XMM-Newton observation of MV Lyr and the sandwiched model confirmation

We present spectral and timing analyses of simultaneous X-ray and UV observations of the VY Scl system MV Lyr taken by XMM-Newton, containing the longest continuous X-ray+UV light curve and highest signal-to-noise X-ray (EPIC) spectrum to date. The RGS spectrum displays emission lines plus continuum, confirming model approaches to be based on thermal plasma models. We test the sandwiched model based on fast variability that predicts a geometrically thick corona that surrounds an inner geometrically thin disc. The EPIC spectra are consistent with either a cooling flow model or a 2-T collisional plasma plus Fe emission lines in which the hotter component may be partially absorbed which would then originate in a central corona or a partially obscured boundary layer, respectively. The cooling flow model yields a lower mass accretion rate than expected during the bright state, suggesting an evaporated plasma with a low density, thus consistent with a corona. Timing analysis confirms the presence of a dominant break frequency around log(f/Hz) = -3 in the X-ray Power Density Spectrum (PDS) as in the optical PDS. The complex soft/hard X-ray light curve behaviour is consistent with a region close to the white dwarf where the hot component is generated. The soft component can be connected to an extended region. We find another break frequency around log(f/Hz) = -3.4 that is also detected by Kepler. We compared flares at different wavelengths and found that the peaks are simultaneous but the rise to maximum is delayed in X-rays with respect to UV.Comment: 17 pages, 21 figures, 4 tables, Accepted for publication in MNRA

Alternation of the flickering morphology between the high and low state in MV Lyr

AIMS: We studied unique data of a nova-like system MV Lyr during transition from the high to low state and vice versa taken by the Kepler space telescope. We were interested in evolution of frequency components found previously by Scaringi et al. in different data also obtained by Kepler. METHODS: We divided the light curve into 10 day segments and investigated the corresponding power density spectra. We searched for individual frequency components by fitting with Lorentzian functions. Additionally, we investigated the variability using averaged shot profiles calculated from the light curve divided into 10 equally spaces subsamples. RESULTS: We found very complex changes of the power density spectra. We focused our study onto three frequency components. Strong activity increase is seen at low frequencies. Contrariwise, the high frequency part of the spectrum strongly decreases in power with specific rise in characteristic frequencies of the individual components. We discuss various scenarios of this phenomenology as reprocessing of X-rays in a receding accretion disc or a radiation from a more active region at the outer disc. Finally, we show that various cataclysmic variables show similar characteristic frequencies in their power density spectra. These are dependent on activity stage, making the situation similar to X-ray binaries.Comment: accepted for publication to A&

Acoustic Scene Classification from Speech

Téma tejto diplomovej práce je klasifikácia audio nahrávky do 15 tried akustických prostredí, v ktorých sa ľudia bežne nachádzajú. Práca popisuje 2 metódy založené na GMM a i-vektoroch a ich vzájomnú fúziu. Na dátach zo súťaže DCASE dosiahol najlepší GMM systém úspešnosť 60.4% a i-vektor systém 68.4%. Fúzia GMM systému a najlepšieho i-vektor systému výsledok ešte zlepšila na 69.3%, čo by v dobe súťaže stačilo na 20. miesto z 98 odovzdaných systémov z celého sveta.The topic of this thesis is an audio recording classification with 15 different acoustic scene classes that represent common scenes and places where people are situated on a regular basis. The thesis describes 2 approaches based on GMM and i-vectors and a fusion of the both approaches. The score of the best GMM system which was evaluated on the evaluation dataset of the DCASE Challenge is 60.4%. The best i-vector system's score is 68.4%. The fusion of the GMM system and the best i-vector system achieves score of 69.3%, which would lead to the 20th place in the all systems ranking of the DCASE 2017 Challenge (among 98 submitted systems from all over the world).