Abstract
Design and hierarchical control of three phase parallel Voltage Source Inverters are developed in this paper. The control scheme is based on synchronous reference frame and consists of primary and secondary control levels. The primary control consists of the droop control and the virtual output impedance loops. This control level is designed to share the active and reactive power correctly between the connected VSIs in order to avoid the undesired circulating current and overload of the connected VSIs. The secondary control is designed to clear the magnitude and the frequency deviations caused by the primary control. The control structure is validated through dynamics simulations. The obtained results demonstrate the effectiveness of the control structure.

Abstract
Stochastic search algorithms are black-box optimizer of an objective function. They have recently gained a lot of attention in operations research, machine learning and policy search of robot motor skills due to their ease of use and their generality. However, when the task or objective function slightly changes, many stochastic search algorithms require complete re-leaming in order to adapt thesolution to the new objective function or the new context. As such, we consider the contextual stochastic search paradigm. Here, we want to find good parameter vectors for multiple related tasks, where each task is described by a continuous context vector. Hence, the objective function might change slightly for each parameter vector evaluation. In this paper, we investigate a contextual stochastic search algorithm known as Contextual Relative Entropy Policy Search (CREPS), an information-theoretic algorithm that can learn from multiple tasks simultaneously. We show the application of CREPS for simulated robotic tasks.

Abstract
We describe different scenarios where a learning mechanism is capable of acquiring experience on a source task, and subsequently exploit such experience on a target task. The core ideas behind this ability to transfer knowledge from one task to another have been studied in the machine learning literature under different titles and perspectives. Here we describe some of them under the names of inductive transfer, transfer learning, multitask learning, meta-searching, meta-generalization, and domain adaptation. © Springer Science+Business Media New York 2011, 2017

Abstract
Currently Information and Communication Technologies (ICT) support most of the industrial manufacturing processes. The IT revolution has brought an important transformation in organizations with high impacts, which are comparable to the mechanization and electricity brought in the first and second industrial revolution. This evolvement has promoted the emergence of cloud-based systems, the Internet of Things (IoT), Big Data, Industry 4.0, BYOD (Bring Your Own Device) and CYOD (Choose Your Own Device) trends. However, new technological solutions always carry security vulnerabilities, which most of time reveal unexpected risks. In fact, with increasing reliance on technology to gain competitive advantage, security issues have been one of the most critical and challenging requirements for conducting successful business. In this paper, it is highlighted some reflections regarding the challenges of Industry 4.0 emphasizing the security issues, towards raising awareness for security good practices within Industry 4.0. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
GRAVITY is a new instrument to coherently combine the light of the European Southern Observatory Very Large Telescope Interferometer to form a telescope with an equivalent 130m diameter angular resolution and a collecting area of 200 m(2). The instrument comprises fiber fed integrated optics beam combination, high resolution spectroscopy, built-in beam analysis and control, near-infrared wavefront sensing, phase-tracking, dual-beam operation, and laser metrology. GRAVITY opens up to optical/infrared interferometry the techniques of phase referenced imaging and narrow angle astrometry, in many aspects following the concepts of radio interferometry. This article gives an overview of GRAVITY and reports on the performance and the first astronomical observations during commissioning in 2015/16. We demonstrate phase-tracking on stars as faint as m(K) approximate to 10 mag, phase-referenced interferometry of objects fainter than m(K) approximate to 15 mag with a limiting magnitude of m(K) approximate to 17 mag, minute long coherent integrations, a visibility accuracy of better than 0.25%, and spectro-differential phase and closure phase accuracy better than 0.5 degrees, corresponding to a differential astrometric precision of better than ten microarcseconds (as). The dual-beam astrometry, measuring the phase difference of two objects with laser metrology, is still under commissioning. First observations show residuals as low as 50 mu as when following objects over several months. We illustrate the instrument performance with the observations of archetypical objects for the different instrument modes. Examples include the Galactic center supermassive black hole and its fast orbiting star S2 for phase referenced dual-beam observations and infrared wavefront sensing, the high mass X-ray binary BP Cru and the active galactic nucleus of PDS 456 for a few mu as spectro-differential astrometry, the T Tauri star S CrA for a spectro-differential visibility analysis, xi Tel and 24 Cap for high accuracy visibility observations, and eta Car for interferometric imaging with GRAVITY.

Abstract