Sentence examples for vector dataset from inspiring English sources

The first one is the vector dataset of the entire Istanbul region, prepared by the Istanbul Metropolitan Municipality (IMM), and dates back to 2006 (Fig. 6).

Specifically, in the first twelve trials, a different gene was removed from the vector dataset, while multiple genes were removed from the vector dataset in the last three trials.

Over-representation of TSS-proximal integrations was reduced in the ΔU3-MLV vector dataset (12.5% vs. 16.6 for MLV), with a concomitant, significant increase in intergenic integrations (47.5% vs. 37.0 for MLV, two-sample test for equality of proportions with continuity correction, p<0.01).

We drew North American occurrence data from the U.S. Department of Agriculture's Plants Database [54], summarizing known ranges of each species at the level of counties in which they are known to occur by means of adding fields for each species to the attributes table of a vector dataset summarizing boundaries of 3111 counties across the United States.

These fully predictable distortions are also flagged in the vector datasets.

To prepare data for analysis and modeling, the two land-use vector datasets (multitemporal Landsat thematic mapper (TM) in 1989 and SPOT data in 2005) were rasterized (a grid of cells was created from polygons of land-use/cover patches).

We compared the different raster layers directly, and through comparison of averages within the vector datasets.

We used two vector datasets to subset the AGB maps in different ways.

In order to classify locations from the GPS, we obtained two geospatial vector datasets representing all building footprints in the study area (a polygon dataset from the City of Montreal) and roads (a line dataset from DMTI Spatial, CanMap Streetfiles).

We conducted leave-one-out cross-validation (LOOCV) on the patient gene expression dataset using various combinations of γ and C. In LOOCV, the patient vectors dataset was split into 28 training examples where one of the training examples was used as the test example while the others were used for training the SVM classifier.

For obtaining this LSF vector training dataset, we applied to the audio data the same wavelet-based filterbank that is used for the modeling/encoding procedure (8-bands, critical subsampling, same window length in samples for each band).