Speaker recognition improvement using blind inversion of distortions

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone.

EEG Windowed statitical wavelet deviation for estimation of muscular artifacts

Electroencephalographic (EEG) recordings are, most of the times, corrupted by spurious artifacts, which should be rejected or cleaned by the practitioner. As human scalp EEG screening is error-prone, automatic artifact detection is an issue of capital importance, to ensure objective and reliable results. In this paper we propose a new approach for discrimination of muscular activity in the human scalp quantitative EEG (QEEG), based on the time-frequency shape analysis. The impact of the muscular activity on the EEG can be evaluated from this methodology. We present an application of this scoring as a preprocessing step for EEG signal analysis, in order to evaluate the amount of muscular activity for two set of EEG recordings for dementia patients with early stage of Alzheimer’s disease and control age-matched subjects.

Nonlinear prediction based on score function

The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.

Combined T2 -preparation and two-dimensional pencil-beam inner volume selection.

PURPOSE: To improve coronary magnetic resonance angiography (MRA) by combining a two-dimensional (2D) spatially selective radiofrequency (RF) pulse with a T2 -preparation module ("2D-T2 -Prep"). METHODS: An adiabatic T2 -Prep was modified so that the first and last pulses were of differing spatial selectivity. The first RF pulse was replaced by a 2D pulse, such that a pencil-beam volume is excited. The last RF pulse remains nonselective, thus restoring the T2 -prepared pencil-beam, while tipping the (formerly longitudinal) magnetization outside of the pencil-beam into the transverse plane, where it is then spoiled. Thus, only a cylinder of T2 -prepared tissue remains for imaging. Numerical simulations were followed by phantom validation and in vivo coronary MRA, where the technique was quantitatively evaluated. Reduced field-of-view (rFoV) images were similarly studied. RESULTS: In vivo, full field-of-view 2D-T2 -Prep significantly improved vessel sharpness as compared to conventional T2 -Prep, without adversely affecting signal-to-noise (SNR) or contrast-to-noise ratios (CNR). It also reduced respiratory motion artifacts. In rFoV images, the SNR, CNR, and vessel sharpness decreased, although scan time reduction was 60%. CONCLUSION: When compared with conventional T2 -Prep, the 2D-T2 -Prep improves vessel sharpness and decreases respiratory ghosting while preserving both SNR and CNR. It may also acquire rFoV images for accelerated data acquisition.

Population ageing and ICT: An exploratory review of technology innovation trough digital applications

The multidimensional process of physical, psychological, and social change produced by population ageing affects not only the quality of life of elderly people but also of our societies. Some dimensions of population ageing grow and expand over time (e.g. knowledge of the world events, or experience in particular situations), while others decline (e.g. reaction time, physical and psychological strength, or other functional abilities like reduced speed and tiredness). Information and Communication Technologies (ICTs) can help elderly to overcome possible limitations due to ageing. As a particular case, biometrics can allow the development of new algorithms for early detection of cognitive impairments, by processing continuous speech, handwriting or other challenged abilities. Among all possibilities, digital applications (Apps) for mobile phones or tablets can allow the dissemination of such tools. In this article, after presenting and discussing the process of population ageing and its social implications, we explore how ICTs through different Apps can lead to new solutions for facing this major demographic challenge.

Structured sparsity through reweighting and application to diffusion MRI

We consider the problem of multiple correlated sparse signals reconstruction and propose a new implementation of structured sparsity through a reweighting scheme. We present a particular application for diffusion Magnetic Resonance Imaging data and show how this procedure can be used for fibre orientation reconstruction in the white matter of the brain. In that framework, our structured sparsity prior can be used to exploit the fundamental coherence between fibre directions in neighbour voxels. Our method approaches the ℓ0 minimisation through a reweighted ℓ1-minimisation scheme. The weights are here defined in such a way to promote correlated sparsity between neighbour signals.

Virtalähdejärjestelmän ohjauksen suunnittelu

Virtalähdejärjestelmä koostuu itsenäisesti toimivista virtalähdeyksiköistä. Virtalähdeyksiköt ovat rinnankytketty syöttämään virtaa kuormaan. Tämä diplomityö käsittelee virtalähdeyksiköiden ohjaamiseen liittyviä ongelmia ja ratkaisuja. Työssä suunnitellaan virtalähdejärjestelmän ohjauselektroniikkaa sekä mikrokontrollerin ohjelmakoodia. Lisäksi kehitetään ratkaisuja virtalähteen hallintaan ja automaattiseen ohjaukseen. Huomiota kiinnitetään vikasietoisuuteen ja käyttäjäystävällisyyteen.

Secure logarithmic audio watermarking scheme based on the human auditory system

Peer-reviewed

Fourier self-deconvolution in coherent anti-Stokes Raman scattering spectrum analysis

Coherent anti-Stokes Raman scattering (CARS) microscopy is rapidly developing into a unique microscopic tool in biophysics, biology and the material sciences. The nonlinear nature of CARS spectroscopy complicates the analysis of the received spectra. There were developed mathematical methods for signal processing and for calculations spectra. Fourier self-deconvolution is a special high pass FFT filter which synthetically narrows the effective trace bandwidth features. As Fourier self-deconvolution can effectively reduce the noise, which may be at a higher spatial frequency than the peaks, without losing peak resolution. The idea of the work is to experiment the possibility of using wavelet decomposition in spectroscopic for background and noise removal, and Fourier transformation for linenarrowing.

Resina de Protium heptaphyllum: isolamento, caracterização estrutural e avaliação das propriedades térmicas

Three mixtures of triterpenes (maniladiol and breine; alpha and beta-amyrin; lupenone, alpha and beta-amyrinone) were isolated from Protium heptaphyllum March resin. The structural identification was based on NMR and mass spectrometry data. Lupenone, and alpha and beta-amyrinone were not reported before as constituents of this resin. The resin was submitted to methylation and acetylation reactions. The pure and derivatized resins and the mixtures (maniladiol and breine; alpha and beta-amyrin) were analyzed by TG and DSC. The TG curves revealed that the derivatization decreases the thermal stability of the resin. The DSC curves showed peaks that can be assigned to evaporation and phase transitions processes.

A Preliminary Review of Behavioural Biometrics for Health Monitoring in the Elderly

This article explores the potential of ICT-based biometrics for monitoring the health status of the elderly people. It departs from specific ageing and biometric traits to then focus on behavioural biometric traits like handwriting, speech and gait to finally explore their practical application in health monitoring of elderly.

Salient Pole Synchronous Machine Modelling in an Industrial Direct Torque Controlled Drive Application

Synchronous motors are used mainly in large drives, for example in ship propulsion systems and in steel factories' rolling mills because of their high efficiency, high overload capacity and good performance in the field weakening range. This, however, requires an extremely good torque control system. A fast torque response and a torque accuracy are basic requirements for such a drive. For large power, high dynamic performance drives the commonly known principle of field oriented vector control has been used solely hitherto, but nowadays it is not the only way to implement such a drive. A new control method Direct Torque Control (DTC) has also emerged. The performance of such a high quality torque control as DTC in dynamically demanding industrial applications is mainly based on the accurate estimate of the various flux linkages' space vectors. Nowadays industrial motor control systems are real time applications with restricted calculation capacity. At the same time the control system requires a simple, fast calculable and reasonably accurate motor model. In this work a method to handle these problems in a Direct Torque Controlled (DTC) salient pole synchronous motor drive is proposed. A motor model which combines the induction law based "voltage model" and motor inductance parameters based "current model" is presented. The voltage model operates as a main model and is calculated at a very fast sampling rate (for example 40 kHz). The stator flux linkage calculated via integration from the stator voltages is corrected using the stator flux linkage computed from the current model. The current model acts as a supervisor that prevents only the motor stator flux linkage from drifting erroneous during longer time intervals. At very low speeds the role of the current model is emphasised but, nevertheless, the voltage model always stays the main model. At higher speeds the function of the current model correction is to act as a stabiliser of the control system. The current model contains a set of inductance parameters which must be known. The validation of the current model in steady state is not self evident. It depends on the accuracy of the saturated value of the inductances. Parameter measurement of the motor model where the supply inverter is used as a measurement signal generator is presented. This so called identification run can be performed prior to delivery or during drive commissioning. A derivation method for the inductance models used for the representation of the saturation effects is proposed. The performance of the electrically excited synchronous motor supplied with the DTC inverter is proven with experimental results. It is shown that it is possible to obtain a good static accuracy of the DTC's torque controller for an electrically excited synchronous motor. The dynamic response is fast and a new operation point is achieved without oscillation. The operation is stable throughout the speed range. The modelling of the magnetising inductance saturation is essential and cross saturation has to be considered as well. The effect of cross saturation is very significant. A DTC inverter can be used as a measuring equipment and the parameters needed for the motor model can be defined by the inverter itself. The main advantage is that the parameters defined are measured in similar magnetic operation conditions and no disagreement between the parameters will exist. The inductance models generated are adequate to meet the requirements of dynamically demanding drives.

Brain-Computer Interfaces, Virtual Reality, and Videogames

Major challenges must be tackled for brain-computer interfaces to mature into an established communications medium for VR applications, which will range from basic neuroscience studies to developing optimal peripherals and mental gamepads and more efficient brain-signal processing techniques.

Cafeína: revisão sobre métodos de análise

Gravimetric and Bailey-Andrew methods are tedious and provide inflated results. Spectrofotometry is adequate for caffeine analysis but is lengthy. Gas chromatography also is applied to the caffeine analysis but derivatization is needed. High performance liquid chromatography with ultraviolet detection (HPLC-UV) and reversed phase is simple and rapid for xanthine multianalysis. In HPLC-UV-gel permeation, organic solvents are not used. HPLC-mass spectrometry provides an unequivocal structural identification of xanthines. Capillary electrophoresis is fast and the solvent consumption is smaller than in HPLC. Chemometric methods offer an effective means for chemical data handling in multivariate analysis. Infrared spectroscopy alone or associated with chemometries could predict the caffeine content in a very accurate form. Electroanalytical methods are considered of low cost and easy application in caffeine analysis.