Abstract
Biometric systems are vulnerable to different kinds of attacks. Particularly, the systems based on iris are vulnerable to direct attacks consisting on the presentation of a fake iris to the sensor trying to access the system as it was from a legitimate user. The analysis of some countermeasures against this type of attacking scheme is the problem addressed in the present paper. Several state-of-the-art methods were implemented and included in a feature selection framework so as to determine the best cardinality and the best subset that conducts to the highest classification rate. Three different classifiers were used: Discriminant analysis, K nearest neighbours and Support Vector Machines. The implemented methods were tested in existing databases for iris liveness purposes (Biosec and Clarkson) and in a new fake database which was constructed for evaluation of iris liveness detection methods in the mobile scenario. The results suggest that this new database is more challenging than the others. Therefore, improvements are required in this line of research to achieve good performance in real world mobile applications.

Abstract
The Arteriolar-to-Venular Ratio (AVR) is a well known index for the early diagnosis of diseases such as diabetes, hypertension or cardio-vascular pathologies. This paper presents an automatic approach for the estimation of the AVR in retinal images. The proposed method includes vessel segmentation, vessel caliber estimation, optic disc detection, region of interest determination, artery/vein classification and finally AVR calculation. This method was evaluated using the images of the INSPIRE-AVR dataset. The mean error of the measured AVR values with respect to the reference ones was 0.05, which is identical to the one achieved by a medical expert using a semi-automated system, thus demonstrating the reliability of the herein proposed solution for AVR estimation.

Abstract
Biometrics represents a return to a natural way of identification: testing someone by what (s) he is, instead of relying on something (s) he owns or knows seems likely to be the way forward. Biometric systems that include multiple sources of information are known as multimodal. Such systems are generally regarded as an alternative to fight a variety of problems all unimodal systems stumble upon. One of the main challenges found in the development of biometric recognition systems is the shortage of publicly available databases acquired under real unconstrained working conditions. Motivated by such need the MobBIO database was created using an Asus EeePad Transformer tablet, with mobile biometric systems in mind. The proposed database is composed by three modalities: iris, face and voice.

Abstract
In order to assess the atherosclerotic plaque disruption risk from B-mode ultrasound images of the carotid, an appropriate normalization of the plaque regions is required. This is usually achieved through the manual selection of two sample regions in the image containing blood and adventitia tissues, which are used as reference. In this work, we propose a new plaque region normalization method that takes advantage of multiple blood and adventitia reference samples per image, and a method for the automatic selection of these reference samples. Several preliminary results are provided in order to demonstrate the possible capabilities of the proposed methods.

Abstract
The main motivation of this work was to provide a valid contribution for the assessment of the cardiovascular condition by the analysis of several Arterial Pressure Waveform (APW) parameters collected by a new non-invasive device. Three sets of recordings for the carotid pressure waveform at left and right carotid arteries were performed, under standardized conditions, in 20 volunteers by three trained operators. The mean of the inter-operator differences were higher for the right artery, comparatively to the left artery. In this case, an Augmentation Index (AIx) value of -2.31 ± 7.29 % and a Systolic Wave Transit Time (SWTT) value of -12.94 ± 31.46 ms were observed, which are higher than the left measurements, 0.94 ± 7.52 % and -2.96 ± 22.67 ms, respectively. Intra-operator differences were calculated for each of the three sets of measurements and showed good reproducibility. The pulse-by-pulse variability analysis gives very good markers for the Left Ventricular Ejection Time (LVET), Dicrotic Wave Amplitude (DWA), Reflection Wave Amplitude (RWA), Coefficient of Variation (CV) < 10 %, and satisfactory values for the AIx (CV< 30 %). The SWTT and Reflected Wave Transit Time (RWTT) also presented satisfactory results (10 %

Abstract
A gas pressure sensor based on an all-fiber Fabry-Perot interferometer (FFPI) is reported. The sensing head consists of a small section of silica rod spliced with a large offset between two single-mode fibers. The silica rod is used only as mechanical support so that an air cavity can be formed between both SMF. It is shown that the FFPI sensor is sensitive to gas pressure variation and when submitted to different gaseous environments, namely carbon dioxide, nitrogen and oxygen - sensitivities of 6.2, 4.1 and 3.6 nm/MPa, respectively, were attained. The refractive index change on nitrogen environment by means of gas pressure variation was also determined and a sensitivity of 1526 nm/RIU was obtained. The response of the sensing device to temperature variations in air was also studied and a sensitivity of -14 pm/degrees C was attained.