Sentence examples for training we present from inspiring English sources

In this study, in order to better assess applicant quality and preparation for EM residency training, we present the first evaluation of subjective ratings of applicant characteristics in a new residency program, comparing applicants to our program prior to and with the use of ERAS.

Due to the low survey response rate and small numbers of respondents according to each level of training, we present outcomes for all respondents with some general findings by level of training.

Given a combined network and a set of annotated genes that serve as training examples, we present a method for learning networks of improved quality.

To motivate participants during the training, we also presented three green stars if the sequence was produced 20% faster than the median MT (three points).

During a training test, we presented a subject with the same four feeders in the test room as during training, except that each of the four feeders now contained a piece of banana.

To examine the training effect, we presented the upright-face conditions twice.

In the performance phase, after patients had acquired the task contingencies, along with all the training pairings, we presented the best (the one with 80% chance of being correct) and worst stimulus (the one with only 20% chance of being correct) in novel pairings with all the other stimuli (Fig. 1).

Specifically, since clustering is a NP-hard task and the corresponding training problem likewise must make use of approximate inference during training of the parameters, we present a detailed theoretical and empirical analysis of the general use of approximations in structural SVM training.

First, we present training effects of the new statutory minimum wage in Germany, which was introduced on 1 January 2015.

To visualize the quality of the model on the observations in the training and test dataset we present Figures 4. These plots are visualizations of the coverage of observations by patterns in the model.

Once training was completed, we presented the visible condition of " Experiment 1".