Sentence examples for models for background from inspiring English sources

Define 1D constant and powerlaw models for background data set 1 associated with source data set 2, then use them to find the equivalent width of the line between 2.0 and 10.0 keV.

This suggests that one possible approach to improve binding site prediction is to develop better motif (and background) models than the currently used position specific frequency model (PSFM) for binding sites and Markovian models for background.

When investigating the effects of traffic variables we also adjusted all models for background NO2 levels.

In (c) the airborne fraction for a pulse response experiment of 367 Gt CO2 (=100 GtC) released in year 1 obtained with the BICYCLE model for background conditions of 83 kyr ago and of pre-industrial times (PI) are compared with PI results from a MIP30.

In Section 4, Method-1 is introduced with Gaussian mixture model for background and moving object detection.

Each detector has one model for background (learned using non-mine training signatures) and another for mine (learned using trained mine signatures).

In background modeling and motion detection module, they employ an adaptive model for background estimation applying mixture of Gaussians and appearance patterns, thereby presenting a stable and robust background model.

This method mainly includes three parts, namely detecting the moving regions approximately by calculating the inter-frames differences of symmetrical frames and counting the static index of each probable moving point; modeling for background by the statistics of brightness information and updating this model combining motion templates; then extracting moving objects and its edges.

BATWING uses Markov chain Monte Carlo (MCMC) techniques to sample many reconstructed genealogies proportional to their probability under the coalescent model (for background see Wilson et al. [16]) in a Bayesian framework.

Without trying to perform an exhaustive study, we used the following parameters: motif length (m) = 10, number of different motifs to infer (z) = 2, expected number of sites in a given set of sequences (y) = 120, order of the Markov model for background probabilities (N) = 3.

The RMA convolution model for background correction of microarray data from Affymetrix platforms is very popular.