A recent blog by CISCO speaks of how QCM – Quantitative Complexity Management – is used in anomaly detection in highly complex systems and contexts. In particular, it speaks of QCM as being able to detect the existence of an anomaly without having seen it before. Such capability goes beyond Machine Learning in that QCM…
In an interesting article entitled Reliability Paradox for Worldwide Automotive Electronics and published in: 2017 Annual Reliability and Maintainability Symposium (RAMS), one may read: “Automotive Electronics is growing ever since the technological advancement has brought about a revolution in the Automotive Semiconductor and Telematics industry, especially in the past decade. Utilization of microelectronics and hence circuits’…
Wikipedia: “In data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text.…
For applications requiring ultra-fast and safe monitoring of the complexity of critical components, products or infrastructures, Ontonix offers a specific Complexity Chip. The chip is based on FPGA technology and has been developed jointly by Ontonix and SAIC in the framework of a project funded by the US Department of Defense Executive Agent for Printed…
Since its founding in 2005 Ontonix has focused its QCM (Quantitative Complexity Management) technology on protection, problem prevention, ‘robustification’, early warnings and identification of crisis precursors in diverse fields and industries (manufacturing, engineering design, economics, finance, traffic control, medicine, etc.). The present blog introduces a new exotic application of the QCM technology – the use…
