476 resultados para .NET Framework


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The direct effect of human capital on economic growth has been widely analysed in the economic literature. This paper, however, focuses on its indirect effect as a stimulus for private investment in physical capital. The methodological framework used is the duality theory, estimating a cost system aggregated with human capital. Empirical evidence is given for Spain for the period 1980-2000. We provide evidence on the indirect effect of human capital in making private capital investment more attractive. Among the main explanations forthis process, we observe that higher worker skill levels enable higher returns to be extracted from investment in physical capital.

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ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. RESULTS: We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. CONCLUSIONS: We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

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Background: This paper aimed to use the Delphi technique to develop a consensus framework for a multinational, workplace walking intervention. Methods: Ideas were gathered and ranked from eight recognized and emerging experts in the fields of physical activity and health, from universities in Australia, Canada, England, the Netherlands, Northern Ireland, and Spain. Members of the panel were asked to consider the key characteristics of a successful campus walking intervention. Consensus was reached by an inductive, content analytic approach, conducted through an anonymous, three-round, e-mail process. Results: The resulting framework consisted of three interlinking themes defined as “design, implementation, and evaluation.” Top-ranked subitems in these themes included the need to generate research capacity (design), to respond to group needs through different walking approaches (implementation), and to undertake physical activity assessment (evaluation). Themes were set within an underpinning domain, referred to as the “institution” and sites are currently engaging with subitems in this domain, to provide sustainable interventions that reflect the practicalities of local contexts and needs. Conclusions: Findings provide a unique framework for designing, implementing, and evaluating walking projects in universities and highlight the value of adopting the Delphi technique for planning international, multisite health initiatives.

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Within the context of rising competition between territories, identity has become the most important element of recognition, differentiation and commodification in the communicative process within which cities, regions and countries position themselves. Geographical spaces thus compete in terms of this identity, which is then subjected to fierce comparison and competition (Nogué, 1999; Anholt, 2007a). The territorial brand thus entails the reinvention of places through a process of brand construction (branding) based on the promotion of the individual and collective identities of geographical spaces; these identities, in turn, are imbued with the intangible factors associated with their respective territorial identities.

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El present projecte de final de carrera consisteix en el desenvolupament d'un marc de treball o framework per a la capa de presentació d'aplicacions J2EE.

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El objetivo principal es analizar y desarrollar un framework que haga que el desarrollo de la capa de presentación sea más sencillo y fácil de implementar en el caso de aplicaciones J2EE con un cliente ligero.

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Aquest projecte de fi de carrera persegueix la finalitat d'analitzar i desenvolupar un conjunt de components en la direcció de simplificar i agilitzar el desenvolupament de l'accés a dades en aplicacions distribuïdes, sovint amb bases de dades relacionals.

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Desarrollo de un framework de persistencia y posterior estudio de este como objetivo del Proyecto Final de Carrera

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Estudio sobre los frameworks Java de presentación. Creación de un framework de presentación propio y de una aplicación JEE que lo utiliza.

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Aquest projecte consisteix en la realització d'un framework de persistència per realitzar l'enllaç entre el model de dades relacional i el model de dades orientat a objectes. L'aplicació que implementarem per tal de provar el nostre framework consisteix en l'adaptació web d'un software financer que serveix per tenir un control de la tresoreria.

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En aquest PFC s'analitzaran els diversos frameworks de persistència que actualment existeixen i es facilitarà el desenvolupament d'un conjunt de components que permetran simplificar la capa de persistència en aplicacions multicapa desenvolupades amb JEE.

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The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.

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The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.