1,116 research outputs found

    Granular synthesis for display of time-varying probability densities

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    We present a method for displaying time-varying probabilistic information to users using an asynchronous granular synthesis technique. We extend the basic synthesis technique to include distribution over waveform source, spatial position, pitch and time inside waveforms. To enhance the synthesis in interactive contexts, we "quicken" the display by integrating predictions of user behaviour into the sonification. This includes summing the derivatives of the distribution during exploration of static densities, and using Monte-Carlo sampling to predict future user states in nonlinear dynamic systems. These techniques can be used to improve user performance in continuous control systems and in the interactive exploration of high dimensional spaces. This technique provides feedback from users potential goals, and their progress toward achieving them; modulating the feedback with quickening can help shape the users actions toward achieving these goals. We have applied these techniques to a simple nonlinear control problem as well as to the sonification of on-line probabilistic gesture recognition. We are applying these displays to mobile, gestural interfaces, where visual display is often impractical. The granular synthesis approach is theoretically elegant and easily applied in contexts where dynamic probabilistic displays are required

    Sonification of probabilistic feedback through granular synthesis

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    We describe a method to improve user feedback, specifically the display of time-varying probabilistic information, through asynchronous granular synthesis. We have applied these techniques to challenging control problems as well as to the sonification of online probabilistic gesture recognition. We're using these displays in mobile, gestural interfaces where visual display is often impractical

    Soft data mining, computational theory of perceptions, and rough-fuzzy approach

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    Soft data mining, computational theory of perceptions, and rough-fuzzy approach

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    Data mining and knowledge discovery is described from pattern recognition point of view along with the relevance of soft computing. Key features of the computational theory of perceptions and its significance in pattern recognition and knowledge discovery problems are explained. Role of fuzzy-granulation (f-granulation) in machine and human intelligence, and its modeling through rough-fuzzy integration are discussed. Merits of fuzzy granular computation, in terms of performance and computation time, for the task of case generation in large scale case-based reasoning systems are illustrated through an example

    Stratospheric aerosol modification by supersonic transport operations with climate implications

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    The potential effects on stratospheric aerosois of supersonic transport emissions of sulfur dioxide gas and submicron size soot granules are estimated. An interactive particle-gas model of the stratospheric aerosol is used to compute particle changes due to exhaust emissions, and an accurate radiation transport model is used to compute the attendant surface temperature changes. It is shown that a fleet of several hundred supersonic aircraft, operating daily at 20 km, could produce about a 20% increase in the concentration of large particles in the stratosphere. Aerosol increases of this magnitude would reduce the global surface temperature by less than 0.01 K
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