952 resultados para Dynamic data set visualization
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Jakarta is vulnerable to flooding mainly caused by prolonged and heavy rainfall and thus a robust hydrological modeling is called for. A good quality of spatial precipitation data is therefore desired so that a good hydrological model could be achieved. Two types of rainfall sources are available: satellite and gauge station observations. At-site rainfall is considered to be a reliable and accurate source of rainfall. However, the limited number of stations makes the spatial interpolation not very much appealing. On the other hand, the gridded rainfall nowadays has high spatial resolution and improved accuracy, but still, relatively less accurate than its counterpart. To achieve a better precipitation data set, the study proposes cokriging method, a blending algorithm, to yield the blended satellite-gauge gridded rainfall at approximately 10-km resolution. The Global Satellite Mapping of Precipitation (GSMaP, 0.1⁰×0.1⁰) and daily rainfall observations from gauge stations are used. The blended product is compared with satellite data by cross-validation method. The newly-yield blended product is then utilized to re-calibrate the hydrological model. Several scenarios are simulated by the hydrological models calibrated by gauge observations alone and blended product. The performance of two calibrated hydrological models is then assessed and compared based on simulated and observed runoff.
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Existing distributed hydrologic models are complex and computationally demanding for using as a rapid-forecasting policy-decision tool, or even as a class-room educational tool. In addition, platform dependence, specific input/output data structures and non-dynamic data-interaction with pluggable software components inside the existing proprietary frameworks make these models restrictive only to the specialized user groups. RWater is a web-based hydrologic analysis and modeling framework that utilizes the commonly used R software within the HUBzero cyber infrastructure of Purdue University. RWater is designed as an integrated framework for distributed hydrologic simulation, along with subsequent parameter optimization and visualization schemes. RWater provides platform independent web-based interface, flexible data integration capacity, grid-based simulations, and user-extensibility. RWater uses RStudio to simulate hydrologic processes on raster based data obtained through conventional GIS pre-processing. The program integrates Shuffled Complex Evolution (SCE) algorithm for parameter optimization. Moreover, RWater enables users to produce different descriptive statistics and visualization of the outputs at different temporal resolutions. The applicability of RWater will be demonstrated by application on two watersheds in Indiana for multiple rainfall events.
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Although there has been substantial research on long-run co-movement (common trends) in the empirical macroeconomics literature. little or no work has been done on short run co-movement (common cycles). Investigating common cycles is important on two grounds: first. their existence is an implication of most dynamic macroeconomic models. Second. they impose important restrictions on dynamic systems. Which can be used for efficient estimation and forecasting. In this paper. using a methodology that takes into account short- and long-run co-movement restrictions. we investigate their existence in a multivariate data set containing U.S. per-capita output. consumption. and investment. As predicted by theory. the data have common trends and common cycles. Based on the results of a post-sample forecasting comparison between restricted and unrestricted systems. we show that a non-trivial loss of efficiency results when common cycles are ignored. If permanent shocks are associated with changes in productivity. the latter fails to be an important source of variation for output and investment contradicting simple aggregate dynamic models. Nevertheless. these shocks play a very important role in explaining the variation of consumption. Showing evidence of smoothing. Furthermore. it seems that permanent shocks to output play a much more important role in explaining unemployment fluctuations than previously thought.
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This paper evaluates the long-run effects of economic instability. In particular, we study the impact of idiosyncratic shocks to father’s income on children’s human capital accumulation variables such as school drop-outs, repetition rates and domestic and non-domestic labor. Although, the problem of child labor in Brazil has declined greatly during the last decade, the number of children working is still substantial. The low levels of educational attainment in Brazil are also a main cause for concern. The large rotating panel data set used allows for the estimation of the impacts of changes in occupational and income status of fathers on changes in his child’s time allocation circumstances. The empirical analysis is restricted to families with fathers, mothers and at least one child between 10 and 15 years of age in the main Brazilian metropolitan areas during the 1982-1999 period. We perform logistic regressions controlling for child characteristics (gender, age, if he/she is behind in school for age), parents characteristics (grade attainment and income) and time and location variables. The main variables analyzed are dynamic proxies of impulses and responses, namely: shocks to household head’s income and unemployment status, on the one hand and child’s probability of dropping out of school, of repeating a grade and of start working, on the other. The findings suggest that father’s income has a significant positive correlation with child’s dropping out of school and of repeating a grade. The findings do not suggest a significant relationship between a father’s becoming unemployed and a child entering the non-domestic labor market. However, the results demonstrate a significant positive relationship between a father becoming unemployed and a child beginning to work in domestic labor. There was also a positive correlation between father becoming unemployed and a child dropping out and repeating a grade. Both gender and age were highly significant with boys and older children being more likely to work, drop-out and repeat grades.
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The aim of this article is to assess the role of real effective exchange rate volatility on long-run economic growth for a set of 82 advanced and emerging economies using a panel data set ranging from 1970 to 2009. With an accurate measure for exchange rate volatility, the results for the two-step system GMM panel growth models show that a more (less) volatile RER has significant negative (positive) impact on economic growth and the results are robust for different model specifications. In addition to that, exchange rate stability seems to be more important to foster long-run economic growth than exchange rate misalignment
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The work described in this thesis aims to support the distributed design of integrated systems and considers specifically the need for collaborative interaction among designers. Particular emphasis was given to issues which were only marginally considered in previous approaches, such as the abstraction of the distribution of design automation resources over the network, the possibility of both synchronous and asynchronous interaction among designers and the support for extensible design data models. Such issues demand a rather complex software infrastructure, as possible solutions must encompass a wide range of software modules: from user interfaces to middleware to databases. To build such structure, several engineering techniques were employed and some original solutions were devised. The core of the proposed solution is based in the joint application of two homonymic technologies: CAD Frameworks and object-oriented frameworks. The former concept was coined in the late 80's within the electronic design automation community and comprehends a layered software environment which aims to support CAD tool developers, CAD administrators/integrators and designers. The latter, developed during the last decade by the software engineering community, is a software architecture model to build extensible and reusable object-oriented software subsystems. In this work, we proposed to create an object-oriented framework which includes extensible sets of design data primitives and design tool building blocks. Such object-oriented framework is included within a CAD Framework, where it plays important roles on typical CAD Framework services such as design data representation and management, versioning, user interfaces, design management and tool integration. The implemented CAD Framework - named Cave2 - followed the classical layered architecture presented by Barnes, Harrison, Newton and Spickelmier, but the possibilities granted by the use of the object-oriented framework foundations allowed a series of improvements which were not available in previous approaches: - object-oriented frameworks are extensible by design, thus this should be also true regarding the implemented sets of design data primitives and design tool building blocks. This means that both the design representation model and the software modules dealing with it can be upgraded or adapted to a particular design methodology, and that such extensions and adaptations will still inherit the architectural and functional aspects implemented in the object-oriented framework foundation; - the design semantics and the design visualization are both part of the object-oriented framework, but in clearly separated models. This allows for different visualization strategies for a given design data set, which gives collaborating parties the flexibility to choose individual visualization settings; - the control of the consistency between semantics and visualization - a particularly important issue in a design environment with multiple views of a single design - is also included in the foundations of the object-oriented framework. Such mechanism is generic enough to be also used by further extensions of the design data model, as it is based on the inversion of control between view and semantics. The view receives the user input and propagates such event to the semantic model, which evaluates if a state change is possible. If positive, it triggers the change of state of both semantics and view. Our approach took advantage of such inversion of control and included an layer between semantics and view to take into account the possibility of multi-view consistency; - to optimize the consistency control mechanism between views and semantics, we propose an event-based approach that captures each discrete interaction of a designer with his/her respective design views. The information about each interaction is encapsulated inside an event object, which may be propagated to the design semantics - and thus to other possible views - according to the consistency policy which is being used. Furthermore, the use of event pools allows for a late synchronization between view and semantics in case of unavailability of a network connection between them; - the use of proxy objects raised significantly the abstraction of the integration of design automation resources, as either remote or local tools and services are accessed through method calls in a local object. The connection to remote tools and services using a look-up protocol also abstracted completely the network location of such resources, allowing for resource addition and removal during runtime; - the implemented CAD Framework is completely based on Java technology, so it relies on the Java Virtual Machine as the layer which grants the independence between the CAD Framework and the operating system. All such improvements contributed to a higher abstraction on the distribution of design automation resources and also introduced a new paradigm for the remote interaction between designers. The resulting CAD Framework is able to support fine-grained collaboration based on events, so every single design update performed by a designer can be propagated to the rest of the design team regardless of their location in the distributed environment. This can increase the group awareness and allow a richer transfer of experiences among them, improving significantly the collaboration potential when compared to previously proposed file-based or record-based approaches. Three different case studies were conducted to validate the proposed approach, each one focusing one a subset of the contributions of this thesis. The first one uses the proxy-based resource distribution architecture to implement a prototyping platform using reconfigurable hardware modules. The second one extends the foundations of the implemented object-oriented framework to support interface-based design. Such extensions - design representation primitives and tool blocks - are used to implement a design entry tool named IBlaDe, which allows the collaborative creation of functional and structural models of integrated systems. The third case study regards the possibility of integration of multimedia metadata to the design data model. Such possibility is explored in the frame of an online educational and training platform.
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Este trabalho trata do impacto da dívida pública sobre o crescimento econômico utilizando conjunto de dados de painel para o período de 1990 a 2000 nos países da América Latina e Caribe, e considerando técnicas de método GMM para painéis dinâmicos. De acordo com os resultados de nossas estimações, a dívida pública dos países influencia negativamente o crescimento econômico, enquanto o desenvolvimento do mercado de títulos públicos apresenta efeito contrário.
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Housing is an important component of wealth for a typical household in many countries. The objective of this paper is to investigate the effect of real-estate price variation on welfare, trying to close a gap between the welfare literature in Brazil and that in the U.S., the U.K., and other developed countries. Our first motivation relates to the fact that real estate is probably more important here than elsewhere as a proportion of wealth, which potentially makes the impact of a price change bigger here. Our second motivation relates to the fact that real-estate prices boomed in Brazil in the last five years. Prime real estate in Rio de Janeiro and São Paulo have tripled in value in that period, and a smaller but generalized increase has been observed throughout the country. Third, we have also seen a recent consumption boom in Brazil in the last five years. Indeed, the recent rise of some of the poor to middle-income status is well documented not only for Brazil but for other emerging countries as well. Regarding consumption and real-estate prices in Brazil, one cannot imply causality from correlation, but one can do causal inference with an appropriate structural model and proper inference, or with a proper inference in a reduced-form setup. Our last motivation is related to the complete absence of studies of this kind in Brazil, which makes ours a pioneering study. We assemble a panel-data set for the determinants of non-durable consumption growth by Brazilian states, merging the techniques and ideas in Campbell and Cocco (2007) and in Case, Quigley and Shiller (2005). With appropriate controls, and panel-data methods, we investigate whether house-price variation has a positive effect on non-durable consumption. The results show a non-negligible significant impact of the change in the price of real estate on welfare consumption), although smaller then what Campbell and Cocco have found. Our findings support the view that the channel through which house prices affect consumption is a financial one.
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The papers aims at considering the issue of relative efficiency measurement in the context of the public sector. In particular, we consider the efficiency measurement approach provided by Data Envelopment Analysis (DEA). The application considered the main Brazilian federal universities for the year of 1994. Given the large number of inputs and outputs, this paper advances the idea of using factor analysis to explore common dimensions in the data set. Such procedure made possible a meaningful application of DEA, which finally provided a set of efficiency scores for the universities considered .
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In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.
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The objective of the present study was to investigate the effect of data structure on estimated genetic parameters and predicted breeding values of direct and maternal genetic effects for weaning weight (WW) and weight gain from birth to weaning (BWG), including or not the genetic covariance between direct and maternal effects. Records of 97,490 Nellore animals born between 1993 and 2006, from the Jacarezinho cattle raising farm, were used. Two different data sets were analyzed: DI_all, which included all available progenies of dams without their own performance; DII_all, which included DI_all + 20% of recorded progenies with maternal phenotypes. Two subsets were obtained from each data set (DI_all and DII_all): DI_1 and DII_1, which included only dams with three or fewer progenies; DI_5 and DII_5, which included only dams with five or more progenies. (Co)variance components and heritabilities were estimated by Bayesian inference through Gibbs sampling using univariate animal models. In general, for the population and traits studied, the proportion of dams with known phenotypic information and the number of progenies per dam influenced direct and maternal heritabilities, as well as the contribution of maternal permanent environmental variance to phenotypic variance. Only small differences were observed in the genetic and environmental parameters when the genetic covariance between direct and maternal effects was set to zero in the data sets studied. Thus, the inclusion or not of the genetic covariance between direct and maternal effects had little effect on the ranking of animals according to their breeding values for WW and BWG. Accurate estimation of genetic correlations between direct and maternal genetic effects depends on the data structure. Thus, this covariance should be set to zero in Nellore data sets in which the proportion of dams with phenotypic information is low, the number of progenies per dam is small, and pedigree relationships are poorly known. (c) 2012 Elsevier B.V. All rights reserved.
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The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant
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Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.