Sentence examples for multiple scanning of from inspiring English sources

Recording of SAXS data has been carried out under the conditions of multiple scanning of a scintillation detector at scattering angles of 0.03° to 4.0°.

To address this problem, we assume multiple scanning of the same parcel have been performed, as the parcel was travelling from source to destination.

In addition, for Apriori algorithm based techniques [Verykios, V., Elmagarmid, A., Bertino, E., Saygin, Y., & Dasseni, E. (2004). Association rules hiding. IEEE Transactions on Knowledge and Data Engineering, 16(4) 434–447], multiple scanning of the entire database is required.

This device performs multiple scanning of pupil diameter, displaying the percentage of pupil diameter variation within 10 seconds of tetanic stimulation of the median nerve.

They did multiple scans of every single wall, and from what I understand, there is absolutely no indication of a void space".

Common clustering algorithms require multiple scans of all the data to achieve convergence, and this is prohibitive when large databases, with data arriving in streams, must be processed.

Anyway the secondary compression could be possibly improved by applying some incremental model-based technique (see [5]), but modified in such a way to avoid multiple scans of the sample.

Unfortunately both the classical K-means and the K-means++ algorithms require multiple scans of the dataset or a random selection from the entire dataset, in order to solve the minimization problem.

On-line processing varies from traditional offline processing schemes, where for example, the whole video scope is known as a priori, which allows multiple scans of the stored video files during video processing.

Also these algorithms cannot be efficiently applied to analyse data streams, since they either require multiple scans of the sample, or the extraction of a subsample to identify the centroids or medoids, then all data are scanned according to such identification and the medoids are not any more updated with the information coming from the whole dataset.

These algorithms are well suited to detect the presence of non-spherical or nested clusters, but are based on specific assumptions on the data distribution, the number K of clusters is fixed at the very beginning, and, more important, they require multiple scans of the dataset to estimate the parameters of the model.