Sentence examples for mixtures are generated from inspiring English sources

Firstly, multiple droplets containing the same target mixtures are generated in the microchannel, and then fused with later generated different droplets containing corresponding probes, respectively.

Then, the mixtures are generated using the noisy model y=Φx+w, where w is an additive white Gaussian noise with covariance matrix σ w Ι M (I M stands for the M × M identity matrix).

The mixtures are generated with the following setup: a speech source is placed in the front position (i.e. 0° in azimuth, 0° in elevation), and a different noise source is placed at each side of the head.

A number of 1,000 binaural mixtures are generated using the head-related impulse responses (HRIR) included in the CIPIC database [38], which contains recordings of the HRIR with in-the-canal microphones in 43 different human subjects and 2 KEMAR mannequins.

The proposed methodology is first applied to the design of solvents and solvent mixtures for maximising the solubility of ibuprofen, often sought in crystallization processes; next, antisolvents and antisolvent mixtures are generated for minimising the solubility of the drug in drowning out crystallization; and finally, solvent and solvent mixtures are designed for liquid liquid extraction.

The simulated mixtures were generated by convoluting the impulse responses measured in the rooms.

As stated by the authors, the test set of mixtures was generated using the Sphere exclusion method.

The mist/dust/air multiphase mixtures were generated by injecting liquid/dust samples into the experimental tube.

Speech mixtures were generated from a convolution of clean speech sources in TIMIT database with real acoustic impulse responses measured in a room of reverberation time second [18].

Speech mixtures were generated by convolving TIMIT speech sources with acoustic path impulse responses measured in a real room with reverberation time  second.

To determine the effect of filler on hydrolysis yield, synthetic reject mixtures were generated in the laboratory using unbleached softwood kraft pulp (USKP) mixed with various proportions of calcium carbonate (in two commonly used forms: ground, GCC, and precipitated, PCC) and kaolin.