Bacillary dysentery (BD) remains a big public health problem in China. Effective spatio-temporal monitoring of BD incidence is important for successful implementation of control and prevention measures. This study aimed to examine the spatio-temporal pattern of BD and analyze socio-economic factors that may affect BD incidence in Sichuan province, China. Firstly, we used space-time scan statist...

In this paper, a novel structure is proposed for human activity modeling using time sequential spatio-temporal texture primitives. Gabor filters, which are proven to be robust 2D texture representation tools, are extended to 3D domain to capture spatio-temporal texture features. A well known filtering algorithm and an unsupervised clustering algorithm, the Genetic Chromodynamics, are combined t...

The integrated management of both spatial and temporal components of information is crucial in order to extract significant knowledge from datasets concerning phenomena of interest to a large variety of applications. Moreover, multigranularity, i.e., the capability of representing information at different levels of detail, enhances the data modelling flexibility and improves the analysis of inf...

A total of 969 isolates of Campylobacter jejuni originating in the Preston, Lancashire postcode district over a 3-year period were characterized using multi-locus sequence typing. Recently developed statistical methods and a genetic model were used to investigate temporal, spatial, spatio-temporal and genetic variation in human C. jejuni infections. The analysis of the data showed statistically...

Prominent examples of collective systems are often encountered when analysing smart cities and smart transportation systems. We propose a novel modelling and analysis approach combining statistical model checking, spatio-temporal logics, and simulation. The proposed methodology is applied to modelling and statistical analysis of user behaviour in bike sharing systems. We present a tool-chain th...

This paper describes a spatio-temporal configurations building approach, which has been applied to dynamics points in 1-dimensional space. In this approach, a temporal logic, Allen’s time intervals, is crossed with a new spatial logic based on topology called spatial states. These spatial states are derived from topological relationships and a new concept of degenerate topological relationships...

We present a new approach to temporal data modeling based on the very general notion of temporal object . Moreover, we propose the database embedding of temporal objects by means of the abstract data type ( ADT ) approach. We consider the expressiveness of different temporal database embeddings, and we discuss the combination of temporal and spatial objects into spatio-temporal objects in (rela...

PURPOSE: Dynamic Contrast Enhanced (DCE) MRI is a powerful method that can provide comprehensive information to characterize lesions. High temporal resolution is often desired for 3D DCE, but at the cost of lower spatial resolution. Low rank / partial separable methods offer an effective way of balancing this tradeoff by exploiting spatio-temporal correlations of dynamic images. However, existi...

Routing and data aggregation are two important techniques for reducing communication cost of wireless sensor networks (WSNs). To minimize communication cost, routing methods can be merged with data aggregation techniques. Compressive sensing (CS) is one of the effective techniques for aggregating network data, which can reduce the cost of communication by reducing the amount of routed data to t...

This paper presents a novel method to involve both spatial and temporal features for semantic segmentation of street scenes. Current work on convolutional neural networks (CNNs) has shown that CNNs provide advanced spatial features supporting a very good performance of solutions for the semantic segmentation task. We investigate how involving temporal features also has a good effect on segmenti...