Abstract
The AtlasCar is a prototype that is being developed at the University of Aveiro to research advanced driver assistance systems. The car is equipped with several sensors: 3D and 2D laser scanners, a stereo camera, inertial sensors and GPS. The combination of all these sensor data in useful representations is essential. Therefore, calibration is one of the first problems to tackle. This paper focuses on 3D/2D laser calibration. The proposed method uses a 3D Laser Range Finder (LRF) to produce a reference 3D point cloud containing a known calibration object. Manual input from the user and knowledge of the object geometry are used to register the 3D point cloud with the 2D Lasers. Experimental results with simulated and real data demonstrate the effectiveness of the proposed calibration method.

Abstract
The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.

Abstract
This study is focused on the evaluation of the impact of Saccharomyces cerevisiae metabolism in the profile of compounds with antioxidant capacity in a synthetic wine during fermentation. A bioanalytical pipeline, which allows for biological systems fingerprinting and sample classification by combining electrochemical features with biochemical background, is proposed. To achieve this objective, alcoholic fermentations of a minimal medium supplemented with phenolic acids were evaluated daily during 11 days, for electrochemical profile, phenolic acids, and the volatile fermentation fraction, using cyclic voltametry, high-performance liquid chromatography-diode array detection, and headspace/solid-phase microextraction/gas chromatography-mass spectrometry (target and nontarget approaches), respectively. It was found that acetic acid, 2-phenylethanol, and isoamyl acetate are compounds with a significative contribution for samples metabolic variability, and the electrochemical features demonstrated redox-potential changes throughout the alcoholic fermentations, showing at the end a similar pattern to normal wines. Moreover, S. cerevisiae had the capacity of producing chlorogenic acid in the supplemented medium fermentation from simple precursors present in the minimal medium.

Abstract
This paper investigates the cyclical behaviour of the wine production in Douro region during the period 1932-2008. In general, wine production is characterised by large fluctuations which are composed of short-term and/or long-term cycles. The aim of this paper is twofold: firstly, we decompose the wine production's variance in order to find the dominating production cycles, i.e we try to explain whether wine production follows more long-term or short-term cycles. In the next step, we try to explain those cycles using a dependent variable, namely the medium spring temperature (Tm_Sp) for the period 1967-2008. We estimated a Time-Varying Autoregressive Model, which could explain 75% of the production that is characterised by 4.8- and 2.5-year cycles. We use the Short Time Fourier Transform to decompose the link between wine production and temperature. When the temperature was incorporated, the R (2) increased and the Akaike criterion value was lower. Hence, Tm_Sp causes a large amount of these cycles and the wine production variation reflects this relationship. In addition to an upward trend, there is a clearly identifiable cycle around the long-term trend in production. We also show how much of the production cycle and what cycle in particular is explained by the Tm_Sp. There is a stable but not constant link between production and the Tm_Sp. In particular, the temperature is responsible for 5.2- and 2.4-year cycles which has been happening since the 1980s. The Tm_Sp can also be used as an indicator for the 4.8- and 2.5-year cycles of production. The developed model suggests that stationarity is a questionable assumption, and this means that historical distributions of wine production are going to need dynamic updating.

Abstract
Permanent semi-natural grassland meadows (lameiros) are characteristic of the mountain rural landscapes in northeast Portugal and represent the main fodder resource for livestock production. Furthermore, these meadows are recognized for their environmental, historical, cultural and visual landscape value. A monitoring study based on remote-sensing data was implemented to understand the impacts of management practices on the lameiros vegetation dynamics and to analyse changes in vegetation dynamics over the period 1998-2008 in response to inter-annual climatic variability. Ten-day SPOT-VEGETATION (VGT) image composites from this period were used to examine the annual temporal profile using the normalized difference vegetation index (NDVI) and their relationship with ground-based observation of vegetation growth and reflectance inferred with a spectroradiometer. Results show that the NDVI profile fits well the characteristic vegetation growth dynamics and associated management practices in the region. For the period from July 2007 to December 2008, the variation in vegetation height explains 46 to 52% of the variation in NDVI derived respectively from spectroradiometer and VGT data. NDVI referring to dates of specific stages of the vegetation dynamics and management practices in lameiros was tested against climatic variables, for the period 1998-2008. More than 57% of the inter-annual variability of the average NDVI during the lameiros development period can be explained by the mean temperature, and 53% of the variability on the date of occurrence of maximum vegetation development (MVD) can be explained by the mean temperature during the spring period. These results support the analysis of lameiros responses to different scenarios of climate and water management and may support the implementation of more efficient farm activities.

Abstract