Abstract With the rapid increase of amount vehicles in urban areas, pollution vehicle emissions is becoming more and serious. Precise prediction spatiotemporal evolution traffic plays a great role planning policy making. Most existing methods usually focus on estimating at historical or current moments which cannot well meet demands future planning. Recent work has started to pay attention usin...

Distributed photovoltaic power generation can efficiently utilize idle resources and reduce carbon emissions. In order to the impact of grid-connected distributed fluctuations on grid operation, this paper simultaneously exploits temporal dependence series spatial correlation meteorological data propose a combined prediction model with characteristics relationships fused for plants spatiotempor...

In fluid dynamical systems, it is not known a priori whether disturbances grow either in space or in time or as spatiotemporal structures. For a zero pressure gradient boundary layer (also known as the Blasius boundary layer), it is customary to treat it as a spatial problem, and some limited comparison between prediction and laboratory experiments exist. In the present work, the two-dimensiona...

Optogenetic gene switches allow gene expression control at an unprecedented spatiotemporal resolution. Recently, light-responsive transgene expression systems that are activated by UV-B, blue, or red light have been developed. These systems perform well on their own, but their integration into genetic networks has been hampered by the overlapping absorbance spectra of the photoreceptors. We ide...

A spatio-temporal statistical model is proposed for 1to 24-hour-ahead prediction of hourly ozone concentrations. This is a joint work with the National Environmental Agency Singapore, and is Singapore’s first predictive model for ozone concentrations. Unlike many existing models which focus on either daily maximum or 8h average daylight ozone concentrations, the present work is concerned with t...

Semantic place labeling has been actively studied in the past few years due to its importance in understanding human mobility and lifestyle patterns. In the last decade, the rapid growth of geotagged multimedia data from online social networks provides a valuable opportunity to predict people’s POI locations from temporal, spatial and visual cues. Among the massive amount of social media data, ...

Automatic analysis of head gestures and facial expressions is a challenging research area and it has significant applications in humancomputer interfaces. In this study, facial landmark points are detected and tracked over successive video frames using a robust method based on subspace regularization, Kalman prediction and refinement. The trajectories (time series) of facial landmark positions ...

Spatiotemporal air quality datasets are typically collected hourly in monitoring stations deployed non-uniformly across a metropolitan city. These not only big, which poses challenges on the storage and processing capacity of centralized computing systems but also imbalanced spatially heterogeneous, may result biased prediction. To address these challenges, we designed developed parallel predic...