Charged particles contained between these points can be made to reflect back and forth, an effect called magnetic mirroring.
The distance between two points can be calculated by the following Eq. (170).
Generally, numerical approaches based on the radial distance work very well on flat surfaces, such as plates, and on curves with constant curvature, such as spheres and cylinders, because the distance between two points can be easily measured.
The relationship between these points can be found by the rotation matrix: left(begin{array}{c}hfill {x}_{m,n+1}hfill hfill {y}_{m,n+1}hfill end{array}right)kern0.5em =kern0.5em left(begin{array}{c}hfill cosphi - sinphi hfill hfill sinphi kern1.5em cosphi hfill end{array}right)left(begin{array}{c}hfill {x}_{m,n}hfill hfill {y}_{m,n}hfill end{array}right) (4 where φ is − (π − 2θ).
Pairwise correspondence between time points can be combined in longer time series, for example to perform clonal analysis over several days (Vlad et al., 2014).
Given the dataset X, pairwise similarity W X ∈ℝ n × n between data points can be computed using the Gaussian kernel function, (2) where the vector x is calculated using bag-of-word features for one image bag.
When calculating the Silhouette score, the distance between data points can be measured either in one dimension, for example on the x-axis, or in two dimension using vectors, as illustrated in Figure 1.
In a motorway context, the distance between two travelling points can be directly calculated.
The above analysis indicates that the PP between the terminal points can be controlled by adjusting the voltage amplitude and phase angle of each terminal.
The two-point resolution in coherent illumination hard X-rays can be obtained by 0.82λ/NA [9]—if the relative phase between the two points can be considered as zero where λ is the wavelength and NA is the numerical aperture.
