The central subject of the book is the generalization of Loewy's decomposition - originally introduced by him for linear ordinary differential equations - to linear partial differential equations. Equations for a ...
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ISBN:
(数字)9783709112861
ISBN:
(纸本)3709112850
The central subject of the book is the generalization of Loewy's decomposition - originally introduced by him for linear ordinary differential equations - to linear partial differential equations. Equations for a single function in two independent variables of order two or three are comprehensively discussed. A complete list of possible solution types is given. Various ad hoc results available in the literature are obtained algorithmically. The border of decidability for generating a Loewy decomposition are explicitly stated. The methods applied may be generalized in an obvious way to equations of higher order, in more variables or systems of such equations.
In the recent decade, there has been a growing interest in the numerical treatment of high-dimensional problems. It is well known that classical numerical discretization schemes fail in more than three or four dimensi...
ISBN:
(纸本)9783642317026
In the recent decade, there has been a growing interest in the numerical treatment of high-dimensional problems. It is well known that classical numerical discretization schemes fail in more than three or four dimensions due to the curse of dimensionality. The technique of sparse grids helps overcome this problem to some extent under suitable regularity assumptions. This discretization approach is obtained from a multi-scale basis by a tensor product construction and subsequent truncation of the resulting multiresolution series expansion. This volume of LNCSE is a collection of the papers from the proceedings of the workshop on sparse grids and its applications held in Bonn in May 2011. The selected articles present recent advances in the mathematical understanding and analysis of sparse grid discretization. Aspects arising from applications are given particular attention.
Computer simulations of chemical systems can be used to reliably predict physical properties. Accurate molecular models, which are indispensable, are mathematically described by force fields, which have to be paramete...
Computer simulations of chemical systems can be used to reliably predict physical properties. Accurate molecular models, which are indispensable, are mathematically described by force fields, which have to be parameterized. Recently, an automated gradient-based parametrization procedure was published by the authors based on the minimization of a loss function between simulated and experimental physical properties. The applicability of the utilized algorithms is not trivial at all because of two reasons: First, simulation data is affected by statistical noise and second, the molecular simulations required for the loss function evaluations (involving finite differences approximations of gradients and Hessians) are extremely time-consuming. In this work, a more efficient approach to compute gradients and Hessians is presented. The method developed here is based on directional instead of partial derivatives. It is shown that up to 75% of the simulations can be avoided using this method.
In many applications, particularly in the engineering field, the need to consider uncertainties is recognized. To reduce the number of necessary simulations, metamodels can be used. We present a novel method on the ba...
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ISBN:
(纸本)9783950353709
In many applications, particularly in the engineering field, the need to consider uncertainties is recognized. To reduce the number of necessary simulations, metamodels can be used. We present a novel method on the basis of metamodels, that allows us to model not only the deterministic responses, but also the propagation of uncertainty in the entire design space. Our procedure makes it possible to determine the robust optimum quickly with common multi-criteria optimization algorithms. The novel approach offers the possibility to include the tolerance of the metamodel in the calculation. We introduce a new class of robustness measures that characterizes the propagation of uncertainty more accurately than usual: the median as measure of central tendency and the difference between median and a high quantile q as measure of dispersion. This allows the user to adjust the degree of robustness to his wishes via q. It can handle even extremely skewed distributions in an appropriate way. For the determination of the quantiles we use a novel combination of sampling scheme and nonparametric quantile estimation. This enables a fast computation on a local level. The suitability of the proposed proceeding is proved on several examples. The applicability is demonstrated on a real life example from automotive industry.
scientific workflows have emerged as an important tool for combining computational power with data analysis for all scientific domains in e-science. They help scientists to design and execute complex in silico experim...
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scientific workflows have emerged as an important tool for combining computational power with data analysis for all scientific domains in e-science. They help scientists to design and execute complex in silico experiments. However, with increasing complexity it becomes more and more infeasible to optimize scientific workflows by trial and error. To address this issue, this paper describes the design of a new optimization phase integrated in the established scientific workflow life cycle. We have also developed a flexible optimization application programming interface (API) and have integrated it into a scientific workflow management system. A sample plugin for parameter optimization based on genetic algorithms illustrates, how the API enables rapid implementation of concrete workflow optimization methods. Finally, a use case taken from the area of structural bioinformatics validates how the optimization approach facilitates setup, execution and monitoring of workflow parameter optimization in high performance computing e-science environments.
Relation extraction is frequently and successfully addressed by machine learning methods. The downside of this approach is the need for annotated training data, typically generated in tedious manual, cost intensive wo...
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ISBN:
(纸本)9781622764907
Relation extraction is frequently and successfully addressed by machine learning methods. The downside of this approach is the need for annotated training data, typically generated in tedious manual, cost intensive work. Distantly supervised approaches make use of weakly annotated data, like automatically annotated corpora. Recent work in the biomedical domain has applied distant supervision for protein-protein interaction (PPI) with reasonable results making use of the IntAct database. Such data is typically noisy and heuristics to filter the data are commonly applied. We propose a constraint to increase the quality of data used for training based on the assumption that no self-interaction of real-world objects are described in sentences. In addition, we make use of the University of Kansas Proteomics Service (KUPS) database. These two steps show an increase of 7 percentage points (pp) for the PPI corpus AIMed. We demonstrate the broad applicability of our approach by using the same workflow for the analysis of drug-drug interactions, utilizing relationships available from the drug database DrugBank. We achieve 37.31 % in F_1 measure without manually annotated training data on an independent test set.
In many numerical simulation codes the backbone of the application covers the solution of linear systems of equations. Often, being created via a discretization of differential equations, the corresponding matrices ar...
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Hydraulic axial pumps equipped with cam-driven commutation unit (PWK pumps) proved their high efficiency up to 55 MPa and ability to work self-sucking, even at high speed. Displacement of PWK pump may easily be change...
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Aircraft Environmental Control Systems (ECS) are designed to optimize passenger comfort by providing satisfactory cabin pressurization, and temperature and humidity control whilst minimising the risks to passenger hea...
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