Abstract
This work reports a multimode interference-based fiber sensor in a cavity ring-down system (CRD) for sensing temperature-induced refractive index (RI) changes of water. The sensing head is based in multimodal interference (MMI) and it is placed inside the fiber loop cavity of the CRD system. A modulated laser source was used to send pulses down into the fiber loop cavity and an erbium-doped fiber amplifier (EDFA) was placed in the fiber ring to provide an observable signal with a reasonable decay time. The behavior of the sensing head to temperature was studied due to its intrinsic sensitivity to said parameter - a sensitivity of -1.6x10(-9) mu s/degrees C was attained. This allowed eliminating the temperature component from RI measurement of water and a linear sensitivity of 580 mu s/RIU in the RI range of 1.324-1.331 was obtained. The use of a MMI fiber sensor in the proposed CRD configuration allowed achieving a sensitivity similar to 4-fold than that obtained with a tilted fiber Bragg grating and similar to 2-fold than that when a micrometric channel inscribed in the fiber was used.

Abstract
Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement. This paper explores information from daily futures contract trading and forecast of the daily average spot price to correct point and probabilistic forecasting bias. It also shows that an adequate choice of explanatory variables and use of simple models like linear quantile regression can lead to highly accurate spot price point and probabilistic forecasts. In terms of point forecast, the mean absolute error was 3.03 Euro/MWh for day-ahead market and a maximum value of 2.53 Euro/MWh was obtained for intraday session 6. The probabilistic forecast results show sharp forecast intervals and deviations from perfect calibration below 7% for all market sessions.

Abstract
Virtual Reality (VR) is again in the spotlight. However, interactions and modeling operations are still major hurdles to its complete success. To make VR Interaction viable, many have proposed mid-air techniques because of their naturalness and resemblance to physical world operations. Still, natural mid-air metaphors for Constructive Solid Geometry (CSG) are still elusive. This is unfortunate, because CSG is a powerful enabler for more complex modeling tasks, allowing to create complex objects from simple ones via Boolean operations. Moreover, Head-Mounted Displays occlude the real self, and make it difficult for users to be aware of their relationship to the virtual environment. In this paper we propose two new techniques to achieve Boolean operations between two objects in VR. One is based on direct-manipulation via gestures while the other uses menus. We conducted a preliminary evaluation of these techniques. Due to tracking limitations, results allowed no significant conclusions to be drawn. To account for self-representation, we compared full-body avatar against an iconic cursor depiction of users' hands. In this matter, the simplified hands-only representation improved efficiency in CSG modelling tasks. © 2017 IEEE.

Abstract
TourismShare is a context-aware recommendation platform that allows tourists to share private locations and videos and obtain recommendations regarding potential Points of Interest (POI), including complementary articles and videos. The user experience is enhanced with the addition audio immersion during video playback and automatic recommendation features. The developed system consists of a distributed application comprising a front-end client module (Android application), which provides the user interface and consumes directly external support services, and the back-end server module, which includes the central database and recommendation service. The communication between the client and server modules is implemented by a dedicated application level protocol. The recommendations, which are based on the user context (user position, date and current time, past ratings and user activity level), are provide on request or automatically, whenever POI of great relevance to the user are found. The recommended POI are presented on a map, showing the timetable together with complementary articles and videos. The audio immersion at video playback time takes into account the weather conditions of the video recording and the user activity level.

Abstract
In this work we address the development of a fast solver of the ray-tracing equations based on heterogeneous supercomputing using PyOpenCL. We apply this solver to the study of gravitational lensing and light propagation in optical systems.

Abstract
Nowadays, the increase of robotic technology application to industry scenarios is notorious. Proposals for new effective solutions are in continuous development once industry needs a constantly improvement in time as well as in production quality and efficiency. The EuRoC research project proposes a scientific competition in which research and industry manufacturers joint teams are encouraged to develop and test solutions that can solve several issues as well as be useful in manufacturing improvement. This paper presents the TIMAIRIS architecture and approach used in the Challenge 2 - Stage II - Benchmarking phase, namely regarding the perception, manipulation and planning strategy that was applied to achieve the tasks objectives. The used approach proved to be quite robust and efficient, which allowed us to rank first in the Benchmarking phase. © 2017 IEEE.