Abstract
Seville, with a metropolitan population of about 1.5 million, is the capital and largest city of Andalusia (S Spain). It is the 30th most populous municipality in the European Union and contains three UNESCO World Heritage Sites. The Seville harbour, located about 80 km from the Atlantic Ocean, is the only river port in Spain. The city is located on the plain of the Guadalquivir River. Using Multi-Temporal InSAR with ERS-1/2 and Envisat data a subsidence behavior is detected in the period 1992-2010. The geometry of the subsiding areas suggests that it should be conditioned by the fluvial dynamics of the Guadalquivir River and its tributaries. Facies distribution along the fluvial system (paleochannels, flood plains.), with different grain size and matrix proportion, may explain the relative subsidence between the different sectors.

Abstract
We present a dynamic web tool that allows interactive search and visualization of large news archives using an entity-centric approach. Users are able to search entities using keyword phrases expressing news stories or events and the system retrieves the most relevant entities to the user query based on automatically extracted and indexed entity profiles. From the computational journalism perspective, TimeMachine allows users to explore media content through time using automatic identification of entity names, jobs, quotations and relations between entities from co-occurrences networks extracted from the news articles. TimeMachine demo is available at http://maquinadotempo.sapo.pt/. © Springer International Publishing Switzerland 2016.

Abstract
Sports and physical activities allow people with disabilities to have better quality of life. The proposed work aimed to develop a multimodal interaction platform of robotic devices in a simulated environment for users to train different interface options. The suggested scenarios allow a user to interact with an Intelligent Wheelchair (IW) and with an Intelligent Robotic Ramp (IRR) performing different tasks individually or with a multiplayer option. The main objective of this multimodal interaction platform is to allow users, with severe disabilities, to move around and inclusive to play the Boccia Game more independently and autonomously. A preliminary set of experiments with 27 volunteers tested the scenarios and the multimodal interface for driving the intelligent wheelchair and to maneuver the IRR. The results show excellent performance when users maneuver the IRR in which the success achieved 90%. All dimensions of CEGEQ questionnaire presented good results. Therefore the solution created is quite satisfactory for a user point of view.

Abstract
Smart grids play an important role in the modernization and optimization of the existing electrical grid, to accomplish the current European Union Energy and Climate targets. Smart grids require distributed applications to manage the grid more efficiently. The performance of the distributed applications impacts on the communications delay time and on the timely interaction with the devices located in the users' Home Area Networks. This paper presents the results of the ENCOURAGE project related to the development of a software platform to support smart grids. The work presented in this paper assesses four different middleware configurations and analyses the results on the delay performance tests. The results show that the mean end-to-end delay is between 310 ms and 453 ms in proper conditions. In terms of operational costs, the optimal configuration enables managing houses with less than 0.25 Euros per month per house. This paper justifies the maturity of the technology to support smart grids, and the possibility to transfer the ENCOURAGE project results to the industry.

Abstract
This paper proposes a real-time system to provide location based guidance and obstacle avoidance of blind persons in indoor environments. The system integrates navigation features based on visual recognition of markers and the detection and classification of possible obstacles in front of the blind person. The system uses the Microsoft Kinect sensor to acquire RGB-D images of the scene. The RGB camera provides input for a real-time tracking algorithm which identifies a trained set of wall-mounted visual markers. The user's pose is estimated combining marker information with GIS data. Depth information is used to classify nearby obstacles. The results of experimental tests with two blind subjects are presented and discussed. © 2016 ACM.

Abstract