion of the matrix of frequency response functions relating the field measurement points to the strengths of a number of point sources used to represent the source distribution.
One method for deducing the strength of an acoustic source distribution from measurements of the radiated field involves the inversion of the matrix of frequency response functions relating the field measurement points to the strengths of a number of point sources used to represent the source distribution.
The model uses an efficient numerical integration scheme to integrate the contributions of point sources used to represent a line-source.
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