Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
The movement in public transport networks is organized according to schedules. The real-world schedules are specified by a set of periodic rules and a number of irregularities fr...
In this paper, we address the problem of estimating mesoscale dynamics of atmospheric layers from satellite image sequences. Relying on a physically sound vertical decomposition of...
As society enters the twenty-first century there is a growing realization that information technology (IT) is heavily influencing organizational structures [1]. One such structure...
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...