Abstract
People in modern societies have increasingly sedentary lifestyles. They usually do not have time to take part in physical activity on a regular basis. Additionally, due to time constraints, people are consuming more processed and junk foods. This behavior may lead to health issues, such as obesity or cardiovascular disease. On the other hand people are becoming more aware and more interested in doing physical activities, which has resulted in an increase of memberships at gymnasiums. People usually obtain better results in training by having a personal trainer, especially in the beginning, because personal trainers can recommend safer and more effective exercises, as well as provide motivation. Moreover, personal trainers can also play the roles of life coaches or nutritionists. Despite the benefits, having a personal trainer can be difficult. Due to time constraints, it might not be simple to combine both schedules of the personal trainer and the client. In this paper we present a novel health training platform to maximize the personal trainer and client relationship and, therefore, increase the client's well-being. The health training platform allows clients to have sensors connected to their smartphones and send their exercise data to their personal trainer. It also allows personal trainers to observe their clients' evolution and provide feedback. The health training platform has an architecture that allows multiple configurations involving personal trainers, clients and gymnasiums. We have built and tested a prototype of a health training platform.

Abstract
The increasing number of users and data generated is leading the Social Networks to a scenario where the information cannot be verified. Social networks developers have faced problems about unreliable information sharing and availability of content intentionally prepared to confuse or mislead users. This paper presents a solution to add audit capacity in social networks. It is based on a catalog that organizes characteristics and operationalizations which support auditability of information in social networks and a guide that can help developers to build software that allow evaluation of information reliability. © Springer International Publishing Switzerland 2016.

Abstract
In this paper we present a 12-dimensional tonal space in the context of the Tonnetz, Chew's Spiral Array, and Harte's 6-dimensional Tonal Centroid Space. The proposed Tonal Interval Space is calculated as the weighted Discrete Fourier Transform of normalized 12-element chroma vectors, which we represent as six circles covering the set of all possible pitch intervals in the chroma space. By weighting the contribution of each circle (and hence pitch interval) independently, we can create a space in which angular and Euclidean distances among pitches, chords, and regions concur with music theory principles. Furthermore, the Euclidean distance of pitch configurations from the centre of the space acts as an indicator of consonance.

Abstract
A long-period grating (LPG) written on a standard single mode fiber is investigated as a curvature and vibration sensor. It is demonstrated a high sensitivity to applied curvature and the possibility to monitor vibration in a wide range of frequencies from 30 Hz to 2000 Hz. The system was tested using an intensity based interrogation scheme with the LPG sensor operating in the curvature regime. Results have shown a reproducible frequency discrimination in the 30 Hz to 2000 Hz, with resolutions between 11 mHz and 913 mHz. Frequency retrieval could be perfouned independent of temperature up to 86 degrees C.

Abstract

Abstract
Climate change has raised consciousness of the need to use cleaner energy instead of fossil fuels. Meanwhile, a change of consciousness regarding resource use has to be achieved, which can be triggered by energy consumption monitoring studies that also provide useful recommendations for energy saving. Over time, researchers have identified behaviors by monitoring energy consumption in households, but these studies are usually limited to the number of monitored households and/or to the geographical region in which the monitoring takes place. In this research work, a study with a global reach is proposed to mitigate these limitations. Using a hierarchical clustering algorithm, three distinct groups were identified using the collected data, representative of distinct behaviors. The results illustrate several behaviors regarding energy consumption, like cold temperatures, seasonal behaviors, wake up hour, stay-at-home periods, and standby device consumption.