Many spatiotemporal data mining methods are dependent on how relationships between a spatiotemporal unit and its neighbors are defined. These relationships are often termed the neighborhood of a spatiotemporal object. The focus of this paper is the discovery of spatiotemporal neighborhoods to find automatically spatiotemporal sub-regions in a sensor dataset. This research is motivated by the ne...

Low-frequency cells in the anteroventral cochlear nucleus (AVCN) can be sensitive to changes in the spatiotemporal pattern of discharges across their auditory nerve (AN) inputs (). This sensitivity suggests that these cells may be tuned to particular spatiotemporal patterns, or features, in the discharge patterns of populations of AN fibers. To evaluate and characterize this sensitivity, we dev...

The ability to process complex spatiotemporal information is a fundamental process underlying the behavior of all higher organisms. However, how the brain processes information in the temporal domain remains incompletely understood. We have explored the spatiotemporal information-processing capability of networks formed from dissociated rat E18 cortical neurons growing in culture. By combining ...

We propose a Multiscale Locality-Constrained Spatiotemporal Coding (MLSC) method to improve the traditional bag of features (BoF) algorithm which ignores the spatiotemporal relationship of local features for human action recognition in video. To model this spatiotemporal relationship, MLSC involves the spatiotemporal position of local feature into feature coding processing. It projects local fe...

The rodent whisker-barrel system has been an ideal model for studying somatosensory representations in the cortex. However, it remains a challenge to experimentally stimulate whiskers with a given pattern under spatiotemporal precision. Recently the optogenetic manipulation of neuronal activity has made possible the analysis of the neuronal network with precise spatiotemporal resolution. Here w...

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in China. The identification of the spatiotemporal pattern of HFRS will provide a foundation for the effective control of the disease. Based on the incidence of HFRS, as well as environmental factors, and social-economic factors of China from 2005-2012, this paper identified the spatiotemporal characteristics of ...

In this research, a hybrid wavelet-artificial neural network (WANN) and a geostatistical method were proposed for spatiotemporal prediction of the groundwater level (GWL) for one month ahead. For this purpose, monthly observed time series of GWL were collected from September 2005 to April 2014 in 10 piezometers around Mashhad City in the Northeast of Iran. In temporal forecasting, an artificial...

Efficient modelling of spatiotemporal change as it is depicted in multitemporal imagery is an important step towards the efficient analysis and management of large motion imagery (MI) datasets. Furthermore, the development of concise representation schemes of MI content is essential for the search, retrieval, interchange, query, and visualization of the information included in MI datasets. Towa...

Examining the two motion processes is an elusive task due to the difficulty of finding a proper stimulus paradigm. A rotational Glass pattern created with a random-dot array by superimposing its rotated version on the top of it can provide such a paradigm. If we displace only its rotated part in the vertical or horizontal direction, a bistable motion occurs; local dot motion in the same directi...

Spatiotemporal reasoning is an important skill that an AGI is expected to have, innately or not. Much work has already been done in defining reasoning systems for space, time and spacetime, such as the Region Connection Calculus for space, Allen’s Interval Algebra for time, or the Qualitative Trajectory Calculus for motion. However, these reasoning systems rarely take adequate account of uncert...