Frequency support characteristics of grid-interactive power converters based on the synchronous power controller

Grid-interactive converters with primary frequency control and inertia emulation have emerged and are promising for future renewable generation plants because of the contribution in power system stabilization. This paper gives a synchronous active power control solution for gridinteractive converters , as a way to emulate synchronous generators for inerita characteristics and load sharing. As design considerations, the virtual angle stability and transient response are both analyzed, and the detailed implementation structure is also given without entailing any difficulty in practice. The analytical and experimental validation of frequency support characteristics differentiates the work from other publications on generator emulation control. The 10 kW simulation and experimental frequency sweep tests on a regenerative source test bed present good performance of the proposed control in showing inertia and droop characteristics, as well as the controllable transient response.Peer ReviewedPostprint (author's final draft

Provision of public goods and violent conflict: Evidence from Colombia

The Colombian conflict has lasted for around 50 years. It has been fueled by the financial opportunities coming from production and traffic of illegal drugs, and predation of other natural resources. In such a context it is not clear what policies are more effective to reduce conflict. Two public policies that are frequently mentioned as effective to reduce conflict are investments in roads and education. However, a priori, both investments in roads and education may either increase or reduce conflict. After controlling for possible problems of endogeneity, we show that increases in roads provision reduces conflict while education does not. Because this is robust to controlling for measures of state capacity and governance, and the opportunity cost of conflict, our results are likely to be explained by the relative mobility of education and roads. Policies that increase roads provision might help to fight against the intensity of conflict. © 2014 by Walter de Gruyter Berlin Boston 2014

A neural network for semantic labelling of structured information

Intelligent systems rely on rich sources of information to make informed decisions. Using information from external sources requires establishing correspondences between the information and known information classes. This can be achieved with semantic labelling, which assigns known labels to structured information by classifying it according to computed features. The existing proposals have explored different sets of features, without focusing on what classification techniques are used. In this paper we present three contributions: first, insights on architectural issues that arise when using neural networks for semantic labelling; second, a novel implementation of semantic labelling that uses a state-of-the-art neural network classifier which achieves significantly better results than other four traditional classifiers; third, a comparison of the results obtained by the former network when using different subsets of features, comparing textual features to structural ones, and domain-dependent features to domain-independent ones. The experiments were carried away with datasets from three real world sources. Our results show that there is a need to develop more semantic labelling proposals with sophisticated classification techniques and large features catalogues.Ministerio de Economía y Competitividad TIN2016-75394-

TAPON: a two-phase machine learning approach for semantic labelling

Through semantic labelling we enrich structured information from sources such as HTML pages, tables, or JSON files, with labels to integrate it into a local ontology. This process involves measuring some features of the information and then nding the classes that best describe it. The problem with current techniques is that they do not model relationships between classes. Their features fall short when some classes have very similar structures or textual formats. In order to deal with this problem, we have devised TAPON: a new semantic labelling technique that computes novel features that take into account the relationships. TAPON computes these features by means of a two-phase approach. In the first phase, we compute simple features and obtain a preliminary set of labels (hints). In the second phase, we inject our novel features and obtain a refined set of labels. Our experimental results show that our technique, thanks to our rich feature catalogue and novel modelling, achieves higher accuracy than other state-of-the-art techniques.Ministerio de Economía y Competitividad TIN2016-75394-

Emergent behaviors in the Internet of things: The ultimate ultra-large-scale system

To reach its potential, the Internet of Things (IoT) must break down the silos that limit applications' interoperability and hinder their manageability. Doing so leads to the building of ultra-large-scale systems (ULSS) in several areas, including autonomous vehicles, smart cities, and smart grids. The scope of ULSS is both large and complex. Thus, the authors propose Hierarchical Emergent Behaviors (HEB), a paradigm that builds on the concepts of emergent behavior and hierarchical organization. Rather than explicitly programming all possible decisions in the vast space of ULSS scenarios, HEB relies on the emergent behaviors induced by local rules at each level of the hierarchy. The authors discuss the modifications to classical IoT architectures required by HEB, as well as the new challenges. They also illustrate the HEB concepts in reference to autonomous vehicles. This use case paves the way to the discussion of new lines of research.Damian Roca work was supported by a Doctoral Scholarship provided by Fundación La Caixa. This work has been supported by the Spanish Government (Severo Ochoa grants SEV2015-0493) and by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P).Peer ReviewedPostprint (author's final draft

AYNEC: All you need for evaluating completion techniques in knowledge graphs

The popularity of knowledge graphs has led to the development of techniques to refine them and increase their quality. One of the main refinement tasks is completion (also known as link prediction for knowledge graphs), which seeks to add missing triples to the graph, usually by classifying potential ones as true or false. While there is a wide variety of graph completion techniques, there is no standard evaluation setup, so each proposal is evaluated using different datasets and metrics. In this paper we present AYNEC, a suite for the evaluation of knowledge graph completion techniques that covers the entire evaluation workflow. It includes a customisable tool for the generation of datasets with multiple variation points related to the preprocessing of graphs, the splitting into training and testing examples, and the generation of negative examples. AYNEC also provides a visual summary of the graph and the optional exportation of the datasets in an open format for their visualisation. We use AYNEC to generate a library of datasets ready to use for evaluation purposes based on several popular knowledge graphs. Finally, it includes a tool that computes relevant metrics and uses significance tests to compare each pair of techniques. These open source tools, along with the datasets, are freely available to the research community and will be maintained.Ministerio de Economía y Competitividad TIN2016-75394-

Dynamics estimation and generalized tuning of stationary frame current controller for grid-tied power converters

The integration of AC-DC power converters to manage the connection of generation to the grid has increased exponentially over the last years. PV or wind generation plants are one of the main applications showing this trend. High power converters are increasingly installed for integrating the renewables in a larger scale. The control design for these converters becomes more challenging due to the reduced control bandwidth and increased complexity in the grid connection filter. A generalized and optimized control tuning approach for converters becomes more favored. This paper proposes an algorithm for estimating the dynamic performance of the stationary frame current controllers, and based on it a generalized and optimized tuning approach is developed. The experience-based specifications of the tuning inputs are not necessary through the tuning approach. Simulation and experimental results in different scenarios are shown to evaluate the proposal.Peer ReviewedPostprint (published version

Quantifying the benefits of SPECint distant parallelism in simultaneous multithreading architectures

We exploit the existence of distant parallelism that future compilers could detect and characterise its performance under simultaneous multithreading architectures. By distant parallelism we mean parallelism that cannot be captured by the processor instruction window and that can produce threads suitable for parallel execution in a multithreaded processor. We show that distant parallelism can make feasible wider issue processors by providing more instructions from the distant threads, thus better exploiting the resources from the processor in the case of speeding up single integer applications. We also investigate the necessity of out-of-order processors in the presence of multiple threads of the same program. It is important to notice at this point that the benefits described are totally orthogonal to any other architectural techniques targeting a single thread.Peer ReviewedPostprint (published version

Alternative implementations of Monte Carlo EM algorithms for likelihood inferences

Two methods of computing Monte Carlo estimators of variance components using restricted maximum likelihood via the expectation-maximisation algorithm are reviewed. A third approach is suggested and the performance of the methods is compared using simulated data

Longitudinal chromatic aberration of the human eye in the visible and near infrared from wavefront sensing, double-pass and psychophysics

15 págs.; 7 figs.; 1 tab.; OCIS codes: (260.0260) Physical optics; (330.0330) Vision, color, and visual optics; (330.4875) Optics of physiological systems; (330.5370) Physiological optics; (220.1010) Aberrations (global); (220.1080) Active or adaptive optics.© 2015 Optical Society of America. Longitudinal Chromatic Aberration (LCA) influences the optical quality of the eye. However, the reported LCA varies across studies, likely associated to differences in the measurement techniques. We present LCA measured in subjects using wavefront sensing, double-pass retinal images, and psychophysical methods with a custom-developed polychromatic Adaptive Optics system in a wide spectral range (450-950 nm), with control of subjects’ natural aberrations. LCA measured psychophysically was significantly higher than that from reflectometric techniques (1.51 D vs 1.00 D in the 488-700 nm range). Ours results indicate that the presence of natural aberrations is not the cause for the discrepancies across techniques.This research has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP/2007-2013) / ERC Grant Agreement. [ERC-2011- AdC 294099]. This study was also supported by Spanish Government grant FIS2011-25637 to SM, CSIC JAE-Pre programs & MICINN FPU Predoctoral Fellowship to MV, and CSIC JAE-Tec program to DC.Peer Reviewe