MARISA-MDD: uma abordagem para transformações entre modelos orientados a aspectos: dos requisitos ao projeto detalhado

Aspect Oriented approaches associated to different activities of the software development process are, in general, independent and their models and artifacts are not aligned and inserted in a coherent process. In the model driven development, the various models and the correspondence between them are rigorously specified. With the integration of aspect oriented software development (DSOA) and model driven development (MDD) it is possible to automatically propagate models from one activity to another, avoiding the loss of information and important decisions established in each activity. This work presents MARISA-MDD, a strategy based on models that integrate aspect-oriented requirements, architecture and detailed design, using the languages AOV-graph, AspectualACME and aSideML, respectively. MARISA-MDD defines, for each activity, representative models (and corresponding metamodels) and a number of transformations between the models of each language. These transformations have been specified and implemented in ATL (Atlas Definition Language), in the Eclipse environment. MARISA-MDD allows the automatic propagation between AOV-graph, AspectualACME, and aSideML models. To validate the proposed approach two case studies, the Health Watcher and the Mobile Media have been used in the MARISA-MDD environment for the automatic generation of AspectualACME and aSideML models, from the AOV-graph model

Implementação Hardware/Software da estimação de movimento segundo o padrão H.264

Motion estimation is the main responsible for data reduction in digital video encoding. It is also the most computational damanding step. H.264 is the newest standard for video compression and was planned to double the compression ratio achievied by previous standards. It was developed by the ITU-T Video Coding Experts Group (VCEG) together with the ISO/IEC Moving Picture Experts Group (MPEG) as the product of a partnership effort known as the Joint Video Team (JVT). H.264 presents novelties that improve the motion estimation efficiency, such as the adoption of variable block-size, quarter pixel precision and multiple reference frames. This work defines an architecture for motion estimation in hardware/software, using a full search algorithm, variable block-size and mode decision. This work consider the use of reconfigurable devices, soft-processors and development tools for embedded systems such as Quartus II, SOPC Builder, Nios II and ModelSim

JFloat: uma biblioteca de ponto flutuante para a linguagem Java com suporte a arredondamento direcionado

This work presents JFLoat, a software implementation of IEEE-754 standard for binary floating point arithmetic. JFloat was built to provide some features not implemented in Java, specifically directed rounding support. That feature is important for Java-XSC, a project developed in this Department. Also, Java programs should have same portability when using floating point operations, mainly because IEEE-754 specifies that programs should have exactly same behavior on every configuration. However, it was noted that programs using Java native floating point types may be machine and operating system dependent. Also, JFloat is a possible solution to that problem

Uma análise da aplicação do modelo de Rede Neural RePART em Comitês de classificadores

RePART (Reward/Punishment ART) is a neural model that constitutes a variation of the Fuzzy Artmap model. This network was proposed in order to minimize the inherent problems in the Artmap-based model, such as the proliferation of categories and misclassification. RePART makes use of additional mechanisms, such as an instance counting parameter, a reward/punishment process and a variable vigilance parameter. The instance counting parameter, for instance, aims to minimize the misclassification problem, which is a consequence of the sensitivity to the noises, frequently presents in Artmap-based models. On the other hand, the use of the variable vigilance parameter tries to smoouth out the category proliferation problem, which is inherent of Artmap-based models, decreasing the complexity of the net. RePART was originally proposed in order to minimize the aforementioned problems and it was shown to have better performance (higer accuracy and lower complexity) than Artmap-based models. This work proposes an investigation of the performance of the RePART model in classifier ensembles. Different sizes, learning strategies and structures will be used in this investigation. As a result of this investigation, it is aimed to define the main advantages and drawbacks of this model, when used as a component in classifier ensembles. This can provide a broader foundation for the use of RePART in other pattern recognition applications

Visual IMML: um perfil UML para a modelagem de interfaces de usuário

The software development processes proposed by the most recent approaches in Software Engineering make use old models. UML was proposed as the standard language for modeling. The user interface is an important part of the software and has a fundamental importance to improve its usability. Unfortunately the standard UML does not offer appropriate resources to model user interfaces. Some proposals have already been proposed to solve this problem: some authors have been using models in the development of interfaces (Model Based Development) and some proposals to extend UML have been elaborated. But none of them considers the theoretical perspective presented by the semiotic engineering, that considers that, through the system, the designer should be able to communicate to the user what he can do, and how to use the system itself. This work presents Visual IMML, an UML Profile that emphasizes the aspects of the semiotic engineering. This Profile is based on IMML, that is a declarative textual language. The Visual IMML is a proposal that aims to improve the specification process by using a visual modeling (using diagrams) language. It proposes a new set of modeling elements (stereotypes) specifically designed to the specification and documentation of user interfaces, considering the aspects of communication, interaction and functionality in an integrated manner

Prova automática de satisfatibilidade módulo teoria aplicada ao método B

Este trabalho apresenta uma extensão do provador haRVey destinada à verificação de obrigações de prova originadas de acordo com o método B. O método B de desenvolvimento de software abrange as fases de especificação, projeto e implementação do ciclo de vida do software. No contexto da verificação, destacam-se as ferramentas de prova Prioni, Z/EVES e Atelier-B/Click n Prove. Elas descrevem formalismos com suporte à checagem satisfatibilidade de fórmulas da teoria axiomática dos conjuntos, ou seja, podem ser aplicadas ao método B. A checagem de SMT consiste na checagem de satisfatibilidade de fórmulas da lógica de primeira-ordem livre de quantificadores dada uma teoria decidível. A abordagem de checagem de SMT implementada pelo provador automático de teoremas haRVey é apresentada, adotando-se a teoria dos vetores que não permite expressar todas as construções necessárias às especificações baseadas em conjuntos. Assim, para estender a checagem de SMT para teorias dos conjuntos destacam-se as teorias dos conjuntos de Zermelo-Frankel (ZFC) e de von Neumann-Bernays-Gödel (NBG). Tendo em vista que a abordagem de checagem de SMT implementada no haRVey requer uma teoria finita e pode ser estendida para as teorias nãodecidíveis, a teoria NBG apresenta-se como uma opção adequada para a expansão da capacidade dedutiva do haRVey à teoria dos conjuntos. Assim, através do mapeamento dos operadores de conjunto fornecidos pela linguagem B a classes da teoria NBG, obtem-se uma abordagem alternativa para a checagem de SMT aplicada ao método B

Um middleware reflexivo e orientado a aspectos: arquitetura e implementações

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Aplicação de ontologias para métodos de negociação de um sistema multiagente para o reconhecimento de padrões

The use of intelligent agents in multi-classifier systems appeared in order to making the centralized decision process of a multi-classifier system into a distributed, flexible and incremental one. Based on this, the NeurAge (Neural Agents) system (Abreu et al 2004) was proposed. This system has a superior performance to some combination-centered methods (Abreu, Canuto, and Santana 2005). The negotiation is important to the multiagent system performance, but most of negotiations are defined informaly. A way to formalize the negotiation process is using an ontology. In the context of classification tasks, the ontology provides an approach to formalize the concepts and rules that manage the relations between these concepts. This work aims at using ontologies to make a formal description of the negotiation methods of a multi-agent system for classification tasks, more specifically the NeurAge system. Through ontologies, we intend to make the NeurAge system more formal and open, allowing that new agents can be part of such system during the negotiation. In this sense, the NeurAge System will be studied on the basis of its functioning and reaching, mainly, the negotiation methods used by the same ones. After that, some negotiation ontologies found in literature will be studied, and then those that were chosen for this work will be adapted to the negotiation methods used in the NeurAge.

Deciding difference logic in a Nelson-Oppen combination framework

O método de combinação de Nelson-Oppen permite que vários procedimentos de decisão, cada um projetado para uma teoria específica, possam ser combinados para inferir sobre teorias mais abrangentes, através do princípio de propagação de igualdades. Provadores de teorema baseados neste modelo são beneficiados por sua característica modular e podem evoluir mais facilmente, incrementalmente. Difference logic é uma subteoria da aritmética linear. Ela é formada por constraints do tipo x − y ≤ c, onde x e y são variáveis e c é uma constante. Difference logic é muito comum em vários problemas, como circuitos digitais, agendamento, sistemas temporais, etc. e se apresenta predominante em vários outros casos. Difference logic ainda se caracteriza por ser modelada usando teoria dos grafos. Isto permite que vários algoritmos eficientes e conhecidos da teoria de grafos possam ser utilizados. Um procedimento de decisão para difference logic é capaz de induzir sobre milhares de constraints. Um procedimento de decisão para a teoria de difference logic tem como objetivo principal informar se um conjunto de constraints de difference logic é satisfatível (as variáveis podem assumir valores que tornam o conjunto consistente) ou não. Além disso, para funcionar em um modelo de combinação baseado em Nelson-Oppen, o procedimento de decisão precisa ter outras funcionalidades, como geração de igualdade de variáveis, prova de inconsistência, premissas, etc. Este trabalho apresenta um procedimento de decisão para a teoria de difference logic dentro de uma arquitetura baseada no método de combinação de Nelson-Oppen. O trabalho foi realizado integrando-se ao provador haRVey, de onde foi possível observar o seu funcionamento. Detalhes de implementação e testes experimentais são relatados

Algoritmos de agrupamento aplicados a dados de expressão gênica de câncer: um estudo comparativo

The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using classic clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. This work presents the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods

Uma arquitetura de referência para o desenvolvimento de sistemas interativos multiplataformas

It is increasingly common use of a single computer system using different devices - personal computers, telephones cellular and others - and software platforms - systems graphical user interfaces, Web and other systems. Depending on the technologies involved, different software architectures may be employed. For example, in Web systems, it utilizes architecture client-server - usually extended in three layers. In systems with graphical interfaces, it is common architecture with the style MVC. The use of architectures with different styles hinders the interoperability of systems with multiple platforms. Another aggravating is that often the user interface in each of the devices have structure, appearance and behaviour different on each device, which leads to a low usability. Finally, the user interfaces specific to each of the devices involved, with distinct features and technologies is a job that needs to be done individually and not allow scalability. This study sought to address some of these problems by presenting a reference architecture platform-independent and that allows the user interface can be built from an abstract specification described in the language in the specification of the user interface, the MML. This solution is designed to offer greater interoperability between different platforms, greater consistency between the user interfaces and greater flexibility and scalability for the incorporation of new devices

Construção de mosaicos georreferenciados usando imagens aéreas de pequeno formato

In this work we propose a technique that uses uncontrolled small format aerial images, or SFAI, and stereohotogrammetry techniques to construct georeferenced mosaics. Images are obtained using a simple digital camera coupled with a radio controlled (RC) helicopter. Techniques for removing common distortions are applied and the relative orientation of the models are recovered using projective geometry. Ground truth points are used to get absolute orientation, plus a definition of scale and a coordinate system which relates image measures to the ground. The mosaic is read into a GIS system, providing useful information to different types of users, such as researchers, governmental agencies, employees, fishermen and tourism enterprises. Results are reported, illustrating the applicability of the system. The main contribution is the generation of georeferenced mosaics using SFAIs, which have not yet broadly explored in cartography projects. The proposed architecture presents a viable and much less expensive solution, when compared to systems using controlled pictures

Utilizando mapas de conectividade fuzzy no desenvolvimento de algoritmos reparadores de imagens binárias 3D

A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed. These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices

Dilema da diversidade-acurácia: um estudo empírico no contexto de multiclassificadores

Multi-classifier systems, also known as ensembles, have been widely used to solve several problems, because they, often, present better performance than the individual classifiers that form these systems. But, in order to do so, it s necessary that the base classifiers to be as accurate as diverse among themselves this is also known as diversity/accuracy dilemma. Given its importance, some works have investigate the ensembles behavior in context of this dilemma. However, the majority of them address homogenous ensemble, i.e., ensembles composed only of the same type of classifiers. Thus, motivated by this limitation, this thesis, using genetic algorithms, performs a detailed study on the dilemma diversity/accuracy for heterogeneous ensembles

Uma abordagem baseada em aspectos e composição dinâmica para a construção de aplicações adaptativas cientes ao contexto

Ubiquitous computing systems operate in environments where the available resources significantly change during the system operation, thus requiring adaptive and context aware mechanisms to sense changes in the environment and adapt to new execution contexts. Motivated by this requirement, a framework for developing and executing adaptive context aware applications is proposed. The PACCA framework employs aspect-oriented techniques to modularize the adaptive behavior and to keep apart the application logic from this behavior. PACCA uses abstract aspect concept to provide flexibility by addition of new adaptive concerns that extend the abstract aspect. Furthermore, PACCA has a default aspect model that considers habitual adaptive concerns in ubiquitous applications. It exploits the synergy between aspect-orientation and dynamic composition to achieve context-aware adaptation, guided by predefined policies and aim to allow software modules on demand load making possible better use of mobile devices and yours limited resources. A Development Process for the ubiquitous applications conception is also proposed and presents a set of activities that guide adaptive context-aware developer. Finally, a quantitative study evaluates the approach based on aspects and dynamic composition for the construction of ubiquitous applications based in metrics