Abstract
The measurement and analysis of the arterial pulse waveform (APW) are the means for cardiovascular risk assessment. Optical sensors represent an attractive instrumental solution to APW assessment due to their truly non-contact nature that makes the measurement of the skin surface displacement possible, especially at the carotid artery site. In this work, an automatic method to extract and classify the acquired data of APW signals and noise segments was proposed. Two classifiers were implemented: k-nearest neighbours and support vector machine (SVM), and a comparative study was made, considering widely used performance metrics. This work represents a wide study in feature creation for APW. A pool of 37 features was extracted and split in different subsets: amplitude features, time domain statistics, wavelet features, cross-correlation features and frequency domain statistics. The support vector machine recursive feature elimination was implemented for feature selection in order to identify the most relevant feature. The best result (0.952 accuracy) in discrimination between signals and noise was obtained for the SVM classifier with an optimal feature subset .

Abstract
Body skin temperature is a useful parameter for diagnosing diseases and infrared thermography can, be a powerful tool in providing important information to detect body temperature changes in a noninvasive way. The aim of this work was to study the pattern of skin temperature during pregnancy, to establish skin temperature reference values and to find correlations between these and the pregnant population characteristics. Sixty-one healthy pregnant women (mean age 30.6 +/- 5.1 years) in the 8th-40th gestational week with normal pregnancies were examined in 31 regions of interest (ROI). The ROIs were defined all over the body in order to determine the most influenced by factors such as age or body mass index (BMI). The results obtained in this work highlight that in normal pregnant women the skin temperature is symmetrically distributed, with the symmetrical areas differing less than 0.5 degrees C, with a mean value of 0.25 +/- 0.23 degrees C. This study identified a significant negative correlation between the BMI and temperature. Age has been shown to have great influence on the skin temperature, with a significant increase of temperature observed with age. This work explores a novel medical application of infrared thermography and provides a characterization of thermal skin profile in human pregnancy for a large set of ROIs while also evaluating the effects of age and BMI.

Abstract
A multi-wavelengths analysis for pulse waveform extraction using laser speckle is conducted. The proposed system consists of three coherent light sources (532 nm, 635 nm, 850 nm). A bench-test composed of a moving skin-like phantom (silicone membrane) is used to compare the results obtained from different wavelengths. The system is able to identify a skin-like phantom vibration frequency, within physiological values, with a minimum error of 0.5 mHz for the 635 nm and 850 nm wavelengths and a minimum error of 1.3 mHz for the 532 nm light wavelength using a FFT-based algorithm. The phantom velocity profile is estimated with an error ranging from 27% to 9% using a bidimensional correlation coefficient-based algorithm. An in vivo trial is also conducted, using the 532 nm and 635 nm laser sources. The 850 nm light source has not been able to extract the pulse waveform. The heart rate is identified with a minimum error of 0.48 beats per minute for the 532 nm light source and a minimal error of 1.15 beats per minute for the 635 nm light source. Our work reveals that a laser speckle-based system with a 532 nm wavelength is able to give arterial pulse waveform with better results than those given with a 635 nm laser.

Abstract
This paper presents a counting system project for the Naturtejo Global Geopark, which is structured in two phases. The objective of the first phase was to develop, install and test an electronic system able to remotely count the number of visitors on the Naturtejo Geopark walking routes and touristic sites. The data is reported through a web interface. A Pilot test is currently installed on Trail PR3 – “Fossil’s Route”, near the village of Penha Garcia. Since May 2015, more than 6000 tourists where monitored. The second phase of the project aims to track tourists based on the detection of Wi-Fi signals generated by their smartphones. Thanks to data mining algorithms, useful insights can be extracted that helps to understand the behaviour of tourists when they travel around the large territory of the Geopark.

Abstract
This paper presents a computational framework for the optimization of maintenance activities for infrastructure assets, with particular emphasis being placed on road network assets. This framework incorporates degradation and maintenance models for infrastructure assets along with multi-objective optimization for searching optimal maintenance schedules. Given a schedule of maintenance actions, the future performance is estimated by means of a Monte Carlo simulation that enables to account for inherent uncertainties. The design variables of optimization are the types of maintenance actions and their timing over the planning horizon. The objectives are to minimize both the asset degradation and maintenance cost. This includes satisfaction of constraints representing performance demands. The proposed framework is general and can be applied to different types of infrastructure assets. The numerical results, obtained for a road bridge managed by a highway operating agency, demonstrate the validity and usefulness of the proposed framework.

Abstract
A great number of masonry arch bridges dates back to past centuries, being preserved by society due to their historical and still economic importance. Thereby, adequate preservation measures are required. Regarding masonry arch bridge's structural condition, it is relevant to consider its age, and consequently deterioration, and the fact that these bridges are submitted to loads higher than those for which they were conceived, being imperative to assess their structural performance. Regarding safety assessment requirements, there are different reliability levels, whose objectives are to analyse the ultimate load carrying capacity and the serviceability performance. This paper presents and discusses a framework that allows to determine the ultimate load-carrying capacity (Ultimate Limit State) of masonry arch bridges, using limit analysis and probabilistic approaches. Geometric and material data and load characterization, as well as inherent uncertainties will be also introduced. In order to determine the ultimate load-carrying capacity, the plastic theory will be employed, namely the limit analysis theorem, which is based on kinematic mechanisms. Since one of the main drawbacks of a probabilistic analysis is the required high computational resources, a sensitivity analysis is incorporated in order to reduce the analysis time. The presented framework is validated with an application to a set of existing Portuguese railway masonry arch bridges. (C) 2016 Published by Elsevier Ltd.