In this paper we present the research objectives and methodology for a running project of distributed web processing geo-services for spatio-temporal analysis of geo-data, the case of Lloyd’s lists. We introduce the current problems and discuss the solutions in means of theoretical and practical perspectives. Initial results from geo-data modeling using Unified Modeling Language (UML) is presen...

This paper is motivated by spatio-temporal pattern in the occurrence of Leishmaniasis in Afghanistan and the relatively high number of zero counts. We hold the view that correlations that arise from spatial and temporal sources are inherently distinct. Our method decouples these two sources of correlations, there are at least two advantages in taking this approach. First, it circumvents the nee...

Parkinson’s disease (PD) is traditionally associated with motor symptoms. However, impairments in language functioning may also accompany this disorder. The present study investigated pragmatic language deficits in PD and their relationship to cognitive functioning. Forty patients with PD were compared to ageand IQ-matched controls on measures of pragmatic language functioning using the Test of...

Fine motor skills like typing involve a mapping problem that trades Fitts' law against Hick's law. Eight fingers have to be mapped onto 26 keys. Movement time increases with distance, so Fitts' law is optimized by recruiting more fingers. Choice difficulty increases with the number of alternatives, so Hick's law is optimized by recruiting fewer fingers. The effect of the number of alternatives ...

Abstract— In this paper, the double-directional channel measurement and spatio-temporal analysis of UWB propagation based on the clusterization approach were reported. After separating the deterministic and diffuse components on both transmit (Tx) and Receive (Rx) positions, the clusters can be coupled based on similar time of arrivals (TOAs). The relation of direction of departure (DOD) and di...

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...

As efforts grow to develop spatio-temporal database systems and temporal geographic information systems that are capable of conveying how geographic phenomena change, it is urgent to analyze the impetus and mechanism that the spatio-temporal process happed. The authors proposed a set of universal change patterns for modelling of spatio-temporal processes, which builds a fundamental basis for th...

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...

Spatio-temporal networks are becoming popular with the rise of traffic information being incorporated into street mapping utilities such as Google Maps. This additional information adds potentially large time series of traffic information to each road segment. Naive implementations of secondary storage of spatio-temporal networks may not be sufficient, as current techniques commonly store entir...

We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. In a real-world application we compare spatio-temporal interpolations using these models with a purely spatial kriging approach. The target variable of the...