Clinical and medical knowledge evolve and this causes changes in concepts and terms that describe them. The objective of this work is to formally present an ontology-based standard architecture that will be used in th...
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With the rapidly increasing amount of molecular biological data available, the computer-based analysis of molecular interactions becomes more and more feasible. Methods for computer-aided molecular docking have to inc...
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With the rapidly increasing amount of molecular biological data available, the computer-based analysis of molecular interactions becomes more and more feasible. Methods for computer-aided molecular docking have to include a reasonably accurate model of energy and must be able to deal with the combinatorial complexity incurred by the molecular flexibility of the docking partners. In both respects, recent years have seen substantial progress.
We present new results in stochastic multi-objective optimization applied to focused ultrasonic therapy planning. This type of non-invasive therapy uses focused ultrasound for the destruction of tumor cells and magnet...
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ISBN:
(纸本)9789898565693
We present new results in stochastic multi-objective optimization applied to focused ultrasonic therapy planning. This type of non-invasive therapy uses focused ultrasound for the destruction of tumor cells and magnetic resonance tomography for identification of tumor volume and healthy organs. During the therapy planning the treatment parameters, such as frequency and intensity of ultrasound, are adjusted to achieve maximal tumor destruction and minimal influence to the healthy organs. For this purpose multi-objective optimization is used. RBF metamodeling is employed for continuous representation of discretely sampled results of numerical simulation and for evaluation of inherent uncertainties. We apply two algorithms for multi-objective optimization capable of non-convex Pareto front detection in the considered problem. Cross-validation procedure and sensitivity analysis are used for estimation of uncertainties. A realistic application case demonstrates the efficiency of the approach.
The quality of uni-directional tape in its production process is affected by environmental conditions like temperature and production speed. In this paper, computer vision algorithms on the scanned images are needed t...
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The large impact of civil water engineering to nature and society imposes high requirements for the precision of numerical simulations used in planning and evaluation of river engineering concepts. In particular, coup...
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ISBN:
(纸本)9789898565693
The large impact of civil water engineering to nature and society imposes high requirements for the precision of numerical simulations used in planning and evaluation of river engineering concepts. In particular, coupled morphodynamic - hydrodynamic simulation uses models of river bed evolution possessing uncertain parameters. The sources of uncertainty can be the natural variability, the deficient description of the physical processes in the model and the imprecision of the model parameters. The propagation of these uncertainties to the variance of the model result can be quantified with the aid of stochastic analysis. Precise evaluation of stochastic characteristics normally requires a huge amount of samples, which can be provided by surrogate-based modeling of simulation results. In this paper we present our advances in quantile estimation of morphodynamic simulations of river bed evolution. We use metamodeling of bulky simulation results with radial basis functions (RBF), quasi-Monte Carlo sampling (QMC) and efficient quantile estimator (QE). Four different quantile estimators have been tested. A realistic application case is used to demonstrate the efficiency of the approach.
In (Griebel and Hamaekers, Fast discrete Fourier transform on generalized sparse grids, Sparse grids and Applications, volume 97 of Lecture Notes in Computational Science and Engineering, pages 75–108, Springer, 2014...
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System-algebraic multigrid (AMG) provides a flexible framework for linear systems in simulation applications that involve various types of physical unknowns. Reservoir-simulation applications, with their driving ellip...
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Biological and medical researchers explore the mechanisms of living organisms and tend to gain a better understanding of underlying fundamental biological processes of life. To tackle such complex tasks they constantl...
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Relevance feedback for document retrieval systems is a technique where user feedback is used to improve a query response. In this work we propose a system that uses multiple clusterings and a semi-supervised heuristic...
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Knowledge Graphs are becoming a key instrument for biomedical knowledge discovery and modeling. These approaches rely on structured data, e.g. about related proteins or genes, and form cause-and-effect networks or - i...
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