Sentence examples for data distribution model from inspiring English sources

"Real‑time data distribution model for robots" section proposes a real-time data distribution model for robots.

To realize this goal, as shown in "Real‑time data distribution model for robots" section, two kinds of topics are strictly distinguished in our data distribution model, and the APIs of the general topic are identical with those in ROS.

Different from the Z-score, box plots make no assumptions about the data distribution model, however, for multivariate datasets, it is possible to perform a pairwise distance measure.

To address this issue, we strictly constrain the capability of the data distribution model as a subset of the minimum profile of the DDS standard.

Therefore, four kinds of time-related QoS parameters are supported in our model: Fig. 3 Real-time data distribution model for robots.

When a change is detected, the previously learned data distribution model must be forgotten and the mixture of normal distributions must be relearned with newly incoming data items.

To implement this system, we also propose a data distribution approximation model, Polygon descriptor, and a shape difference measurement, called Deforming distance method.

In particular, such a diagnostic bias can happen to any classifiers due to different decision models, input data distributions, and/or model selection choices.

Such a scenario would explain the seemingly contradictory results from the genetic data and distribution models.

The combination of multi-locus data, species distribution modeling, and comparative phylogeography offer a powerful approach for better understanding the evolutionary history of A. lugubris.

Our goal is to use a combination of multi-locus data, species distribution modeling, and comparative phylogeography to better understand the evolutionary history of a species of salamander endemic to the California floristic province, the Arboreal Salamander (Aneides lugubris).