The flow structure around rising single air bubbles in water and their characteristics, such as equivalent diameter, rising velocity and shape, was investigated using Particle Image Velocimetry (PIV) and Shadowgraphy in a transparent apparatus with a volume of 120 mL. The effect of different volumetric gas flow rates, ranging from 4 μL/min to 2 mL/min on the liquid velocity was studied. Ellipsoidal bubbleswere observedwith a rising velocity of 0.25–0.29m/s. It was found that a Kármán vortex street existed behind the rising bubbles. Furthermore, the wake region expanded with increasing volumetric gas flow rate as well as the number and size of the vortices.
In order to understand commands given through voice by an operator, user or any human, a robot needs to focus on a single source, to acquire a clear speech sample and to recognize it. A two-step approach to the deconvolution of speech and sound mixtures in the time-domain is proposed. At first, we apply a deconvolution procedure, constrained in the sense, that the de-mixing matrix has fixed diagonal values without non-zero delay parameters. We derive an adaptive rule for the modification of the de-convolution matrix. Hence, the individual outputs extracted in the first step are eventually still self-convolved. This corruption we try to eliminate by a de-correlation process independently for every individual output channel.