953 resultados para open data capabilities


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The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.

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To estimate the mid-point of an open-ended income category and to assess the impact of two equivalence scales on income-health associations. Data were obtained from the 2010 Brazilian Oral Health Survey ( Pesquisa Nacional de Saúde Bucal – SBBrasil 2010). Income was converted from categorical to two continuous variables ( per capita and equivalized) for each mid-point. The median mid-point was R$ 14,523.50 and the mean, R$ 24,507.10. When per capita income was applied, 53% of the population were below the poverty line, compared with 15% with equivalized income. The magnitude of income-health associations was similar for continuous income, but categorized equivalized income tended to decrease the strength of association.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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Climatic reconstructions based on palynological data from Aquitaine outcrops emphasize an important degradation phase during the Lower Serravallian. Climatic and environmental changes can be related to sea-level variations (Bur 5 / Lan 1, Lan 2 / Ser 1 and Ser 2 cycles). Transgressive phases feature warmer conditions and more open environments whereas regressive phases are marked by a cooler climate and an extent of the forest cover. From Langhian to Middle Serravallian, a general cooling is highlighted, with disappearance of most megathermic taxa and a transition from warm and dry climate to warm-temperate and much more humid conditions. Conclusions are consistent with studies on bordering areas and place the major degradation phase around 14 My. The palynologic data allow filling a gap in the climatic evolution of Southern France, as a connection between Lower and Upper Miocene, both well recorded. These results document, on Western Europe scale, latitudinal climatic gradient across Northern hemisphere while featuring a transition between Mediterranean area and northeastern Atlantic frontage.

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Trabalho final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

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The rapidly increasing computing power, available storage and communication capabilities of mobile devices makes it possible to start processing and storing data locally, rather than offloading it to remote servers; allowing scenarios of mobile clouds without infrastructure dependency. We can now aim at connecting neighboring mobile devices, creating a local mobile cloud that provides storage and computing services on local generated data. In this paper, we describe an early overview of a distributed mobile system that allows accessing and processing of data distributed across mobile devices without an external communication infrastructure. Copyright © 2015 ICST.

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A correlation and predictive scheme for the viscosity and self-diffusivity of liquid dialkyl adipates is presented. The scheme is based on the kinetic theory for dense hard-sphere fluids, applied to the van der Waals model of a liquid to predict the transport properties. A "universal" curve for a dimensionless viscosity of dialkyl adipates was obtained using recently published experimental viscosity and density data of compressed liquid dimethyl (DMA), dipropyl (DPA), and dibutyl (DBA) adipates. The experimental data are described by the correlation scheme with a root-mean-square deviation of +/- 0.34 %. The parameters describing the temperature dependence of the characteristic volume, V-0, and the roughness parameter, R-eta, for each adipate are well correlated with one single molecular parameter. Recently published experimental self-diffusion coefficients of the same set of liquid dialkyl adipates at atmospheric pressure were correlated using the characteristic volumes obtained from the viscosity data. The roughness factors, R-D, are well correlated with the same single molecular parameter found for viscosity. The root-mean-square deviation of the data from the correlation is less than 1.07 %. Tests are presented in order to assess the capability of the correlation scheme to estimate the viscosity of compressed liquid diethyl adipate (DEA) in a range of temperatures and pressures by comparison with literature data and of its self-diffusivity at atmospheric pressure in a range of temperatures. It is noteworthy that no data for DEA were used to build the correlation scheme. The deviations encountered between predicted and experimental data for the viscosity and self-diffusivity do not exceed 2.0 % and 2.2 %, respectively, which are commensurate with the estimated experimental measurement uncertainty, in both cases.

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

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Electric power networks, namely distribution networks, have been suffering several changes during the last years due to changes in the power systems operation, towards the implementation of smart grids. Several approaches to the operation of the resources have been introduced, as the case of demand response, making use of the new capabilities of the smart grids. In the initial levels of the smart grids implementation reduced amounts of data are generated, namely consumption data. The methodology proposed in the present paper makes use of demand response consumers’ performance evaluation methods to determine the expected consumption for a given consumer. Then, potential commercial losses are identified using monthly historic consumption data. Real consumption data is used in the case study to demonstrate the application of the proposed method.

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WWW is a huge, open, heterogeneous system, however its contents data is mainly human oriented. The Semantic Web needs to assure that data is readable and “understandable” to intelligent software agents, though the use of explicit and formal semantics. Ontologies constitute a privileged artifact for capturing the semantic of the WWW data. Temporal and spatial dimensions are transversal to the generality of knowledge domains and therefore are fundamental for the reasoning process of software agents. Representing temporal/spatial evolution of concepts and their relations in OWL (W3C standard for ontologies) it is not straightforward. Although proposed several strategies to tackle this problem but there is still no formal and standard approach. This work main goal consists of development of methods/tools to support the engineering of temporal and spatial aspects in intelligent systems through the use of OWL ontologies. An existing method for ontology engineering, Fonte was used as framework for the development of this work. As main contributions of this work Fonte was re-engineered in order to: i) support the spatial dimension; ii) work with OWL Ontologies; iii) and support the application of Ontology Design Patterns. Finally, the capabilities of the proposed approach were demonstrated by engineering time and space in a demo ontology about football.

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.