With the rapid progress of network technologies and sensors, monitoring the sensor data
such as pressure, temperature, current, vibration and other electrical, mechanical and …

Detection of anomalous behaviors in data centers is crucial to predictive maintenance and
data safety. With data centers, we mean any computer network that allows users to transmit …

We introduce a method called evolving Log Parsing (eLP) to extract information granules
and an interval rule-based classification model from streams of words in unstructured log …

Annually, the Large Hadron Collider (LHC) demands a huge amount of computing
resources to deal with petabytes of produced data. In the next years, a scheduled LHC …

In the near future, large scientific collaborations will face unprecedented computing
challenges. Processing and storing exabyte datasets require a federated infrastructure of …

As a joint effort from various communities involved in the Worldwide LHC Computing Grid,
the Operational Intelligence project aims at increasing the level of automation in computing …

Abstract The Large Hadron Collider (LHC) demands a huge amount of computing resources
to deal with petabytes of data generated from High Energy Physics (HEP) experiments and …

In the context of Industry 4.0, the physical and digital worlds are closely connected, and
robots are widely used to achieve system automation. Digital twin solutions have contributed …

In the context of the upcoming 4th generation industrial revolution (industry 4.0), mechanical
failures in the cyber-physical systems have huge financial impacts. The IT industry like …

Prognostics and Health Management (PHM) has emerged as a subject of topical interest in
the field of smart manufacturing. Recent industrial advancements under the umbrella of …