Um ambiente de data warehousing oferece suporte ao processo de tomada de decisão. Ele consolida dados de fontes de informação distribuições, autônomas e heterogêneas em um único componente, o data warehouse, e realiza o processamento eficiente de consultas analíticas, denominadas OLAP (on-line analytical processing). Um data warehouse convencional armazena apenas dados alfanuméricos. Por outro lado, um data warehouse de imagens armazena, além desses dados convencionais, características intrínsecas de imagens, permitindo a realização de consultas analíticas estendidas com predicados de similaridade entre imagens. Esses ambientes demandam, portanto, a criação de estratégias que possibilitem o processamento eficiente dessas consultas complexas e custosas. Apesar de haver na literatura trabalhos voltados a índices bitmap para ambientes de data warehousing e métodos de acesso métricos para melhorar o desempenho de consultas por similaridade entre imagens, no melhor do nosso conhecimento, não há uma técnica que investigue essas duas questões em um mesmo contexto. Esta dissertação visa preencher essa lacuna na literatura por meio das seguintes contribuições: (i) proposta do ImageDWindex, um mecanismo para a otimização de consultas analíticas estendidas com predicados de similaridade entre imagens; e (ii) definição de diferentes estratégias de processamento de consultas sobre data warehouses de imagens usando o ImageDW-index. Para validar as soluções propostas, foram desenvolvidas duas outras contribuições secundárias, que são: (iii) o ImageDW-Gen, um gerador de dados com o objetivo de povoar o data warehouse de imagens; e (iv) a proposta de quatro classes de consulta, as quais enfocam em diferentes custos de processamento dos predicados de similaridade entre imagens. Utilizando o ImageDW-Gen, foram realizados testes de desempenho para investigar as vantagens introduzidas pelas estratégias propostas, de acordo com as classes de consultas definidas. Comparado com o trabalho mais correlato existente na literatura, o uso do ImageDWindex proveu uma melhora no desempenho do processamento de consultas IOLAP que variou em média de 55,57% até 82,16%, considerando uma das estratégias propostas. / A data warehousing environment offers support to the decision-making process. It consolidates data from distributed, autonomous and heterogeneous information sources into one of its main components, the data warehouse. Furthermore, it provides effcient processing of analytical queries (i.e. OLAP queries). A conventional data warehouse stores only alphanumeric data. On the other hand, an image data warehouse stores not only alphanumeric data but also intrinsic features of images, thus allowing data warehousing environments to perform analytical similarity queries over images. This requires the development of strategies to provide efficient processing of these complex and costly queries. Although there are a number of approaches in the literature aimed at the development of bitmap index for data warehouses and metric access methods for the efficient processing of similarity queries over images, to the best of our knowledge, there is not an approach that investigate these two issues in the same setting. In this research, we fill this gap in the literature by introducing the following main contributions: (i) the proposal of the ImageDW-index, an optimization mechanism aimed at the efficient processing of analytical queries extended with similarity predicates over images; and (ii) definition of different processing strategies for image data warehouses using the ImageDW-index. In order to validate these main proposals, we also introduce two secondary contributions, as follows: (iii) the ImageDW-Gen, a data generator to populate image data warehouses; and (iv) the proposal of four query classes, each one enforcing different query processing costs associated to the similarity predicates in image data warehousing environments. Using the ImageDW-Gen, performance tests were carried out in order to investigate the advantages introduced by the proposed strategies, according to the query classes. Compared to the most related work available in the literature, the ImageDW-index provided a performance gain that varied from 55.57% to 82.16%, considering one of the proposed strategies.

<p>This paper describes our game engine written in C++, using the DirectX libraries for graphics, sound and input. Since the engine is written using DirectX, an introduction to this system is given. The report gives a description of the structure of the game and the game kernel. Following this is a description of the graphics engine and its core components. The main focus of the engine is on the physics and how it is used in the game to simulate reality. Input is discussed briefly, with examples to show how it relates to the physics engine. Implementation of audio in the game engine is not described, but a general description of how sound is used in games is given. A theory for the basics of how artificial intelligence can be used in the engine is presented. The system for the architecture of the levels is described as is its connection to the graphics engine. The last section of the report is an evaluation and suggestions for what to do in the future. A user manual for the level editor is included as an appendix.</p>

The task of Data Mining is to find the useful information within the incredible sets of data. One of important research areas of Data Mining is Mining Sequential Patterns. For a transaction database, sequential pattern means that there are some relations between the items bought by customers in a period of time. If we can find these relations by mining sequential patterns, we can provide better selling strategy to gain more customers' attentions. However, since the transaction database contains a lot of data, and it will be scanned during the mining process again and again, to improve the running efficiency is an important topic. In the GSP algorithm proposed by Srikant and Agrawal, they use a complex data structure to store and generate candidates. The generated candidates satisfy a property, ``the subsets of a frequent itemset are also frequent'. The property leads to fewer number of candidates; however, it still spends too much time to counting candidates. In the SPAM algorithm proposed by Aryes et al., they use the bitwise operations to reduce the time for counting candidates. However, it generates too many candidates which will never become frequent itemsets, which decreases the efficiency. In this thesis, we proposed a new bitmap-based algorithm. By modifying the way to generate candidates in the GSP algorithm and applying the bitwise operations in the SPAM algorithm, the proposed algorithm can mine sequential patterns efficiently. That is, we use the similar candidate generation method presented in the GSP algorithm to reduce the number of candidates and the similar counting method proposed in the SPAM algorithm to reduce the time of counting candidates. In the proposed algorithm, we classify the itemsets into two cases, simultaneous occurrence (noted as AB) and sequential occurrence (noted as A-> B). In the case of simultaneous occurrence, the number of candidate is C(n,k) based on the exhausted method. In order to prevent too many candidates generated, we make use of the property, ``the subsets of a frequent itemset are also frequent', to reduce the number of candidates from C(n,k) to C(y,k), k <= y < n. In the case of sequential occurrence, the candidates are generated by using a special join operation which could combine, for example, A->B and B->C to A->B->C. Moreover, we have to consider two other cases: (1) combing A->B and A->C to A->BC; (2) combing A->C and B->C to AB->C. The method of counting candidates is similar to the SPAM algorithm (i.e., bitwise operations). From our simulation results, based on the same bit representation for the transaction database, we show that our proposed algorithm could provide better performance than the SPAM algorithm in terms of the processing time, since our algorithm could generate fewer number of candidates than the SPAM algorithm.

This paper describes our game engine written in C++, using the DirectX libraries for graphics, sound and input. Since the engine is written using DirectX, an introduction to this system is given. The report gives a description of the structure of the game and the game kernel. Following this is a description of the graphics engine and its core components. The main focus of the engine is on the physics and how it is used in the game to simulate reality. Input is discussed briefly, with examples to show how it relates to the physics engine. Implementation of audio in the game engine is not described, but a general description of how sound is used in games is given. A theory for the basics of how artificial intelligence can be used in the engine is presented. The system for the architecture of the levels is described as is its connection to the graphics engine. The last section of the report is an evaluation and suggestions for what to do in the future. A user manual for the level editor is included as an appendix.

In my master's thesis I start fromthedescriptionofthebasics and thebeginningsofsteganography, itsmethods and purposes. Detaileddescriptionof BMP fileswithhidden data follows. A filestructureisanalysedintothesmallestdetails to avoiddamagingfilewhilehiding. At thesametime to make profit oftheinformationincluded in a fileheader in the most effectiveway. Anotheraimwas to explain a principalofsteganographicalmethoditself, usedforhiding data into BMP file. Based on these findings, a programmeconceptwasdesigned and consequentlythatprogrammewas made. Itcarriesoutthehiding and revealing data intothe image files. Directionsfor use are made to thisprogramme and thereisalso a demo ofthefeaturesdescribingeach step. At the end ofmymaster's thesis anattentionispaid to thoseinfluencesthatcanbelimitingforthismethod. Exceeding these limitswouldlead to breakingthesteganographicalmethod, whichmeansrevealingthehidden data.

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The objective of this master's thesis is to design and implement a system which would be able to transfer a picture (either a bitmap or a vector image) on a foundational material. The main part of the apparatus consists of a plotter controlled by two stepping motors. The engraving itself is provided by a marker mounted to a movable part of engraving head. There was a PCB created for controlling the entire system. It contains power supplies, a microcontroller and motor and engraving head controlling circuits. The second part of the thesis shows a microcontroller program and a user interface in a PC. The image is trasfered from the PC into the microcontroller where it is processed and, based on the controlling program, engraved to the material.

This thesis studies the optimization of diagnosis defects of the photovoltaic cells in the darkroom by the help of new operating software for the used CCD camera. First the present situation and the possible solutions are analyzed. Then the attention is paid to the theory of light-sensitive CCD sensors, their construction, their principles of operation and the theory of scanning images. The thesis also focuses on the analysis of the function of the operating libraries which were provided by the equipment producer. The key part is the development of the application for the camera G2-3200 of the "Moravske pristroje" company which significantly accelerates the work with the camera in the darkroom.