Sentence examples for iteration trials from inspiring English sources

All significant (P<0.05) gene categories were determined by EASE score, corrected for multiplicity with the global false-discovery rate function using 1000 iteration trials.

At each iteration, trial order and ITI length were pseudo-randomized (no probability condition was repeated more than twice in a row, mean ITI length for all conditions was equalized) for all trials in a given experimental sequence and a design matrix was generated using AFNI's 3dDeconvolve script, assuming a TR of 2.5 seconds.

The processing time of the algorithm depends on how many iterations (trial swaps) are needed, and how much time each iteration takes.

However, the algorithm does not know when to stop, and we therefore need to estimate how many iterations (trial swaps) should be applied.

In this paper, we have analyzed the number of iterations (trial swaps) needed to solve the global allocation of the clusters.

To understand the significance of these we plot the distribution of the iterations (trial swaps) required in Fig. 13 as observed in the reality.

We estimate the number of iterations (trial swaps) required to find the clustering for three given probabilities of failure (10, 1, 0.1%).

We can estimate the number of iterations (trial swaps) needed to find the successful swap with the probability of q as follows: log q = T cdot log left( {1 - frac{{alpha^{2} }}{{k^{2} }}} right) Leftrightarrow T = frac{log left( q right)}{{log left( {1 - frac{{alpha^{2} }}{{k^{2} }}} right)}} (8).

But iteration takes trial and error.

It is often necessary to go through several iterations of trial-and-error to optimize the homogeneity, stability and solubility of the protein sample.

Several iterations were trialled using two reference studies.