Abstract
Controlling a biped robot with several degrees of freedom is a challenging task that takes the attention of several researchers in the fields of biology, physics, electronics, computer science and mechanics. For a humanoid robot to perform in complex environments, fast;, stable and adaptive behaviors are required. This paper proposes a solution for automatic generation of a walking gait using genetic algorithms (CA). A method based oil partial Fourier series was developed for joint; trajectory planning. GAs Were then used for off-line generation of the parameters that define the gait. GAs proved to be a powerful method for automatic generation of humanoid behaviors resulting Oil a walk forward velocity of 0.51m/s which is a good result considering the results of the three best teams of RoboCup 3D simulation league for the same movement.

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Shoreline change in the Espinho area ( northwest Portugal) is a chronic problem. The present study takes advantage of geographical information system (GIS) tools to contribute to the knowledge of the geologic and geomorphological dynamics of the Espinho shoreline. A GIS-based monitoring project was compiled, which gathers information on all coastal works located along the Espinho shoreline, focusing especially on construction, monitoring, and repair aspects. Shoreline change was analyzed using the ArcGIS extension "Digital Shoreline Analysis System'' (DSAS) to understand this important aspect of coastal management. This work also emphasizes the importance of geotechnical assessment of coastal protection structures in diagnosing their degree of damage and/or deterioration so that one can plan more efficient maintenance works. Our results indicate a general trend of erosion to the south and accretion to the north of the Espinho coastal area. Geoengineering characterization of the Paramos groin defines three main zones for the armor block materials (i.e., Zones I, II/III, and IV), which show, respectively, very low, medium to high, and low deterioration levels.

Abstract
The growing concern about global climate change has led the European Union and the Portuguese Government to set targets for the percentage of electricity to be produced from renewable sources. In order to achieve the defined targets, Distributed Generation (DG) is expected to be increasingly integrated into networks. However, the intermittency of some of those DGs (such as wind energy) may enhance network operating costs or decrease network security. Thus, Network Operators started to concern about these effects and in order to avoid them, new wind parks were required to provide ancillary services to the network. These ancillary services include the ride-through-fault capability. Although some wind parks can already supply ride-through-fault capability to the distribution network (i.e. wind parks with Double Fed Induction Generators (DFIG)), most of them are still largely unable to do so due to the current DG protection scheme. This work concentrates on the development of new settings for the DG protection scheme which aims at allowing DG to provide ride-through fault capability to the distribution network. A DFIG with ride-through-fault capability was modeled on PSCAD/EMTDC and tested under the Portuguese Distributed Generation Protection Scheme Regulation Code. New relay settings for the DG protection scheme are advanced and simulated on PSCAD/EMTDC software in order to permit DGs providing ride-through fault capability to the distribution network. Conclusions of the new relay settings performance are withdrawn and commented on.

Abstract
The high-order statistics (moments and cumulants of order higher than two) have been widely applied in several fields, specially in problems where it is conjectured a lack of Gaussianity and/or non-linearity. Since the INteger-valued AutoRegressive, INAR, processes are non-Gaussian, the high-order statistics can provide additional information that allows a better characterization of these processes. Thus, an estimation method for the parameters of an INAR process, based on Least Squares for the third-order moments is proposed. The results of a Monte Carlo study to investigate the performance of the estimator are presented and the method is applied to a set of real data.