CLUSTERING AND INDEXING HISTORIC VESSEL MOVEMENT DATA WITH SPACE FILLING CURVES

Clustering Microarray Data with Space Filling Curves

We introduce a new clustering method for DNA microarray data that is based on space filling curves and wavelet denoising. The proposed method is much faster than the established fuzzy c-means clustering because clustering occurs in one dimension and it clusters cells that contain data, instead of data themselves. Moreover, preliminary evaluation results on data sets from Small Round Blue-Cell t...

Using Space-Filling Curves for Multi-dimensional Indexing

A Optimality of Clustering Properties of Space Filling Curves

Space filling curves have been used in the design of data structures for multidimensional data since many decades. A fundamental quality metric of a space filling curve is its “clustering number” with respect to a class of queries, which is the average number of contiguous segments on the space filling curve that a query region can be partitioned into. We present a characterization of the clust...

Unconventional Space-filling Curves

A 2-dimensional space-filling curve, here, is a surjective continuous map from an interval to a 2-dimensional space. To construct a new space-filling curve distinct and much different from Hilbert’s, Peano’s, and the Z-order, we first observe that all three of these curves are based on self-similar fractals–in particular, the recursive definition of the sequences of functions that converge to t...

Image Encryption with Space - filling Curves

Conventional encryption techniques are usually applicable for text data and often unsuited for encrypting multimedia objects for two reasons. Firstly, the huge sizes associated with multimedia objects make conventional encryption computationally costly. Secondly, multimedia objects come with massive redundancies which are useful in avoiding encryption of the objects in their entirety. Hence a c...