Sentence examples for by combining three types from inspiring English sources

Exact(3)

In achieving the goal, we generated a technology superstructure for the energy supply systems using nine different scenarios by combining three types of building and three representing regions.

The mass transport in the electrolyte was fully characterised by combining three types of electrochemical experiments; concentration cells, galvanostatic polarisation experiments and electrochemical impedance measurements with a mathematical description of the mass transport in the electrolyte.

There were six interaction types in total by combining three types of pair contact sites ('cap-core', 'cap-cap' and 'core-core') with two types of helicandorientations.

Similar(57)

Thus, by combining two types of microsensors, an artificial flavour sensing system has been developed.

These two limitations can be addressed by combining two types of channel waveguides, namely strip-loaded and slot waveguide.

We are developing PRactical INTEligent aPplicationS (PRINTEPS), which is a user-centric platform to develop integrated intelligent applications only by combining four types of modules such as knowledge-based reasoning, speech dialog, image sensing and motion management.

At the 50% precision, 14906 known protein-term associations can be recovered on average by combining five types of data.

By combining five types of data, the number of correctly recovered known gene-term associations is increased by 18% at the same precision (50%), compared to using PPI data alone.

Moreover, the total performance gain by combining two types of word representation features was a bit higher than the gain from any of them, indicating that these two types of word representation methods could be complementary to each other.

For each protein pair in the physical and GI data, we assigned a confidence score to each connection by combining four types of biological evidence: physical interaction, GI, DDI and GO term similarity.

A key contribution of our work is the development and evaluation of a methodologically simple meta-model, which improves prediction by combining two types of genomic signal, the GWAMA-based risk score and a dense whole-genome predictor estimated from our population data.

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