An approach on place attachment, involvement and behavioural intentions in cross-border tourist regions

This study aims at gaining a deeper understanding of customer profiling and behaviour in cross-border tourism destinations. The study is developed under a niche marketing perspective. It is our view that niche marketing is not confined to the limits of national markets. Previous studies suggest that cross-border regions are an attractive notion, yet they require further theoretical and empirical research. There is still a gap in the understanding of destination management in cross-border regions and the customer profile and motivations. Overall this research attempts to produce a deeper understanding of the profile and behaviour of consumers in tourism settings, addressing the predisposition for the destination in specific contexts (cross-border tourism regions).

Perceptions of residents of hosting the “Guimarães 2012 European Capital of Culture”: an ex-ante approach

The European Capital of Culture is an annual mega-event, which can provide a good forum though which to challenge and engage local citizens, thus generating feelings of common citizenship. In addition, it presents an ideal opportunity to promote the restructuring of the hosting urban space. However, the success of both the organization and the city that hosts the cultural event depends on the residents’ commitment towards it, the consistency of the tourism attractions and activities supplied, and the capacity of anticipating and monitoring the evolution of tourists’ preferences. The present study aims to assess the intention to participate and the impacts perceived by residents of Guimarães from hosting one of the 2012 European Capitals of Culture (2012 ECOC) in the ex-ante period (2011). Through a convenience sample of 471 usable surveys applied to the local population, conducted between October and December 2011, we tried to identify some of these potential impacts. According to the results received, 40% of residents had a low or very low knowledge of the cultural program, although only 11% demonstrated no intention of attending any activity during the event. The comparison of the mean scores of the expected 2012 ECOC impacts by gender reveals that the most valued and least valued factors are common to female and male respondents. With regard to the differences between those that intended to attend the event and the ones that did not, expected participants rated positive and negative impact factors more than did the ones that did not intend to attend.

Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.