Abstract
Information technology and information systems have evolved dramatically over the last half-century, playing an absolutely central and crucial role in the success of today's organizations. Therefore the complexity of the work of the chief information officer has also increased significantly with the current demand for the use of more evolved software tools to support the chief information officer job. With the purpose of identifying and characterizing which software tools chief information officers of large Portuguese companies use in their work,, we dei,eloped a study with the participation. of several chief information officers. The study seeks answers to the question: Does the chief information officer in Portuguese large companies uses advanced information technology solutions in his/her work or, as that old saying, the shoemaker's wife is the worse shod. The findings of this study reveal that the chief information officers are not using all the potential of the software tools that would give them a better performance in their jobs.

Abstract

Abstract
This paper focuses on the positioning control of of a small size autonomous surface vessel (ASV) that can be used to carry a multitude of payload systems, including acoustic devices for underwater positioning and for communications with autonomous underwater vehicles. Its main motivation is the development of highly operational systems, by replacing typically moored support infrastructures with others that can dynamically position themselves. This work covers the design of feedback control laws that assure that the underactuated surface vessel Zarco can keep its position even in the presence of water currents and wind, and without special sensors to estimate such disturbances. Experimental results showing the performance of the designed control laws are also shown.

Abstract
First-Order Theory Revision from Examples is the process of improving user-defined or automatically generated First-Order Logic (FOL) theories, given a set of examples. So far, the usefulness of Theory Revision systems has been limited by the cost of searching the huge search spaces they generate. This is a general difficulty when learning FOL theories but recent work showed that Stochastic Local Search (SLS) techniques may be effective, at least when learning FOL theories from scratch. Motivated by these results, we propose novel SLS based search strategies for First-Order Theory Revision from Examples. Experimental results show that introducing stochastic search significantly speeds up the runtime performance and improve accuracy.

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This paper reports new results in adopting entropy concepts to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. Renyi's Entropy is combined with a Parzen Windows estimation of the error pdf to form the basis of three criteria (MEE, MCC and MEEF) under which neural networks are trained. The results are favourably compared with the traditional minimum square error (MSE) criterion. Real case examples for two distinct wind parks are presented.

Abstract
This work addresses the implementation of the navigation, guidance and control of autonomous underwater vehicles on mobile acoustic networks. After a theoretical discussion of the algorithms required for such operation, we present results from simulation and real experiments that validate the proposed solutions.