This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.

This diploma thesis deals with the creation and testing of optical measurement system. There are basic parts of computer vision. Some ways of image preprocessing and templates matching are discussed. Everything is directed to a particular practical task. Selected methods for templates matching are the Correlation Method, the Classical and Hybrid Hausdorff Distance, Radial and Circular Sampling Space. These methods are programmed in C++ and they are compared with function for searching templates from specific library.

This work is dedicated to dynamic time warping in biosignal processing, especially it´s application for ECG signals. On the beginning the theoretical notes about cardiography are summarized. Then, the DTW analysis follows along with conditions and demands assessments for it’s successful application. Next, several variants and application possibilities are described. The practical part covers the design of this method, the outputs comprehension, settings optimization and realization of methods related with DTW

Title: Cover Song Identification using Music Harmony Features, Model and Complexity Analysis Author: Ladislav Maršík Department: Department of Software Engineering Supervisor: Prof. RNDr. Jaroslav Pokorný, CSc., Department of Software Engineering Abstract: Analysis of digital music and its retrieval based on the audio fe- atures is one of the popular topics within the music information retrieval (MIR) field. Every musical piece has its characteristic harmony structure, but harmony analysis is seldom used for retrieval. Retrieval systems that do not focus on similarities in harmony progressions may consider two versions of the same song different, even though they differ only in instrumentation or a singing voice. This thesis takes various paths in exploring, how music harmony can be used in MIR, and in particular, the cover song identification (CSI) task. We first create a music harmony model based on the knowledge of music theory. We define novel concepts: a harmonic complexity of a mu- sical piece, as well as the chord and chroma distance features. We show how these concepts can be used for retrieval, complexity analysis, and how they compare with the state-of-the-art of music harmony modeling. An extensive comparison of harmony features is then performed, using both the novel fe- atures and the...

Cluster analysis is one of the classification methods of multivariate statistical analysis. The task of this analysis is to classify the objects into clusters so that objects inside these clusters are as similar as possible. The aim of this study is to evaluate the success of the classification of objects using six hierarchical cluster analysis methods. To reflect the distance between the objects, are used squared Euclidean and Mahalanobis distances. The success methods are evaluated through the information, which cluster the object belongs to, and this information is already contained in the data files. This thesis pointed out that the Ward's method is one of the most successful hierarchical method in a classification of objects into clusters. This method has been more successful in sorting objects than the other hierarchical methods, both in the case of leaving the correlated variables in the data file as well as removing them. The results of this work show that the highest success of classification objects into clusters is when the data set is cleaned of correlated variables. If the data file is not cleaned, the methods reach better results when the distance between objects is measured by Euclidean metric.

Cluster analysis is a popular method of multivariate statistics. Based on mutual similarities between objects this method is able to classify and divide objects into several groups or clusters. The results of the clustering can be different by using different methods, measures of distance and procedures. The main aim of this thesis is to compare the results of several methods of cluster analysis with the known classification of classes from the original data file. In total, there are 15 data files, which were analyzed and each of them contained known information about the right allocation of objects in groups. The success of clustering of each method was calculated by comparing the known classification of classes and resulted clusters. In addition to the comparison of individual methods of cluster analysis was compared the impact of standardization and correlation to the success of each method. To reflect the distance betweeen the objects within each clusters, squared Euclidean distance was used. The results of this thesis point out that better success of clustering were achieved in the case of correlated variables in data file. The succes of clustering was higher about 2 percent points than in the case when correlated variables were deleted from data set. The methods divided 69,8 % objects before standardization and 70,8 % objects after standardization. The results also show a large importance of standardization in the case of Ward´s method. After standardization this method rank the most objects into correct classification classes and were more succesful, about nine percent points. In the case of correlated variables is the succes of the method 76,4 %. Standardization positively influences also centroid method and the method of farthest neighbour. Median method, nearest neighbour method and the method of average linkage achieve higher success of clustering in the case of original, nonstandardized variables (uneven variables).

The subject of this diploma thesis is the study of a sample position influence on results of an experiment in laser spectroscopy. The aim is to design an appropriate way for standardization of signal obtained at different conditions with the respect to its applicability for stand-off analysis. In the theoretical part of the diploma thesis there are the basics of LIBS method described together with the issues of stand-off experiment and both, basic and advanced approches for the processing and correction of obtained spectra. Also the experiment is designed here, which is used for the analysis of the sample inclination and distance influence on the detected signal. The choice of appropriate ways for the signal correction follows and their applicability and efficiency is then experimentally tested.

This work is about diploids and tetraploids of Vicia cracca species, the two commonly occurring cytotypes. The first part is devoted to the distribution of cytotypes of this species in the secondary range in North America. It was hypothesised that polyploid species become invasive more frequently than diploid species. Their greater success may be given by greater variability of genes obtained by polyploidisation and gene subfunkcionalizing. All invasive populations of Vicia cracca species involved in this study were tetraploid. Based on this we can say that only tetraploids are invasive in this secondary colonized area. Polyploid species can be better competitors thanks to their expected better growth characteristics and stress resistance. Therefore the second part of this work is testing the hypothesis that polyploids are more variable in size of different parts of the plant body and therefore more able to grow even in conditions that are not suitable for diploids. As predicted by the EICA hypothesis (evolution of increased competitive ability), secondary colonized area also provide more space for further evolution and we can expect that growth characteristics of plants from the invasive range will differ from plants of the same ploidy from the original distribution range. This part of the work...

2 ABSTRACT The degree of spatial activity, especially the home-range size, is one of the basic biolog- ical characteristics of animals and whether it has enough resources is crucial for the survival and reproduction of the individual. Therefore, it is not surprising that many studies trying to make clear the effect of various ecological and morphological variables and explain the varia- bility of space activities. Bats are a group of mammals, for which until recently, existed only few information about their spatial activity. However, due to the miniaturization of technology and the use of radiotelemetry amount of information rapidly increasing. The aim of this study was to assemble the most complete information about the home- range size and foraging distance of bats and analyze the effect of variables that can influence the spatial activity. From published papers I collected data on 106 species representing 8 fami- lies. The influence of 6 variables (weight, wing loading, aspect ratio, food specialization, colony size, primary productivity of environment) on home-range size and average foraging distance of bat was analysed by phylogenetic regression (PGLS). The best predictor of the home-range size is the primary productivity of the environment, food specialization and body size. The best explanation of...

Title: Analysis and comparison of boxing styles of elite amateur boxers from Cuba and Kazakhstan Objectives: The main goal of this thesis was to find out whether the frequency of use of punching techniques and the distance from which these punching techniques are used are statistically significant for the style of two the most successful countries in amateur boxing. The countries were compared in the use and success of the strikes and compared to their preference for long or medium combat distance. Methods: The method of quantitative observation was used, in which data was obtained by watching video recordings. Part of the matches was evaluated by recording the results manually on paper, the other part in the BORIS program. All data was then transcribed into a Microsoft Excel spreadsheet, where it was also processed. The source for the data were publicly available video recordings from top competitions in 2010-2020. Results: Differences between countries in the monitored indicators are insignificant and boxing styles do not differ much. In the frequency of the use of striking techniques between the rounds, a significant difference was found only between the first and second round of the Kazakhs. In the case of determining the preference for long and medium distance combat between the rounds, there...