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In each case, amplitude images in dual and/or full polarization modes and polarimetric decomposition data from the full polarization mode were extracted and integrated into a spatial analysis platform.

An unsupervised cluster analysis was performed to fractionate each bacterial trajectory into run and tumble segments, and then the distribution of parameters for each mode were extracted by fitting mathematical distributions best representing the data.

The particle displacement associated to a particular mode is extracted from the modulus, of each transform.

The only difference between SEMD algorithm and the conventional EMD is step A, where the first mode is extracted by smoothing instead of interpolation.

The dominant unstable mode is extracted by performing CEA based on a linear finite element (FE) model, and the negative damping ratio corresponding to the dominant unstable mode is selected as the indicator of instability.

System matrices are first obtained by using a general system identification technique, and then the natural frequency and damping ratio of each mode are extracted from the obtained system matrices.

By utilizing a high refractive index substrate, a high light scattering electrode, and an external light extraction structure, trapped photons in the wave-guided and substrate modes were extracted effectively.

Following the eigen decomposition for the estimation of frequency and damping, the mode shapes corresponding to the identified inter-area oscillation modes were extracted and shown in Fig. 4 for both Cases 1 and 2. Table 2 Modes identified by applying SSI-DATA to simulated data Case Mode no.

From the DTI data, subject modes were extracted from thalamic DTI bundles that showed significantly different connectivity.

Optimal POD modes are extracted from a chaotic Galerkin mode responses.

The most important vibration modes are extracted from a real mechanical system.