Sentence examples for achieving discrimination from inspiring English sources

From Table 4, it is also evident that at moderate noise level rotation invariant operators ( LBP 8, 1 ri and LBP 8, 1 riu 2 ) cannot exhibit higher accuracy as rotation invariance disregards many alternative patterns which would contribute for achieving discrimination between the fault types.

Furthermore, the data did not exclude a reduction in inflammation as the primary mechanism of neuroprotection again without achieving discrimination whether the amelioration of injurious intracellular axonal levels of Na+ and Ca2+ were the targets of amiloride treatment.

The structure of weighting factors for the discriminant dimensions suggests that although the arm movements have been sampled at only four discrete angles, the computation implemented by the projection methods takes advantage of the continuous modulation of neurons by pooling units with similar tuning properties to achieve discrimination between different types of movements.

He showed that a system at thermodynamic equilibrium could not achieve discrimination beyond a certain minimum level but that with sufficient dissipation of energy, arbitrarily high levels of discrimination were possible.

Third, our sample size of 25 per group was higher than the minimal sample size of 17 calculated (on the basis of an independent pretest sample of size 4) to achieve discrimination power.

To achieve discrimination at a level of 5%, M was set so that 5% of test-native genes were predicted to be foreign (or PA in the language of Mrázek et al).

For example, we achieved discrimination of strains within the same serovar (Salmonella), of different pathovars within the same species (X. arboricola pv. juglandis and pv. pruni) and at the subspecies level with a strain-variant cured of a single plasmid (P. agglomerans).

If the above method is insufficient to discriminate between the models then a further method of 'mutating' the two models in biological terms or changing parameters/initial conditions (e.g. alter the initial protein concentrations) in engineering terms is applied to achieve discrimination.

By sweeping the applied electrode potential of potentiostatic EIS, −0.1 V to +0.1 V was determined to be the optimal range for achieving best discrimination between specific target binding and non-specific protein adsorption on aptamer-modified silicon surface.

Furthermore, this meta-analysis can be accomplished simply by using UniGene and RefSeq identifiers as common variables between array platforms, though UniGene is shown to be slightly better at achieving this discrimination in our dataset.

Successful validation of a model means achieving satisfactory discrimination and calibration (prediction accuracy) in the validation sample.