Writhe
The writhing number is a standard measure of the global geometry of a closed space
curve. We give an algorithm for computing the writhing number
for a polygonal knot with n edges in time O(n^{1.6+ε}),
for any arbitrarily small constant ε>0.
We implement a simple algorithm, which works in O(n
log n) time in practice, and provide experimental
evidence for its practical efficiency. |
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Scalable Simulator for Forest Dynamics
This software is developed as part of an interdisciplinary project between Computer Science and Ecology. We have developed an individual based, spatially
explicit forest growth model. We have implemented a simulator
that simulates the evoution of such a forest. We have designed
efficient algorithms using techniques that include:
• Using graphics hardware
for fast geometric computation • Hierarchical spatial
decomposition using quad-tree like structures • Monopole
approximation. These techniques allow us to efficiently
simulate large forests (few sq. kilometres) for long periods
of time (few thousand time steps). |
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Graphics-Hardware Based Algorithms
Geometric Optimization: Graphics hardware based algorithms for efficiently computing several shape measures such as width, diameter, bounding box and penetration depth
Depth Contour: Graphics hardware based algorithm for several data-depth problems
Map Simplification: Graphics hardware based algorithm for map simplification |
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Core Sets
This software includes practical implementations for computing the core set of points in any dimension, and various shape fitting problems and kinetic data structures using core sets. |
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Curve Simplification
Near-linear algorithms for curve simplification in two and three dimensions. Software for approximating a piece-wise linear curve with fewer vertices. Implements the factor-2 approximation algorithm. |
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CRB-tree: an I/O Efficient Data Structure for Orthogonal Range Counting
We have devoped an I/O efficient data structure for performing range aggregate query. The data structure has been implemented in the TPIE framework at Duke. Currently our implementation can perform range counting queries in 2D. |
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k-Means Projective Clustering
A k-means type algorithm for projective clustering |
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