Submitted by Renata Lopes (renatasil82@gmail.com) on 2018-08-13T13:07:32Z No. of bitstreams: 1 fernandotadeudearaujolima.pdf: 30345992 bytes, checksum: 11b123f41224b7ae8946de219847f74e (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-08-13T13:08:14Z (GMT) No. of bitstreams: 1 fernandotadeudearaujolima.pdf: 30345992 bytes, checksum: 11b123f41224b7ae8946de219847f74e (MD5) / Made available in DSpace on 2018-08-13T13:08:14Z (GMT). No. of bitstreams: 1 fernandotadeudearaujolima.pdf: 30345992 bytes, checksum: 11b123f41224b7ae8946de219847f74e (MD5) Previous issue date: 2017-04-29 / PROQUALI (UFJF) / Esta investigação centra-se na elaboração de um sistema que articula métricas de avaliação de desempenho a recursos e funcionalidades algorítmico-paramétricas, de maneira a permitir analisar e otimizar diferentes aspectos relativos ao grau de eficiência e às possibilidades de operação de configurações geométricas e algébricas de uma determinada área urbana. Neste âmbito, esta tese aborda o uso de recursos computacionais e ferramentas algorítmicas especificamente elaboradas para mensurar a performance de áreas urbanas, sob a perspectiva de princípios objetivamente mensuráveis do Desenvolvimento Orientado pelo Transporte (DOT), um modelo de desenvolvimento urbano que visa a cidades mais autônomas e mais sustentáveis. Mais especificamente, a presente pesquisa visa a verificar como atributos mensuráveis, geométricos e algébricos (e, portanto, programáveis) do DOT podem ser implementados por meio de um modelo computacional que utiliza métodos de otimização para dar suporte à tomada de decisão no processo de projetos urbanos. Assim, este trabalho é orientado no sentido da elaboração de um sistema que possa ser integrado a processos de projeto urbano, fornecendo suporte à organização de bairros e cidades e contribuindo para o aprimoramento das possibilidades de análise e proposição em contextos urbanísticos. / This research focuses on the development of a system that articulates performance evaluation metrics to algorithmic-parametric features and functionalities, in order to analyze and optimize different aspects related to the degree of efficiency and to the possibilities of operation of geometric and algebraic configurations of a given urban area. In this context, this thesis deals with the use of computational resources and algorithmic tools specifically designed to assess the performance of urban areas, from the perspective of objectively measurable principles of Transit Oriented Development (TOD), an urban development model aimed at more autonomous and sustainable cities. More specifically, the present research aims at verifying how TOD's measurable, geometric and algebraic (and therefore programmable) attributes can be implemented through a computational model that uses optimization methods to support decision making in urban design processes. Thus, this work is oriented toward the elaboration of a system that can be integrated to urban design processes, providing support to the organization of neighborhoods and cities and contributing to the improvement of analysis and proposition possibilities in urbanistic contexts.

Unreliable communication channels are a practical reality. They add to the complexity of protocol design and verification. In this work, we consider noisy channels which can corrupt messages. We present an approach to model and verify protocols which combine error detection and error control to provide reliable communication over noisy channels. We call these protocols retransmission protocols as they achieve reliable communication through repeated retransmissions of messages. These protocols typically use cyclic redundancy checks and sliding window protocols for error detection and control respectively. We propose models of these protocols as regular transducers operating on bit strings. Deterministic streaming string transducers provide a natural way of modeling these protocols and formalizing correctness requirements. The verification problem is posed as functional equivalence between the protocol transducer and the specification transducer. Functional equivalence checking is decidable for this class of transducers and this makes the transducer models amenable to algorithmic verification. In our transducer models, message lengths and retransmission rounds are unbounded. We present case studies based on TinyOS serial communication and the HDLC retransmission protocol. We further extend our protocol models to capture the effects of a noisy channel with non-determinism. We present two non-deterministic yet decidable extensions of transducer models of retransmission protocols. For one of our models, we achieve decidable verification by bounding the retransmission rounds, whereas for the other, even retransmission rounds are unbounded.

Title: Solving Endgames in Large Imperfect-Information Games such as Poker Author: Bc. Karel Ha Department: Department of Applied Mathematics Supervisor: doc. Mgr. Milan Hladík, Ph.D., Department of Applied Mathematics Abstract: Endgames have a distinctive role for players. At the late stage of games, many aspects are finally clearly defined, deeming exhaustive analysis tractable. Specialised endgame handling is rewarding for games with perfect information (e.g., Chess databases pre-computed for entire classes of endings, or dividing Go board into separate independent subgames). An appealing idea would be to extend this approach to imperfect-information games such as the famous Poker: play the early parts of the game, and once the subgame becomes feasible, calculate an ending solution. However, the problem is much more complex for imperfect information. Subgames need to be generalized to account for information sets. Unfortunately, such a generalization cannot be solved straightaway, as it does not generally preserve optimality. As a consequence, we may end up with a far more exploitable strategy. There are currently three techniques to deal with this challenge: (a) disregard the problem entirely; (b) use a decomposition technique, which sadly retains only the same quality; (c) or formalize improvements of...

This thesis describes the development and setup of hybrid index structures. They are access methods for retrieval techniques in hybrid data spaces which are formed by one or more relational or normalised columns in conjunction with one non-relational or non-normalised column. Examples for these hybrid data spaces are, among others, textual data combined with geographical ones or data from enterprise content management systems. However, all non-relational data types may be stored as well as image feature vectors or comparable types. Hybrid index structures are known to function efficiently regarding retrieval operations. Unfortunately, little information is available about reorganisation operations which insert or update the row tuples. The fundamental research is mainly executed in simulation based environments. This work is written ensuing from a previous thesis that implements hybrid access structures in realistic database surroundings. During this implementation it has become obvious that retrieval works efficiently. Yet, the restructuring approaches require too much effort to be set up, e.g., in web search engine environments where several thousands of documents are inserted or modified every day. These search engines rely on relational database systems as storage backends. Hence, the setup of these access methods for hybrid data spaces is required in real world database management systems. This thesis tries to apply a systematic approach for the optimisation of the rearrangement algorithms inside realistic scenarios. Thus, a measurement and evaluation scheme is created which is repeatedly deployed to an evolving state and a model of hybrid index structures in order to optimise the regrouping algorithms to make a setup of hybrid index structures in real world information systems possible. Thus, a set of input corpora is selected which is applied to the test suite as well as an evaluation scheme. To sum up, it can be said that this thesis describes input sets, a test suite including an evaluation scheme as well as optimisation iterations on reorganisation algorithms reflecting a theoretical model framework to provide efficient reorganisations of hybrid index structures supporting multimedia search criteria.

The presented work deals with analysis and implementation of algorithmic trading applications based on client requirements. Applications developed in this work are supposed to be used to collect and manage data from the stock exchange, to view information about active trading orders, and to send trading orders to the exchange via the API from Interactive Brokers. The first chapter gives an overview of selected books focused on developing applications for C # and analysis. Then the concepts of UML, OOAD, and UP are introduced. In the next chapter, requirements of the customer are defined. In the following chapter, based on the results of literature research and defined client requirements, the initial architectural design is created and cases of use with subsequent specifications are presented. This section is followed by finding analytical classes, creating a domain model, implementation of some use cases using sequence diagrams. The last two chapters describe the implementation details - the language used, the libraries, database schema, and user manual.

Diploma thesis is focused on research and description of current state of machine learning field, focusing on methods that can be used for prediction and classification of time series, which could be then applied in the algorithmic trading field. Reading of theoretical section should explain basic principles of financial markets, algorithmic trading and machine learning also to reader, which was previously familiar with the subject only very thoroughly. Main objective of application part is to choose appropriate methods and procedures, which match current state of art techniques in machine learning field. Next step is to apply it to historical price data. Result of application of selected methods is determination of their success at out of sample data that was not used during model calibration. Success of prediction was evaluated by accuracy metric along with Sharpe ratio of basic trading strategy that is based on model predictions. Secondary outcome of this work is to explore possibilities and test usability of technologies used in application part. Specifically is tested and used SciPy environment, that combines Python with packages and tools designed for data analysis, statistics and machine learning.

This master's thesis is focused on algorithmic trading on the forex market using artificial neural networks. In the introduction, there are generally described terms concerning the trading. Subsequently, in the following chapters, the thesis describes the theory of neural networks and their possible use. The practical part contains designed business strategies with neural networks. Inputs used in the network are indicators of technical analysis or directly price level. Business strategies have been implemented and tested. In the conclusion, there are summarized findings of individual business models.

This work is focused on description how the light impact human live, description of light sources and finally design and construction of light source with adjustable colour temperature and luminous flux. In introduction is mentioned the process of vision and how the light impact humans. In next part is characterization of currently used light sources, their construction, properties, benefits and drawback with their main parameters. Important part of this chapter is more extensive description of light emitting diodes with their operational parameters. The last two parts is focused on design and measuring the parameters of created light source with adjustable colour temperature and luminous flux and evaluating the results.

The main goal of this thesis is the analysis, design and implementation of a new system, which would be able to generate music in real-time, based on terrain data or any raster image. The thesis deals with history of development of various attempts to formalize musical composition and presents contemporary approaches to its algorithmic creation. Technique of constraint programming is explored as well, because it is suitable also for automatic composition, and it is a part of implemented solution. Application components (interface, generator, music core and sound unit) and their interactions are examined in more detail. All approaches used for generating music are described in depth and, moreover, they are supported by many pictures and practical examples. Musical outputs are tested and results of these tests outline strengths, weaknesses and also inner possibilities of the designed system. Conclusion summarises author's contribution to the field of computer generated music and reveals possible prospects for application usage and its extensions.

This diploma thesis delas with algoritmic trading using neural networks. In the first part, some basic information about stock trading, algorithmic trading and neural networks are given. In the second part, data sets of historical market data are used in trading simulation and also as training input of neural networks. Neural networks are used by automated strategy for predicting future stock price. Couple of automated strategies with different variants of neural networks are evaluated in the last part of this work.