Abstract
In general, the aim of selling up collaborative networks is the reduction of uncertainty and the increase of competitiveness. One of the main goals is the exploitation of this collaboration networks guaranteeing the legal independence of partners on the basis of common and aligned strategic aims. Nevertheless, its practical implementation is not straight forward because of all the several dimensions it involves. This paper addresses some relevant issues in the domain of collaborative networks, in the scope of a research project based on a case study centered on a large industrial pole in Brazil and mainly established by SME.

Abstract
A genetic algorithm (GA) is a search technique based on the natural selection process. The GAs provide further flexibility and robustness that are unique for signal process. Recently, a closer look of some phenomena present in electrical systems, such as motors, transformers and lines, and the motivation towards the development of comprehensive models, seem to point out the requirement for a fractional calculus approach. Bearing these ideas in mind, we address the analysis and the synthesis of fractional-order multipoles, based in a GA optimization scheme. © 2006 Civil-Comp Press.

Abstract
The Maxwell equations constitute a formalism for the development of models describing electromagnetic phenomena. The four Maxwell laws have been adopted successfully in many applications and involve only the integer order differential calculus. Recently, a closer look for the cases of transmission lines, electrical motors and transformers, that reveal the socalled skin effect, motivated a new perspective towards the replacement of classical models by fractional-order mathematical descriptions. Bearing these facts in mind this paper addresses the concept of static fractional electric potential. The fractional potential was suggested some years ago. However, the idea was not fully explored and practical methods of implementation were not proposed. In this line of thought, this paper develops a new approximation algorithm for establishing the fractional order electrical potential and analyzes its characteristics.

Abstract
Multi-master update everywhere database replication, as achieved by protocols based on group communication such as DBSM and Postgres-R, addresses both performance and availability. By scaling it to wide area networks, one could save costly bandwidth and avoid large round-trips to a distant master server Also, by ensuring that updates are safely stored at a remote site within transaction boundaries, disaster recovery is guaranteed. Unfortunately, scaling existing cluster based replication protocols is troublesome. In this paper we present a database replication protocol based on group communication that targets interconnected clusters. In contrast with previous proposals, it uses a separate multicast group for each cluster and thus does not impose any additional requirements on group communication, easing implementation and deployment in a rea setting. Nonetheless, the protocol ensures one-copy equivalence while allowing all sites to execute update transactions. Experimental evaluation using the workload of the industry standard TPC-C benchmark confirms the advantages of the approach.

Abstract
This paper deals with the discretization of integrals and derivatives (i.e., differintegrals) of complex order. Several methods for the discretization of the operator s?, where ? = u+jv is a complex value, are proposed. The concept of conjugated-order differintegral is also presented. The conjugated-order operator allows the use of complex-order differintegrals while still resulting in real time responses and real transfer functions. The performance of the resulting approximations is evaluated both in the time and frequency domains. Copyright © 2006 IFAC.

Abstract
This work addresses the autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry mission. Datasets from remote sensing applications are typically very large and correlated both in time and space. Multivariate analysis methods are useful tools to summarise and extract information from such large space-time datasets. Multivariate autoregressive analysis is a generalisation of Principal Oscillation Pattern (POP) analysis, widely used in the geosciences for the extraction of dynamical modes by eigen-decomposition of a first order autoregressive model fitted to the multivariate dataset of observations. The extension of the POP methodology to autoregressions of higher order, although increasing the difficulties in estimation, allows one to model a larger class of complex systems. Here, sea level variability in the North Atlantic is modelled by a third order multivariate autoreerressive model estimated by stepwise least squares. Eigen-decomposition of the fitted model yields physically-interpretable seasonal modes. The leading autoregressive mode is an annual oscillation and exhibits a very homogeneous spatial structure in terms of amplitude reflecting the large scale coherent behaviour of the annual pattern in the Northern hemisphere. The phase structure reflects the seesaw pattern between the western and eastern regions in the tropical North Atlantic associated with the trade winds regime. The second mode is close to a semi-annual oscillation. Multivariate autoregressive models provide a useful framework for the description of time-varying fields while enclosing a predictive potential.