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Publications

2013

The airport business in a competitive environment

Authors
Jimenez, E; Claro, J; de Sousa, JP;

Publication
EUROPEAN JOURNAL OF TRANSPORT AND INFRASTRUCTURE RESEARCH

Abstract
The liberalisation of the European air transport market has introduced new dynamics in the airport industry. In recent decades, airports evolved from infrastructure providers in a monopolistic context, to commercially orientated enterprises in a competitive environment. Current studies of airport strategic management lack a comprehensive perspective that enables airport operators to best identify the opportunities created by such dynamics. This paper analyses an airport as a multi-service firm that interacts with a network of stakeholders - the airport business network - to deliver several service packages to different groups of customers. An integrated conceptual framework was developed to aid academics and practitioners in the appraisal and design of competitive strategies for airports. Such framework covers a clear gap in existing literature, partly due to the fact that current perspectives on airport management fail to address the complexity of the industry in the present competitive environment.

2013

Automatic localization of the optic disc by combining vascular and intensity information

Authors
Mendonça, AM; Sousa, A; Mendonça, L; Campilho, A;

Publication
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Abstract
This paper describes a new methodology for automatic location of the optic disc in retinal images, based on the combination of information taken from the blood vessel network with intensity data. The distribution of vessel orientations around an image point is quantified using the new concept of entropy of vascular directions. The robustness of the method for OD localization is improved by constraining the search for maximal values of entropy to image areas with high intensities. The method was able to obtain a valid location for the optic disc in 1357 out of the 1361 images of the four datasets.

2013

Multiple Intermediate Structure Deforestation by Shortcut Fusion

Authors
Pardo, A; Fernandes, JP; Saraiva, J;

Publication
SBLP

Abstract
Shortcut fusion is a well-known optimization technique for functional programs. Its aim is to transform multi-pass algorithms into single pass ones, achieving deforestation of the intermediate structures that multi-pass algorithms need to construct. Shortcut fusion has already been extended in several ways. It can be applied to monadic programs, maintaining the global effects, and also to obtain circular and higher-order programs. The techniques proposed so far, however, only consider programs defined as the composition of a single producer with a single consumer. In this paper, we analyse shortcut fusion laws to deal with programs consisting of an arbitrary number of function compositions. © 2013 Springer-Verlag.

2013

A Statistical Classifier for Assessing the Level of Stress from the Analysis of Interaction Patterns in a Touch Screen

Authors
Carneiro, D; Novais, P; Gomes, M; Oliveira, PM; Neves, J;

Publication
SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS

Abstract
This paper describes an approach for assessing the level of stress of users of mobile devices with tactile screens by analysing their touch patterns. Two features are extracted from touches: duration and intensity. These features allow to analyse the intensity curve of each touch. We use decision trees (J48) and support vector machines (SMO) to train a stress detection classifier using additional data collected in previous experiments. This data includes the amount of movement, acceleration on the device, cognitive performance, among others. In previous work we have shown the co-relation between these parameters and stress. Both algorithms show around 80% of correctly classified instances. The decision tree can be used to classify, in real time, the touches of the users, serving as an input to the assessment of the stress level.

2013

Using remote sensing energy balance and evapotranspiration to characterize montane landscape vegetation with focus on grass and pasture lands

Authors
Pocas, I; Cunha, M; Pereira, LS; Allen, RG;

Publication
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION

Abstract
Water and energy balance interactions with vegetation in mountainous terrain are influenced by topographic effects, spatial variation in vegetation type and density, and water availability. This is the case for the mountainous areas of northern Portugal, where ancestral irrigated meadows (lameiros) are a main component of a complex vegetation mosaic. The widely used surface energy balance model METRIC was applied to four Landsat images to determine the spatial and temporal distribution of the energy balance terms in the identified land cover types (LCT). A discussion on the variability of evapotranspiration (ET) through the various vegetation types was supported by a comparison between the respective crop coefficients and those available in the literature corresponding to the LC, which has shown the appropriateness of METRIC estimates of ET. METRIC products derived from images of May and June - NDVI, surface temperature, net radiation, soil heat flux, sensible heat flux, and ET - were used to characterize the LCTs, through application of principal component analysis. Three principal components explained the variance of observed variables and their varimax rotated loadings allowed a good explanation of the behaviour of the explanatory variables in association with the LCTs. Information gained contributes to improve the characterization of the study area and may further support conservation and management of these mountain landscapes.

2013

Evaluation of Features for Leaf Discrimination

Authors
Silva, PFB; Marcal, ARS; Almeida da Silva, RMA;

Publication
IMAGE ANALYSIS AND RECOGNITION

Abstract
A number of shape features for automatic plant recognition based on digital image processing have been proposed by Pauwels et al. in 2009. A database with 15 classes and 171 leaf samples was considered for the evaluation of these measures using linear discriminant analysis and hierarchical clustering. The results obtained match the human visual shape perception with an overall accuracy of 87%.

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