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Natural toxins in food and their effect on human health
Houdková, Kristine ; Bušová, Milena (advisor) ; Schlenker, Anna (referee)
This bachelor thesis deals with the occurrence of natural toxic substances in food and describes their effect on human health. It focuses on toxic substances that are a natural part of plants, animals, and also on natural contaminants. This work is divided into theoretical and practical part. The aim of this work is to provide information and raise awareness about these substances, because they are an integral part of most foods. The purpose of the practical part is find out the level of public awareness of toxins in food and discover the frequency of mycotoxins appearences in food from the Rapid Alert System for Food and Feed (RASFF), which operates within the European Union. Mold toxins are a major worldwide problem, both in terms of public health and global economic. The research part of the work was carried out using a questionnaire survey through social networks. The general public seems to have a basic awareness of food safety and toxins substances in food. The bachelor thesis can serve as an informative and educational material for the public. Key words natural toxins - toxic substances - mycotoxins - alkaloids - poison
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IT Security in Biomedicine.
Schlenker, Anna ; Šárek, Milan (advisor) ; Nakládalová, Marie (referee) ; Brechlerová, Dagmar (referee)
Title: IT Security in Biomedicine Author: Ing. Anna Schlenker Supervisor: Ing. Milan Šárek, CSc. Abstract: The aim of this work is to propose a solution to the biomedical data security strategy. The work provides an overview of the most commonly used biometric methods designed to identify or authenticate users. From these methods, the keystroke dynamics was chosen and used in the application solution. The reliability of this method has been tested by classical and modern classification methods. The greatest benefit of the work is the use of the created application in combination with the measurement using integrated electromyography to objectify the evaluation of the work related to keyboard typing in terms of local muscle load. Keywords: Biometrics, Data Security, Keystroke Dynamics, Local Muscle Load
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Robustness of High-Dimensional Data Mining
Kalina, Jan ; Duintjer Tebbens, Jurjen ; Schlenker, Anna
Standard data mining procedures are sensitive to the presence of outlying measurements in the data. This work has the aim to propose robust versions of some existing data mining procedures, i.e. methods resistant to outliers. In the area of classification analysis, we propose a new robust method based on a regularized version of the minimum weighted covariance determinant estimator. The method is suitable for data with the number of variables exceeding the number of observations. The method is based on implicit weights assigned to individual observations. Our approach is a unique attempt to combine regularization and high robustness, allowing to downweight outlying high-dimensional observations. Classification performance of new methods and some ideas concerning classification analysis of high-dimensional data are illustrated on real raw data as well as on data contaminated by severe outliers.
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