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Sleep EEG analysis
Vávrová, Eva ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
The bachelor´s thesis is focused on analysis of sleep electroencephalograms based on extraction of chosen parameters in time and frequency domain. The parameters are acquired from segments of EEG signals coincident with sleep stages. The parameters used for automatic detection of sleep stages are selected according to statistical analysis. The program with a graphical user interface for selection, display and analysis EEG was created using Matlab.
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Automatic sleep scoring using polysomnographic data
Vávrová, Eva ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
The thesis is focused on analysis of polysomnographic signals based on extraction of chosen parameters in time, frequency and time-frequency domain. The parameters are acquired from 30 seconds long segments of EEG, EMG and EOG signals recorded during different sleep stages. The parameters used for automatic classification of sleep stages are selected according to statistical analysis. The classification is realized by artificial neural networks, k-NN classifier and linear discriminant analysis. The program with a graphical user interface was created using Matlab.
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Maps for mentally handicapped people
Vávrová, Eva ; Polášková, Martina (referee) ; Plánka, Ladislav (advisor)
The thesis deals with problems of creating maps for people with developmental disabilities. After analysis, it was necessary to admit that types of maps intended for people with developmental disabilities do not exist. Therefore, it was suggested to do our own cartographic work in co-operation with schools for students with developmental disabilities. It ought to make working with maps easier, especially for students attending schools for people with developmental disabilities. Three charts of the Czech Republic were created in scale 1 : 2 000 000. Subsequently a plan of Zlín was created in scale 1 : 4 000. The whole thesis is connected with issues of developmental disabilities, special education, especially educating of students with developmental disabilities. The main aim is joining creation cartographic work with intellectual level of people with developmental disabilities.
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Forest regeneration within the treeline ecotone in the Giant Mountains under climate change
Cudlín, Ondřej ; Chumanová-Vávrová, Eva ; Edwards-Jonášová, Magda ; Heřman, Michal ; Štěpánek, Petr ; Cudlín, Pavel
Natural regeneration of mountain spruce forests began in the Giant Mountains 25 years ago after a reduction\nof severe and long-enduring air pollution. This process has been influenced by climatic change.\nThe aim of our contribution was to present background data for the potential elevational shift of spruce\nregeneration under conditions of climate change. These upslope shifts may also depend on constraints\nsuch as climate extremes, unfavourable soil conditions, absence of ectomycorrhizal symbionts, and lack of\nmicrosites suitable for seedlings. Since 2014, we have studied the main driving factors affecting Norway\nspruce regeneration, and in particular soil conditions, ectomycorrhizal symbionts, ground vegetation cover,\nand forest health, in six transects across the treeline ecotone located on a NW-to-NE transect through\nthe Giant Mountains. Microclimatic measurements showed that the mean difference in growing season\ntemperature between the montane spruce forests and forests at the treeline was −0.54°C. The model\nHADGEM2 predicted that in 20 years the temperature at the treeline will be similar to the current one at\nmontane elevations. The difference in prevailing soil types between the montane spruce forests and forests\nat the current treeline (i.e. podzol vs. ranker type) could be an important factor limiting success of the\nupslope spreading of spruce. Furthermore, areas covered by microsites favourable for natural spruce regeneration,\nespecially spruce litter patches, decaying wood, mosses, and Avenella flexuosa stands, were\nshown to decrease with increasing elevation. It is likely that spruce will move upslope in response to climate\nchange, but the process is likely to be slow or even blocked for some periods, especially by unfavourable\nsoil conditions and climatic extremes.
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Automatic sleep scoring using polysomnographic data
Vávrová, Eva ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
The thesis is focused on analysis of polysomnographic signals based on extraction of chosen parameters in time, frequency and time-frequency domain. The parameters are acquired from 30 seconds long segments of EEG, EMG and EOG signals recorded during different sleep stages. The parameters used for automatic classification of sleep stages are selected according to statistical analysis. The classification is realized by artificial neural networks, k-NN classifier and linear discriminant analysis. The program with a graphical user interface was created using Matlab.
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Sleep EEG analysis
Vávrová, Eva ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
The bachelor´s thesis is focused on analysis of sleep electroencephalograms based on extraction of chosen parameters in time and frequency domain. The parameters are acquired from segments of EEG signals coincident with sleep stages. The parameters used for automatic detection of sleep stages are selected according to statistical analysis. The program with a graphical user interface for selection, display and analysis EEG was created using Matlab.
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