Anomaly detection on time series data has been successfully used in power grid operation
and maintenance, flow detection, fault diagnosis, and other applications. However …

With the development of the Cyber-Physical-Social Systems (CPSS), a large number of
multidimensional time series have been generated in today's world, such as: sensor data for …

This article introduces a method for the detection of knock occurrences in an internal
combustion engine (ICE) using a 1-D convolutional neural network trained on in-cylinder …

In order to support the perception and defense of the operation risk of the medium and low
voltage distribution system, it is crucial to conduct data mining on the time series generated …

In recent years anomaly detection has been wildly applied in many fields, from zero day
attack detection to insider threat detection, from situational awareness to intrusion detection …

High-Performance Computing (HPC) systems need to be constantly monitored to ensure
their stability. The monitoring systems collect a tremendous amount of data about different …

In recent years the demand for High-performance computing (HPC) data centers has
increased. HPC often consists of thousands of computing services. Given the high costs …

Anomaly detection is the science of identifying one or more rare or unexplainable samples
or events in a dataset or data stream. The field of anomaly detection has been extensively …