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Forest condition monitoring in the Czech Republic: Annual report ICP Forests - Data 2003
Boháčová, Ludmila ; Uhlířová, Hana ; Lomský, Bohumír ; Buriánek, V. ; Damašková, J. ; Fabiánek, P. ; Fadrhonsová, V. ; Hejdová, J. ; Novotný, R. ; Neumann, L. ; Šrámek, V.
In the yearbook the methods of assessment and evaluation are presented, and the results at Level I and Level II plots.
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Forest condition monitoring in the Czech Republic: Annual report Forest Focus – Data 2004
Boháčová, Ludmila ; Uhlířová, Hana ; Šrámek, Vít ; Buriánek, V. ; Fabiánek, P. ; Hejdová, J. ; Kapitola, P. ; Lachmanová, Z. ; Lomský, B. ; Neumann, L. ; Novotný, R.
In the yearbook the methods of assessment and evaluation are presented, and the results in the systematic network of plots and intensive monitoring plots (Level I and Level II).
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Animal Protagonist in Texts Usable in Education
Vomastková, Martina ; Brožová, Věra (advisor) ; Neumann, Lukáš (referee)
This thesis is focused on an animal protagonist in literary texts which could be used in education because of their didactic potential. The aim of this thesis is to describe the form of representation of an animal protagonist (and nature in general) in chosen literary texts and to design the possible ways how to use these texts in education. The first part is dedicated to a theme of animal in the cultural context, especially in the literature with a short ethology-digression. The second part deals with a literary-theoretical analysis of texts from Rudyard Kipling, Jack London, Vitaly Bianki and Ceridwen Dovey. The third part of this thesis is focused on the didactic potential of analyzed texts aiming to econarratology. In the last chapter are described possibilities of the didactic work with all the formerly analyzed texts. Keywords animal protagonist, anthropomorphism, literature for children and youth, Rudyard Kipling, Jack London, Vitaly Bianki, Ceridwen Dovey, education, econarratology, didactic potential
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Images of the Jews in the Work of Vojtěch Rakous
Matoušek, Martin ; Mocná, Dagmar (advisor) ; Neumann, Lukáš (referee)
This bachelor thesis analyses and interprets the literary works of the Czech writer Vojtěch Rakous. Particular attention is paid to the characteristics of characters who are portrayed as Jewish. In the literary interpretation a sociological point of view is applied. The first chapter defines the Jewish people and deals with the history of Jews in the Czech lands. Special attention is paid to the process of emancipation and assimilation of Czech Jews. Two main ideological streams of Czech Jews are also described - the Czech-Jewish movement and Zionism. The second chapter presents biographical information about Vojtěch Rakous and shows his Czech-Jewish ideas and opinions and explains his perception of his own identity. The third chapter prepares the literary theoretical basis for the interpretation of literary characters. It addresses the question of what a literary character is, what narrative practices it is made up of. In particular, the realistic poetics of the literary character are taken into account. The fourth chapter analyses the material of the stories of Vojtěch Rakous and interprets the figures of the Jews. Jewish figures in this chapter are categorised according to social criteria into the following literary types: Jewish married couples, Christian-Jewish friends, rich Jews, poor Jews,...
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Character recognition of real scenes using neural networks
Fiala, Petr ; Neumann, Lukáš (advisor) ; Berka, Petr (referee)
This thesis focuses on a problem of character recognition from real scenes, which has earned significant amount of attention with the development of modern technology. The aim of the paper is to use an algorithm that has state-of-art performance on standard data sets and apply it for the recognition task. The chosen algorithm is a convolution network with deep structure where the application of the specified model has not yet been published. The implemented solution is built on theoretical parts which are provided in comprehensive overview. Two types of neural network are used in the practical part: a multilayer perceptron and the convolution model. But as the complex structure of the convolution networks gives much better performance compare with the classification error of the MLP on the first data set, only the convolution structure is used in the further experiments. The model is validated on two public data sets that correspond with the specification of the task. In order to obtain an optimal solution based on the data structure several tests had been made on the modificated network and with various adjustments on the input data. Presented solution provided comparable prediction rate compare to the best results of the other studies while using artificially generated learning pattern. In conclusion, the thesis describes possible extensions and improvements of the model, which should lead to the decrease of the classification error.
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