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.

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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.

Abstract
A methodology for estimating the destination of passenger journeys from automated fare collection (AFC) system data is described. It proposes new spatial validation features to increase the accuracy of destination inference results and to verify key assumptions present in previous origin-destination estimation literature. The methodology applies to entry-only system configurations combined with distance-based fare structures, and it aims to enhance raw AFC system data with the destination of individual journeys. This paper describes an algorithm developed to implement the methodology and the results from its application to bus service data from Porto. The data relate to an AFC system integrated with an automatic vehicle location system that records a transaction for each passenger boarding a bus, containing attributes regarding the route, the vehicle, and the travel card used, along with the time and the location where the journey began. Some of these are recorded for the purpose of allowing onboard ticket inspection but additionally enable innovative spatial validation features introduced by the methodology. The results led to the conclusion that the methodology is effective for estimating journey destinations at the disaggregate level and identifies false positives reliably.