Sentence examples for benchmarking of different from inspiring English sources

This information is used for benchmarking of different types of fibers by the paper and packaging industries.

Gray [14] identified four criteria for a successful benchmark: (i) relevance to an application domain; (ii) portability to allow benchmarking of different systems; (iii) scalability to support benchmarking large systems; and (iv) simplicity so the results are understandable.

The advantages of such databases and third party testing bodies are that firstly it allows more direct and unbiased benchmarking of different algorithms, and secondly it increases trustworthiness of the performance report, since developers do not have a direct access to the database for tuning algorithm's parameters to adapt to the database.

Fully anonymized data concerning ESA users were centrally aggregated and underwent quality control through benchmarking of different parameters across the four participating centers.

It was not our intention to provide a technical benchmarking of different expression platforms, because such a benchmarking exercise would require controlled microarray, SAGE and EST experiments starting with identical RNA samples derived from the same tissue specimen, and would be beyond the resources of most laboratories.

Most DDS studies present comparisons between and benchmarks of different DDS vendors' implementations, such as [26 28], but none of them mention wireless networks or mobile DDS deployments.

A benchmark of different classification methods is proposed on a database recorded from sixteen healthy subjects during a rapid serial visual presentation task.

The performance of the HRBFNNs is quantified through a series of experiments, in which we use several modeling benchmarks of different levels of complexity (different number of input variables and the number of available data).

We motivate the design of our analyses with a study of the kinds of unnecessary synchronization found in a suite of single- and multi-threaded benchmarks of different sizes and drawn from a variety of domains.

Extensive experiments on various widely used benchmarks of different origins and features show that our model achieves a great enhancement in the prediction accuracy and short-term memory capacity, without significant tradeoff in the model's computational efficiency.

Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07.