10,186 research outputs found

    Uma extensão temporal a teoria das coberturas parcimoniosas

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    Orientador: Jacques WainerDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica Estatistica e Ciencia da ComputaçãoResumo: Nesta dissertação propõe-se uma extensão temporal à Teoria das Coberturas Parcimoniosas. Esta teoria provê um fundamento teórico ao processo de raciocínio diagnóstico, como um raciocínio abdutivo baseado nos modelos que associam causas à suas conseqüências (ou doenças com seus sinais e sintomas). A extensão temporal proposta para a Teoria das Coberturas Parcimoniosas possibilita associar a cada doença a evolução temporal dos seus sinais e sintomas. A eliminação de hipóteses temporalmente inconsistentes minimiza uma das maiores limitações da Teoria das Coberturas Parcimoniosas: a teoria pode incluir um grande número de hipóteses alternativas. Além do mais, a inclusão de aspectos temporais a uma extensão da teoria que inclua informações probabilísticas também elimina o problema de rejeições incorretas de hipóteses quando um sintoma necessário não estiver presente. A extensão temporal proposta é aplicada a um problema de diagnóstico médico em que o tempo é importante na diagnose. Os resultados obtidos foram bastante satisfatórios, como a construção rápida da base de conhecimento, a eliminação significativa do número de hipóteses e a redução do tempo gasto na obtenção da solução do problema. Finalmente, são apresentadas as contribuições, limitações e extensões futuras desta dissertaçãoAbstract: In this work we propose a temporal extension to the Parsimonious Covering Theory. This theory provides a theoretical foundation for the diagnostic reasoning process as an abdutive reasonig based on models that associate causes with their consequences (or diseases and their symptoms). Our temporal extension of the Parsimonious Covering Theory allows one to associate to a disease a temporal evolution of symptoms. The elimination of temporally inconsistent hypothesis minimizes one of the greatest limitation of the Parsimonious Covering Theory: the theory may include a large number of alternative hypothesis. Furthermore, the inclusion of temporal aspects to an extension of this theory that includes probabilistic information also eliminates the problem of incorrectly rejecting hypothesis if a necessary symptom has not yet ocurred. Finally, the limitations of the representation formalism and the problems with the temporal reasoning in a diagnostic system are also describedMestradoMestre em Ciência da Computaçã

    Unravelling the Impact of Temporal and Geographical Locality in Content Caching Systems

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    To assess the performance of caching systems, the definition of a proper process describing the content requests generated by users is required. Starting from the analysis of traces of YouTube video requests collected inside operational networks, we identify the characteristics of real traffic that need to be represented and those that instead can be safely neglected. Based on our observations, we introduce a simple, parsimonious traffic model, named Shot Noise Model (SNM), that allows us to capture temporal and geographical locality of content popularity. The SNM is sufficiently simple to be effectively employed in both analytical and scalable simulative studies of caching systems. We demonstrate this by analytically characterizing the performance of the LRU caching policy under the SNM, for both a single cache and a network of caches. With respect to the standard Independent Reference Model (IRM), some paradigmatic shifts, concerning the impact of various traffic characteristics on cache performance, clearly emerge from our results.Comment: 14 pages, 11 Figures, 2 Appendice

    Developments in the Analysis of Spatial Data

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    Disregarding spatial dependence can invalidate methods for analyzingcross-sectional and panel data. We discuss ongoing work on developingmethods that allow for, test for, or estimate, spatial dependence. Muchof the stress is on nonparametric and semiparametric methods.

    Quantum Holism: Reconciling Extended Simples with Supersubstantivalism

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    I argue that the extended simples picture (ESP) is compatible with supersubstantivalism under the quantum holism model, and that reevaluating our limits on the ways an object may be located by fusing the two ontologies can benefit our understanding of modern physics. I first illustrate the explanatory utility of extended simples, using examples of superposition and entanglement. Second, I advocate the use of supersubstantivalism as a way to understand the interface between objects and spacetime, and argue that the ESP suitably fits into a supersubstantivalist interpretation of quantum field theory. In the last section, I propose quantum holism as a framework to reconcile supersubstantivalism with extended simples, and conclude that the causal relationship that interweaves material objects and spacetime render the two ontologies compatible. I will demonstrate that a combined ontology is useful for its parsimony, and for our understanding of quantum field theory

    A proposal for a minimalist ontology

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    This paper seeks to answer the following question: What is a minimal set of entities that form an ontology of the natural world, given our well-established physical theories? The proposal is that the following two axioms are sufficient to obtain such a minimalist ontology: (1) There are distance relations that individuate simple objects, namely matter points. (2) The matter points are permanent, with the distances between them changing. I sketch out how one can obtain our well-established physical theories on the basis of just these two axioms. The argument for minimalism in ontology then is that it yields all the explanations that one can reasonably demand in science and philosophy, while avoiding the drawbacks that come with a richer ontology

    Large-sample inference on spatial dependence

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    We consider cross-sectional data that exhibit no spatial correlation, but are feared to be spatially dependent. We demonstrate that a spatial version of the stochastic volatility model of financial econometrics, entailing a form of spatial autoregression, can explain such behaviour. The parameters are estimated by pseudo Gaussian maximum likelihood based on log-transformed squares, and consistency and asymptotic normality are established. Asymptotically valid tests for spatial independence are developed.

    Correlation Testing in Time Series, SpatialandCross-Sectional Data

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    We provide a general class of tests for correlation in time series, spatial, spatiotemporaland cross-sectional data. We motivate our focus by reviewing howcomputational and theoretical difficulties of point estimation mount as one movesfrom regularly-spaced time series data, through forms of irregular spacing, and tospatial data of various kinds. A broad class of computationally simple tests isjustified. These specialize to Lagrange multiplier tests against parametric departuresof various kinds. Their forms are illustrated in case of several models for describingcorrelation in various kinds of data. The initial focus assumes homoscedasticity, butwe also robustify the tests to nonparametric heteroscedasticity.heteroscedasticity, Lagrange multiplier tests.

    Large-Sample Inference on SpatialDependence

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    We consider cross-sectional data that exhibit no spatial correla-tion, but are feared to be spatially dependent. We demonstrate that a spatialversion of the stochastic volatility model of financial econometrics, entailing aform of spatial autoregression, can explain such behaviour. The parameters areestimated by pseudo Gaussian maximum likelihood based on log-transformedsquares, and consistency and asymptotic normality are established. Asymptotically valid tests for spatial independence are developed.Spatial dependence, Parameter estimation, Asymptotic theory,Independence testing.
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