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Foreign-Owned Banks and Host Economies
Fišerová, Tereza ; Teplý, Petr (advisor) ; Mejstřík, Michal (referee)
In the past two decades, significant changes have been shaping and transforming the banking sectors worldwide. Among these trends we find an intensive surge in foreign bank ownership which is especially remarkable in the countries of the Central, Eastern and South-Eastern European region. Using the sample of 17 countries and filtering out more than 140 domestically-operating foreign-owned banks, we examine the determinants of their performance in relation to host country conditions and home country banking sector performance over the period of seven years between 2005 and 2011. Due to the topic's currency, we additionally provide an insight into the link between sovereign debt and bank ownership. By means of system GMM model, or fixed effects model, we reveal that macroeconomic fundamentals of the host country affect the foreign-owned banks' performance but do not suffice in explaining it fully. Moreover, the depth of the current crisis as demonstrated in the home country impacts negatively on the host-country-operating foreign-owned banks. We did not find any convincing evidence of the host sovereign debt and bank ownership nature of relationship.
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Methods of Robust Econometrics with Applications to Economic Data
Michalíková, Eva ; Víšek, Jan Ámos (advisor) ; Egger, Peter (referee) ; Lachout, Petr (referee) ; Grendár, Marian (referee)
This thesis if focused on the application of methods of robust econometrics to real economic data. We focuse on the issuies of international trade in Czech Republic and the problem of employment and growth of small businesses in Europe. We also focues on estimation of panel data by classical approaches (least squares, fixed effects, GMM) and bzy robust techniques. The first part of dissertation focuses on analyzing determinants of FDI in Czech manufacturing industry. The aim is to estimate a model where the stock of FDI is expressed as a function of several economic factors (K/L, profit per worker, R&D, Balassa index and others). We estimate these models by OLS, fixed effects and GMM. With regard to ambiguous results we used least trimmed squares as a diagnostic tool for detection of outliers. Elimination of two polluting industries out of the data set brings certain improvement in significance of some factors. The second part of dissertation we focus on an estimation of models of employment and net production in 28 European countries for small businesses as a function of economic and institutional variables by special technique of estimation. We describe robust version of within group fixed effects estimation. The aim of paper is to estimate a set of models and to test the properties of estimator. With...
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How Tax, Labor Market and Product Markets Reforms Influence Foreign Direct Investment
Tydlačková, Stanislava ; Vacek, Pavel (advisor) ; Serdarevič, Goran (referee)
This work analyses industry level Foreign Direct Investment (FDI) inflows in order to find out if their determinants are the same for all industries or if they differ and how. The second important question is if various qualitative variables as labour market or product market liberalization or taxation determines flows to individual industries. I analyse seven industries by System GMM model for period from 1994 till 2009. The results suggests that inflows to each industry are driven by distinct set of determinants. While there are nearly non-significant determinants for agriculture among explanatory variables I used, there is many of them significant for services. Concerning qualitative variables, labour market liberalization influence FDI inflows to manufacturing and mining, product market liberalization influence inflows to transportation and electricity, gas and water industry. The level of taxation seem to be significant determinant of FDI inflows to manufacturing. Keywords FDI, Foreign direct investment by industry, Structural reforms, Labour Market, Lib- eralization, GMM, taxation 4
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Speech-signal-based recognition of type of transmission channel
Kopřiva, Tomáš ; Burget, Radim (referee) ; Atassi, Hicham (advisor)
This work deals with the classification of five different transmission channels by speech signal processing. The channels considered are: GSM, two PSTN channels and two VoIP channels. For the training and testing purposes, a speech database for the transmission channels called SPLAB_TranCh was constructed. The speech signals of this corpus originally come from well-known TIMIT database, where each utterance passed through each mentioned transmission channel. The main objective of this work is to find optimal features and classification accuracy that yield best classification accuracy. Several types of features, including MFCC, LPCC and spectral characteristics were put under examination. The best suprasegmental features were identified by using mRMR algorithm. Several classifiers were tested as well. The results suggested that the classification of transmission channel can be performed with high accuracy (around 90 %). Influence of adverse effects, which can occur during transmission, is also examined. Considered types of distortions are: saturation, thresholding, echo, crackling noises and different colors of noises and filters.
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Smoke and Fire Detection in Video Sequences
Tomek, Peter ; Štancl, Vít (referee) ; Švub, Miroslav (advisor)
This thesis aims to analyse a videosignal given in input and find segments that contains fire or smoke. The problem is divided into two cases-detection of fire and detection of smoke. The first and main step of analysation is detection of segments by Gaussian mixture model that is trained by Expectation-Maximization algorithm, or shortly EM algorithm. For smoke detection is than used method of optical flow. The final segments are than processed by some morphological methods and determination of their position is made. Finally, the output of algorithm is again a videosignal in which segments that probably contains fire or smoke are highlighted.
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Voice Activity Detection
Břenek, Roman ; Grézl, František (referee) ; Matějka, Pavel (advisor)
This thesis describes techniques for voice activity detection in audio recordings. It is necessary to correctly classify all non-speech segments and recognize speech with noisy background. The whole process of voice activity detection (VAD) is described in this thesis, i.e. digitizing audio signal, feature extraction, training of the system, post-processing and final evaluation. There are three different systems compared within the thesis . The first one is based on phoneme recognition using neural network, the other two are variations of Gaussian Mixture Models (GMM). Each system was tested on three data sets - Tactical Speaker Identification Speech Corpus (TSID), Ham Radio (HR) and Rich Transcription Evaluation (RT05-RT07). The best results of each system are compared with the results of the third side.
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Text Dependent Speaker Verification
Fux, Jan ; Glembek, Ondřej (referee) ; Matějka, Pavel (advisor)
The goal of this Bachelor's thesis was to design text dependent speaker recognition system. There were few systems tested for MIT database. This database contains recordings of 0.46s average length. Best case for recognition is to use a combination of DTW system using posterior probability estimation (posteriograms) as an output of Phoneme recognizer and acoustic SID system based on iVectors and PLDA (Probabilistic Linear Component Analysis). Fusion with Neural network gives the best results (EER). These are 17.84% EER for women and 16.38% for men. It's 49.9% relative improvement for women and 54.2% for men against acoustic recognition alone.
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Recognition of Poses and Gestures
Jiřík, Leoš ; Hradiš, Michal (referee) ; Zemčík, Pavel (advisor)
This thesis inquires the existing methods on the field of image recognition with regards to gesture recognition. Some methods have been chosen for deeper study and these are to be discussed later on. The second part goes in for the concenpt of an algorithm that would be able of robust gesture recognition based on data acquired within the AMI and M4 projects. A new ways to achieve precise information on participants position are suggested along with dynamic data processing approaches toward recognition. As an alternative, recognition using Gaussian Mixture Models and periodicity analysis are brought in. The gesture class in focus are speech supporting gestures. The last part demonstrates the results and discusses future work.
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Multiplatform Application for Speaker Verification
Görig, Jan ; Matějka, Pavel (referee) ; Glembek, Ondřej (advisor)
Bachelor thesis considers speaker recognition without knowledge of spoken message. There are described current feature extraction methods and their evaluation using Gaussian mixture model. The practical output of this work is application for visualization of the recognition process. Developed application is cross platform and it uses Qt and BSAPI libraries.
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Speech Recognition For Selected Languages
Schmitt, Jan ; Karafiát, Martin (referee) ; Janda, Miloš (advisor)
This bachelor's thesis deals with recognition of continues speech for three languages - Bulgarian, Croatian and Swedish. There are described basics of speech processing and recognition methods like acoustic modeling using hidden Markov models and gaussian mixture models. Another aim of this work is preparing data for those languages from GlobalPhone database, so they may be used with speech recognition toolkits Kaldi and HTK. With data prepared there are several models trained and tested using Kaldi toolkit.
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