To maintain the spherical orientation of the droplets over the solution, the breath figures method requires immiscibility between the solvent and the water [25].
The conventional method requires joint iteration between phase and position error estimations.
Another problem that occurs during computation on a massively parallel computer is that the spectral transform method requires extensive data movement between computer nodes.
This method requires that the angle between the great circle connecting the given two stations and the great circle connecting this specific event to the station pair is small.
Because the GSM method requires the similarity measures between a query and all samples to be calculated, the computational cost for recognition is in proportion to the number of samples.
When comparing the models built here to the Naïve Bayes method proposed by Koutsoukas et al. [39], in order to achieve a recall of between 80 and 87%% as reported in this study, the author's method requires top-k positions between 6 and 27 in order to achieve comparable recall performance.
Moreover, our method requires that the interactions between these modules will account for a large portion of the data.
This method requires calculating travel time derivatives between two nodes, with respect to the demand between them, assuming that the flow distributes in a way that equilibrium is maintained.
First, our method requires only a single iteration between the local fine-grid solutions and the global coarse representation.
This mask-less electrodeposition method requires the inter-electrode distance between the anode tool and the cathode substrate to be maintained at 300 μm, and sufficient stirring of the electrolyte by ultrasound agitation.
