Power converter topologies for wind energy conversion systems: Integrated modeling, control strategy and performance simulation

This paper presents new integrated model for variable-speed wind energy conversion systems, considering a more accurate dynamic of the wind turbine, rotor, generator, power converter and filter. Pulse width modulation by space vector modulation associated with sliding mode is used for controlling the power converters. Also, power factor control is introduced at the output of the power converters. Comprehensive performance simulation studies are carried out with matrix, two-level and multilevel power converter topologies in order to adequately assert the system performance. Conclusions are duly drawn.

Simulation of offshore wind system with two-level converters: HVDC power transmission

A new integrated mathematical model for the simulation of offshore wind energy conversion system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using full-power two-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a high voltage DC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the structure and tower due to the need to emulate the effects of the moving surface. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistor of the converter. Finally, a case study is presented to access the system performance. �� 2014 IEEE.

A simulation of integrated photovoltaic conversion into electric grid

This paper presents a systemic modeling for a PV system integrated into an electric grid. The modeling includes models for a DC-DC boost converter and a DC-AC two-level inverter. Classical or fuzzy PI controllers with pulse width modulation by space vector modulation associated with sliding mode control is used for controlling the PV system and power factor control is introduced at the output of the system. Comprehensive performance simulation studies are carried out with the modeling of the DC-DC boost converter followed by a two-level power inverter in order to compare the performance with the experimental results obtained during in situ operation with three commercial inverters. Also, studies are carried out to assess the quality of the energy injected into the electric grid in terms of harmonic distortion. Finally, conclusions regarding the integration of the PV system into the electric grid are presented. (C) 2014 Elsevier Ltd. All rights reserved.

Simulation of offshore wind system with two levels converters: HVDC power transmission

A new integrated mathematical model for the simulation of offshore wind energy conversion system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using full-power two-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a high voltage DC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the structure and tower due to the need to emulate the effects of the moving surface. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistor of the converter. Finally, a case study is presented to access the system performance. �� 2014 IEEE.

Simulation of a-Si PV system grid connected by boost and inverter

This paper is about a PV system connected to the electric grid by power electronic converters, using classical PI controller. The modelling for the converters emulates the association of a DC-DC boost with a two-level power inverter (TwLI) or three-level power inverter (ThLI) in order to follow the performance of a testing experimental system. Pulse width modulation (PWMo) by sliding mode control (SMCo) associated with space vector modulation (SVMo) is applied to the boost and the inverter. The PV system is described by the five parameters equivalent circuit. Parameter identification and simulation studies are performed for comparison with the testing experimental system.

Simulation of a-Si PV system linked to the grid by DC boost and three-level inverter under cloud scope

This paper is about a PV system linked to the electric grid through power converters under cloud scope. The PV system is modeled by the five parameters equivalent circuit and a MPPT procedure is integrated into the modeling. The modeling for the converters models the association of a DC-DC boost with a three-level inverter. PI controllers are used with PWM by sliding mode control associated with space vector modulation controlling the booster and the inverter. A case study addresses a simulation to assess the performance of a PV system linked to the electric grid. Conclusions regarding the integration of the PV system into the electric grid are presented. �� IFIP International Federation for Information Processing 2015.

Agrupamento multi-orador

Actualmente tem-se observado um aumento do volume de sinais de fala em diversas aplica����es, que refor��am a necessidade de um processamento autom��tico dos ficheiros. No campo do processamento autom��tico destacam-se as aplica����es de ���diariza����o de orador���, que permitem catalogar os ficheiros de fala com a identidade de oradores e limites temporais de fala de cada um, atrav��s de um processo de segmenta����o e agrupamento. No contexto de agrupamento, este trabalho visa dar continuidade ao trabalho intitulado ���Detec����o do Orador���, com o desenvolvimento de um algoritmo de ���agrupamento multi-orador��� capaz de identificar e agrupar correctamente os oradores, sem conhecimento pr��vio do n��mero ou da identidade dos oradores presentes no ficheiro de fala. O sistema utiliza os coeficientes ���Mel Line Spectrum Frequencies��� (MLSF) como caracter��stica ac��stica de fala, uma segmenta����o de fala baseada na energia e uma estrutura do tipo ���Universal Background Model - Gaussian Mixture Model��� (UBM-GMM) adaptado com o classificador ���Support Vector Machine��� (SVM). No trabalho foram analisadas tr��s m��tricas de discrimina����o dos modelos SVM e a avalia����o dos resultados foi feita atrav��s da taxa de erro ���Speaker Error Rate��� (SER), que quantifica percentualmente o n��mero de segmentos ���fala��� mal classificados. O algoritmo implementado foi ajustado ��s caracter��sticas da l��ngua portuguesa atrav��s de um corpus com 14 ficheiros de treino e 30 ficheiros de teste. Os ficheiros de treino dos modelos e classifica����o final, enquanto os ficheiros de foram utilizados para avaliar o desempenho do algoritmo. A interac����o com o algoritmo foi dinamizada com a cria����o de uma interface gr��fica que permite receber o ficheiro de teste, process��-lo, listar os resultados ou gerar um v��deo para o utilizador confrontar o sinal de fala com os resultados de classifica����o.

Learning techniques for automatic email message tagging

A organiza����o autom��tica de mensagens de correio electr��nico �� um desafio actual na ��rea da aprendizagem autom��tica. O n��mero excessivo de mensagens afecta cada vez mais utilizadores, especialmente os que usam o correio electr��nico como ferramenta de comunica����o e trabalho. Esta tese aborda o problema da organiza����o autom��tica de mensagens de correio electr��nico propondo uma solu����o que tem como objectivo a etiquetagem autom��tica de mensagens. A etiquetagem autom��tica �� feita com recurso ��s pastas de correio electr��nico anteriormente criadas pelos utilizadores, tratando-as como etiquetas, e �� sugest��o de m��ltiplas etiquetas para cada mensagem (top-N). S��o estudadas v��rias t��cnicas de aprendizagem e os v��rios campos que comp��e uma mensagem de correio electr��nico s��o analisados de forma a determinar a sua adequa����o como elementos de classifica����o. O foco deste trabalho recai sobre os campos textuais (o assunto e o corpo das mensagens), estudando-se diferentes formas de representa����o, selec����o de caracter��sticas e algoritmos de classifica����o. �� ainda efectuada a avalia����o dos campos de participantes atrav��s de algoritmos de classifica����o que os representam usando o modelo vectorial ou como um grafo. Os v��rios campos s��o combinados para classifica����o utilizando a t��cnica de combina����o de classificadores Vota����o por Maioria. Os testes s��o efectuados com um subconjunto de mensagens de correio electr��nico da Enron e um conjunto de dados privados disponibilizados pelo Institute for Systems and Technologies of Information, Control and Communication (INSTICC). Estes conjuntos s��o analisados de forma a perceber as caracter��sticas dos dados. A avalia����o do sistema �� realizada atrav��s da percentagem de acerto dos classificadores. Os resultados obtidos apresentam melhorias significativas em compara����o com os trabalhos relacionados.

Receptor MIMO em FPGA baseado no esquema de Alamouti

A oferta de servi��os baseados em comunica����es sem fios tem vindo a crescer exponencialmente na ��ltima d��cada. Cada vez mais s��o exigidas maiores taxas de transmiss��o assim como uma melhor QoS, sem comprometer a pot��ncia de transmiss��o ou argura de banda dispon��vel. A tecnologia MIMO consegue oferecer um aumento da capacidade destes sistemas sem requerer aumento da largura de banda ou da pot��ncia transmitida. O trabalho desenvolvido nesta disserta����o consistiu no estudo dos sistemas MIMO, caracterizados pela utiliza����o de m��ltiplas antenas para transmitir e receber a informa����o. Com um sistema deste tipo consegue-se obter um ganho de diversidade espacial utilizando c��digos espa��o-temporais, que exploram simultaneamente o dom��nio espacial e o dom��nio do tempo. Nesta disserta����o �� dado especial ��nfase �� codifica����o por blocos no espa��o-tempo de Alamouti, a qual ser�� implementada em FPGA, nomeadamente a parte de recep����o. Esta implementa����o �� efectuada para uma configura����o de antenas 2x1, utilizando v��rgula flutuante e para tr��s tipos de modula����o: BPSK, QPSK e 16-QAM. Por fim ser�� analisada a rela����o entre a precis��o alcan��ada na representa����o num��rica dos resultados e os recursos consumidos pela FPGA. Com a arquitectura adoptada conseguem se obter taxas de transfer��ncia na ordem dos 29,141 Msimb/s (sem pipelines) a 262,674 Msimb/s (com pipelines), para a modula����o BPSK.

Dynamical behaviour on the parameter space: new populational growth models proportional to beta densities

We present new populational growth models, generalized logistic models which are proportional to beta densities with shape parameters p and 2, where p > 1, with Malthusian parameter r. The complex dynamical behaviour of these models is investigated in the parameter space (r, p), in terms of topological entropy, using explicit methods, when the Malthusian parameter r increases. This parameter space is split into different regions, according to the chaotic behaviour of the models.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Simulation of the Magnetic Induction Vector of a Magnetic Core to be Used in FFC NMR Relaxometry

This paper is a contribution for the assessment and comparison of magnet properties based on magnetic field characteristics particularly concerning the magnetic induction uniformity in the air gaps. For this aim, a solver was developed and implemented to determine the magnetic field of a magnetic core to be used in Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry. The electromagnetic field computation is based on a 2D finite-element method (FEM) using both the scalar and the vector potential formulation. Results for the magnetic field lines and the magnetic induction vector in the air gap are presented. The target magnetic induction is 0.2 T, which is a typical requirement of the FFC NMR technique, which can be achieved with a magnetic core based on permanent magnets or coils. In addition, this application requires high magnetic induction uniformity. To achieve this goal, a solution including superconducting pieces is analyzed. Results are compared with a different FEM program.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

Modulation of translation factor's gene expression by histone deacetylase inhibitors in breast cancer cells

The histone deacetylase inhibitors sodium butyrate (NaBu) and trichostatin A (TSA) exhibit anti-proliferative activity by causing cell cycle arrest and apoptosis. The mechanisms by which NaBu and TSA cause apoptosis and cell cycle arrest are not yet completely clarified, although these agents are known to modulate the expression of several genes including cell-cycle- and apoptosis-related genes. The enzymes involved in the process of translation have important roles in controlling cell growth and apoptosis, and several of these translation factors have been described as having a causal role in the development of cancer. The expression patterns of the translation mechanism, namely of the elongation factors eEF1A1 and eEF1A2, and of the termination factors eRF1 and eRF3, were studied in the breast cancer cell line MCF-7 by real-time quantitative reverse transcription-polymerase chain reaction after a 24-h treatment with NaBu and TSA. NaBu induced inhibition of translation factors' transcription, whereas TSA caused an increase in mRNA levels. Thus, these two agents may modulate the expression of translation factors through different pathways. We propose that the inhibition caused by NaBu may, in part, be responsible for the cell cycle arrest and apoptosis induced by this agent in MCF-7 cells.