Abstract
As Collaborative Filtering becomes increasingly important in both academia and industry recommendation solutions, it also becomes imperative to study the algorithm selection task in this domain. This problem aims at inding automatic solutions which enable the selection of the best algorithms for a new problem, without performing full-ledged training and validation procedures. Existing work in this area includes several approaches using Metalearning, which relate the characteristics of the problem domain with the performance of the algorithms. This study explores an alternative approach to deal with this problem. Since, in essence, the algorithm selection problem is a recommendation problem, we investigate the use of Collaborative Filtering algorithms to select Collaborative Filtering algorithms. The proposed approach integrates subsampling landmarkers, a data characterization approach commonly used in Metalearning, with a Collaborative Filtering methodology, named CF4CF. The predictive performance obtained by CF4CF using benchmark recommendation datasets was similar or superior to that obtained with Metalearning.

Abstract
The advent of small and low-cost Unmanned Aerial Vehicles (UAVs) is paving the way to use swarms of UAVs to perform missions such as aerial video monitoring and infrastructure inspection. Within a swarm, UAVs communicate by means of a Flying Multi-hop Network (FMN), which due to its dynamics induces frequent changes of network topology and quality of the links. Recently, UAVs have also been used to provide Internet access and enhance the capacity of existing networks in Temporary Events. This brings up additional routing challenges not yet addressed, in order to provide always-on and high capacity paths able to meet the Quality of Service expected by the users. This paper presents RedeFINE, a centralized routing solution for FMNs that selects high-capacity paths between UAVs and avoids communications disruptions, by defining in advance the forwarding tables and the instants they shall be updated in the UAVs; this represents a major step forward with respect to traditional routing protocols. The performance evaluation of RedeFINE shows promising results, especially regarding Throughput and Packet Delivery Ratio, when compared with state of the art routing solutions.

Abstract
Power and energy systems are being subject to relevant changes, mostly due to the large increase of distributed generation. These changes include the deregulation of electricity markets, which has become a more competitive marketplace due to the increase of the number of players based on renewable energy sources. This paper proposes a new portfolio optimization model for the participation in multiple alternative/complementary market opportunities, considering the risk management. The proposed model considers electricity as the asset to be negotiated. The risk is measured using the prediction error of electricity prices. A case study based on real data from Iberian electricity market-MIBEL assesses the results of the proposed model, using a particle swarm based optimization. Results show that using the proposed portfolio optimization model, market players are able to balance their market participation strategies depending on their risk aversion and profit seeking nature. © 2018 Power Systems Computation Conference.

Abstract
Complex cyber-physical systems are more and more a set of components working tightly coupled, with little or no human intervention. Assessing the correctness of these systems by testing components individually, one-by-one, is obviously not sufficient, being required to also test and validate the overall system. KhronoSim is a modular and extensible platform for testing cyber-physical systems in closed-loop, which enables the integration of simulation models and platform emulators to build a closed loop test environment. This paper presents the emulator module of KhronoSim, developed to integrate the well-known QEMU emulator in the closed-loop testing platform. © 2018 IEEE.

Abstract
Scientific exploitation in ground-based astronomy is improved thanks to adaptive optics (AO) that restore diffraction-limit angular resolution. Besides, the ultimate data interpretation is delivered by post-processing techniques that usually relies on a Point spread function (PSF) model. Nevertheless, existing methods to constrain this model based on standard pipeline encounter the spatial and time variations of the AO PSF. In order to improve accuracy on key science observables, such as photometry and astrometry, alternative methods are investigated, such as PSF reconstruction (PSF-R), designed to estimate the PSF from AO control-loop data and key atmosphere and system parameters. We aim in this paper at retrieving directly these relevant inputs we need to reconstruct the PSF using an hybrid approach, that couples AO telemetry with focal plane images, named as Focal plane profiling and reconstruction (FPPR). It adjusts atmosphere parameters (the C2n (h) profile) and optical gains in the system. We describe the FPPR method that is applied to on-sky Keck images in engineering mode operated with either natural or laser guide star and show we get 1% of accuracy on respectively the Strehl-ratio and the PSF FWHM reconstruction.

Abstract
The highly elliptical, 16-year-period orbit of the star S2 around the massive black hole candidate Sgr A* is a sensitive probe of the gravitational field in the Galactic centre. Near pericentre at 120 AU approximate to 1400 Schwarzschild radii, the star has an orbital speed of approximate to 7650 km s(-1), such that the first-order effects of Special and General Relativity have now become detectable with current capabilities. Over the past 26 years, we have monitored the radial velocity and motion on the sky of S2, mainly with the SINFONI and NACO adaptive optics instruments on the ESO Very Large Telescope, and since 2016 and leading up to the pericentre approach in May 2018, with the four-telescope interferometric beam-combiner instrument GRAVITY. From data up to and including pericentre, we robustly detect the combined gravitational redshift and relativistic transverse Doppler effect for S2 of z = Delta lambda/lambda approximate to 200 km s(-1)/c with different statistical analysis methods. When parameterising the post-Newtonian contribution from these effects by a factor f, with f = 0 and f = 1 corresponding to the Newtonian and general relativistic limits, respectively, we find from posterior fitting with different weighting schemes f = 0.90 +/- 0.09 vertical bar(stat) +/- 0.151 vertical bar(sys). The S2 data are inconsistent with pure Newtonian dynamics.