3 resultados para Idols and images.

em SAPIENTIA - Universidade do Algarve - Portugal


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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.

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Dissertação de Mestrado, Comunicação, Cultura e Artes, Faculdade de Ciências Humanas e Sociais, Universidade do Alagrve, 2014

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In this study, Artificial Neural Networks are applied to multistep long term solar radiation prediction. The networks are trained as one-step-ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and Auto-regressive with exogenous inputs solar radiationmodels are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images. The input-output structure of the neural network models is selected using evolutionary computation methods.