Sentence examples for dataset and time from inspiring English sources

The results of our study not only confirm an association between different variables but also show that the integration of PFP-growth algorithm with Apache Spark framework solve the problems of the large dataset and time consumption due to the capabilities of Apache Spark.

Patient movement data are extracted to produce a cohort dataset and time-series analysis of patients transitioning in the following units: the medical ICU (nine beds), surgical ICU (11 bed), coronary care unit (18 beds), step-down unit (nine beds), monitored medical (15 beds), monitored surgical (12 beds), nonmonitored medical (44 beds) and surgical (19 beds).

Reference gene biclustering will only find biclusters relevant for a single reference gene; differential co-expression biclustering requires exactly two well annotated datasets; and time series biclustering requires time series data.

The number of iterations in the task of analyzing structural variation is 2 because it runs one time on the original dataset and one time on randomized dataset of the same size.

For a TCGx dataset with h time points covering three cell cycles, we take the first ⌊ h/3⌋ + 1 time points as a TCGxCC dataset, the last ⌊ h/3⌋ + 1 time points as another TCGxCC dataset, and the time points from ⌊ h/3⌋- th to 2*⌊ h/3⌋- th as the other TCGxCC dataset.

The large spectrum of the data available makes the data integration and curation of new short read datasets harder and time consuming, forcing the need for endless filtering and post-processing data procedures.

The semi-supervised approach is interesting, as has been pointed out, for example, in [4], because obtaining position labels for all points in a large dataset is expensive and time consuming.

In analyzing the performance of the ApproxMap algorithm, we considered both the delta size calculated from mapping pairs of RDF datasets and the time spent on this task.