Sentence examples for elaboration algorithms from inspiring English sources

Methodological and technological aspects as well as architecture and elaboration algorithms are considered.

The main attention of researchers engaged in developing CASE systems was focused on the creation of the optimal methods for selecting appropriate fragments and elaboration algorithms for structure generation from fragments and free atoms.

The elaboration of practical algorithms is intended to help physicians choose suitable drugs for therapy routines and for the general follow-up of patients and the management of disease concomitants.

Current DL technology is restricted to neural net development, but future methods will be elaborations of other algorithms.

Finally, the Kalman filter model allows the elaboration of an algorithm to estimate the optimal state vector values.

This study is devoted to creation of metal oxide semiconductor (MOS) materials for gas sensor array for determination of nitrogen oxides and ammonia traces in sub-Threshold Limit Value (TLV) concentrations in air, and to elaboration of data processing algorithms for identification and quantification of single gases.

Robustness to the backhaul latencies and adaptation to the backhaul throughput constraints are other key technical issues, as well as the elaboration of efficient handover algorithms working in an environment composed of unmanaged, small, and dense cells.

In order to achieve it, the algorithm of elaboration of the set of variants and the determination of the structure of the "input output" matrix has been developed.

Elaboration of the complete mathematical algorithms for the above five-point-two-photo approach can be found in (Dai and Lu 2013).

This would allow the elaboration of evidence-based diagnosis-treatment algorithms centred on patients in resource-constrained settings, where data availability is scarce and patient management often driven by experience and local beliefs.

The overarching goal is the elaboration of evidence-based diagnosis-treatment algorithms centred on patients in resource-constrained settings, where available data are scant and patient management is often driven by 'empirical evidence' and local beliefs.