A blind classification algorithm is presented that uses hyperdimensional geometric algorithms to locate a hypothesis, in the form of a convex polytope or hyper-sphere. The convex polytope geometric model provides a well-fitted class representation that does not require training with instances of opposing classes. Further, the classification algorithm creates models for as many training classes ...

We present a novel methodology for incompressible multi-phase flow simulations in which the fluid indicator is a local signed distance (level set) function, and FrontTracking is used to evaluate accurately geometric interfacial quantities and forces. Employing ideas from Computational Geometry , we propose a procedure in which the level set function is obtained at optimal computational cost wit...

One of the most common visualization tasks is the extraction of significant boundaries, often performed with isosurfaces or level set segmentation. Isosurface extraction is simple and can be guided by geometric and topological analysis, yet frequently does not extract the desired boundary. Level set segmentation is better at boundary extraction, but either leads to global segmentation without e...