With the recent increase in urban drift, which has led to an unprecedented surge in urban
population, the smart city (SC) transportation industry faces a myriad of challenges …

In individuals with sensory-motor impairments, missing limb functions can be restored using
neuroprosthetic devices that directly interface with the nervous system. However, restoring …

Every day, our living city produces a tremendous amount of spatial-temporal data, involved
with multiple sources from the individual scale to the city scale. Undoubtedly, such massive …

This paper examines the use of Elasticsearch for data warehousing and analyses of geo-
referenced sensor data. Elasticsearch has several advantages compared to its direct …

With the rapid evolution of the Internet, Internet of Things (IoT), and geographic information
systems (GIS), spatio-temporal big data (STBD) is experiencing exponential growth, marking …

With the progress of human daily interaction activities and the development of industrial
society, a large amount of media data and sensor data become accessible. Humans collect …

In most recent research, the traffic forecasting task is typically formulated as a spatio-
temporal graph modeling problem. For spatial correlation, they typically learn the shared …

Studies on multiplex temporal networks (MTNs) can lead to a more precise understanding of
real-world systems. Previous research tends to identify key nodes in an MTN by computing …

The rapid growth of remote sensing data calls for the construction of new computational
models for algorithmic exploration, which requires on-demand execution, instant response …

Cardinality estimation, which involves estimating the result size of queries, is a critical aspect
of query processing and optimization. Deep Neural Networks (DNNs) are data hungry, and …