6,823 research outputs found

    Distributed Partitioned Big-Data Optimization via Asynchronous Dual Decomposition

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    In this paper we consider a novel partitioned framework for distributed optimization in peer-to-peer networks. In several important applications the agents of a network have to solve an optimization problem with two key features: (i) the dimension of the decision variable depends on the network size, and (ii) cost function and constraints have a sparsity structure related to the communication graph. For this class of problems a straightforward application of existing consensus methods would show two inefficiencies: poor scalability and redundancy of shared information. We propose an asynchronous distributed algorithm, based on dual decomposition and coordinate methods, to solve partitioned optimization problems. We show that, by exploiting the problem structure, the solution can be partitioned among the nodes, so that each node just stores a local copy of a portion of the decision variable (rather than a copy of the entire decision vector) and solves a small-scale local problem

    NETVOLC: An algorithm for automatic delimitation of volcano edifice boundaries using DEMs

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    Accurately delimiting boundaries is required for characterizing landforms through measurement of their geomorphometric parameters. Volcanism produces a wide range of landforms, from symmetric cones to very irregular massifs, that can gradually merge with the surroundings and contain other elements, thus complicating landform delimitation. Most morphometric studies of volcanoes delimit landforms manually, with the inconvenience of being time-consuming and subjective. Here we propose an algorithm, NETVOLC, for automatic volcano landform delimitation based on the premise that edifices are bounded by concave breaks in slope. NETVOLC applies minimum cost flow (MCF) networks for computing the best possible edifice outline using a DEM and its first- and second-order derivatives. The main cost function considers only profile convexity and aspect; three alternative functions (useful in complex cases) also consider slope, elevation and/or radial distance. NETVOLC performance is tested by processing the Mauna Kea pyroclastic cone field. Results using the main cost function compare favorably to manually delineated outlines in 2/3rds of cases, whereas for the remaining 1/3rd of cases an alternative cost function is needed, introducing some degree of subjectivity. Our algorithm provides a flexible, objective and time-saving tool for automatically delineating volcanic edifices. Furthermore, it could be used for delineating other landforms with concave breaks in slope boundaries. Finally, straightforward modifications can be implemented to extend the algorithm capabilities for delimiting landforms bounded by convex breaks in slope, such as summit craters and calderas.Fil: Euillades, Leonardo Daniel. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mendoza; ArgentinaFil: Grosse, Pablo. Fundación Miguel Lillo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Euillades, Pablo Andrés. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mendoza; Argentin
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