This paper presents a component-based modeling technique for systems with continuous and discrete dynamics. It uses hierarchical composition to hide the implementation details of one component from other components, and keeps the components at the same level of hierarchy interacting under a well-defined model of computation. Continuous time, discrete event, and finite state machine models are c...

In this paper, we present a new approach to embedded system design based on modeling discrete and also continuous system parts with high level Petri-Nets. Our investigations concentrate on a complete design flow, analysis on high level Petri-Nets and their meaning for hardware/software partitioning of real-time embedded systems. The concepts for hybrid modeling of discrete and continuous system...

The rising trend towards continuous production in the field of small-scale crystallization has generated many creative concepts for apparatuses active pharmaceutical ingredients. One these promising is Slug Flow Crystallizer (SFC), which enables adjustment particle size distribution and achievement high yields through its alternating slug flow. To realize understand inside SFC, experimental eff...

Probabilistic programming is related to a compositional approach to stochastic modeling by switching from discrete to continuous time dynamics. In continuous time, an operator-algebra semantics is available in which processes proceeding in parallel (and possibly interacting) have summed time-evolution operators. From this foundation, algorithms for simulation, inference and model reduction may ...