This thesis deals with image object detection and its classification into classes. Classification is provided by models of framework for deep learning BVLC/Caffe. Object detection is provided by AlpacaDB/selectivesearch and belltailjp/selective_search_py algorithms. One of results of this thesis is modification and usage of deep convolutional neural network AlexNet in BVLC/Caffe framework. This model was trained with precision 51,75% for classification into 1 000 classes. Then it was modified and trained for classification into 20 classes with precision 75.50%. Contribution of this thesis is implementation of graphical interface for object detction and their classification into classes, which is implemented as aplication based on web server in Python language. Aplication integrates object detection algorithms mentioned abowe with classification with help of BVLC/Caffe. Resulting aplication can be used for both object detection (and classification) and for fast verification of any classification model of BVLC/Caffe. This aplication was published on server GitHub under license Apache 2.0 so it can be further implemented and used.

Final thesis titled Collective Intelligence and the Functions of Individual: Using an Example of Social Activism Online uses definition of collective intelligence by Pierre Lévy, and tries to verify it throught practice of social activism on the internet using a smartphone as a tool for accessing cyberspace. The theses is based on media theory works focusing in particular on a new kind of intelligence of community and the impact of new communication technologies on humans. Next part is about the topics of social activism, when considering together or independently with collective intelligence, provides the potential for direct democracy. Lastly there are few examples of social activism online or forerunners of direct democracy. As an important issue of collective intelligence in practice emerge the rules of behavior of individuals and Lévy's vision of collective intelligence as a peak of humanity.

This work deals with the issue of swarm intelligence as a subdiscipline of artificial intelligence. It describes biological background of the dilemma briefly and presents the principles of searching paths in ant colonies as well. There is also adduced combinatorial optimization and two selected tasks are defined in detail: Travelling Salesman Problem and Quadratic Assignment Problem. The main part of this work consists of description of swarm intelligence methods for solving mentioned problems and evaluation of experiments that were made on these methods. There were tested Ant System, Ant Colony System, Hybrid Ant System and Max-Min Ant System algorithm. Within the work there were also designed and tested my own method Genetic Ant System which enriches the basic Ant System i.a. with development of unit parameters based on genetical principles. The results of described methods were compared together with the ones of classical artificial intelligence within the frame of both solved problems.

The work deals with the possibility of interconnecting the teaching of mathematics with music. The theoretical part focuses on the relationship between mathematics and music, student motivation, the theory of multiple intelligence and also on whether music can contribute to the development of mathematical thinking. The practical part delivers five lesson preparations, where the main topic is music education and several other ways to use music education in another mathematical topic. KEYWORDS Music in mathematics, rhythm in mathematics, musical instruments in mathematics, motivation, word problems, equations, intersubject relations, Gardner's theory of multiple intelligence.

The intention of this diploma work is based on legacy of Master Peter de Letovic which is till now unknown. He worked at Prague University before initiation of the Hussite Revolution. The thesis proceed from his question Utrum cuiuslibet spiritus rationalis eadem essentia sit substantialiter ratio memoria et voluntas which gave him Master Matthew de Knin at quodlibet in the year 1409. The principal part of the thesis deal with a critic transcription and translation of manuscript from the codex UK Praha X H 18. The author, furthermore, attempt to interpret the question in a commentary and classify it in the context of philosophical thoughts at Prague University. Powered by TCPDF (www.tcpdf.org)

This thesis attempts to contribute to the general recognition of the phenomenon known as active audience that is generated by technical possibilities of contemporary digitalized media world collectively known as the era of Web 2.0. In this respect, the thesis follows the specific aspects, which accompany the transition from traditional ways of communication and methods of spreading information in the new and constantly evolving world of cyberspace. The thesis is based on the current general principles and theories, which are applied and compared in a relevant form at the Fan community site Slavistickenoviny.cz. The thesis follows two main directions. The first one focuses on the Web site as a product of citizen journalism. It deals with a comparison of the efforts of its authors with professional media outcomes. It also observes the rules, that are taken from the media and on the contrary evaluates differences. At the same time, the thesis deals with professional media taking over the amateur content. The second main aim focuses on a virtual community formed around the web itself. With application of qualitative research and discourse analyses, the thesis focuses on the search of internal mechanisms and the principles of the virtual community functioning. It reveals its overt and covert manifestations and...

This paper outlines the concept of labour in socialist Czechoslovakia of the 1960s. It examines on discourses of social and economic reforms and that of the post-Stalin era. The focus lays on main social, economic and ideological categories on which those projects based, on extent of their construction as well as on shifting the emphasis between their particular elements. The paper concerns above all conceivable relation of the newly shaped discourse to effort to reconstitute social differentiation and to overcome the social leveling of the previous Stalin era. An attempt will be made to connect Honnet's theory of recognition with G. Cohen's concept of egalitarian justice. From that perspective, the paper will examine historical tranformations of conceptions of justice, division of labour, a social ethos of different social groups (particullary the educated intelligentsia), legitimacy of given forms of redistribution etc.

Title: Level of Detail AI: a prototype of a large virtual world Author: David Skupien Department: Department of Software and Computer Science Education Supervisor: Mgr. Cyril Brom, Ph.D. Abstract: The Level Of Detail technique (LOD) is an established means of optimization in computer graphics. It uses the limitations of human perception to spare system resources. Progressively, this approach has found its use in artificial intelligence. This adaptation, commonly known as LOD AI, is used to optimize autonomous agent control in large virval worlds. This thesis consists of two parts. The first part deals with standing LOD AI uses, mostly focusing on the IVE project. The second part directly uses the IVE project to implement a LOD AI game using the LOD based reactive planning algorithm called S-GHRP over the ISMA representation. The above game is then tested on respondents to verify the practical usability of S-GHRP/ISMA. In its conclusion, this thesis briefly ponders the possibilities of further development of techniques used in the IVE project, based on previous findings. Keywords: artificial intelligence, LOD AI, virtual agent, large virtual world, IVE

Orientador: Irineu Bicudo / Banca: Antônio Marmo de Oliveira / Banca: Idania Blanca Peña Grass / Banca: Antonio Vicente Marafioti Garnica / Banca: Renata Cristina Geromel Meneghetti / Resumo: Este trabalho mostra um caminho para a mudança, na prática pedagógica, pela inserção da Lógica no currículo, como tema transdisciplinar, articulador do raciocínio e construtor da argumentação. A proposta é inverter o papel do "modo de pensar": de coadjuvante para protagonista. Quando as idéias forem veículos para os alunos compreenderem que podem pensar bem e reinventar idéias, os conteúdos serão menos esquecidos. Ensinando modos de pensar, otimizamos a capacidade de análise de quaisquer textos, tenham informações matemáticas ou não. Pela linguagem, construímos consensos que nos possibilitam viver em sociedade: quanto mais construímos sentidos para nossa vida, mais nos tornamos sujeitos históricos partícipes da realidade, assumindo posição na reconstrução dos discursos, passando da simples repetição das falas dos outros à nossa condição de autores, críticos e criativos. Que esta proposta possa ser um embrião para a Lógica passar a ser meio e método de transformação do conhecimento real pela análise crítica, contribuindo para um futuro melhor, ajudando os educadores a desenvolver em seus alunos as capacidades discursiva e argumentativa, o raciocínio e o senso crítico. / Abstract: This work shows a way to improve teachers posture by inserting "Logic" as a subject at regular schools programs. We understand 'Logic" as a thought articulator e and argumentation builder. The idea is to create a main role for the ways of how to think. When the ideas are tools for the students to understand they can think about and re-invent ideas, the contents taught will not be so quite forgotten. By teaching how to think, we optimize the analysis capacity of any texts, whether they involve mathematical issues or not. We build consenses that will make our life in society possible: the more we build sense to our life, the more aware we become of our role of citizens who should take part in the society's decisions, not by repeating other people's speeches, but creating our own, becoming authors, critics and creative. May this project be a seed so "Logic" can become a tool to change real knowledge by critical analysis, contributing to a better future, helping teachers to develop the speech and argumentation capacity of the students, improving their critical sense. / Doutor

Hoje em dia, com a privatização e aumento da competitividade no mercado elétrico, as empresas precisam encontrar formas de melhorar a qualidade do serviço e garantir lucratividade. A previsão de carga de curto prazo é uma atividade indispensável à operação que pode melhorar a segurança e diminuir custos de geração. A fim de realizar a previsão da carga, é necessária a identificação de padrões de comportamento de consumo e da sua relação com variáveis exógenas ao sistema tais como condições climáticas. Originalmente o problema foi resolvido de forma matemática e estatística através de técnicas tais como as séries numéricas, que fornecem bons resultados, mas utilizam processos complexos e de difícil modelamento. O surgimento das técnicas de inteligência artificial forneceu uma nova ferramenta capaz de lidar com a grande massa de dados das cargas e inferir por si mesmo a relação entre as variáveis do sistema. Notadamente, as redes neurais e a lógica fuzzy se destacaram como as técnicas mais adequadas, sendo que já vem sendo estudadas e utilizadas para a previsão de carga a mais de 20 anos. Este trabalho apresenta uma metodologia para a previsão da curva de carga diária de áreas elétricas através do uso de técnicas de inteligência artificial, mais especificamente as redes neurais. Inicialmente são apresentadas as principais técnicas de previsão sendo dado maior detalhamento as redes neurais e a lógica fuzzy. É feita a análise dos dados necessários à previsão e seu tratamento. Em seguida, o processo do uso de redes neurais e lógica fuzzy na previsão é descrito e é apresentado o desenvolvimento e resultados obtidos com o desenvolvimento e implementação de um sistema de previsão com redes neurais na concessionária CTEEP Transmissão Paulista. Como contribuição dessa tese, a transformada Wavelet é analisada como ferramenta para a filtragem e compactação de dados na previsão com redes neurais. / Nowadays, with privatization of utility companies and increase in competition in the energy market, companies must increase their service quality and ensure profits. Short term load forecasting is essential for operation of power systems and can increases security and reduces generation costs. Forecasting the load demands the identification of load patterns and its relations with exogenous variables such as weather. Originally, the problem was solved using mathematics and statistics with techniques such as time series, which produces good results but are complex and have a difficult modeling. With the advent of artificial intelligence techniques, new tools capable of dealing with large amounts of data and learn by themselves system variables relations were available. Artificial neural networks and fuzzy logic came up as the most suitable for load forecasting that have been tested and used for load forecasting for the last 20 years. This work presents a methodology for daily load forecasting of electrical areas using artificial intelligence techniques, specifically neural networks. At first, forecasting techniques are presented with emphasis on neural networks and fuzzy logic. Acquisition and treatment of data are analyzed. The load forecasting using neural networks and fuzzy logic is described and the results of the development and tests of a load forecasting system at CTEEP Transmissão Paulista presented. As contribution of this thesis, Wavelet transform is analyzed as a tool for denoising and data compression for neural network load forecasting.