Showing papers by "Polytechnic University of Catalonia published in 2009"

A Review of the State of the Art of Power Electronics for Wind Turbines

Abstract: This paper reviews the power electronic applications for wind energy systems. Various wind turbine systems with different generators and power electronic converters are described, and different technical features are compared. The electrical topologies of wind farms with different wind turbines are summarized and the possible uses of power electronic converters with wind farms are shown. Finally, the possible methods of using the power electronic technology for improving wind turbine performance in power systems to meet the main grid connection requirements are discussed.

The Hysteresis Bouc-Wen Model, a Survey

Abstract: Structural systems often show nonlinear behavior under severe excitations generated by natural hazards. In that condition, the restoring force becomes highly nonlinear showing significant hysteresis. The hereditary nature of this nonlinear restoring force indicates that the force cannot be described as a function of the instantaneous displacement and velocity. Accordingly, many hysteretic restoring force models were developed to include the time dependent nature using a set of differential equations. This survey contains a review of the past, recent developments and implementations of the Bouc-Wen model which is used extensively in modeling the hysteresis phenomenon in the dynamically excited nonlinear structures.

New ensemble methods for evolving data streams

Abstract: Advanced analysis of data streams is quickly becoming a key area of data mining research as the number of applications demanding such processing increases. Online mining when such data streams evolve over time, that is when concepts drift or change completely, is becoming one of the core issues. When tackling non-stationary concepts, ensembles of classifiers have several advantages over single classifier methods: they are easy to scale and parallelize, they can adapt to change quickly by pruning under-performing parts of the ensemble, and they therefore usually also generate more accurate concept descriptions. This paper proposes a new experimental data stream framework for studying concept drift, and two new variants of Bagging: ADWIN Bagging and Adaptive-Size Hoeffding Tree (ASHT) Bagging. Using the new experimental framework, an evaluation study on synthetic and real-world datasets comprising up to ten million examples shows that the new ensemble methods perform very well compared to several known methods.

Regulated Fluctuations in Nanog Expression Mediate Cell Fate Decisions in Embryonic Stem Cells

Abstract: There is evidence that pluripotency of mouse embryonic stem (ES) cells is associated with the activity of a network of transcription factors with Sox2, Oct4, and Nanog at the core. Using fluorescent reporters for the expression of Nanog, we observed that a population of ES cells is best described by a dynamic distribution of Nanog expression characterized by two peaks defined by high (HN) and low (LN) Nanog expression. Typically, the LN state is 5%–20% of the total population, depending on the culture conditions. Modelling of the activity of Nanog reveals that a simple network of Oct4/Sox2 and Nanog activity can account for the observed distribution and its properties as long as the transcriptional activity is tuned by transcriptional noise. The model also predicts that the LN state is unstable, something that is born out experimentally. While in this state, cells can differentiate. We suggest that transcriptional fluctuations in Nanog expression are an essential element of the pluripotent state and that the function of Sox2, Oct4, and Nanog is to act as a network that promotes and maintains transcriptional noise to interfere with the differentiation signals.

Horizontal visibility graphs: Exact results for random time series

Abstract: networks. This procedure allows us to apply methods of complex network theory for characterizing time series. In this work we present the horizontal visibility algorithm, a geometrically simpler and analytically solvable version of our former algorithm, focusing on the mapping of random series series of independent identically distributed random variables. After presenting some properties of the algorithm, we present exact results on the topological properties of graphs associated with random series, namely, the degree distribution, the clustering coefficient, and the mean path length. We show that the horizontal visibility algorithm stands as a simple method to discriminate randomness in time series since any random series maps to a graph with an exponential degree distribution of the shape Pk=1 /32 /3 k2 , independent of the probability distribution from which the series was generated. Accordingly, visibility graphs with other Pk are related to nonrandom series. Numerical simulations confirm the accuracy of the theorems for finite series. In a second part, we show that the method is able to distinguish chaotic series from independent and identically distributed i.i.d. theory, studying the following situations: i noise-free low-dimensional chaotic series, ii low-dimensional noisy chaotic series, even in the presence of large amounts of noise, and iii high-dimensional chaotic series coupled map lattice, without needs for additional techniques such as surrogate data or noise reduction methods. Finally, heuristic arguments are given to explain the topological properties of chaotic series, and several sequences that are conjectured to be random are analyzed.

The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages

Abstract: For the 11th straight year, the Conference on Computational Natural Language Learning has been accompanied by a shared task whose purpose is to promote natural language processing applications and evaluate them in a standard setting. In 2009, the shared task was dedicated to the joint parsing of syntactic and semantic dependencies in multiple languages. This shared task combines the shared tasks of the previous five years under a unique dependency-based formalism similar to the 2008 task. In this paper, we define the shared task, describe how the data sets were created and show their quantitative properties, report the results and summarize the approaches of the participating systems.

Methods derived from nonlinear dynamics for analysing heart rate variability

Abstract: Methods from nonlinear dynamics (NLD) have shown new insights into heart rate (HR) variability changes under various physiological and pathological conditions, providing additional prognostic information and complementing traditional time- and frequency-domain analyses. In this review, some of the most prominent indices of nonlinear and fractal dynamics are summarized and their algorithmic implementations and applications in clinical trials are discussed. Several of those indices have been proven to be of diagnostic relevance or have contributed to risk stratification. In particular, techniques based on mono- and multifractal analyses and symbolic dynamics have been successfully applied to clinical studies. Further advances in HR variability analysis are expected through multidimensional and multivariate assessments. Today, the question is no longer about whether or not methods from NLD should be applied; however, it is relevant to ask which of the methods should be selected and under which basic and standardized conditions should they be applied.

Quantitative benchmark computations of two-dimensional bubble dynamics

Abstract: Benchmark configurations for quantitative validation and comparison of incompressible interfacial flow codes, which model two-dimensional bubbles rising in liquid columns, are proposed. The benchmark quantities: circularity, center of mass, and mean rise velocity are defined and measured to monitor convergence toward a reference solution. Comprehensive studies are undertaken by three independent research groups, two representing Eulerian level set finite-element codes and one representing an arbitrary Lagrangian-Eulerian moving grid approach.

Positive solutions of nonlinear problems involving the square root of the Laplacian

Abstract: We consider nonlinear elliptic problems involving a nonlocal operator: the square root of the Laplacian in a bounded domain with zero Dirichlet boundary conditions. For positive solutions to problems with power nonlinearities, we establish existence and regularity results, as well as a priori estimates of Gidas-Spruck type. In addition, among other results, we prove a symmetry theorem of Gidas-Ni-Nirenberg type.

Elastic bending modulus of monolayer graphene

Abstract: An analytic formula is derived for the elastic bending modulus of monolayer graphene based on an empirical potential for solid-state carbon atoms. Two physical origins are identified for the non-vanishing bending stiffness of the atomically thin graphene sheet, one due to the bond-angle effect and the other resulting from the bond-order term associated with the dihedral angles. The analytical prediction compares closely with ab initio energy calculations. Pure bending of graphene monolayers into cylindrical tubes is simulated by a molecular mechanics approach, showing slight nonlinearity and anisotropy in the tangent bending modulus as the bending curvature increases. An intrinsic coupling between bending and in-plane strain is noted for graphene monolayers rolled into carbon nanotubes. (Some figures in this article are in colour only in the electronic version)

Adaptive Learning from Evolving Data Streams

Abstract: We propose and illustrate a method for developing algorithms that can adaptively learn from data streams that drift over time. As an example, we take Hoeffding Tree, an incremental decision tree inducer for data streams, and use as a basis it to build two new methods that can deal with distribution and concept drift: a sliding window-based algorithm, Hoeffding Window Tree, and an adaptive method, Hoeffding Adaptive Tree. Our methods are based on using change detectors and estimator modules at the right places; we choose implementations with theoretical guarantees in order to extend such guarantees to the resulting adaptive learning algorithm. A main advantage of our methods is that they require no guess about how fast or how often the stream will drift; other methods typically have several user-defined parameters to this effect. In our experiments, the new methods never do worse, and in some cases do much better, than CVFDT, a well-known method for tree induction on data streams with drift.

Effects of artificial micro- and nano-structured surfaces on cell behaviour.

Abstract: Substrate topography, independently of substrate chemistry, has been reported to have significant effects on cell behaviour. Based on the use of fabrication techniques developed by the silicon microtechnology industry, numerous studies can now be found in the literature analyzing cell behaviour as to various micro- and nano-features such as lines, wells, holes and more. Most of these works have been found to relate the micro- and nano-sized topographical features with cell orientation, migration, morphology and proliferation. In recent papers, even the influence of substrate nanotopography on cell gene expression and differentiation has been pointed out. However, despite the large number of papers published on this topic, significant general trends in cell behaviour are difficult to establish due to differences in cell type, substrate material, feature aspect-ratio, feature geometry and parameters measured. This paper intends to compile and review the relevant existing information on the behaviour of cells on micro- and nano-structured artificial substrates and analyze possible general behavioural trends.

Control Strategies Based on Symmetrical Components for Grid-Connected Converters Under Voltage Dips

Abstract: Low-voltage ride-through (LVRT) requirements demand wind-power plants to remain connected to the network in presence of grid-voltage dips. Most dips present positive-, negative-, and zero-sequence components. Hence, regulators based on symmetrical components are well suited to control grid-connected converters. A neutral-point-clamped topology has been considered as an active front end of a distributed power-generation system, following the trend of increasing power and voltage levels in wind-power systems. Three different current controllers based on symmetrical components and linear quadratic regulator have been considered. The performance of each controller is evaluated on LVRT requirement fulfillment, grid-current balancing, maximum grid-current value control, and oscillating power flow. Simulation and experimental results show that all three controllers meet LVRT requirements, although different system performance is found for each control approach. Therefore, controller selection depends on the system constraints and the type of preferred performance features.

The visibility graph: A new method for estimating the Hurst exponent of fractional Brownian motion

Abstract: Fractional Brownian motion (fBm) has been used as a theoretical framework to study real-time series appearing in diverse scientific fields. Because of its intrinsic nonstationarity and long-range dependence, its characterization via the Hurst parameter, H, requires sophisticated techniques that often yield ambiguous results. In this work we show that fBm series map into a scale-free visibility graph whose degree distribution is a function of H. Concretely, it is shown that the exponent of the power law degree distribution depends linearly on H. This also applies to fractional Gaussian noises (fGn) and generic f−β noises. Taking advantage of these facts, we propose a brand new methodology to quantify long-range dependence in these series. Its reliability is confirmed with extensive numerical simulations and analytical developments. Finally, we illustrate this method quantifying the persistent behavior of human gait dynamics.

Hardware support for WCET analysis of hard real-time multicore systems

Abstract: The increasing demand for new functionalities in current and future hard real-time embedded systems like automotive, avionics and space industries is driving an increase in the performance required in embedded processors. Multicore processors represent a good design solution for such systems due to their high performance, low cost and power consumption characteristics. However, hard real-time embedded systems require time analyzability and current multicore processors are less analyzable than single-core processors due to the interferences between different tasks when accessing shared hardware resources. In this paper we propose a multicore architecture with shared resources that allows the execution of applications with hard real-time and non hard real-time constraints at the same time, providing time analizability for the hard real-time tasks so that they can meet their deadlines. Moreover our architecture proposal provides high-performance for the non hard real-time tasks.

Modeling of a variable speed wind turbine with a Permanent Magnet Synchronous Generator

Abstract: The aim of this work is to analyze a typical configuration of a Wind Turbine Generator System (WTGS) equipped with a Variable Speed Generator. Nowadays, doubly-fed induction generators are being widely used on WTGS, although synchronous generators are being extensively utilized too. There are different types of synchronous generators, but the multi-pole Permanent Magnet Synchronous Generator (PMSG) is chosen in order to obtain its model. It offers better performance due to higher efficiency and less maintenance since it does not have rotor current and can be used without a gearbox, which also implies a reduction of the weight of the nacelle and a reduction of costs. Apart from the generator, the analyzed WTGS consists of another three parts: wind speed, wind turbine and drive train. These elements have been modeled and the equations that explain their behavior have been introduced. What is more, the whole WTGS has been implemented in MATLAB/Simulink interface. Moreover, the concept of the Maximum Power Point Tracking (MPPT) has been presented in terms of the adjustment of the generator rotor speed according to instantaneous wind speed.

Podcasting: A new technological tool to facilitate good practice in higher education

Abstract: The literature has frequently highlighted the usefulness of podcasting in higher education; however, there is an important gap between the theory on good practice in higher education and empirical studies about podcasting. With this in mind, we carried out an empirical study on an undergraduate degree course in Information Systems Management. The study consisted of the creation and broadcast of 13 podcasts, distributed over four months in which ninety distance students took part. The analysis follows the suggestions proposed in previous literature about the evaluation of technologies in a university learning environment. The findings, discussed within the framework of principles for good practice in higher education, suggest some interesting issues in distance courses, such as: (1) podcasting is a powerful tool as a complement to the traditional resources on a course, but not a substitute for them; (2) the characteristics of podcasting increase the impression of permanent contact between students and teachers, increasing students' motivation; (3) the use of podcasting allows for a diverse range of student skills and learning methods. Other secondary findings are discussed and some suggestions for future research are proposed at the end of this paper.

Nanofaceted Pd ? O Sites in Pd ? Ce Surface Superstructures: Enhanced Activity in Catalytic Combustion of Methane

Abstract: An open superstructure: A Pd/CeO2 catalyst prepared by solution combustion synthesis is three to five times more active for CH4 combustion than the best conventional palladium-based systems. The catalyst contains an ordered, stable Pd-O-Ce surface superstructure (see picture; cyan arrow is a square-planar Pd site, red arrow is an undercoordinated O atom) and is an example of ultra-highly dispersed, stable PdO within an oxide carrier.

Position Tracking for Non-linear Teleoperators with Variable Time Delay

Abstract: In this paper the problem of position tracking in the presence of variable time delay is studied. It is proved that simple P-like and PD-like controllers can stabilize the teleoperator under variable time delays and, moreover, they provide position tracking. Then, a controller based on the scattering transformation that also provides position tracking is proposed. In this paper we present the conditions under which the velocities and position error of the non-linear teleoperator, for the three controllers, are bounded, and if the human does not move the local manipulator and the remote manipulator does not interact with the environment, then it is proved that velocities and position error converge to zero. Simulations and real experiments, using the Internet from Urbana-Champaign (USA) to Barcelona (Spain), validate the proposed schemes.

REAL—Ensemble radar precipitation estimation for hydrology in a mountainous region

Abstract: An elegant solution to characterise the residual errors in radar precipitation estimates is to generate an ensemble of precipitation fields. The paper proposes a radar ensemble generator designed for usage in the Alps using LU decomposition (REAL), and presents first results from a real-time implementation coupling the radar ensemble with a semi-distributed rainfall-runoff model for flash flood modelling in a steep Alpine catchment. Each member of the radar ensemble is a possible realisation of the unknown true precipitation field given the observed radar field and knowledge of the space-time error structure of radar precipitation estimates. Feeding the alternative realisations into a hydrological model yields a distribution of response values, the spread of which represents the sensitivity of runoff to uncertainties in the input radar precipitation field. The presented ensemble generator is based on singular value decomposition of the error covariance matrix, stochastic simulation using the LU decomposition algorithm, and autoregressive filtering. It allows full representation of spatial dependence of the mean and covariances of radar errors. This is of particular importance in a mountainous region with large uncertainty in radar precipitation estimates and strong dependence of error structure on location. The real-time implementation of the radar ensemble generator coupled with a semi-distributed hydrological model in the framework of the forecast demonstration project MAP D-PHASE is one of the first experiments of this type worldwide, and is a fully novel contribution to this evolving area of applied research. Copyright c ! 2009 Royal Meteorological Society

Soliton Shape and Mobility Control in Optical Lattices

Abstract: We present a progress overview focused on the recent theoretical and experimental advances in the area of soliton manipulation in optical lattices Optical lattices offer the possibility to engineer and to control the diffraction of light beams in media with periodically-modulated optical properties, to manage the corresponding reflection and transmission bands, and to form specially designed defects Consequently, they afford the existence of a rich variety of new families of nonlinear stationary waves and solitons, lead to new rich dynamical phenomena, and offer novel conceptual opportunities for all-optical shaping, switching and routing of optical signals encoded in soliton formats In this overview, we consider reconfigurable optically-induced lattices as well as waveguide arrays made in suitable nonlinear materials We address both, one-dimensional and multi-dimensional geometries We specially target the new possibilities made possible by optical lattices induced by a variety of existing nondiffracting light patterns, we address nonlinear lattices and soliton arrays, and we briefly explore the unique features exhibited by light propagation in defect modes and in random lattices, an area of current topical interest and of potential cross-disciplinary impact