Design and implementation of a subject identification system based on Electroencephalogram

Biometrics are essential methods of identifying people nowadays. There are many types of biometrics, such as the classic methods for iris, face and fingerprint; but most of these are not robust or secure. Recently, biometrics based on electroencephalogram signals using machine learning algorithms have proven to be one of the highest quality and robust methods. Electroencephalograms have advantages over traditional modalities as they are extremely difficult to reproduce and cannot be captured stealthily from a distance. This work describes a system capable of acquiring real-time electroencephalogram signals, processing them using the PREP pipeline, to clean them and improve performance, and making subject identity predictions from electroencephalogram signals using different artificial intelligence algorithms. The system is portable, robust, low-cost and connected to the network to send the results to a server. It is composed of an acquisition system using an analog-to-digital converter and protection systems for electroencephalogram signals. The system is based on a Raspberry Pi Zero 2W as the computer in charge of performing all the computational work of the artificial intelligence algorithms and managing the different tasks. Several deep learning algorithms have been used and compared in terms of results and performance. The EEGNet model has provided the best results with an accuracy of 86.74% in its predictions. The data input to the model has been preprocessed with the PREP pipeline, which has proven to be effective in the results, as it improves the performance of all models that use it. The system provides a functional device with outstanding results that leads the way for future work and applications

Estimating stellar mean density through seismic inversions

Determining the mass of stars is crucial both to improving stellar evolution theory and to characterising exoplanetary systems. Asteroseismology offers a promising way to estimate stellar mean density. When combined with accurate radii determinations, such as is expected from GAIA, this yields accurate stellar masses. The main difficulty is finding the best way to extract the mean density from a set of observed frequencies. We seek to establish a new method for estimating stellar mean density, which combines the simplicity of a scaling law while providing the accuracy of an inversion technique. We provide a framework in which to construct and evaluate kernel-based linear inversions which yield directly the mean density of a star. We then describe three different inversion techniques (SOLA and two scaling laws) and apply them to the sun, several test cases and three stars. The SOLA approach and the scaling law based on the surface correcting technique described by Kjeldsen et al. (2008) yield comparable results which can reach an accuracy of 0.5 % and are better than scaling the large frequency separation. The reason for this is that the averaging kernels from the two first methods are comparable in quality and are better than what is obtained with the large frequency separation. It is also shown that scaling the large frequency separation is more sensitive to near-surface effects, but is much less affected by an incorrect mode identification. As a result, one can identify pulsation modes by looking for an l and n assignment which provides the best agreement between the results from the large frequency separation and those from one of the two other methods. Non-linear effects are also discussed as is the effects of mixed modes. In particular, it is shown that mixed modes bring little improvement as a result of their poorly adapted kernels.Comment: Accepted for publication in A&A, 20 pages, 19 figure

Anomalous expansion and phonon damping due to the Co spin-state transition in RCoO_3 with R = La, Pr, Nd and Eu

We present a combined study of the thermal expansion and the thermal conductivity of the perovskite series RCoO_3 with R = La, Nd, Pr and Eu. The well-known spin-state transition in LaCoO_3 is strongly affected by the exchange of the R ions due to their different ionic radii, i.e. chemical pressure. This can be monitored in detail by measurements of the thermal expansion, which is a highly sensitive probe for detecting spin-state transitions. The Co ions in the higher spin state act as additional scattering centers for phonons, therefore suppressing the phonon thermal conductivity. Based on the analysis of the interplay between spin-state transition and heat transport, we present a quantitative model of the thermal conductivity for the entire series. In PrCoO_3, an additional scattering effect is active at low temperatures. This effect arises from the crystal field splitting of the 4f multiplet, which allows for resonant scattering of phonons between the various 4f levels.Comment: 15 pages including 5 figure

Oscillation mode frequencies of 61 main sequence and subgiant stars observed by Kepler

Solar-like oscillations have been observed by Kepler and CoRoT in several solar-type stars, thereby providing a way to probe the stars using asteroseismology. We provide the mode frequencies of the oscillations of various stars required to perform a comparison with those obtained from stellar modelling. We used a time series of nine months of data for each star. The 61 stars observed were categorised in three groups: simple, F-like and mixed-mode. The simple group includes stars for which the identification of the mode degree is obvious. The F-like group includes stars for which the identification of the degree is ambiguous. The mixed-mode group includes evolved stars for which the modes do not follow the asymptotic relation of low-degree frequencies. Following this categorisation, the power spectra of the 61 main sequence and subgiant stars were analysed using both maximum likelihood estimators and Bayesian estimators, providing individual mode characteristics such as frequencies, linewidths, and mode heights. We developed and describe a methodology for extracting a single set of mode frequencies from multiple sets derived by different methods and individual scientists. We report on how one can assess the quality of the fitted parameters using the likelihood ratio test and the posterior probabilities. We provide the mode frequencies of 61 stars (with their 1-sigma error bars), as well as their associated echelle diagrams.Comment: 83 pages, 17 figures, 61 tables, paper accepted by Astronomy and Astrophysic

Open issues in probing interiors of solar-like oscillating main sequence stars: 2. Diversity in the HR diagram

We review some major open issues in the current modelling of low and intermediate mass, main sequence stars based on seismological studies. The solar case was discussed in a companion paper, here several issues specific to other stars than the Sun are illustrated with a few stars observed with CoRoT and expectations from Kepler data.Comment: GONG 2010 - SoHO 24, A new era of seismology of the Sun and solar-like stars, To be published in the Journal of Physics: Conference Series (JPCS