1,490 research outputs found

    Customized risk assessment in military shipbuilding

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    This paper describes a customized risk assessment framework to be applied in military shipbuilding projects. The framework incorporates the Delphi method with visual diagrams, Bayesian Networks (BN) and the expression of expert opinions through linguistic variables. Noisy-OR and Leak Canonical models are used to determine the conditional probabilities of the BN model. The approach can easily be adapted for other shipbuilding construction projects. The visual diagrams that support the Delphi questionnaire favor the comprehensive visualization of the interdependencies between risks, causes, risks and causes, and risks and effects. The applicability of the framework is illustrated through the assessment of risk of two real military shipbuilding projects. This assessment includes a sensitivity analysis that is useful to prioritize mitigation actions. In the two cases studies, the risks with higher probability of occurrence were failures or errors in production, of the contracted, in the requirements, and in planning. The results of the sensitivity analysis showed that a set of mitigation actions directed at relatively easily controllable causes would have achieved important reductions in risk probabilities.- (undefined

    A Geneaology of Correspondence Analysis: Part 2 - The Variants

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    In 2012, a comprehensive historical and genealogical discussion of correspondence analysis was published in Australian and New Zealand Journal of Statistics. That genealogy consisted of more than 270 key books and articles and focused on an historical development of the correspondence analysis,a statistical tool which provides the analyst with a visual inspection of the association between two or more categorical variables. In this new genealogy, we provide a brief overview of over 30 variants of correspondence analysis that now exist outside of the traditional approaches used to analysethe association between two or more categorical variables. It comprises of a bibliography of a more than 300 books and articles that were not included in the 2012 bibliography and highlights the growth in the development ofcorrespondence analysis across all areas of research

    Dynamic load balancing for the distributed mining of molecular structures

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    In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable for large-scale, multi-domain, heterogeneous environments, such as computational grids

    Optimization of Trading Physics Models of Markets

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    We describe an end-to-end real-time S&P futures trading system. Inner-shell stochastic nonlinear dynamic models are developed, and Canonical Momenta Indicators (CMI) are derived from a fitted Lagrangian used by outer-shell trading models dependent on these indicators. Recursive and adaptive optimization using Adaptive Simulated Annealing (ASA) is used for fitting parameters shared across these shells of dynamic and trading models

    Vol. 13, No. 1 (Full Issue)

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