Kanimathi Duraisamy

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Efficient analysis of complex networks is often a challenging task due to its large size and the noise inherent in the system. One popular method of overcoming this problem is through graph sampling, that is extracting a representative subgraph from the larger network. The accuracy of the sample is validated by comparing the combinatorial properties of the(More)
The availability of biological data in massive scales continues to represent unlimited opportunities as well as great challenges in bioinformatics research. Developing innovative data mining techniques and efficient parallel computational methods to implement them will be crucial in extracting useful knowledge from this raw unprocessed data, such as in(More)
A novel 4-quadrant analog multiplier using Floating Gate MOS (FGMOS) transistors operating in saturation region are implemented. Floating gate MOSFETs are being utilized in a number of new and existing analog applications. These devices are not only useful for designing memory elements but also we can implement circuit elements. The main advantage in FGMOS(More)
Diverse arrays of modern applications require accurate predictions of complex turbulent flows. These range from flows across aircraft and inside turbomachinery, over the planet for weather prediction and through the heart for cardiac auscultation, etc. Due to the disparate character of these complex flows, predictive methods must be robust so as to be(More)
The algebraic structure-based turbulence model (ASBM) incorporates information about the structure of turbulence to provide closure to the Reynolds-averaged Navier-Stokes equations. In the past, the model has been applied to several well documented Computational Fluid Dynamic (CFD) benchmark test cases, showing reasonable improvement compared to standard(More)
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