Abstract
This work represents one of the first successful applications of Autonomous Underwater Vehicles (AUVs) for interdisciplinary coastal research. A monitoring mission to study the shape and estimate the initial dilution of the S. Jacinto sewage outfall plume using an AUV was performed on July 2002. An efficient sampling strategy enabling greater improvements in spatial and temporal range of detection demonstrated that the sewage effluent plume can be clearly traced using naturally occurring tracers in the wastewater. The outfall plume was found at the surface highly influenced by the weak stratification and low currents. Dilution varying with distance downstream was estimated from the plume rise over the outfall diffuser until a nearly constant value of 130:1, 60 m from the diffuser, indicating the near field end. Our results demonstrate that AUVs can provide high-quality measurements of physical properties of effluent plumes in a very effective manner and valuable considerations about the initial mixing processes under real oceanic conditions can be further investigated.

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The revision of the 1995 land cover dataset for the Vale do Sousa region, in the northwest of Portugal, was carried out by supervised classification of a multi-spectral image from the Advanced Spaceborne Thermal Emission and Reflectance Radiometer ( ASTER) sensor. The nine reflective bands of ASTER were used, covering the spectral range from 0.52-2.43 μ m. The image was initially ortho-rectified and segmented into 51 186 objects, with an average object size of 135 pixels ( about 3 ha). A total of 582 of these objects were identified for training nine land cover classes. The image was classified using an algorithm based on a fuzzy classifier, Support Vector Machines (SVM), K Nearest Neighbours (K-NN) and a Logistic Discrimination (LD) classifier. The results from the classification were evaluated using a set of 277 validation sites, independently gathered. The overall accuracy was 44.6% for the fuzzy classifier, 70.5% for the SVM, 60.9% for the K-NN and 72.2% for the LD classifier. The difficulty in discriminating between some of the forest land cover classes was examined by separability analysis and unsupervised classification with hierarchical clustering. The forest classes were found to overlap in the multi-spectral space defined by the nine ASTER bands used.

Abstract
Interpreted languages are widely used due to ease to use, portability, and safety. On the other hand, interpretation imposes a significance overhead. Just-in-Time (JIT) compilation is a popular approach to improving the runtime performance of languages such as Java. We compare the performance of a JIT compiler with a traditional compiler and with an emulator. We show that the compilation overhead from using JIT is negligible, and that the JIT compiler achieves better overall performance, suggesting the case for aggresive compilation in JIT compilers. © J. UCS.

Abstract
This paper aims at evaluate the impact of imitation networks on organizations' survival rates within a Portuguese industrial cluster. We used a Multi-Agent framework to represent the industrial cluster, its firms and the rules underlying the imitation strategies. Several experiments were based on the density dependence model, where vital rates are related with the size of the population (population density). We have concluded that imitation seems to improve the vital dynamics of the population and that present information about a firm is enough to establish an imitation network.