Sentence examples for is able to partition from inspiring English sources

This paper gives a multi-view relational fuzzy c-medoid vectors clustering algorithm that is able to partition objects taking into account simultaneously several dissimilarity matrices.

Through automatic calculation of the respiratory system elastance and resistance and using the respiratory system equation of motion, PAV with load adjustable gain factors (PAV+) is able to partition the ventilator (P aw) and the patient (P mus) contribution to total pressure of the respiratory system (P tot) [7 9].

Extensive experiments and quantitative analysis demonstrate that the proposed method is able to partition high-quality teeth automatically with robustness and efficiency.

It is useful to be able to partition parameter space into parameters that induce motor stalling versus those for which the motors recover for a particular fault.

She said the hotel was able to partition off bandwidth for her group's exclusive use, which included high-definition video streaming.

This paper introduces hard clustering algorithms that are able to partition objects taking into account simultaneously their relational descriptions given by multiple dissimilarity matrices.

When tested on a collection of 69 isolates, 96-MLST was able to partition strains with the same ST and diverse serotypes into groups that were homogenous for capsular serotype, improving our understanding of the evolution of epidemiologically relevant lineages.

The results were confirmed by linear modeling in a subset of the data, and in confirmatory experiments, in which we were able to partition the variance of this complex trait among genetic (27%), environmental (42%) and genetic×environmental (18%) sources.

At St . Lukes, a brown-brick building with 363 pupils in pre-kindergarten through eighth grade, the principal, Sister Pat Howell, was able to partition an upstairs classroom with file cabinets to make room this year for the classes in English as a second language and remedial reading.

In contrast, in this paper, we are able to partition the data into four key dimensions: gender, wealth, rural vs. urban location, and nuclear family migration status.

This is related to the non-linear behavior of the pattern database and the fact that Spectral methods are able to partition the pattern space through the non-linear boundary, whereas K-means is only capable of regarding linear borders between the clusters.