Interactive Visual Analysis of Networked Systems: Workflows for Two Industrial Domains

We report on a first study of interactive visual analysis of networked systems. Working with ABB Corporate Research and Ericsson Research, we have created workflows which demonstrate the potential of visualization in the domains of industrial automation and telecommunications. By a workflow in this context, we mean a sequence of visualizations and the actions for generating them. Visualizations can be any images that represent properties of the data sets analyzed, and actions typically either change the selection of data visualized or change the visualization by choice of technique or change of parameters

Efficient algorithms for multidimensional global optimization in genetic mapping of complex traits

We present a two-phase strategy for optimizing a multidimensional, nonconvex function arising during genetic mapping of quantitative traits. Such traits are believed to be affected by multiple so called quantitative trait loci (QTL), and searching for d QTL results in a d-dimensional optimization problem with a large number of local optima. We combine the global algorithm DIRECT with a number of local optimization methods that accelerate the final convergence, and adapt the algorithms to problem-specific features. We also improve the evaluation of the QTL mapping objective function to enable exploitation of the smoothness properties of the optimization landscape. Our best two-phase method is demonstrated to be accurate in at least six dimensions and up to ten times faster than currently used QTL mapping algorithms

Проектирование электрической части подстанции 110/10 кВ "Мясокомбинат" Волковысских электрических сетей

eSSENC

A parallel domain decomposition method for the Helmholtz equation

A parallel solver for the Helmholtz equation in a domain consisting of layers with different material properties is presented. A fourth-order accurate finite difference discretization is used. The arising system of equations is solved with a preconditioned Krylov subspace method. A domain decomposition framework is employed, where fast transform subdomain preconditioners are used. Three ways of treating the Schur complement of the preconditioner are investigated, and the corresponding preconditioned iterative methods are compared with a standard direct method. It is noted that the convergence rate of the iterative methods is closely related to how the Schur complement system for the preconditioner is formed, and how accurately it is solved. However, in almost all cases, the gain in both memory requirements and arithmetic complexity is large compared with the direct method. Furthermore, the gain increases with problem size, allowing problems with many unknowns to be solved efficiently. The efficiency is further improved by parallelization using message-passing, enabling us to solve even larger Helmholtz problems in less time