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The first QCA device was implemented and tested using metal dots at near 0 K [5].
A schematic diagram of the experimental apparatus in which such a device was implemented is displayed in Fig. 32.
Finally, a machine learning model (naïve Bayes classifier) [56] using data from smartphone and OBD-II device was implemented.
The device was implemented with microfabrication technology using polydimethylsiloxane (PDMS) structures on a silicon or glass substrate.
The model for the integrated device was implemented in gPROMS, and hence the built-in NLP solver was used.
A particle image velocity (PIV) device was implemented to the experimental setup in order to highlight the effect of the wake-induced flow on the heat transfer.
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Another device is implemented in [3] called the Sensatag.
Heat storage device is implemented to store the air compression thermal.
Transmitter performance tests are aimed at quantifying how well the transmitter functions of a WLAN device are implemented.
However, we recommend that proper done controlled and randomized studies are required before a given neurostimulation device is implemented and clinically used.
The focusing lens and beam-steering device are implemented using two-dimensional graded photonic crystals with dielectric elastomer tube array embedded in air background.
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