Sentence examples for redundant object from inspiring English sources

It should refer to taking the component parts of a redundant object and using them to create a new, useful object, thereby reducing the use of virgin materials".

The protein is then given a unique key called a ROGID (redundant object group identifier), consisting of a concatenation of the SEGUID and the NCBI taxonomy ID.

The manoeuvre ensured Vega limits its contribution to the growing population of redundant objects that now litter the space environment.

Only essential properties and classes are included in the schema; extensional conciseness, which refers to the case when the data set does not contain redundant objects (instances).

Since Biozon employs a non-redundant object model, these identical sequences are mapped to the same nucleic acid sequence object in Biozon.

Unlike identifiers such as accession numbers and cross-references that are potentially unstable or inconsistent (as each database uses its own set of identifiers), relationships that are established based on physical non-redundant Biozon objects are highly reliable and are materialized explicitly in the data graph.

The phase retrieval problem is made tractable in ptychography by recording multiple diffraction patterns from overlapping regions of the object, providing redundant datasets to compensate for the lack of the phase information.

As several segments of an object contour contain redundant points, these redundant points can be removed through sampling.

From the redundant information about the scanned object within the recorded scattering intensities, due to the spot overlap, the real space image of the object's structure and the 3D wave field of the focused beam can be calculated.

Thus, in the presence of widespread positive correlations, neurons coding for the same object provide partially redundant information, whereas neurons coding for different objects can be used to remove the influence of global activity fluctuations (common noise) unrelated to selective attention.

Since the background and foreground moving objects are highly redundant from one image to another (videos come from surveillance cameras) the model does not need a large number of examples to accurately fit the data.