The capability to be able to determine the future progression on the worlds stock exchange is an important issue, which has become discernible in the last decades. An important role of this progression lies within the fast advancements in computerized technology.Aforementioned document describes a mechanism used for prediction of the future price of a certain stock. The strategy of trading is build upon this mechanism, and the core of this prediction system is an artificial neural network. Inputs used in this network are indicators derived from technical analysis. This trading system was implemented into historical trades and successfully tested.

Eukaryotní DNA se váže kolem nukleozomů, čím ovplyvnuje vyšši strukturu DNA a přístup k vazebním mistům pro všeobecní transkripční faktory a oblasti genů. Je proto důležité vědet, kde se nukleozomy vážou na DNA, a jak silná tato vazba je, abychom mohli porozumět mechanizmům regulace genů. V rámci projektu byla implementována nová metoda pro predikci nukleozomů založená na rozšíření Skrytých Markovových modelů, kde jako trénovací a testovací sada posloužila publikována data z Brogaard et al. (Brogaard K, Wang J-P, Widom, J. Nature 486(7404), 496-501 (2012). doi:10.1038/nature11142). Správne predikováno bylo zhruba 50% nukleozomů, co je porovnatenlný výsledek s existujícimi metodami. Okrem toho byla provedena řada experimentů popisující vlastnosti sekvencí nukleozomů a ich organizace.

This thesis discusses theoretical analysis of the origin of speech, introduces applications of speech technologies and explains the contemporary approach to phonetical transcription of speech recordings. Furthermore, it describes the metrics of audio recordings quality assessment, which is split into two discrete classes. The first one groups signal quality metrics, while the other one groups content richness metrics. The first goal of the practical section is to create a statistical model for accuracy prediction of machine transcription of speech recordings based on a measurement of their quality. The second goal is to evaluate which partial metrics are the most essential for accuracy prediction of machine transcription.

Diplomová práce se zabývá aplikací vybraných metod umělé inteligence v prostředí kapitálových, potažmo akciových, trhů. Konkrétně se zaměřuje na využití umělých neuronových sítí pro predikci trendu a na možnost aplikace genetických algoritmů k řešení problému optimalizace investičního portfolia. Obsahuje návrh řešení uvedených problémů v praxi. Návrhy jsou koncipovány ve formě modelů zpracovaných ve vývojovém prostředí Matlab.

The master‘s thesis examines the issue of the interconnection of market potential with financial indicators and other variables. Data from the financial statements of ABC, s. r. o. operating on the Slovak IT market are used. The dependence of market potential and other market variables was evaluated using statistical methods. Subsequently, the analysis of selected financial indicators of the company ABC, s. r. o. is statistically evaluated and the dependence with market potential is verified. Thanks to the results, the company's proposals are determined, taking into account the current situation in the world.

This diploma thesis deals with the issue of bankruptcy prediction of small and medium-sized enterprises operating in the manufacturing industry in selected Central European countries. The theoretical part of the thesis defines the concepts related to the prediction of bankruptcy and methods of model creation. The analytical part of the work includes testing the accuracy of selected bankruptcy model by other authors and creating a new bankruptcy model. The accuracy of the newly created model is then compared with the accuracy of selected models by other authors.

This thesis introduces company ABB Brno and its products. It describes the manufacturing process of a switchgear and it is focused at working procedures at particular points of the assembly line. The main part analyzes the root causes of the incompleteness of switchgears in the relation to the components availability. Time footprint was worked out. As a conclusion the proposal of changes in manufacturing process to improve the level of completeness are stated.

Diploma thesis deals with usage of artificial coordinate systems used for localization of a station on the internet and prediction of delay between the stations. There are described and compared basic properties of centralized and decentralized algorithms providing station localization on the internet and RTT prediction. More in depth are presented main representatives of both types of algorithms such as GNP, IDMAPS or Lighthouse. Central part of thesis is aimed at getting to know Vivaldi distributed algorithm. Basic principle of the algorithm for constant and variable time step, using two dimensional coordinate system with 3rd parameter height, is here outlined. Further more implementation of this algorithm as a library Vivaldi-lib in the environment of Java is implemented. Part of the thesis are simulations of behaviour of this algorithm for both variations realized on artificial networks and data obtained from PlanetLab experimental network, using simulation created program VIVALDIMONITOR.

Difficult problems are tasks which number of possible solutions increase exponentially or factorially. Application of common mathematical methods for finding proper solution in polynomial time is ineffective. Signal prediction is an example of diffucult problem. Signal is represented with a time serie and there is no explicit mathematical formula describing the signal. When genetic algorithms are applicated, they try to discover hidden patterns in time serie. These patterns can be used for prediction. Implication rules are used for discovery of these hidden patterns in time serie. Each rule is represented by one chromosome in population. Rules consist of two parts: conditional part and result part. Rules in population are compared with time serie and then the rules are evaluated according to their success in prediction. After the evaluation of rules, simulated evolution is started. Result of this evolution process is a group of rules which represent the most distinct patterns in time serie. These rules are then validated on validation set. Application is implemented in JAVA programming language.

This thesis is focused on methods for nodes localization in Internet using latency prediction in synthetic coordinates systems. Thesis also deal with methods, which latency prediction between nodes is based on other systems. Among such a methods particularly belongs King, which uses DNS (domain name service). Furthermore, thesis deal with relevance of overlay networks in latency prediction and their use for different services. Practical part of this thesis concentrates on method for latency prediction in synthetic coordinate system Global Network positioning. There were made two programs for counting coordinates of landmarks and hosts in this system. Measurements and calculations made in this thesis, are focused to determine accuracy of latency prediction of this method and their evaluation is made at the end of thesis.