A demanda por aplicações que processam vídeos digitais têm obtido atenção na indústria e na academia. Considerando a manipulação de um elevado volume de dados em vídeos de alta resolução, a compressão de vídeo é uma ferramenta fundamental para reduzir a quantidade de informações de modo a manter a qualidade viabilizando a respectiva transmissão e armazenamento. Diferentes padrões de codificação de vídeo foram desenvolvidos para impulsionar o desenvolvimento de técnicas avançadas para este fim, como por exemplo, o padrão H.264/AVC. Este padrão é considerado o estado-da-arte, pois proporciona maior eficiência em codificação em relação a padrões existentes (MPEG-4). Entre todas as ferramentas inovadoras apresentadas pelas mais recentes normas de codificação, a Estimação de Movimento (ME) é a técnica que provê a maior parcela dos ganhos. A ME busca obter a relação de similaridade entre quadros vizinhos de uma cena, porém estes ganhos são obtidos ao custo de um elevado custo computacional representando a maior parte da complexidade total dos codificadores atuais. O objetivo do trabalho é acelerar o processo de ME, principalmente quando vídeos de alta resolução são codificados. Esta aceleração concentra-se no uso de uma plataforma massivamente paralela, denominada GPU (Graphics Processing Unit). Os algoritmos da ME apresentam um elevado potencial de paralelização e são adequados para implementação em arquiteturas paralelas. Assim, diferentes algoritmos têm sido propostos a fim de diminuir o custo computacional deste módulo. Este trabalho apresenta a implementação e a exploração do paralelismo de dois algoritmos da ME em GPU, focados na codificação de vídeo de alta definição e no processamento em tempo real. O algoritmo Full Search (FS) é conhecido como algoritmo ótimo, pois encontra os melhores resultados a partir de uma busca exaustiva entre os quadros. O algoritmo rápido Diamond Search (DS) reduz significativamente a complexidade da ME mantendo a qualidade de vídeo próxima ao desempenho apresentado pelo FS. A partir da exploração máxima do paralelismo dos algoritmos FS e DS e do processamento paralelo disponível nas GPUs, este trabalho apresenta um método para mapear estes algoritmos em GPU, considerando a arquitetura CUDA (Compute Unified Device Architecture). Para avaliação de desempenho, as soluções CUDA são comparadas com as respectivas versões multi-core (utilizando biblioteca OpenMP) e distribuídas (utilizando MPI como infraestrutura de suporte). Todas as versões foram avaliadas em diferentes resoluções e os resultados foram comparados com algoritmos da literatura. As implementações propostas em GPU apresentam aumentos significativos, em termos de desempenho, em relação ao software de referência do codificador H.264/AVC e, além disso, apresentam ganhos expressivos em relação às respectivas versões multi-core, distribuída e trabalhos GPGPU propostos na literatura. / The demand for applications processing digital videos has become the focus of attention in industry and academy. Considering the manipulation of the high volume of data contained in high resolution digital videos, video compression is a fundamental tool for reduction in the amount of information in order to maintain the quality and, thus enabling its respective transfer and storage. As to obtain the development of advanced video coding techniques, different standards of video encoding were developed, for example, the H.264/AVC. This standard is considered the state-of-art for proving high coding efficiency compared to previous standards (MPEG-4). Among all innovative tools featured by the latest video coding standards, the Motion Estimation is the technique that provides the most important coding gains. ME searches obtain the similarity relation between neighboring frames of the one scene. However, these gains were obtained by the elevated computational cost, representing the greater part of the total complexity of the current encoders. The goal of this project is to accelerate the Motion Estimation process, mainly when high resolution digital videos were encoded. This acceleration focuses on the use of a massively parallel platform called GPU (Graphics Processing Unit). The Motion Estimation block matching algorithms present a high potential for parallelization and are suitable for implementation in parallel architectures. Therefore, different algorithms have been proposed to decrease the computational complexity of this module. This work presents the implementation and parallelism exploitation of two motion estimation algorithms in GPU focused in encoding high definition video and the real time processing. Full Search algorithm (FS) is known as optimal since it finds the best match by exhaustively searching between frames. The fast Diamond Search algorithm reduces significantly the ME complexity while keeping the video quality near FS performance. By exploring the maximum inherent parallelism of FS and DS and the available parallel processing capability of GPUs, this work presents an efficient method to map out these algorithms onto GPU considering the CUDA architecture (Compute Unified Device Architecture). For performance evaluation, the CUDA solutions are compared with respective multi-core (using OpenMP library) and distributed (using MPI as supporting infrastructure) versions. All versions were evaluated in different video resolutions and the results were compared with algorithms found in the literature. The proposed implementations onto GPU present significant increase, in terms of performance, in relation with the H.264/AVC encoder reference software and, moreover, present expressive gains in relation with multi-core, distributed versions and GPGPU alternatives proposed in literature.

Orientador: Antonio Carlos Moretti / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-06T12:59:52Z (GMT). No. of bitstreams: 1 Sousa_VaniaNobrede_M.pdf: 984501 bytes, checksum: f58d5baf5c8e4dc8e704f4cb9aa47c6b (MD5) Previous issue date: 2006 / Mestrado / Matematica Aplicada / Mestre em Matemática Aplicada

A maior parte dos trabalhos sobre substituição de moeda encontra como fonte geradora deste fenômeno a diferença de capacidade entre as diferentes moedas em manterem os seus valores ao longo do tempo. Existe, entretanto, um aspecto pouco explorado nesta literatura. É necessário estudar a relação entre o grau de integração comercial e o processo de substituição de moeda. Em concordância com esta necessidade, o objetivo desta dissertação consiste em analisar os impactos sobre a demanda pelas moedas nacionais decorrentes de um processo de integração comercial, focalizando sobre o motivo transacional da demanda por moeda. Para isto, desenvolvem-se dois modelos de equilíbrio geral dinâmico com trocas descentralizadas (search) em economia aberta. De acordo com os resultados obtidos, elevados níveis de integração comercial podem deflagrar um processo de substituição de moeda em que o meio de pagamento estrangeiro passa a ser utilizado também em trocas envolvendo apenas indivíduos domésticos. Daí se seguem importantes mudanças de preços relativos e novas condições sobre a condução da política monetária. / Most works on currency substitution finds the origin of this phenomenon at the difference of money prices inflation between two currencies. However, there is a remaining issue. It is necessary to study the relation between the degree of commercial integration and the currency substitution process. In accordance to this need, the purpose of this dissertation consists in analyzing the impacts upon national currency demand due to a process of commercial integration, focusing on the transactional demand for money. To accomplish that, two open economy dynamic general equilibrium with decentralized exchanges (search) models are developed. According to the results, high levels of commercial integration may start a process where the foreign currency is used as a medium-of-exchange for trades between domestic agents. Moreover, there are important relative prices changes and relevant consequences upon monetary policy making.

There are two symmetrical resolution rules applicable to logic programs - SL-resolution which yields a top-down refutation and unit-resolution which yields a bottom-up refutation. Both resolution principles need to be coupled with a search rule before they can be used in practice. The search rule determines in which order program clauses are used in the refutation and affects both performance, completeness and quality of solutions. The thesis surveys exhaustive and heuristic search rules for SL-resolution and transformation techniques for (general) logic programs that makes unit-resolution goal oriented. The search rules were implemented as meta-interpreters for Prolog and were benchmarked on a suite of programs incorporating both deterministic and nondeterministic code. Whenever deemed applicable benchmark programs were permuted with respect to clause and goal ordering to see if it affected the interpreters performance and termination. With the help of the evaluation the conclusion was that alternative search rules for SL-resolution should not be used for performance gains but can in some cases greatly improve the quality of solutions, e.g. in planning or other applications where the quality of an answer correlates with the length of the refutation. It was also established that A* is more flexible than exhaustive search rules since its behavior can be fine-tuned with weighting, and can in some cases be more efficient than both iterative deepening and breadth-first search. The bottom-up interpreter based on unit-resolution and magic transformation had several advantages over the top-down interpreters. Notably for programs where subgoals are recomputed many times. The great disparity in implementation techniques made direct performance comparisons hard however, and it is not clear if even an optimized bottom-up interpreter is competitive against a top-down interpreter with tabling of answers.

This thesis explores the possibility of estimating the outcome of a flight ticket fare comparison search, also called flight meta search, before it has been performed, as being able to do thiscould be highly useful in improving the flight meta search technology used today. The algorithm explored in this thesis is a distance weighted k-nearest neighbour, where the distance metric is a linear equation with sixteen features of first degree extracted from the input of the search. It is found that while the approach may have potential, the distance metric used in this thesis isnot sufficient to capture the similarities needed, and the end algorithm performs only slightly better than random. At the end of this thesis a series of possible further improvements are presented, that could potentially help improve the performance of the algorithm to a level that would be more useful.

Graph-structured databases are widely prevalent, and the problem of effective search and retrieval from such graphs has been receiving much attention recently. For example, the Web can be naturally viewed as a graph. Likewise, a relational database can be viewed as a graph where tuples are modeled as vertices connected via foreign-key relationships. Keyword search querying has emerged as one of the most effective paradigms for information discovery, especially over HTML documents in the World Wide Web. One of the key advantages of keyword search querying is its simplicity – users do not have to learn a complex query language, and can issue queries without any prior knowledge about the structure of the underlying data. The purpose of this dissertation was to develop techniques for user-friendly, high quality and efficient searching of graph structured databases. Several ranked search methods on data graphs have been studied in the recent years. Given a top-k keyword search query on a graph and some ranking criteria, a keyword proximity search finds the top-k answers where each answer is a substructure of the graph containing all query keywords, which illustrates the relationship between the keyword present in the graph. We applied keyword proximity search on the web and the page graph of web documents to find top-k answers that satisfy user’s information need and increase user satisfaction. Another effective ranking mechanism applied on data graphs is the authority flow based ranking mechanism. Given a top-k keyword search query on a graph, an authority-flow based search finds the top-k answers where each answer is a node in the graph ranked according to its relevance and importance to the query. We developed techniques that improved the authority flow based search on data graphs by creating a framework to explain and reformulate them taking in to consideration user preferences and feedback. We also applied the proposed graph search techniques for Information Discovery over biological databases. Our algorithms were experimentally evaluated for performance and quality. The quality of our method was compared to current approaches by using user surveys.

Search engine algorithms are constantly improved in order to provide the highest quality and most relevant results for the user. Google algorithm updates called Panda and Penguin have recently been one of the most significant and many websites that use black hat SEO techniques were hit by them. Nowadays, using this search optimization's techniques raises the risk of Google penalty, which in most of the cases cause decrease in traffic from organic search. The aim of this thesis is to describe techniques of search engine optimization (SEO) and their possible impact on website's ranking. The thesis also aims to verify whether Penguin and Panda updates have the impact on websites for which the methods of black hat SEO have been used and specify the result of this impact. In the theoretical part of this thesis it is described function of search engines Seznam.cz and Google, their algorithm change in history and possible factors on which the ranking score is based. Briefly are also described tools, which can be used to identify and analyze possible causes of penalization. After reading this thesis, the reader will have a basic orientation in search engine optimization methods and their appropriate use. Also, he will be able to recognize possible causes of Google penalty and propose an appropriate strategy for its removal.

O Job Shop Scheduling Problem é um problema NP-Difícil que chama a atenção de muitos pesquisadores devido seu desafio matemático e sua aplicabilidade em contextos reais. Geralmente, principalmente em cenários próximos aos de fábricas e indústrias, obter um escalonamento ótimo por meio de métodos computacionais exatos implica em um alto desprendimento de tempo. Em contrapartida, devido às exigências de um mercado cada vez mais competitivo, as decisões de onde, como, quando e com o que produzir devem ser tomadas rapidamente. O presente trabalho propõe o desenvolvimento de um método heurístico Beam Search para solucionar o Job Shop Scheduling Problem e o Flexible Job Shop Scheduling Problem. Para isso, inicialmente um algoritmo do tipo list scheduling é definido e então o método Beam Search é construído baseado neste algoritmo. Os métodos propostos foram avaliados em diferentes níveis de complexidade utilizando instâncias da literatura que retratam diferentes cenários de planejamento. Em linhas gerais, as soluções encontradas se mostraram bastante competitivas quando comparadas a outras soluções da literatura. / The Job Shop Scheduling Problem is a NP-Hard problem which draws the attention of researchers due to both its mathematical challenge and its applicability in real contexts. Usually, mainly in industry and factory environments, an optimal schedule got by the use of exact computational methods implies in a long spending time. On the other hand, due to a more and more competitive marketplace, the decisions on where, how, when and with which to produce must be taken quickly. The present work proposes the development of an heuristic Beam Search method to solve both the Job Shop Scheduling Problem and the Flexible Job Shop Scheduling Problem. To that end, at rst a list scheduling algorithm is dened and then the Beam Search method is built based on the list scheduling algorithm. The proposed methods were evaluated over dierent complexity levels using instances from the literature that report dierent planning environments. In general terms, the solutions implemented have been proved very competitive when compared against other solutions in the literature.

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京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第22805号 / 情博第735号 / 新制||情||126(附属図書館) / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 吉川 正俊, 教授 森 信介, 教授 田島 敬史 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM