244 resultados para Replicação


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Operational procedures may negatively interfere in negotiation and execution regarding universities and business companies. In some cases it may even derail business interaction. Thus, aiming to overcome this and other barriers a university-industry interaction model was structured. The model enhances the appropriation of technological solutions on behalf of enterprises, as well as aim to improve the quality of teaching and research done at the university. In order to conduct a case study, sampling considering the Federal University of Rio Grande do Norte (UFRN) was made as well as the Oil and Gas sector. For data collection questionnaires, classroom observation, document analysis, semi-structured interviews were used. The study describes the companies as well as the internal organization of UFRN in their interaction context. The diagnosis related to past interactions as well as the expectations of the companies and the university s internal subjects regarding the university-industry relationship were also studied. Thus, specific questionnaires were applied for the three types of groups: researchers, managers and business companies. These subjects pointed out that the great deal of barriers they identified were related to issues regarding the university internal management. Given these barriers, the critical factors were then identified in order to overcome this reality. Among the nine critical factors only one belongs to the macro environment, while the remaining factors are related to organizational issues present in the university context. It was possible to formulate a university-business interaction model one the researched focused on the case study results and contribution from a theoretical framework that was enabled trough literature review. The model considers all business collaboration mechanisms; it focuses on a particular strategic productive sector and provides a co-evolution vision over time, according to the sector´s development strategy. The need for institutionalizing the relationship with the companies involved is pointed out. The proposed model considers all the critical factors identified by the research; it aims long-term relationship with the company and integrates teaching, research and extension actions. The model implementation was also considered. It was seen that it must be done in three phases. The phases will be defined by the level of maturity in the relationship between the university and the companies. Thus, a framework was developed in order to assess the interaction level regarding company institutionalization. Whilst structuring the model was a concern with replication came up. It was pointed out that this model should not only serve to this specific case study situation. So the final result is a model of university-industry relationship appropriate in the first instance, for UFRN, but has applicability, in general, to any Brazilian university

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Biológicas, Programa de Pós Graduação em Biologia Molecular, 2015.

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A necessidade de conhecer uma população impulsiona um processo de recolha e análise de informação. Usualmente é muito difícil ou impossível estudar a totalidade da população, daí a importância do estudo com recurso a amostras. Conceber um estudo por amostragem é um processo complexo, desde antes da recolha dos dados até a fase de análise dos mesmos. Na maior parte dos estudos utilizam-se combinações de vários métodos probabilísticos de amostragem para seleção de uma amostra, que se pretende representativa da população, denominado delineamento de amostragem complexo. O conhecimento dos erros de amostragem é necessário à correta interpretação dos resultados de inquéritos e à avaliação dos seus planos de amostragem. Em amostras complexas, têm sido usadas aproximações ajustadas à natureza complexa do plano da amostra para a estimação da variância, sendo as mais utilizadas: o método de linearização Taylor e as técnicas de reamostragem e replicação. O principal objetivo deste trabalho é avaliar o desempenho dos estimadores usuais da variância em amostras complexas. Inspirado num conjunto de dados reais foram geradas três populações com características distintas, das quais foram sorteadas amostras com diferentes delineamentos de amostragem, na expectativa de obter alguma indicação sobre em que situações se deve optar por cada um dos estimadores da variância. Com base nos resultados obtidos, podemos concluir que o desempenho dos estimadores da variância da média amostral de Taylor, Jacknife e Bootstrap varia com o tipo de delineamento e população. De um modo geral, o estimador de Bootstrap é o menos preciso e em delineamentos estratificados os estimadores de Taylor e Jackknife fornecem os mesmos resultados; Evaluation of variance estimation methods in complex samples ABSTRACT: The need to know a population drives a process of collecting and analyzing information. Usually is to hard or even impossible to study the whole population, hence the importance of sampling. Framing a study by sampling is a complex process, from before the data collection until the data analysis. Many studies have used combinations of various probabilistic sampling methods for selecting a representative sample of the population, calling it complex sampling design. Knowledge of sampling errors is essential for correct interpretation of the survey results and evaluation of the sampling plans. In complex samples to estimate the variance has been approaches adjusted to the complex nature of the sample plane. The most common are: the linearization method of Taylor and techniques of resampling and replication. The main objective of this study is to evaluate the performance of usual estimators of the variance in complex samples. Inspired on real data we will generate three populations with distinct characteristics. From this populations will be drawn samples using different sampling designs. In the end we intend to get some lights about in which situations we should opt for each one of the variance estimators. Our results show that the performance of the variance estimators of sample mean Taylor, Jacknife and Bootstrap varies with the design and population. In general, the Bootstrap estimator is less precise and in stratified design Taylor and Jackknife estimators provide the same results.

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A replicação de base de dados tem como objectivo a cópia de dados entre bases de dados distribuídas numa rede de computadores. A replicação de dados é importante em várias situações, desde a realização de cópias de segurança da informação, ao balanceamento de carga, à distribuição da informação por vários locais, até à integração de sistemas heterogéneos. A replicação possibilita uma diminuição do tráfego de rede, pois os dados ficam disponíveis localmente possibilitando também o seu acesso no caso de indisponibilidade da rede. Esta dissertação baseia-se na realização de um trabalho que consistiu no desenvolvimento de uma aplicação genérica para a replicação de bases de dados a disponibilizar como open source software. A aplicação desenvolvida possibilita a integração de dados entre vários sistemas, com foco na integração de dados heterogéneos, na fragmentação de dados e também na possibilidade de adaptação a várias situações. ABSTRACT: Data replication is a mechanism to synchronize and integrate data between distributed databases over a computer network. Data replication is an important tool in several situations, such as the creation of backup systems, load balancing between various nodes, distribution of information between various locations, integration of heterogeneous systems. Replication enables a reduction in network traffic, because data remains available locally even in the event of a temporary network failure. This thesis is based on the work carried out to develop an application for database replication to be made accessible as open source software. The application that was built allows for data integration between various systems, with particular focus on, amongst others, the integration of heterogeneous data, the fragmentation of data, replication in cascade, data format changes between replicas, master/slave and multi master synchronization.