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Web Server for Protein Secondary Structure Prediction
Villem, Lukáš ; Očenášek, Pavel (referee) ; Burgetová, Ivana (advisor)
This master’s thesis deals with protein secondary structure prediction. There is a theoretical introduction followed by study of available tools, proposal and implementation of web application, which combines functionality of several web tools used to predict secondary structure. User is asked to choose prediction methods and insert input sequence as plain text or upload a file. Results collected from selected tools serve to convert data into common format, show the result and create new type of prediction. Finally, the testing is applied and influences of tools are adjusted in order to increase percentage of prediction. The output of application is a result of prediction also available as plain text or as a file.
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Web Server for Protein Secondary Structure Prediction
Villem, Lukáš ; Očenášek, Pavel (referee) ; Burgetová, Ivana (advisor)
This master’s thesis deals with protein secondary structure prediction. There is a theoretical introduction followed by study of available tools, proposal and implementation of web application, which combines functionality of several web tools used to predict secondary structure. User is asked to choose prediction methods and insert input sequence as plain text or upload a file. Results collected from selected tools serve to convert data into common format, show the result and create new type of prediction. Finally, the testing is applied and influences of tools are adjusted in order to increase percentage of prediction. The output of application is a result of prediction also available as plain text or as a file.
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Predikce příjmů obecních rozpočtů
Kramoliš, Jakub ; Sedmihradská, Lucie (advisor) ; Kostohryz, Jiří (referee)
The subject of my bachelor thesis is the elaboration of a case study that deals with the preparation of the revenue side of the budget of the municipality Hodslavice. The main aim of my work is to determine the accuracy of the actual estimates of the municipality and to compare the accuracy of predictions of several statistical methods. I use these statistical methods: simple moving average, exponential smoothing, transformation moving average, regression against time with an exponential trend. Drawn from the analysis, I found that for the prediction of each type of revenue, there is a more accurate method than expert's assessment of the budget administrator in Hodslavice, but there can not be applies a single method of prediction for all types of revenues. The most accurate method for predicting taxes of individual revenues is exponential smoothing. However the differences between the predictions by this method and the expert's estimation of the administrator of the budget are minimal. Regression against time was the best in forecasting tax corporation income and value added tax. For real estate tax and non-tax revenue, which the municipality has at least some competence in influencing the future level of revenue appears to be the most accurate method of simple moving averages.
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The prediction of revenues of municipal budgets
Radilová, Marcela ; Sedmihradská, Lucie (advisor) ; Sedmihradská, Lucie (referee)
The core theme of this bachelor thesis is the prediction of revenues of municipal budgets. For this work I have chosen budgets from the town Humpolec. The main goal of this bachelor thesis is to describe how Humpolec prepares the revenue side of the budget and evaluate which one of the methods of prediction is suitable. These methods of prediction are: simple moving average, exponential smoothing, transformation moving average, regression against time and expert's assessment of the town Humpolec. During the calculation of prediction I determined that the expert's assessment is not the most ideal prediction method for all tax revenues. The expert's assessment is the right prediction method for all types of the individual income tax and for the corporation income tax paid by municipalities. For the value added tax and corporation income tax it would be more suitable use the regression against time method. Transformation moving average is the best for prediction of fees. It is more complicated with real estate tax, because no method of prediction emerged as a definitive "winner". For this kind of tax revenue I would choose either the expert's assessment or the regression against time method. Through my research I have demonstrated that it is not recommended to use one method of prediction for all revenues; rather, it is better to assess each section and choose the method of prediction best suited to the specific revenue type.
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