24 resultados para Approximate Bayesian computation, Posterior distribution, Quantile distribution, Response time data


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On the last years, several middleware platforms for Wireless Sensor Networks (WSN) were proposed. Most of these platforms does not consider issues of how integrate components from generic middleware architectures. Many requirements need to be considered in a middleware design for WSN and the design, in this case, it is possibility to modify the source code of the middleware without changing the external behavior of the middleware. Thus, it is desired that there is a middleware generic architecture that is able to offer an optimal configuration according to the requirements of the application. The adoption of middleware based in component model consists of a promising approach because it allows a better abstraction, low coupling, modularization and management features built-in middleware. Another problem present in current middleware consists of treatment of interoperability with external networks to sensor networks, such as Web. Most current middleware lacks the functionality to access the data provided by the WSN via the World Wide Web in order to treat these data as Web resources, and they can be accessed through protocols already adopted the World Wide Web. Thus, this work presents the Midgard, a component-based middleware specifically designed for WSNs, which adopts the architectural patterns microkernel and REST. The microkernel architectural complements the component model, since microkernel can be understood as a component that encapsulates the core system and it is responsible for initializing the core services only when needed, as well as remove them when are no more needed. Already REST defines a standardized way of communication between different applications based on standards adopted by the Web and enables him to treat WSN data as web resources, allowing them to be accessed through protocol already adopted in the World Wide Web. The main goals of Midgard are: (i) to provide easy Web access to data generated by WSN, exposing such data as Web resources, following the principles of Web of Things paradigm and (ii) to provide WSN application developer with capabilities to instantiate only specific services required by the application, thus generating a customized middleware and saving node resources. The Midgard allows use the WSN as Web resources and still provide a cohesive and weakly coupled software architecture, addressing interoperability and customization. In addition, Midgard provides two services needed for most WSN applications: (i) configuration and (ii) inspection and adaptation services. New services can be implemented by others and easily incorporated into the middleware, because of its flexible and extensible architecture. According to the assessment, the Midgard provides interoperability between the WSN and external networks, such as web, as well as between different applications within a single WSN. In addition, we assessed the memory consumption, the application image size, the size of messages exchanged in the network, and response time, overhead and scalability on Midgard. During the evaluation, the Midgard proved satisfies their goals and shown to be scalable without consuming resources prohibitively

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This thesis is part of research on new materials for catalysis and gas sensors more active, sensitive, selective. The aim of this thesis was to develop and characterize cobalt ferrite in different morphologies, in order to study their influence on the electrical response and the catalytic activity, and to hierarchize these grains for greater diffusivity of gas in the material. The powders were produced via hydrothermal and solvothermal, and were characterized by thermogravimetric analysis, X-ray diffraction, scanning electron microscopy, transmission electron microscopy (electron diffraction, highresolution simulations), and energy dispersive spectroscopy. The catalytic and electrical properties were tested in the presence of CO and NO2 gases, the latter in different concentrations (1-100 ppm) and at different temperatures (room temperature to 350 ° C). Nanooctahedra with an average size of 20 nm were obtained by hydrothermal route. It has been determined that the shape of the grains is mainly linked to the nature of the precipitating agent and the presence of OH ions in the reaction medium. By solvothermal method CoFe2O4 spherical powders were prepared with grain size of 8 and 20 nm. CoFe2O4 powders exhibit a strong response to small amounts of NO2 (10 ppm to 200 ° C). The nanooctahedra have greater sensitivity than the spherical grains of the same size, and have smaller response time and shorter recovery times. These results were confirmed by modeling the kinetics of response and recovery of the sensor. Initial tests of catalytic activity in the oxidation of CO between temperatures of 100 °C and 350 °C show that the size effect is predominant in relation the effect of the form with respect to the conversion of the reaction. The morphology of the grains influence the rate of reaction. A higher reaction rate is obtained in the presence of nanooctahedra. In order to improve the detection and catalytic properties of the material, we have developed a methodology for hierarchizing grains which involves the use of carbonbased templates.

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Data Visualization is widely used to facilitate the comprehension of information and find relationships between data. One of the most widely used techniques for multivariate data (4 or more variables) visualization is the 2D scatterplot. This technique associates each data item to a visual mark in the following way: two variables are mapped to Cartesian coordinates so that a visual mark can be placed on the Cartesian plane; the others variables are mapped gradually to visual properties of the mark, such as size, color, shape, among others. As the number of variables to be visualized increases, the amount of visual properties associated to the mark increases as well. As a result, the complexity of the final visualization is higher. However, increasing the complexity of the visualization does not necessarily implies a better visualization and, sometimes, it provides an inverse situation, producing a visually polluted and confusing visualization—this problem is called visual properties overload. This work aims to investigate whether it is possible to work around the overload of the visual channel and improve insight about multivariate data visualized through a modification in the 2D scatterplot technique. In this modification, we map the variables from data items to multisensoriy marks. These marks are composed not only by visual properties, but haptic properties, such as vibration, viscosity and elastic resistance, as well. We believed that this approach could ease the insight process, through the transposition of properties from the visual channel to the haptic channel. The hypothesis was verified through experiments, in which we have analyzed (a) the accuracy of the answers; (b) response time; and (c) the grade of personal satisfaction with the proposed approach. However, the hypothesis was not validated. The results suggest that there is an equivalence between the investigated visual and haptic properties in all analyzed aspects, though in strictly numeric terms the multisensory visualization achieved better results in response time and personal satisfaction.

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Cloud computing can be defined as a distributed computational model by through resources (hardware, storage, development platforms and communication) are shared, as paid services accessible with minimal management effort and interaction. A great benefit of this model is to enable the use of various providers (e.g a multi-cloud architecture) to compose a set of services in order to obtain an optimal configuration for performance and cost. However, the multi-cloud use is precluded by the problem of cloud lock-in. The cloud lock-in is the dependency between an application and a cloud platform. It is commonly addressed by three strategies: (i) use of intermediate layer that stands to consumers of cloud services and the provider, (ii) use of standardized interfaces to access the cloud, or (iii) use of models with open specifications. This paper outlines an approach to evaluate these strategies. This approach was performed and it was found that despite the advances made by these strategies, none of them actually solves the problem of lock-in cloud. In this sense, this work proposes the use of Semantic Web to avoid cloud lock-in, where RDF models are used to specify the features of a cloud, which are managed by SPARQL queries. In this direction, this work: (i) presents an evaluation model that quantifies the problem of cloud lock-in, (ii) evaluates the cloud lock-in from three multi-cloud solutions and three cloud platforms, (iii) proposes using RDF and SPARQL on management of cloud resources, (iv) presents the cloud Query Manager (CQM), an SPARQL server that implements the proposal, and (v) comparing three multi-cloud solutions in relation to CQM on the response time and the effectiveness in the resolution of cloud lock-in.

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Multi-Cloud Applications are composed of services offered by multiple cloud platforms where the user/developer has full knowledge of the use of such platforms. The use of multiple cloud platforms avoids the following problems: (i) vendor lock-in, which is dependency on the application of a certain cloud platform, which is prejudicial in the case of degradation or failure of platform services, or even price increasing on service usage; (ii) degradation or failure of the application due to fluctuations in quality of service (QoS) provided by some cloud platform, or even due to a failure of any service. In multi-cloud scenario is possible to change a service in failure or with QoS problems for an equivalent of another cloud platform. So that an application can adopt the perspective multi-cloud is necessary to create mechanisms that are able to select which cloud services/platforms should be used in accordance with the requirements determined by the programmer/user. In this context, the major challenges in terms of development of such applications include questions such as: (i) the choice of which underlying services and cloud computing platforms should be used based on the defined user requirements in terms of functionality and quality (ii) the need to continually monitor the dynamic information (such as response time, availability, price, availability), related to cloud services, in addition to the wide variety of services, and (iii) the need to adapt the application if QoS violations affect user defined requirements. This PhD thesis proposes an approach for dynamic adaptation of multi-cloud applications to be applied when a service is unavailable or when the requirements set by the user/developer point out that other available multi-cloud configuration meets more efficiently. Thus, this work proposes a strategy composed of two phases. The first phase consists of the application modeling, exploring the similarities representation capacity and variability proposals in the context of the paradigm of Software Product Lines (SPL). In this phase it is used an extended feature model to specify the cloud service configuration to be used by the application (similarities) and the different possible providers for each service (variability). Furthermore, the non-functional requirements associated with cloud services are specified by properties in this model by describing dynamic information about these services. The second phase consists of an autonomic process based on MAPE-K control loop, which is responsible for selecting, optimally, a multicloud configuration that meets the established requirements, and perform the adaptation. The adaptation strategy proposed is independent of the used programming technique for performing the adaptation. In this work we implement the adaptation strategy using various programming techniques such as aspect-oriented programming, context-oriented programming and components and services oriented programming. Based on the proposed steps, we tried to assess the following: (i) the process of modeling and the specification of non-functional requirements can ensure effective monitoring of user satisfaction; (ii) if the optimal selection process presents significant gains compared to sequential approach; and (iii) which techniques have the best trade-off when compared efforts to development/modularity and performance.

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A manutenção e evolução de sistemas de software tornou-se uma tarefa bastante crítica ao longo dos últimos anos devido à diversidade e alta demanda de funcionalidades, dispositivos e usuários. Entender e analisar como novas mudanças impactam os atributos de qualidade da arquitetura de tais sistemas é um pré-requisito essencial para evitar a deterioração de sua qualidade durante sua evolução. Esta tese propõe uma abordagem automatizada para a análise de variação do atributo de qualidade de desempenho em termos de tempo de execução (tempo de resposta). Ela é implementada por um framework que adota técnicas de análise dinâmica e mineração de repositório de software para fornecer uma forma automatizada de revelar fontes potenciais – commits e issues – de variação de desempenho em cenários durante a evolução de sistemas de software. A abordagem define quatro fases: (i) preparação – escolher os cenários e preparar os releases alvos; (ii) análise dinâmica – determinar o desempenho de cenários e métodos calculando seus tempos de execução; (iii) análise de variação – processar e comparar os resultados da análise dinâmica para releases diferentes; e (iv) mineração de repositório – identificar issues e commits associados com a variação de desempenho detectada. Estudos empíricos foram realizados para avaliar a abordagem de diferentes perspectivas. Um estudo exploratório analisou a viabilidade de se aplicar a abordagem em sistemas de diferentes domínios para identificar automaticamente elementos de código fonte com variação de desempenho e as mudanças que afetaram tais elementos durante uma evolução. Esse estudo analisou três sistemas: (i) SIGAA – um sistema web para gerência acadêmica; (ii) ArgoUML – uma ferramenta de modelagem UML; e (iii) Netty – um framework para aplicações de rede. Outro estudo realizou uma análise evolucionária ao aplicar a abordagem em múltiplos releases do Netty, e dos frameworks web Wicket e Jetty. Nesse estudo foram analisados 21 releases (sete de cada sistema), totalizando 57 cenários. Em resumo, foram encontrados 14 cenários com variação significante de desempenho para Netty, 13 para Wicket e 9 para Jetty. Adicionalmente, foi obtido feedback de oito desenvolvedores desses sistemas através de um formulário online. Finalmente, no último estudo, um modelo de regressão para desempenho foi desenvolvido visando indicar propriedades de commits que são mais prováveis a causar degradação de desempenho. No geral, 997 commits foram minerados, sendo 103 recuperados de elementos de código fonte degradados e 19 de otimizados, enquanto 875 não tiveram impacto no tempo de execução. O número de dias antes de disponibilizar o release e o dia da semana se mostraram como as variáveis mais relevantes dos commits que degradam desempenho no nosso modelo. A área de característica de operação do receptor (ROC – Receiver Operating Characteristic) do modelo de regressão é 60%, o que significa que usar o modelo para decidir se um commit causará degradação ou não é 10% melhor do que uma decisão aleatória.

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A manutenção e evolução de sistemas de software tornou-se uma tarefa bastante crítica ao longo dos últimos anos devido à diversidade e alta demanda de funcionalidades, dispositivos e usuários. Entender e analisar como novas mudanças impactam os atributos de qualidade da arquitetura de tais sistemas é um pré-requisito essencial para evitar a deterioração de sua qualidade durante sua evolução. Esta tese propõe uma abordagem automatizada para a análise de variação do atributo de qualidade de desempenho em termos de tempo de execução (tempo de resposta). Ela é implementada por um framework que adota técnicas de análise dinâmica e mineração de repositório de software para fornecer uma forma automatizada de revelar fontes potenciais – commits e issues – de variação de desempenho em cenários durante a evolução de sistemas de software. A abordagem define quatro fases: (i) preparação – escolher os cenários e preparar os releases alvos; (ii) análise dinâmica – determinar o desempenho de cenários e métodos calculando seus tempos de execução; (iii) análise de variação – processar e comparar os resultados da análise dinâmica para releases diferentes; e (iv) mineração de repositório – identificar issues e commits associados com a variação de desempenho detectada. Estudos empíricos foram realizados para avaliar a abordagem de diferentes perspectivas. Um estudo exploratório analisou a viabilidade de se aplicar a abordagem em sistemas de diferentes domínios para identificar automaticamente elementos de código fonte com variação de desempenho e as mudanças que afetaram tais elementos durante uma evolução. Esse estudo analisou três sistemas: (i) SIGAA – um sistema web para gerência acadêmica; (ii) ArgoUML – uma ferramenta de modelagem UML; e (iii) Netty – um framework para aplicações de rede. Outro estudo realizou uma análise evolucionária ao aplicar a abordagem em múltiplos releases do Netty, e dos frameworks web Wicket e Jetty. Nesse estudo foram analisados 21 releases (sete de cada sistema), totalizando 57 cenários. Em resumo, foram encontrados 14 cenários com variação significante de desempenho para Netty, 13 para Wicket e 9 para Jetty. Adicionalmente, foi obtido feedback de oito desenvolvedores desses sistemas através de um formulário online. Finalmente, no último estudo, um modelo de regressão para desempenho foi desenvolvido visando indicar propriedades de commits que são mais prováveis a causar degradação de desempenho. No geral, 997 commits foram minerados, sendo 103 recuperados de elementos de código fonte degradados e 19 de otimizados, enquanto 875 não tiveram impacto no tempo de execução. O número de dias antes de disponibilizar o release e o dia da semana se mostraram como as variáveis mais relevantes dos commits que degradam desempenho no nosso modelo. A área de característica de operação do receptor (ROC – Receiver Operating Characteristic) do modelo de regressão é 60%, o que significa que usar o modelo para decidir se um commit causará degradação ou não é 10% melhor do que uma decisão aleatória.

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BRITTO, Ricardo S.; MEDEIROS, Adelardo A. D.; ALSINA, Pablo J. Uma arquitetura distribuída de hardware e software para controle de um robô móvel autônomo. In: SIMPÓSIO BRASILEIRO DE AUTOMAÇÃO INTELIGENTE,8., 2007, Florianópolis. Anais... Florianópolis: SBAI, 2007.

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This work aims to analyze risks related to information technology (IT) in procedures related to data migration. This is done considering ALEPH, Integrated Libray System (ILS) that migrated data to the Library Module present in the software called Sistema Integrado de Gestão de Atividades Acadêmicas (SIGAA) at the Zila Mamede Central Library at the Federal University of Rio Grande do Norte (UFRN) in Natal/Brazil. The methodological procedure used was of a qualitative exploratory research with the realization of case study at the referred library in order to better understand this phenomenon. Data collection was able once there was use of a semi-structured interview that was applied with (11) subjects that are employed at the library as well as in the Technology Superintendence at UFRN. In order to examine data Content analysis as well as thematic review process was performed. After data migration the results of the interview were then linked to both analysis units and their system register with category correspondence. The main risks detected were: data destruction; data loss; data bank communication failure; user response delay; data inconsistency and duplicity. These elements point out implication and generate disorders that affect external and internal system users and lead to stress, work duplicity and hassles. Thus, some measures were taken related to risk management such as adequate planning, central management support, and pilot test simulations. For the advantages it has reduced of: risk, occurrence of problems and possible unforeseen costs, and allows achieving organizational objectives, among other. It is inferred therefore that the risks present in data bank conversion in libraries exist and some are predictable, however, it is seen that librarians do not know or ignore and are not very worried in the identification risks in data bank conversion, their acknowledge would minimize or even extinguish them. Another important aspect to consider is the existence of few empirical research that deal specifically with this subject and thus presenting the new of new approaches in order to promote better understanding of the matter in the corporate environment of the information units