The design of mobility-aware framework for edge/fog computing for IoT systems with back-
end cloud is gaining research interest. In this paper, a mobility-driven cloud-fog-edge …

Outlier detection is a major research field for data mining. In recent years, rough set and
granular computing have been successfully applied to outlier detection, and a series of …

With the pervasiveness of IoT devices, smart-phones and improvement of location-tracking
technologies, huge volume of heterogeneous geo-tagged (location specific) data is …

The large-scale data collected by automated fare collection (AFC) systems provide
opportunities for researching both individual travelling behavior and mobility pattern in …

Understanding intra-urban human mobility patterns and their potential driving forces are vital
to city planning and commercial site selection. In this paper, we first investigate the functions …

Mobility pattern recognition is a central aspect of transportation and data mining research.
Despite the development of various machine learning techniques for this problem, most …

The proliferation of sensor-equipped smartphones has led to the generation of vast amounts
of GPS data, such as timestamped location points, enabling a range of location-based …

Considering the massive increase in the number of crimes in the last decade, as well as the
outlook toward smarter cities and more sustainable urban living, the emerging cyber …

Due to the massive congestion in ground transportation in Beijing, underground rail transit
has gradually become the main mode of travel for residents of large urban areas. Because …

In order to mitigate gas leakage damage, it is important to assess systematic risk of gas
leakage in utility networks. In practice, leakage detection systems heavily rely on tedious …