Triangular Irregular Network (TIN) and Regular Square Grid (RSG) are widely used for representing 2.5 dimensional spatial data. However, these models are not defined from the topo...
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
We envision that in some wireless sensor network applications, such as environmental monitoring, assisted living, and industrial control, handheld devices will be used from time t...
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
The widespread deployment of sensor networks is on the horizon. One of the main challenges in sensor networks is to process and aggregate data in the network rather than wasting e...