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In the Spad software (version 7.4), the classification follows a factor analysis that maximises both the homogeneity intra-cluster and the separateness inter-cluster.
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In scenario e, R was drawn from a central Wishart distribution with p + 1 degrees of freedom and therefore was full rank and did not follow a factor structure at all.
To estimate an error of the ASL method, we added random fluctuations to the site amplification factor of each station based on the assumption that the site amplification factor follows a log-normal distribution (standard deviations are listed in Table 1), then we conducted a grid search 100 times for each event with the fluctuated site amplification factors.
The screening window coefficient, or Z-factor, was determined as followed: A Z-factor >0.5 represented an excellent assay suitable for high-throughput screening.
The total flux of the surface modified membrane increased with increasing the feed composition, feed temperature, feed flow rate of the mixture whereas the separation factor follows a reversed order except for flow rate.
This factor follows a function for the dose response curve, describing the effect of a compound on the maximum current flowing through the target.
In essence, if one accepts this assumption then the distribution of associated factors follows a tri-modal distribution and it will be intuitive to measure the level of association for different factors with respect to a given disease.
In what follows a description of these factors is given.
The bold black line indicates the corresponding value of the EM potential scaling factor, which follows a linear ramp function (See 'Materials and methods').
Note that the contracted received signal tensor Y ̄ ∈ ℂ I × N × P given by (19) follows a PARAFAC model with matrix factors ( H ̄ , S, C).
a A fast linear canonical wavelet transform is computed with a cascade of filtering with ({bar h_{M,0}} k)) and ({bar h_{M,1}} k)) in the LCT domain followed by a factor 2 subsampling.
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