The tourist potential of the Minho-Lima region (Portugal)

Visions for Global Tourism Industry: Creating and Sustaining Competitive Strategies

Planning Considerations for Tourism in the Minho-Lima Region (Northwest Portugal)

In administering their territories, most local municipalities aim to preserve their natural, historical and ethnographical resources while simultaneously using them to increase revenue and employment. In order to efficiently promote the products and services available and attract tourists, decision makers, private and public, need to know and incorporate tourists’ preferences in their marketing strategies. In this chapter we illustrate the use of stated preferences as an instrument to identify national and foreign tourists’ preferences regarding the products and services that the touristic destination of the Minho-Lima region (Northwest Portugal) should offer. As a starting point, we have taken the three general groups of touristic resources mentioned above as attributes. We take Ponte de Lima, a municipality in this region that has a strong cultural tourism potential as an example to identify possible future tourism scenarios for this territory. We believe the previously identified methodology can be a valuable instrument in the identification of the strengths and weaknesses of the selected territory and, thus, support the decision making process behind its future tourist development and marketing strategies.

Portugal’s Minho-Lima region as a tourist destination: tourism operators’ attitudes towards its management and promotion

The success of tourism development depends on the capacity of a region’s tourism agents to establish and sustain networks, involving both private-sector companies and the public sector. Creating an attractive destination able to compete with others that are better positioned and consolidated requires cooperative behaviour among the various agents involved. This behaviour will facilitate both external and internal competition, which in turn will assure better product quality, continuous product renewal, a strong offer of unique experiences and the efficient use of endogenous resources. In this paper, the authors discuss the results of a survey of restaurant owners and of interviews conducted with the main institutional agents concerned with tourism promotion and the economic development of the Minho–Lima region. Such an approach, the authors argue, can be valuable in identifying the strengths and weaknesses of the area in question with regard to future tourism development. The authors work from the premise that the commitment of tourism agents constitutes a precondition for the success of the strategy to be defined. This is especially applicable to Minho–Lima, which to date has suffered from an absence of commitment and coordination on the part of those agents.

Error bounds for low-rank approximations of the first exponential integral kernel

A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix technique in the numerical solution of a large scale eigenvalue problem arising from a finite rank discretization of an integral operator. The operator is of convolution type, it is defined through the first exponential-integral function and, hence, it is weakly singular. We develop analytical expressions for the approximate degenerate kernels and deduce error upper bounds for these approximations. Some computational results illustrating the efficiency and robustness of the approach are presented.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Fast left ventricle tracking in CMR images using localized anatomical affine optical flow

In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 ± 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction.