Sentence examples for contribution estimation from inspiring English sources

The objectives of this work are to (1) verify whether an optimum composite fingerprint exists, (2) present a new direction of using multiple composite fingerprints to improve the accuracy and reliability of source contribution estimation, and (3) evaluate the optimization model formulation and the validity of the tracer discriminatory weighting.

8) The section 'Human contribution estimation' needs some revision.

Since delivery delays of messages originated by MN3 and SN4 are built over the delays of nearer nodes MN1 and/or SN2, and since they are consequently obtained as sum of independent contributions, whose estimations suffer from unavoidable errors, the difference between minimum (or, equivalently, maximum) delays under experimental and theoretical analysis tends to increase.

However, the contribution lacks proper estimation of the intra-cluster distance.

Instead, it was the dependence of the maximum velocity on the Doppler angle that made, by far, the greatest contribution to the estimation error.

Using this group contribution base properties estimation method, our reverse design system cyclopaedically generated ILs structures corresponding to particular physical properties.

Actually, this is expected due to the pattern contribution in location estimation since more signal measurements are available for such cases.

Group contribution first-order estimation methods are coupled with property clustering methods to define the targets of the property search space and to predict the properties of the synthesized formulations.

Assessment of the land use type-specific contribution to ES. Estimation of the EP (e.g., nitrogen retention potential, yield potential) based on the site-specific ecosystem properties (cf. Bastian et al. 2012).

It turns out that the limiting distribution of the ICM type test statistic that we propose is a functional of a Gaussian process with a covariance kernel that reflects both the time series structure of the data as well as the contribution of parameter estimation error.

8It thus follows that the a posteriori error estimation contribution to the cost of the greedy algorithm of Section 5 is O ( Q N max N ⋅ ) + O ( Q 2 N max 2 N ) + O ( n train Q 2 N max 3 ) : we may thus choose N and n train independently (and large).