Abstract
This paper presents an autonomous navigation and position estimation framework which enables an Unmanned Aerial Vehicle (UAV) to possess the ability to safely navigate in indoor environments. This system uses both the on-board Inertial Measurement Unit (IMU) and the front camera of a AR. Drone platform and a laptop computer were all the data is processed. The system is composed of the following modules: navigation, door detection and position estimation. For the navigation part, the system relies on the detection of the vanishing point using the Hough transform for wall detection and avoidance. The door detection part relies not only on the detection of the contours but also on the recesses of each door using the latter as the main detector and the former as an additional validation for a higher precision. For the position estimation part, the system relies on pre-coded information of the floor in which the drone is navigating, and the velocity of the drone provided by its IMU. Several flight experiments show that the drone is able to safely navigate in corridors while detecting evident doors and estimate its position. The developed navigation and door detection methods are reliable and enable an UAV to fly without the need of human intervention.

Abstract
The olive tree (Olea europaea L.) can be affected by Colletotrichum acutatum, causing a loss of yield and quality of the final products, whilst the incidence of this fungal infection depends on several factors, including cultivar susceptibility. Thus, the effect of C. acutatum infection in cultivars displaying different susceptibilities to this fungal disease (Galega Vulgar' - susceptible, Cobrancosa' - moderately susceptible, Picual' - tolerant) has been assessed through spectrophotometric methods and HPLC, while the FTIR spectra of the cuticles have been concomitantly registered, resorting to the ATR accessory. With the support of multivariate analysis, these spectra allowed to discriminate olives with distinct infection times, besides retrieving evidences concerning the different susceptibility of each cultivar, while these observations were reinforced by the spectrophotometric and chromatographic methods. Furthermore, the assessment of the phenolic profile evidenced individual compounds in the distinct cultivars, so as their variations in response to the fungal infection. Distinct olive cultivars were inoculated with Colletotrichum acutatum. The most resistant olive tree cultivars display the highest content in phenolics. FTIR-ATR-based analyses allow to monitor the response of olive fruits to C. acutatum.

Abstract
We introduced a new method for distinguishing two probability ensembles called one from each method, in which the distinguisher receives as input two samples, one from each ensemble. We compare this new method with multi-sample from the same method already exiting in the literature and prove that there are ensembles distinguishable by the new method, but indistinguishable by the multi-sample from the same method. To evaluate the power of the proposed method we also show that if non-uniform distinguishers (probabilistic circuits) are used, the one from each method is not more powerful than the classical one, in the sense that does not distinguish more probability ensembles. Moreover we obtain that there are classes of ensembles, such that any two members of the class are easily distinguishable (a definition introduced in this paper) using one sample from each ensemble; there are pairs of ensembles in the same class that are indistinguishable by multi-sample from the same method.

Abstract
The electricity sector has been subjected to major changes in the last few years. Previously, there existed a regulated system where electric companies could know beforehand the amount of energy each generator would produce, hence basing their largely operational strategy on cost minimization in order to increase their profits. In Spain, from 1988 till 1997, electricity prices were established by the 'Marco Legal Estable' Stable Legal Framework, where the Ministry of Industry and Energy acknowledged the existence of certain generation costs related to each type of technology. It was an industrial sector with no actual competition and therefore, with very few controllable risks. In the aftermath of the electricity market liberalization competition and uncertainty arose. Electricity spot prices became highly volatile due to the specific characteristics of electricity as a commodity. Long-term contracts allowed for hedge funds to act against price fluctuation in the electricity market. As a consequence, developing an accurate electricity price forecasting model is an extremely difficult task for electricity market agents. This work aims to propose a methodology to improve the limitations of those methodologies just using historical data to forecast electricity prices. In this manner, and in order to gain access to more recent data, instead of using natural gas prices and electricity load historical data, a regression model to forecast the evolution of natural gas prices, and a model based on artificial neural networks (ANN) to forecast electricity loads, are proposed. The results of these models are used as input for an electricity price forecast model. Finally, and to demonstrate the effectiveness of the proposed methodology, several study cases applied to the Spanish market, using real price data, are presented.

Abstract
Physical disability can, in certain cases, be a barrier for traditional human-computer interaction based on keyboard and mouse devices. Alternative ways of interaction based on computer vision may be successfully adapted in particular cases of disability. This paper purposes a vision-based assistive technology to help a child with a degenerative neuromuscular disease to interact with the computer through facial expression recognition. The proposed algorithm was evaluated in images extracted from videos of the child and the preliminary results indicate that computer-interaction via facial expression recognition can break down barriers for people with reduced mobility regarding their relation with computers.

Abstract