A query optimizer requires cost models to calculate the costs of various access plans for a query. An effective method to estimate the number of disk (or page) accesses for spatio-temporal queries has not yet been proposed. The TPR-tree is an efficient index that supports spatio-temporal queries for moving objects. Existing cost models for the spatial index such as the R-tree do not accurately ...

Large volumes of spatio-temporal data are increasingly collected and studied in diverse domains including, climate science, social sciences, neuroscience, epidemiology, transportation, mobile health, and Earth sciences. Spatio-temporal data differs from relational data for which computational approaches are developed in the data mining community for multiple decades, in that both spatial and te...

Spatio-temporal data analysis plays an important role in many scientific applications like environmental epidemiology and public health. Our approach STARS (SpatioTemporal dAtabase system Realized with Shore) integrates spatio-temporal aspects in the persistent object system SHORE [1]. STARS provides an object oriented query language to formulate spatio-temporal queries which can be processed b...

Spatio-temporal extensions to the classical optical ow technique are presented. A novel optical ow estimator is derived capable of incorporating spatio-temporal motion models by iteratively rening initial motion estimates. These initial estimates may be derived from motion in previous frames using a spatio-temporal processing architecture, or from block matching or feature matching techniques. ...

s of Talks ______________________________________________________________ 7 What are spatioTemporal Databases ___________________________________________________8 CHOROCHRONOS: A Research Network for Spatio-temporal Database Systems (TMR Programme) ______8 Requirements of Traffic Telematics to Spatial and Temporal Databases _______________________________9 Ontology-Based Map Integration _______...

Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively new subfield of data mining which gained high popularity especially in geographic information sciences due to the pervasiveness of all kinds of location-based or environmental devices that record position, time or/and environmental properties of an object or set of object...

In this paper we propose a methodology for mining very large spatio-temporal datasets. We propose a two-pass strategy for mining and manipulating spatio-temporal datasets at different levels of detail (i.e., granularities). The approach takes advantage of the multi-granular capability of the underlying spatio-temporal model to reduce the amount of data that can be accessed initially. The approa...

Excitable dynamics of a neuron generates dynamical phenomena with various attractors, which include deterministic chaos and multistability [1, 2]. A neural network composed of neurons with such excitable dynamics also produces much more interesting and richer nonlinear dynamics with spatio– temporal structure of spikes [3, 4]. In this talk, I consider nonlinear dynamics with spatio–temporal spi...

s of Talks ______________________________________________________________ 7 What are spatioTemporal Databases ___________________________________________________8 CHOROCHRONOS: A Research Network for Spatio-temporal Database Systems (TMR Programme) ______8 Requirements of Traffic Telematics to Spatial and Temporal Databases _______________________________9 Ontology-Based Map Integration _______...