1,720,958 research outputs found
Adaptive und nichtintrusive Unsicherheitsbestimmung für hochdimensionale parametrische Differentialgleichungen
No full textThis thesis concerns the combination of dependable error control and data based approximation to derive non-intrusive and reliable algorithms for uncertainty quantification in forward and inverse problems. In particular Bayesian inverse problems subject to high-dimensional parametric forward models driven by partial differential equations are the main focus. Access to stochastic moments or marginals of the Bayesian posterior typically requires many evaluations of the time-consuming forward model due to slowconverging sampling methods or high-dimensional numerical quadrature. Alternative surrogate modelling of the forward process through polynomial expansions succumbs to the curse of dimensionality, i.e. the exponential dependence of the number of expansion terms with respect to the parameter dimension. Hierarchical tensor representations, in particular the Tensor Train format, are employed to alleviate this exponential scaling under the assumption of a low-rank representability of the sought functions. To reduce the computational complexity of the forward model even further, adaptive strategies based on a posteriori error estimators are employed and investigated with regard to solvability, convergence and stability in the low-rank tensor format. The non-intrusiveness of the presented methods is ensured by linear and non-linear regression techniques that solely rely on pointwise evaluations of the parametric forward model and are equivalent to a Galerkin approximation with high probability if enough samples are used. Both the Bayesian framework under the assumption of Gaussian noise and the computation of the error estimator for the case of a lognormal coefficient field involve the exponentiation of functions naturally accessible in the hierarchical tensor format. For those exponentials, a Galerkin-type method, which yields computable upper and lower bounds for the approximation error for any discrete function in an induced energy norm, is derived. These results are applied to two different types of real-world parametric problems, namely steady-state diffusion through a medium and optical scattering of electromagnetic waves on nanostructures. For the latter, shape parameters of silicon line gratings are reconstructed for two different types of measurement techniques and their associated uncertainties are determined through a surrogate based posterior sampling scheme and via a measure transport approach.Diese Dissertation beschäftigt sich mit der Kombination aus verlässlicher Fehlerkontrolle und datenbasierter Approximation um nicht-intrusive und zuverlässige Algorithmen zur Bestimmung von Unsicherheiten bei Vorwärts- und inversen Problemen zu entwickeln. Der Fokus liegt hierbei insbesondere auf Bayesschen inversen Problemen mit hoch-dimensionalen parameterabhängigen Vorwärtsmodellen denen partielle Differentialgleichungen zu Grunde liegen. Die Berechnung stochastischer Momente oder Marginale der Bayesschen Posterior-Dichte benötigt typischer Weise sehr viele Auswertungen des zeitaufwendigen Vorwärtsmodells aufgrund von langsam konvergierenden Sampling-Methoden oder hoch-dimensionalen Quadraturformeln. Eine alternative Surrogatmodellierung des Vorwärtsprozesses durch eine Polynomreihenentwicklung leidet unter dem Fluch der Dimensionen, d.h. unter der exponentiellen Abhängigkeit der Anzahl der Entwicklungsterme bezüglich der Parameterdimension. Hierarchische Tensordarstellungen, insbesondere das Tensor Train Format, werden angewendet um diese exponentielle Abhängigkeit abzumildern. Dabei wird angenommen, dass die gesuchten Funktionen mit einem niedrigen Rang dargestellt werden können. Um die Komplexität des Vorärtsmodells noch weiter zu reduzieren werden adaptive Strategien, die auf a posteriori Fehlerschätzern basieren, angewendet und auf Lösbarkeit, Konvergenz und Stabilität bezüglich des angewendeten niedrigrang Tensorformats untersucht. Die Nichtintrusivität der vorgestellten Methode wird gesichert indem lineare und nichtlineare Regressionsverfahren angewendet werden, die einzig auf punktweisen Auswertungen des parametrischen Vorwärtsmodells basieren und mit hoher Wahrscheinlichkeit äquivalent zu einer Galerkin Approximation sind, sofern genug Trainingsdaten verwendet werden. Sowohl das Bayessche Framework unter der Annahme von Gaußschem Messrauschen als auch die Berechnung der Fehlerschätzer für den Fall eines lognormalen Koeffizientenfeldes involvieren die Exponentiation von Funktionen die auf natürliche Weise in einem hierarchischen Tensorformat gegeben sind. Für diese Exponentiale wird eine Galerkin Methode, die berechenbare untere und obere Fehlerschranken für den Approximationsfehler durch beliebige diskrete Funktionen in der induzierten Energienorm aufweist, hergeleitet. Diese Resultate werden auf zwei verschiedene Typen von realen parametrischen Problemen, die zeitharmonische Diffusion durch ein Medium sowie die optische Streuung von elektromagnetischen Wellen an Nanostrukturen, angewendet. Für die optische Streuung werden Formparameter von Siliziumgittern für zwei verschiedene experimentelle Messtechniken rekonstruiert und deren Unsicherheiten durch ein Surrogat basiertes Sampling Schema sowie durch einen Maß-Transport Ansatz bestimmt.BMWK, ZF4014017RR7, Zentrales Innovationsprogramm Mittelstand (ZIM
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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