In this paper, we propose a solution to the problem of designing a flexible query processor for spatio-temporal databases. Our solution is to design a bottom-up interface, whose parameters handle different spatiotemporal applications. We propose a relational schema that can cope with various spatio-temporal data types. Based on this model, we have design a flexible query processor for spatio-te...

We present a method to estimate Gibbs distributions with spatio-temporal constraints on spike trains statistics. We apply this method to spike trains recorded from ganglion cells of the salamander retina, in response to natural movies. Our analysis, restricted to a few neurons, performs more accurately than pairwise synchronization models (Ising) or the 1-time step Markov models (Marre et al., ...

BACKGROUND In spring 2008, a goat farm experiencing Q fever abortions ("Farm A") was identified as the probable source of a human Q fever outbreak in a Dutch town. In 2009, a larger outbreak with 347 cases occurred in the town, despite no clinical Q fever being reported from any local farm. METHODS Our study aimed to identify the source of the 2009 outbreak by applying a combination of interd...

Preface Complex, spatial and spatio-temporal data arise in a plethora of modern database and data mining applications and complex information systems. Complex, spatial and spatio-temporal data require more and more for effective and efficient models, algorithms and techniques for representing, managing, querying , indexing and discovering useful knowledge beyond such kind of data. A successful ...

In the paper, we consider the problem of discovering sequential patterns from event-based spatio-temporal data. The problem is defined as follows: for a set of event types F and for a dataset of events instances D (where each instance in D denotes an occurrence of a particular event type in considered spatio-temporal space), discover all sequential patterns defining the following relation betwe...

We introduce the land-cover cascade (LCC) as a conceptual framework to quantify the transfer of land-cover-disturbance effects to stream biota. We hypothesize that disturbance is propagated through multivariate systems through key variables that transform a disturbance and pass a reorganized disturbance effect to the next hierarchical level where the process repeats until ultimately affecting b...

A technique to forecast spatiotemporal time series is presented. It uses a proper orthogonal or Karhunen-Loève decomposition to encode large spatiotemporal data sets in a few time series, and genetic algorithms to efficiently extract dynamical rules from the data. The method works very well for confined systems displaying spatiotemporal chaos, as exemplified here by forecasting the evolution of...

The Spatial Semantic Hierarchy (SSH) is a multi-level representation of the cognitive map used for navigation in largescale space. We propose a method for learning a portion of this representation, specifically, the representation of views in the causal level of the SSH using self-organizing neural networks (SOMs). We describe the criteria that a good view representation should meet, and why SO...

Análise da estabilidade de sistemas fuzzy de Takagi-Sugeno via LMI: Metodologia baseda numa nova função de Lyapunov fuzzy A análise de estabilidade de sistemas fuzzy TS pode ser aprimorada com o uso de funções de Lyapunov fuzzy, uma vez que as mesmas são parametrizadas por funções de pertinência e podem definir melhor a ca-racteŕıstica variante no tempo de tais sistemas através do uso da inform...