Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Sistema de visão para aterragem automática de UAV

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Projecto de avaliação de interfaces – PAI

Para obtenção do grau de Doutor pela Universidade de Vigo com menção internacional Departamento de Informática

Add/drop filters based on SiC technology for optical interconnects

In this paper we demonstrate an add/drop filter based on SiC technology. Tailoring of the channel bandwidth and wavelength is experimentally demonstrated. The concept is extended to implement a 1 by 4 wavelength division multiplexer with channel separation in the visible range. The device consists of a p-i'(a-SiC:H)-n/p-i(a-Si: H)-n heterostructure. Several monochromatic pulsed lights, separately or in a polychromatic mixture illuminated the device. Independent tuning of each channel is performed by steady state violet bias superimposed either from the front and back sides. Results show that, front background enhances the light-to-dark sensitivity of the long and medium wavelength channels and quench strongly the others. Back violet background has the opposite behaviour. This nonlinearity provides the possibility for selective removal or addition of wavelengths. An optoelectronic model is presented and explains the light filtering properties of the add/drop filter, under different optical bias conditions.

Fractional-order impulse response of the respiratory system

This paper presents the measurement, frequency-response modeling and identification, and the corresponding impulse time response of the human respiratory impedance and admittance. The investigated adult patient groups were healthy, diagnosed with chronic obstructive pulmonary disease and kyphoscoliosis, respectively. The investigated children patient groups were healthy, diagnosed with asthma and cystic fibrosis, respectively. Fractional order (FO) models are identified on the measured impedance to quantify the respiratory mechanical properties. Two methods are presented for obtaining and simulating the time-domain impulse response from FO models of the respiratory admittance: (i) the classical pole-zero interpolation proposed by Oustaloup in the early 90s, and (ii) the inverse discrete Fourier Transform (DFT). The results of the identified FO models for the respiratory admittance are presented by means of their average values for each group of patients. Consequently, the impulse time response calculated from the frequency response of the averaged FO models is given by means of the two methods mentioned above. Our results indicate that both methods provide similar impulse response data. However, we suggest that the inverse DFT is a more suitable alternative to the high order transfer functions obtained using the classical Oustaloup filter. Additionally, a power law model is fitted on the impulse response data, emphasizing the intrinsic fractal dynamics of the respiratory system.

Tunnig optical A-Sic/A-Si active filters by UV bias light in the visible and infrared spectral ranges

Visible range to telecom band spectral translation is accomplished using an amorphous SiC pi'n/pin wavelength selector under appropriate front and back optical light bias. Results show that background intensity works as selectors in the infrared region, shifting the sensor sensitivity. Low intensities select the near-infrared range while high intensities select the visible part according to its wavelength. Here, the optical gain is very high in the infrared/red range, decreases in the green range, stays close to one in the blue region and strongly decreases in the near-UV range. The transfer characteristics effects due to changes in steady state light intensity and wavelength backgrounds are presented. The relationship between the optical inputs and the output signal is established. A capacitive optoelectronic model is presented and tested using the experimental results. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inverse dynamics based predictive control for unified power flow controllers without DC bus

This paper presents a new predictive digital control method applied to Matrix Converters (MC) operating as Unified Power Flow Controllers (UPFC). This control method, based on the inverse dynamics model equations of the MC operating as UPFC, just needs to compute the optimal control vector once in each control cycle, in contrast to direct dynamics predictive methods that needs 27 vector calculations. The theoretical principles of the inverse dynamics power flow predictive control of the MC based UPFC with input filter are established. The proposed inverse dynamics predictive power control method is tested using Matlab/Simulink Power Systems toolbox and the obtained results show that the designed power controllers guarantees decoupled active and reactive power control, zero error tracking, fast response times and an overall good dynamic and steady-state response.

Optical nonlinearity in Tandem SI-C photodetectors

The behavior of tandem pin heterojunctions based on a-SiC: H alloys is investigated under different optical and electrical bias conditions. The devices are optimized to act as optically selective wavelength filters. Depending on the device configuration (optical gaps, thickness, sequence of cells in the stack structure) and on the applied voltage (positive or negative) and optical bias (wavelength, intensity, frequency) it is possible to combine the wavelength discrimination function with the self amplification of the signal. This wavelength nonlinearity allows the amplification or the rejection of a weak signal-impulse. The device works as an active tunable optical filter for wavelength selection and can be used as an add/drop multiplexer (ADM) which enables data to enter and leave an optical network bit stream without having to demultiplex the stream. Results show that, even under weak transient input signals, the background wavelength controls the output signal. This nonlinearity, due to the transient asymmetrical light penetration of the input channels across the device together with the modification on the electrical field profile due to the optical bias, allows tuning an input channel without demultiplexing the stream. This high optical nonlinearity makes the optimized devices attractive for the amplification of all optical signals. Transfer characteristics effects due to changes in steady state light, control d.c. voltage and applied light pulses are presented. Based on the experimental results and device configuration an optoelectronic model is developed. The transfer characteristics effects due to changes in steady state light, dc control voltage or applied light pulses are simulated and compared with the experimental data. A good agreement was achieved.

Urban land use change analysis and modelling: a case study of Setubal-Sesimbra, Portugal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Towards a Mobile Three-dimensional Modelling System for Underground Structures

Robotica 2012: 12th International Conference on Autonomous Robot Systems and Competitions April 11, 2012, Guimarães, Portugal

Formation Control Driven by Cooperative Object Tracking

In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Three transducers for one photodetector: essays for optical communications

Dissertation presented to obtain the PhD degree in Electrical and Computer Engineering - Electronics

Conceção e Análise de um Demonstrador para a Monitorização Estrutural

Os sistemas de monitorização de estruturas fornecem diversas vantagens, não só no que diz respeito à durabilidade da obra, ao aumento da segurança e do conhecimento relativamente ao comportamento das estruturas ao longo do tempo, à otimização do aspeto estrutural, bem como aos aspetos económicos do processo de construção e manutenção. A monitorização deve realizar-se durante a fase de construção e/ou de exploração da obra para permitir o registo integral do seu comportamento no meio externo. Deve efetuar-se de forma contínua e automática, executando intervenções de rotina para que se possa detetar precocemente sinais de alterações, respetivamente à segurança, integridade e desempenho funcional. Assim se poderá manter a estrutura dentro de parâmetros aceitáveis de segurança. Assim, na presente dissertação será concebido um demonstrador experimental, para ser estudado em laboratório, no qual será implementado um sistema de monitorização contínuo e automático. Sobre este demonstrador será feita uma análise de diferentes grandezas em medição, tais como: deslocamentos, extensões, temperatura, rotações e acelerações. Com carácter inovador, pretende-se ainda incluir neste modelo em sintonia de medição de coordenadas GNSS com o qual se torna possível medir deslocamentos absolutos. Os resultados experimentais alcançados serão analisados e comparados com modelos numéricos. Conferem-se os resultados experimentais de natureza estática e dinâmica, com os resultados numéricos de dois modelos de elementos finitos: um de barras e outro de casca. Realizaram-se diferentes abordagens tendo em conta as características identificadas por via experimental e calculadas nos modelos numéricos para melhor ajuste e calibração dos modelos numéricos Por fim, recorre-se a algoritmos de processamento e tratamento do respetivo sinal com aplicação de filtros, que revelam melhorar com rigor o sinal, de forma a potenciar as técnicas de fusão multisensor. Pretende-se integrar o sinal GNSS com os demais sensores presentes no sistema de monitorização. As técnicas de fusão multisensor visam melhor o desempenho deste potencial sistema de medição, demonstrando as suas valências no domínio da monitorização estrutural.