Semiconductor fabrication factories are large enterprises with many toolsets, each having multiple production machines. The process flow is highly reentrant, therefore modeling is best done by discrete-event simulation. To describe such a fab, the author has developed a new discrete event simulator called FabSim. It is written in C++. As the simulation engine it uses SystemC, a C++ class librar...

Discrete Event Systems Specification (DEVS) formalism has been used in recent decades for modeling and simulation of discrete event systems as well as for some hybrid systems, since it has a sound semantics for modular hierarchical semantics and good simulation development environments. Nevertheless there are still deep gaps in understanding between the formalism and the practical modeling of l...

Diverse modeling and simulation methods are being applied in the area of Systems Biology. Most models in Systems Biology can easily be located within the space that is spanned by three dimensions of modeling: continuous and discrete; quantitative and qualitative; stochastic and deterministic. These dimensions are not entirely independent nor are they exclusive. Many modeling approaches are hybr...

Several variable selection procedures are available for continuous time-to-event data. However, if time is measured in a discrete way and therefore many ties occur models for continuous time are inadequate. We propose penalized likelihood methods that perform efficient variable selection in discrete survival modeling with explicit modeling of the heterogeneity in the population. The method is b...

Earlier research in the modeling and simulation of hybrid systems led to the development of a general hybrid systems modeling language (hsml). EEort is underway to implement this concept in software. The standard matlab model framework and integration algorithms have been extended to support state-event handling in continuous-time components and to handle embedded discrete-time components. In t...

In the discrete modeling approach for hybrid control systems, the continuous plant is reduced to a discrete event approximation, called the DES-plant, that is governed by a discrete event system, representing the controller. The observability of the DES-plant model is crucial for the synthesis of the controller and for the proper closed loop evolution of the hybrid control system. Based on a ve...

The new DEVS-NS2 modeling and simulation environment supports both high and low levels of abstraction network modeling and simulation. DEVS (Discrete Event System Specification) is a well-defined mathematical formalism specification for structure and behavior of dynamic systems. The NS-2 is a discrete event network simulator, whose primary use is intended to build and run various detailed netwo...

We present the definition of a specification language to outline sections of cities as discrete-event cell spaces. Streets are characterized by their traffic direction, number of lanes, etc. Specialized behavior is included to model traffic lights, trucks, traffic signs, railways, etc. The models are formally specified as DEVS and Cell-DEVS models, avoiding a high number of errors in the develo...

In modeling and simulation, the need for interoperability can be between simulation models or, more broadly, within simulation environments. For example, simulation of biochemical pathways for glycan biosynthesis will need access to glycomics knowledge bases such as the GlycO, EnzyO and ReactO ontologies and bioinformatics resource/databases. Traditionally, developers have studied these informa...

We propose a unified modeling framework for discrete event simulation. Our approach aims to provide a generic framework to simplify construction of simulation models, and at the same time provide the capability to capture the dynamic, static, and functional aspects of a system under study. We adopt a graphical modeling technique that integrates best practices from several powerful modeling para...