Tensor decomposition has been demonstrated to be successful in a wide range of
applications, from neuroscience and wireless communications to social networks. In an …

Recent developments in sensing and monitoring techniques have led to the generation of
high-dimensional data in the field of civil engineering. High-dimensional data analytics …

Detecting anomalies in time series is a vital technique in a wide variety of industrial
application in which sensors monitor expensive machinery. The complexity of this task …

The vigorous development of positioning technology and ubiquitous computing has
spawned trajectory big data. By analyzing and processing the trajectory big data in the form …

Thanks to the advance of novel technologies, such as sensors and Internet of Things (IoT)
technologies, big amounts of data are continuously gathered over time, resulting in a variety …

Vehicle-to-vehicle interaction and collaboration can provide us with a large number of
mobile traffic trajectories that can be used to analyze driving behavior. In this article, we …

Anomaly detection in spatiotemporal data is a problem encountered in a variety of
applications including urban traffic monitoring. For urban traffic data, anomalies refer to …

Urban traffic anomaly diagnosis is crucial for urban road management and smart city
construction. Most existing methods perform anomaly detection from a data-driven …

It is of paramount importance to detect traffic data anomalies in a real-time manner as it
helps efficient traffic control and management. Several unsupervised anomaly detection …

Traffic anomaly detection in road networks is vital for patrol participants to adaptively
optimize patrol routes for hybrid task scheduling. In most cases, the routine patrol routing …