Abstract
The expected behavior of industrial automation systems can be defined and modeled, but since not every event is predicted at design time, additional care has to be taken during the operation to handle situations such as exceptions, failures and new production orders. Another remark is also the limitation of modeling languages used in the control to permit the intervention of higher grade decision mechanisms. This paper discusses the application of decision support system for Petri net based processes to control automation components and devices. The decision mechanisms are used for path planning, production scheduling and preventive maintenance, to support the description of processes in Petri nets formalism. As such, the same Petri nets designed for the control are also used as analytical information input to the decision support system and for the detection process options that require decision. The solution provides a dynamic complement to the static modeling and operational flexibility. Experiments were done in a real service-oriented industrial factory-cell to prove the specified approach.

Abstract
We consider a trade policy model, where the costs of the home firm are private information but can be signaled through the output levels of the firm to a foreign competitor and a home policymaker. We study the influences of the non-homogeneity of the goods and of the uncertainty on the production costs of the home firm in the signalling strategies by the home firm. We show that some results obtained for homogeneous goods are not robust under non-homogeneity.

Abstract
Determining the size of a network and its diameter are important functions in distributed systems, as there are a number of algorithms which rely on such parameters, or at least on estimates of those values. The Extrema Propagation technique allows the estimation of the size of a network in a fast, distributed and fault tolerant manner. The technique was previously studied in a simulation setting where rounds advance synchronously and where there is no message loss. This work presents two main contributions. The first, is the study of the Extrema Propagation technique under asynchronous rounds and integrated in the Network Friendly Epidemic Multicast (NeEM) framework. The second, is the evaluation of a diameter estimation technique associated with the Extrema Propagation. This study also presents a small enhancement to the Extrema Propagation in terms of communication cost and points out some other possible enhancements. Results show that there is a clear trade-off between time and communication that must be considered when configuring the protocol-a faster convergence time implies a higher communication cost Results also show that its possible to reduce the total communication cost by more than 18% using a simple approach. The diameter estimation technique is shown to have a relative error of less than 10% even when using a small sample of nodes.

Abstract
Several e-business frameworks are currently available, which are aimed at modelling e-business. The aim of this article is to analyse and compare relevant industry-neutral and industry-specific e-business frameworks currently in use, emphasising their strengths and weaknesses towards seamless interoperability in a collaborative networked environment. Their main differences and similarities are underlined based on an analytical model for e-business frameworks comparison. The applicability of the Analytic Hierarchy Process multi-criteria method in e-business frameworks selection is discussed. These analytical approaches are then illustrated with two real cases from industry.

Abstract
The basic contact process or the SIS model is a well known epidemic process and have been studied for a wide class of people. In an epidemiological context, many authors worked on the SIS model considering only the dynamic of the first moments of infecteds, i.e., the mean value and the variance of the infected individuals. In this work, we study not only the dynamic of the first moments of infecteds but also on the dynamic of the higher moments. Recursively, we consider the dynamic equations for all the moments of infecteds and, applying the moment closure approximation, we obtain the stationary states of the state variables. We observe that the stationary states of the SIS model, in the moment closure approximation, can be used to obtain good approximations of the quasi-stationary states of the SIS model.

Abstract
Aggregation of data values plays an important role on distributed computations, in particular over peer-to-peer and sensor networks, as it can provide a summary of some global system property and direct the actions of self-adaptive distributed algorithms. Examples include using estimates of the network Size to dimension distributed hash tables or estimates of the average system load to direct load-balancing. Distributed aggregation using non-idempotent functions, like sums, is not trivial as it is not easy to prevent a given value from being accounted for multiple times; this is especially the case if no centralized algorithms or global identifiers can be used. This paper introduces Extrema Propagation, a probabilistic technique for distributed estimation of the sum of positive real numbers. The technique relies on the exchange of duplicate insensitive messages and can be applied in flood and/or epidemic settings, where multi-path routing occurs; it is tolerant of message loss; it is fast, as the number of message exchange steps equals the diameter; and it is fully, distributed, with no single point of failure and the result produced at every node.