Adaptive Sparse Detector for Suppressing Powerline Component in EEG Measurements

Powerline interference (PLI) is a major source of interference in the acquisition of electroencephalogram (EEG) signal. Digital notch filters (DNFs) have been widely used to remove the PLI such that actual features, which are weak in energy and strongly connected to brain states, can be extracted explicitly. However, DNFs are mathematically implemented via discrete Fourier analysis, the problem of overlapping between spectral counterparts of PLI and those of EEG features is inevitable. In spite of their effectiveness, DNFs usually cause distortions on the extracted EEG features, which may lead to incorrect diagnostic results. To address this problem, we investigate an adaptive sparse detector for reducing PLI. This novel approach is proposed based on sparse representation inspired by self-adaptive machine learning. In the coding phase, an overcomplete dictionary, which consists of redundant harmonic waves with equally spaced frequencies, is employed to represent the corrupted EEG signal. A strategy based on the split augmented Lagrangian shrinkage algorithm is employed to optimize the associated representation coefficients. It is verified that spectral components related to PLI are compressed into a narrow area in the frequency domain, thus reducing overlapping with features of interest. In the decoding phase, eliminating of coefficients within the narrow band area can remove the PLI from the reconstructed signal. The sparsity of the signal in the dictionary domain is determined by the redundancy factor. A selection criteria of the redundancy factor is suggested via numerical simulations. Experiments have shown the proposed approach can ensure less distortions on actual EEG features.

Ionospheric turbulence from TEC variations and VLF/LF transmitter signal observations before and during the destructive seismic activity of August and October 2016 in Central Italy

In this paper we investigate the ionospheric turbulence from observations of TEC variations as well as from VLF/LF transmitter signal observations before and during the disastrous seismic activity of August and October 2016 in Central Italy. The Total Electron Content (TEC) data of 8 Global Positioning System (GPS) stations of the EUREF network, which are being provided by IONOLAB (Turkey), were analysed using Discrete Fourier Analysis in order to investigate the TEC variations. The data acquired for VLF/LF signal observations are from the receiver of Thessaloniki (40.59N, 22,78E), Greece, which monitor the VLF/LF transmitters of the International Network for Frontier Research on Earthquake Precursors (INFREP). A method of normalization according to the distance between the receiver and the transmitter is applied on the above data and then they are processed by the Hilbert Huang Transform (HHT) to produce the corresponding spectra for visual analysis. The results of both methods indicate that the High- Frequency limit fo, of the ionospheric turbulence content, increases as the site and the moment of the earthquake occurrence is approaching, pointing to the earthquake locus.

A mass-conservative higher-order ADI method for solving unsteady convection–diffusion equations

In the paper, a high-order alternating direction implicit (ADI) algorithm is presented to solve problems of unsteady convection and diffusion. The method is fourth- and second-order accurate in space and time, respectively. The resulting matrix at each ADI computation can be obtained by repeatedly solving a penta-diagonal system which produces a computationally cost-effective solver. We prove that the proposed scheme is mass-conserved and unconditionally stable by means of discrete Fourier analysis. Numerical experiments are performed to validate the mass conservation and illustrate that the proposed scheme is accurate and reliable for convection-dominated problems.

Lower Ionospheric turbulence variations during the intense seismic activity of the last half of 2019 in the broader Balkan region.

<p>In this paper, we investigate the ionospheric turbulence from TEC observations, before and during the intense seismic activity of September 2019 at Albania (main shock at l=19.445<sup>o</sup>E, j=41.372<sup>o</sup> N, M<sub>w</sub>=5.6)  and at Marmara sea (main shock at l=28.19 <sup>o</sup>E, j=40.872<sup>o</sup>N, M<sub>w</sub>=5.7), as well as of November 2019 at Albania (main shock at l=19.470<sup>o</sup>E, j=41.381<sup>o</sup>N, M<sub>w</sub>=6.4), and at Bosnia-Herzegovina (main shock at l=17.961<sup>o</sup>E, j=43.196<sup>o</sup>N, M<sub>w</sub>=5.4).</p><p>The Total Electron Content (TEC) data of 6 Global Positioning System (GPS) stations of the EUREF network, which are being provided by IONOLAB (Turkey), were analysed using Discrete Fourier Analysis in order to investigate the TEC variations. The results of this investigation indicate that the High- Frequency limit f<sub>o</sub>, of the ionospheric turbulence content, increases by aproaching the site and  the time of the earthquake occurrence, pointing to the earthquake location (epicenter). We conclude that the LAIC mechanism, through acoustic or gravity wave, could explain this phenomenology. In addition the proximity of the tectonic active areas to the GPS stations offer us an opportunity to discriminate the origin of the disturbances</p>

Lower Ionospheric turbulence variations during the tectonic activity of the last quarter of 2019 in the Hellenic Arc (Greece)

<p>In this paper we investigate the ionospheric turbulence from TEC observations before and during the tectonic activity of the last quarter of 2019 in the Hellenic Arc, Greece (main shock at l=23.26<sup>o</sup>E, j=35.69<sup>o</sup>N, M<sub>w</sub>=6.1). The Total Electron Content (TEC) data of 6 Global Positioning System (GPS) stations of the EUREF network, which are being provided by IONOLAB (Turkey), were analysed using Discrete Fourier Analysis in order to investigate the TEC variations. The results of this investigation indicate that the High- Frequency limit f<sub>o</sub>, of the ionospheric turbulence content, increases by aproaching the site and the time of the earthquake occurrence, pointing to the earthquake location (epicenter). We conclude that the LAIC mechanism through acoustic or gravity wave could explain this phenomenology.</p>