Anomaly detection of time series is an important topic that has been widely studied in many
application areas. A number of computational methods were developed for this task in the …

Practical industrial processes usually have nonstationary properties, which make the
monitoring more challenging because the fault information may be buried by nonstationary …

With the increasing complexity and scale of modern industrial processes, there widely exist
two-valued variables (TVs), such as status monitoring and numerical range variables …

Local differential privacy (LDP) is a promising privacy model for distributed data collection. It
has been widely deployed in real-world systems (eg Chrome, iOS, macOS). In LDP-based …

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy
because it is portable and easy to use, especially in remote monitoring health-services …

Testing plays an essential role in ensuring the safety and quality of cyberphysical systems
(CPSs). One of the main challenges in automated and software-in-the-loop simulation …

With the increasing intelligence and integration, a great number of two-valued variables
(generally stored in the form of 0 or 1) often exist in large-scale industrial processes …

Abstract Cognitive Internet of Things (CIoT) is a new subfield of the Internet of Things (IoT)
that aims to integrate cognition into the IoT's architecture and design. Various CIoT …

Abstract The Symbolic Aggregate appro**mation (SAX) is a very popular symbolic
dimensionality reduction technique of time series data, as it has several advantages over …

This paper addresses the challenges in detecting the potential correlation between
numerical data streams, which facilitates the research of data stream mining and pattern …