Sentence examples for fluctuation data are from inspiring English sources

The fluctuation data are obtained first in the space-time coordinates and are then transformed into the spectral domain spanning the wavevectors and frequencies by using the fast Fourier transform algorithm.

The fluctuation data are obtained at each evolution time step for the three field components (x and y are in the direction perpendicular to the mean magnetic field. x is in the direction out of the simulation box or plane, and z is in the direction parallel to the mean field) at all the mesh grid points in the two-dimensional space.

To obtain auto- and cross-correlation curves, raw fluorescence fluctuation data were fitted to a three-dimensional diffusion model with homemade software.

Fluctuation data were analyzed by the Ma Sandri Sarkar maximum-likelihood method (S arkar et al. 1992; F oster 2006).

At the end of the fast spreading phase (approx. 30 min after spreading), M.S.R. fluctuation data was collected for cells, starting at similar time points.

The fluorescence fluctuation data were recorded on a FCS reader (Insight, Inovation GmbH, Osnabrück, Germany), applying a water immersion objective (60× UPLSAPO, NA 1.2, Olympus, Japan).

Completeness levels between 1996 and 2006 were determined by assuming that the completeness of death registration follows a logistic trend over time; that completeness in any age group did not decrease over the period; and that the trend in completeness is smooth (i.e. fluctuations in the data are not due to fluctuations in completeness).

This will include an eagerly awaited update about a mysterious bump in the data that could be evidence for a new particle or just a statistical fluctuation, as more data are being analyzed.

In order to intensively evaluate the performance improvement of FSOC due to the beam ATP control system, the time series plot of beam centroid displacement (wandering) on a 2D opto-electronic position detector (OPD) plane received signal power fluctuation and the demodulated data are continuously recorded and used to carry out on/off line analysis and compute various communication parameters.

However, it is often difficult to determine if fluctuations in human physiological data are chaotic or the result of random neuromuscular noise [1].

Model 1 demonstrates, by using a concentric ring model, that the fluctuations of the contact angle data are due to surface heterogeneity.