The modeling and analysis of hybrid systems is a recent and challenging research area which is actually dominated by two main lines: a functional analysis based on the description of the system in terms of discrete state (hybrid) automata (whose goal is to ascertain conformity and reachability properties), and a stochastic analysis (whose aim is to provide performance and dependability measures...

If hybrid vehicles are to be judged in a fair way, the whole system has to be taken into consideration. This includes not only the specific vehicle with its software, but also the driver and the environment in which the vehicle is driven. Simulation is one way to do this. City buses give an extra potential for hybrid systems, if the software takes the specific route and time table into consider...

Peptide recognition modules (PRMs) are specialised compact protein domains that mediate many important protein-protein interactions. They are responsible for the assembly of critical macromolecular complexes and biochemical pathways (Pawson and Scott, 1997), and they have been implicated in carcinogenesis and various other human diseases (Sudol and Hunter, 2000). PRMs recognise and bind to pept...

Combining discrete state-machines with continuous behavior, hybrid systems are a well-established mathematical model for discrete systems acting in a continuous environment. As a priori infinite state systems, their computational properties are undecidable in the general model and the main line of research concentrates on model checking of finite abstractions of restricted subclasses of the gen...

<p>This article <span>discusses research conducted to conceptualise a secure cloud adoption model. The study surveyed SMEs in the Sri Lankan information technology industry using questionnaire determine computing factors. used Rogers' diffusion of innovation (DOI), Tornatzky and Fleischer's technology-organization-environment (TOE) framework, Venkatesh Bala's acceptance model 3 (TAM...

Predicting and studying the dynamics and properties of environmental systems necessitates the construction and simulation of mathematical models entailing different levels of complexities. Such type of computational experiments often require the combination of discrete and continuous variables as well as processes operating at different time scales. Furthermore, the iterative steps of construct...

In this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the Shabestar Plain, Iran. After initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (GA-BP) should be able to reproduce groundwater ...