The Genomics of Industrial Process through the Qualia of Markovian Behaviour

Abstract

A technique for registering and relating events that cause an observable and definable system state is proposed. Discrete events of system state transfer are expressed by event tracking and clustering in the form of contiguous quanta of data. This approach is capable of describing typical processes in industrial systems in a chain of codes that contain system input/output parameters. The constituent nodes of the Markovian Processes chain form a series akin to genes in the DNA, repeatable and predictable.<br>

Waveguide quality inspection in quantum cascade lasers: A capsule neural network approach

“…images and natural language) in its raw original form (Westphal & Seitz, 2021). The rise of computational power, big data and graphical processing units (GPUs) brought the application of deep 50 learning (DL) techniques to closer to solving actual and real manufacturing process applications and replace conventional ML methods (Danishvar et al, 2021;Sodhro et al, 2019). DL networks allows to process the raw data and perform feature extraction automatically due to the multiple and complex layers that they have.…”