Introduction to Industrial Control Networks

An Introduction to Inference and Learning in Bayesian Networks

Bayesian networks (BNs) are modern tools for modeling phenomena in dynamic and static systems and are used in different subjects such as disease diagnosis, weather forecasting, decision making and clustering. A BN is a graphical-probabilistic model which represents causal relations among random variables and consists of a directed acyclic graph and a set of conditional probabilities. Structure...

Introduction to the "Industrial Benchmark"

A novel reinforcement learning benchmark, called Industrial Benchmark, is introduced. The Industrial Benchmark aims at being be realistic in the sense, that it includes a variety of aspects that we found to be vital in industrial applications. It is not designed to be an approximation of any real system, but to pose the same hardness and complexity.

Application of trusted network technology to industrial control networks

Interconnections between industrial control networks and enterprise networks expose instrumentation and control systems and the critical infrastructure components they operate to a variety of cyber attacks. Several architectural standards and security best practices have been proposed for industrial control systems. However, they are based on older architectures and do not leverage the latest h...

An introduction to neural networks An introduction to neural networks

LonWorks and Pyxos in industrial control networks

The LonWorks platform for device networking has been widely adopted in buildings, industrial facilities, Supervisory Control And Data Acquisition (SCADA) applications, homes, semiconductor equipment, and transportation systems. Historically, it has seen limited use in the more traditional industrial sectors and machine controls. The new Pyxos embedded control networking platform has dramaticall...