1,936 research outputs found

    Bayesian networks for enterprise risk assessment

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    According to different typologies of activity and priority, risks can assume diverse meanings and it can be assessed in different ways. In general risk is measured in terms of a probability combination of an event (frequency) and its consequence (impact). To estimate the frequency and the impact (severity) historical data or expert opinions (either qualitative or quantitative data) are used. Moreover qualitative data must be converted in numerical values to be used in the model. In the case of enterprise risk assessment the considered risks are, for instance, strategic, operational, legal and of image, which many times are difficult to be quantified. So in most cases only expert data, gathered by scorecard approaches, are available for risk analysis. The Bayesian Network is a useful tool to integrate different information and in particular to study the risk's joint distribution by using data collected from experts. In this paper we want to show a possible approach for building a Bayesian networks in the particular case in which only prior probabilities of node states and marginal correlations between nodes are available, and when the variables have only two states

    Intrinsic gap and exciton condensation in the nu_T=1 bilayer system

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    We investigate the quasiparticle excitation of the bilayer quantum Hall (QH) system at total filling factor νT=1\nu_{\mathrm{T}} = 1 in the limit of negligible interlayer tunneling under tilted magnetic field. We show that the intrinsic quasiparticle excitation is of purely pseudospin origin and solely governed by the inter- and intra-layer electron interactions. A model based on exciton formation successfully explains the quantitative behavior of the quasiparticle excitation gap, demonstrating the existence of a link between the excitonic QH state and the composite fermion liquid. Our results provide a new insight into the nature of the phase transition between the two states.Comment: 4 pages, 3 figure

    Strade: costi, opportunità e tutela dell’ambiente

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    Per raggiungere gli obiettivi di sostenibilità, è necessario rivedere l’intero sistema di governo del territorio ottimizzando, in un’ottica federalista, ruoli, poteri e risors

    An integrated approach project for the revaluation of a traditional sourdough bread production chain

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    The influence of organic and conventional farming systems on the performance of a panel of old and modern Italian bread wheat varieties has been evaluated, with the aim to individuate an agronomic protocol suitable for the production of a sourdough bread traditionally prepared in a hill zone of Emilia-Romagna. The agronomic and technological characterisation of the wheat samples obtained in organic and conventional farming conditions has been done and the sensorial qualities of the sourdough bread obtained have been evaluated

    Markov Chain Monte Carlo Model Selection for DAG Models

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    We present two methodologies for Bayesian model choice and averaging in Gaussian directed acyclic graphs (dags). In both cases model determination is carried out by implementing a reversible jump Markov Chain Monte Carlo sampler. The dimension-changing move involves adding or dropping a (directed) edge from the graph. The first methodology extends the results in Giudici and Green (1999), by excluding all non-moralized dags and searching in the space of their essential graphs. The second methodology employs the results in Geiger and Heckerman (1999) and searches directly in the space of all dags. To achieve this aim we rely on the concept of adjacency matrices, which provides a relatively inexpensive check for acyclicity. The performance of our procedure is illustrated by means of two simulated datasets
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