Abstract
Industrial companies are faced today with strong competition and fast changing markets. To reduce the risk and evaluate alternatives, simulation is often considered to be an adequate tool. Industrial companies' simulation models must have enough internal detail to be useful but, at the same time, must take into account the external environmental behaviour. Distributed simulation has specific characteristics to allow the integration of these models but its complexity limits its use in industry as stated in the literature. To overcome these difficulties, a framework is proposed, using Agent-based Modelling and Simulation (ABMS) technique and offering communication and synchronization mechanisms, which allow the integration of simulation models in the industrial area. To promote semantic interoperability, a business language is also proposed based on the OASIS Universal Business Language (UBL). To validate the framework a prototype was developed. The experiments made with the prototype shows that a distributed simulation can be more efficient than a single computer simulation as the number of agents increases in the model.

Abstract
This work discusses on the simulation of a ship crew reaction in controlling damage in a single watertight compartment, taking into account ship's hydrostatics and equipment limitation. Three different simulators were built which exchange data using High Level Architecture concepts, implemented with an open source RTI called CERTI and a MatlabHLA Tollbox.

Abstract
This paper is concerned with the use of simulation as a decision support tool in maintenance systems, specifically in MFS (Maintenance Float Systems). For this purpose and due to its high complexity, in this paper the authors explore and present a way to develop a flexible MFS model, for any number of machines in the workstation, spare machines and maintenance crews, using Arena simulation language. Also in this paper, some of the most common performance measures are identified, calculated and analysed. Nevertheless this paper would concentrate on the two most important performance measures in maintenance systems: system availability and maintenance total cost. As far as these two indicators are concerned, it was then quite clear that they assumed different behaviour patterns, especially when using extreme values for periodic overhauls rates. In this respect, system availability proved to be a more sensitive parameter.

Abstract

Abstract
The adoption of mobile payment systems is known to face multiple concerns regarding security, usability and value proposition. In this work, we start from the assumption that initial acceptance will always be weak because of the lack of an established usage frame. Instead, we focus on understanding how we can leverage upon the real contact with the technology to create a solid path for gradual acceptance through the development of new practices and the increasing perception of value. In this study, we report on our findings with a real-world prototype of a NFC-based payment system. We identify a set of design lessons that may help to improve the initial phases of NFC-based payment deployments and provide a path for the adoption that focuses on positive initial user experiences and early adoption scenarios. © Springer International Publishing 2013.

Abstract
Artificial Neural Networks (ANN) have been essentially used as regression models to predict the concentration of one or more pollutants usually requiring information collected from air quality stations. In this work we consider a Multilayer Perceptron (MLP) with one hidden layer as a classifier of the impact of air quality on human health, using only traffic and meteorological data as inputs. Our data was obtained from a specific urban area and constitutes a 2-class problem: above or below the legal limits of specific pollutant concentrations. The results show that an MLP with 40 to 50 hidden neurons and trained with the cross-entropy cost function, is able to achieve a mean error around 11%, meaning that air quality impacts can be predicted with good accuracy using only traffic and meteorological data. The use of an ANN without air quality inputs constitutes a significant achievement because governments may therefore minimize the use of such expensive stations.