‘A true feeling of authentic portuguese golf'? The discursive construction of the Algarve region in portuguese golf websites

In an increasingly competitive global marketplace, the need for golf destinations to differentiate themselves from competitors has become more critical than ever. This paper raises questions about the promotional strategies employed by the golf sector in the Algarve, focusing on internet communication strategies, since this medium has become the biggest driving force towards the commoditisation of all aspects of the tourism experience. By offering a complementary perspective to the field of (critical) tourism studies, and drawing on a qualitative, multi-modal discourse analysis, this work-in-progress looks at the particular ways that representations and images presented on the Algarve golf websites constitute and frame identities (of people and places) and socio-spatial relationships. This paper analyses a corpus of 45 texts collected from official websites of the 40 Algarve golf courses and from five entities which promote the Algarve as a golf destination, along with the golf images that are displayed alongside them. Findings point to salient discursive and visual representations of a global setting enjoyed by the global elite. Whereas the courses‟ positioning in relation to their regional competitors draws on similar discursive strategies which reflect those used in tourism advertising discourses in general – e.g. reiteration of explicit comparisons, superlatives and hyperbolic statements -, representations of local emplacedness are not salient; in some cases local place seems to have been almost intentionally suppressed.

On-line operation of an intelligent seismic detector

This study describes the on-line operation of a seismic detection system to act at the level of a seismic station providing similar role to that of a STA /LTA ratio-based detection algorithms. The intelligent detector is a Support Vector Machine (SVM), trained with data consisting of 2903 patterns extracted from records of the PVAQ station, one of the seismographic network's stations of the Institute of Meteorology of Portugal (IM). Records' spectral variations in time and characteristics were reflected in the SVM input patterns, as a set of values of power spectral density at selected frequencies. To ensure that all patterns of the sample data were within the range of variation of the training set, we used an algorithm to separate the universe of data by hyper-convex polyhedrons, determining in this manner a set of patterns that have a mandatory part of the training set. Additionally, an active learning strategy was conducted, by iteratively incorporating poorly classified cases in the training set. After having been trained, the proposed system was experimented in continuous operation for unseen (out of sample) data, and the SVM detector obtained 97.7% and 98.7% of sensitivity and selectivity, respectively. The same type of ANN presented 88.4 % and 99.4% of sensitivity and selectivity when applied to data of a different seismic station of IM. © 2013 Springer-Verlag Berlin Heidelberg.