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New design of combined inventory for Czech text-to-speech synthesis
Hesounová, Alžběta
A new inventory for Czech text-to-speech synthesis is currently developed. Its core consists of triphone segments, the number of all segments being about 1850. Apart from triphones, the inventory will also contain separate segments for vowel bodies and sentence-initial and sentence-final consonants. A special attention is given to consonants in clusters that are treated with respect to the neighbouring speech sounds. The new system is going to work on 16kHz sampling frequency.
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Clustering and regression analysis of micro panel data
Sobíšek, Lukáš ; Pecáková, Iva (advisor) ; Komárek, Arnošt (referee) ; Brabec, Marek (referee)
The main purpose of panel studies is to analyze changes in values of studied variables over time. In micro panel research, a large number of elements are periodically observed within the relatively short time period of just a few years. Moreover, the number of repeated measurements is small. This dissertation deals with contemporary approaches to the regression and the clustering analysis of micro panel data. One of the approaches to the micro panel analysis is to use multivariate statistical models originally designed for crosssectional data and modify them in order to take into account the within-subject correlation. The thesis summarizes available tools for the regression analysis of micro panel data. The known and currently used linear mixed effects models for a normally distributed dependent variable are recapitulated. Besides that, new approaches for analysis of a response variable with other than normal distribution are presented. These approaches include the generalized marginal linear model, the generalized linear mixed effects model and the Bayesian modelling approach. In addition to describing the aforementioned models, the paper also includes a brief overview of their implementation in the R software. The difficulty with the regression models adjusted for micro panel data is the ambiguity of their parameters estimation. This thesis proposes a way to improve the estimations through the cluster analysis. For this reason, the thesis also contains a description of methods of the cluster analysis of micro panel data. Because supply of the methods is limited, the main goal of this paper is to devise its own two-step approach for clustering micro panel data. In the first step, the panel data are transformed into a static form using a set of proposed characteristics of dynamics. These characteristics represent different features of time course of the observed variables. In the second step, the elements are clustered by conventional spatial clustering techniques (agglomerative clustering and the C-means partitioning). The clustering is based on a dissimilarity matrix of the values of clustering variables calculated in the first step. Another goal of this paper is to find out whether the suggested procedure leads to an improvement in quality of the regression models for this type of data. By means of a simulation study, the procedure drafted herein is compared to the procedure applied in the kml package of the R software, as well as to the clustering characteristics proposed by Urso (2004). The simulation study demonstrated better results of the proposed combination of clustering variables as compared to the other combinations currently used. A corresponding script written in the R-language represents another benefit of this paper. It is available on the attached CD and it can be used for analyses of readers own micro panel data.
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název v anglickém jazyce není uveden
Klusáčková, Pavlína ; Pelclová, Daniela (advisor) ; Hajduková, Zdeňka (referee) ; Vízek, Martin (referee)
Early diagnosis of occupational asthma is important especially for the prognosis of this disease. The confirmation of the diagnosis of occupational asthma is sometimes difficult using diagnostic methods available nowadays. That is why searching new methods is very important. Analysis of exhaled breath condensate (EBC) by liquid chromatography combined with mass spectrometry enables the separate detection of cysteinyl leukotrienes (LT) - LTC4, LTD4, LTE4; LTB4 and 8-isoprostane. If patients with occupational asthma and controls were compared, only LTC4 was significantly higher among all EBC parameters studied in asthmatics (despite corticosteroid treatment). This marker could be used in the future diagnostics. Monitoring of 24-hours variability of EBC parameters in patients, in whom occupational asthma is suspected, showed relatively high intraindividual and interindividual variation. It is evident therefore, that if only one daily measurement in asthmatics would be possible (which is common in articles of several authors), it should be collected in the same period of day in all persons. In negative bronchoprovocation tests significant changes of EBC parameters were not found. The evaluation of positive bronchoprovocation tests was limited by small number of patients, however in five persons from six, the...
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Statistical Classification by means of generalized linear models
Sladká, Vladimíra ; Mrázková, Eva (referee) ; Michálek, Jaroslav (advisor)
The goal of this thesis is introduce the theory of generalized linear models, namely probit and logit model. This models are especially used for medical data processing. In our concrete case these mentioned models are applied to data file obtained in teaching hospital Brno. The aim is statically analyzed immune response of child patients in dependence of twelve selected types of genes and find out which combinations of these genes influence septic state of patients.
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Aplikace dataminingových metod na bankovní data
Melichar, Miloš
The thesis deals with pre-processing of two data sets with information on clients, loans and debit cards. The data sets were separately pre-processed and modeled by SPSS Modeler using a number of methods and algorithms. For the modeling purposes, three classification data mining tasks were defined: loan approving or rejecting, loan rating and debit card type assignment. By using the selected methods of machine learning techniques the classification models were built for each task. Models accuracy was tested by script written in SPSS language for automation. All tasks were supplemented by clustering technique based on latent factors gained by factor analysis. Factor analysis combined with clustering presents another approach in pattern discovery.
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Lexical Association Measures Collocation Extraction
Pecina, Pavel ; Hajič, Jan (advisor) ; Semecký, Jiří (referee) ; Baldwin, Timothy (referee)
This thesis is devoted to an empirical study of lexical association measures and their application to collocation extraction. We focus on two-word (bigram) collocations only. We compiled a comprehensive inventory of 82 lexical association measures and present their empirical evaluation on four reference data sets: dependency bigrams from the manually annotated Prague Dependency Treebank, surface bigrams from the same source, instances of surface bigrams from the Czech National Corpus provided with automatically assigned lemmas and part-of-speech tags, and distance verb-noun bigrams from the automatically part-of-speech tagged Swedish Parole corpus. Collocation candidates in the reference data sets were manually annotated and labeled as collocations and non-collocations. The evaluation scheme is based on measuring the quality of ranking collocation candidates according to their chance to form collocations. The methods are compared by precision-recall curves and mean average precision scores adopted from the field of information retrieval. Tests of statistical significance were also performed. Further, we study the possibility of combining lexical association measures and present empirical results of several combination methods that significantly improved the performance in this task. We also propose a model...
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Residual cognitive capacity in unconscious patients. Event related potentials and cerebral blood flow study
Holečková, Irena ; Choc, Milan (advisor) ; Polívka, Jiří (referee) ; Rektor, Ivan (referee) ; Stejskal, Lubor (referee)
UNIVERSITÉ CLAUDE BERNARD LYON 1 - LYON Ecole Doctorale Biologie Moléculaire Intégrée et Cognitive Année Universitaire 2007 - 2008 UNIVERZITA KARLOVA V PRAZE Lékařská fakulta v Plzni Vědní obor : chirurgické obory THESE EN COTTUTELLE FRANCO - TCHEQUE Irena HOLEČKOVÁ Neurochirurgické oddělení Fakultní nemocnice v Plzni Capacités cognitives chez les patients inconscients Étude des potentiels évoqués cognitifs et du débit sanguin cérébral Kognitivní kapacita u pacientů s poruchou vědomí Studie kognitivních evokovaných potenciálů a mozkového krevního průtoku Cognitive capacity in unconscious patients Event related potentials and cerebral blood flow study 2008 Ce travail de thèse a reçu le soutien financier de l'Ambassade de France en République Tchèque L'ensemble des travaux a été réalisé dans le Service de Neurophysiologie Clinique et Epileptologie de l'Hôpital Neurologique de Lyon, au sein de l'équipe de l' Unité INSERM 821 et au sein de CERMEP-imagerie du vivant de Lyon, France. Remerciements Le mot remerciement s'avère insuffisant pour exprimer ma reconnaissance envers Madame Catherine Fischer, Chargée de recherche, pour avoir diriger ce travail. Sa compétence, ses conseils ont été essentiels à la réalisation de cette thèse. Je vous remercie de m'avoir «ouvert les oreilles» au domaine passionnant des...
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Analýza dat týkajících se risku sebevraždy u mentálně nemocných
Hron, Jiří ; Rauch, Jan (advisor) ; Malá, Ivana (referee)
The three goals of this thesis are to present a coherent overview of the research on suicide in both the general population and among mentally ill, to analyse records of hospitalisations of mentally ill from years 2006 to 2012 while looking for patterns either leading to identification of suicide risk factors or useful for predicting probability of suicide at the time of discharge, and finally to compare a selected subset of statistical, data mining and machine learning methods in relation to their applicability to the second goal. The overview is based on information from over 40 published articles. The analysis and the comparison make use of associative rules mining, visual and stepwise methods for exploration, standard and conditional logistic regression models for inference, and variations of random forests for prediction. To the best of author's knowledge, none of the three goals was previously pursued by any other researcher in the Czech Republic, certainly not using the data set provided for purposes of this thesis. A new modification of random forest combined with a set of logistic regression in order to refine prediction accuracy is also briefly explored. The structure closely follows the above--stated goals starting from the chapters on related work and on the theoretical basis of the methods used, and concluding by the analysis itself and discussion of its results.
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Neural Networks Between Integer and Rational Weights
Šíma, Jiří
The analysis of the computational power of neural networks with the weight parameters between integer and rational numbers is refined. We study an intermediate model of binary-state neural networks with integer weights, corresponding to finite automata, which is extended with an extra analog unit with rational weights, as already two additional analog units allow for Turing universality. We characterize the languages that are accepted by this model in terms of so-called cut languages which are combined in a certain way by usual string operations. We employ this characterization for proving that the languages accepted by neural networks with an analog unit are context-sensitive and we present an explicit example of such non-context-free languages. In addition, we formulate a sufficient condition when these networks accept only regular languages in terms of quasi-periodicity of parameters derived from their weights.
Fulltext: content.csg -  PDF
Plný tet: v1237-16 - PDF
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The influence of therapy by Vojta reflex locomotion method on functional abilities of immobile seniors
Černá, Gabriela ; Smékal, David (advisor) ; Zounková, Irena (referee)
This project assesses effects of four -week active rehabilitation combined with Vojta reflex stimulation on mobility of bed-bound seniors. Sixteen female patients were divided into two groups of eight members, i.e. tested group and control group. Both groups were put through training focused on self-support, maintaining or enhancement of range of movement, strengthening of weak muscle groups, stability training, practicing sitting up and lying down from sitting position, and walking in the high walking frame in the case of stronger patients. Besides that the tested group underwent Vojta reflex stimulation (global model of reflex turning), coordination and stability exercise and exercise with rehabilitation tools (elastic band, over ball, small ball, water bottle). In the beginning and in the end of the project the EMS (Elderly Mobility Scale), BI (Barthel Index), and MMSE (Mini-mental State Examination) scales were tested as well as ability to turn from back to side and stability in the sitting position. Statistical comparability of both groups was proved true in the beginning of the therapy by Mann-Whitney test. There was a noticeable tendency towards higher probability of enhancing measured scores in the tested group compared to the control group after the therapy. In case of the EMS this probability was...
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