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This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cramér–von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices.
Armiranobetonske (AB) zgrade sa zidanom ispunom
se izvode u mnogim zemljama širom sveta. Iako se
zidana ispuna posmatra kao nekonstruktivni element, ona
značajno utiče na promenu dinamičkih karakteristika AB
ramovskih konstrukcija u toku zemljotresnog dejstva.
Odskora, značajan napor je utrošen na istraživanje
izolovanih ispuna, koje su odvojene od okolnog rama
obično ostavljanjem prostora između rama i ispune. U
ovom slučaju deformacija rama ne aktivira ispunu i na taj
način ispuna ne utiče na ponašanje rama. Ovaj rad
predstavlja rezultate istraživanja ponašanja AB
ramovskih zgrada sa INODIS sistemom koji izoluje ispunu
u odnosu na okolni ram. Uticaj izolovane ispune je prvo
ispitan na jednospratnim i jednobrodnim ramovima. Ovo
je iskorišćeno kao osnova za parametarsku analizu na
višespratnim i višebrodnim ramovima, kao i na primeru
zgrade. Promena krutosti i dinamičkih karakteristika je
analizirano kao i odgovor pri zemljotresnom dejstvu.
Izvršeno je poređenje sa praznom ramovskom
konstrukcijom kao i ramovima ispunjenim ispunom na
tradicionalni način. Rezultati pokazuju da je ponašanje
ramova sa izolovanom ispunom slično ponašanju praznih
ramova, dok je ponašanje ramova sa tradicionalnom
ispunom daleko drugačije i zahteva kompleksne
numeričke modele. Ovo znači da ukoliko se primeni
adekvatna konstruktivna mera izolacije ispune, proračun
ramovskim zgrada sa zidanom ispunom se može
značajno pojednostaviti.
On the basis of bivariate data, assumed to be observations of independent copies of a random vector (S,N), we consider testing the hypothesis that the distribution of (S,N) belongs to the parametric class of distributions that arise with the compound Poisson exponential model. Typically, this model is used in stochastic hydrology, with N as the number of raindays, and S as total rainfall amount during a certain time period, or in actuarial science, with N as the number of losses, and S as total loss expenditure during a certain time period. The compound Poisson exponential model is characterized in the way that a specific transform associated with the distribution of (S,N) satisfies a certain differential equation. Mimicking the function part of this equation by substituting the empirical counterparts of the transform we obtain an expression the weighted integral of the square of which is used as test statistic. We deal with two variants of the latter, one of which being invariant under scale transformations of the S-part by fixed positive constants. Critical values are obtained by using a parametric bootstrap procedure. The asymptotic behavior of the tests is discussed. A simulation study demonstrates the performance of the tests in the finite sample case. The procedure is applied to rainfall data and to an actuarial dataset. A multivariate extension is also discussed.
FEM shakedown analysis of structures under random strength with chance constrained programming
(2022)
Direct methods, comprising limit and shakedown analysis, are a branch of computational mechanics. They play a significant role in mechanical and civil engineering design. The concept of direct methods aims to determine the ultimate load carrying capacity of structures beyond the elastic range. In practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and constraints. If strength and loading are random quantities, the shakedown analysis can be formulated as stochastic programming problem. In this paper, a method called chance constrained programming is presented, which is an effective method of stochastic programming to solve shakedown analysis problems under random conditions of strength. In this study, the loading is deterministic, and the strength is a normally or lognormally distributed variable.
Purpose
In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset.
Design/methodology/approach
In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments.
Findings
Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model.
Originality/value
For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future.
The European Union's aim to become climate neutral by 2050 necessitates ambitious efforts to reduce carbon emissions. Large reductions can be attained particularly in energy intensive sectors like iron and steel. In order to prevent the relocation of such industries outside the EU in the course of tightening environmental regulations, the establishment of a climate club jointly with other large emitters and alternatively the unilateral implementation of an international cross-border carbon tax mechanism are proposed. This article focuses on the latter option choosing the steel sector as an example. In particular, we investigate the financial conditions under which a European cross border mechanism is capable to protect hydrogen-based steel production routes employed in Europe against more polluting competition from abroad. By using a floor price model, we assess the competitiveness of different steel production routes in selected countries. We evaluate the climate friendliness of steel production on the basis of specific GHG emissions. In addition, we utilize an input-output price model. It enables us to assess impacts of rising cost of steel production on commodities using steel as intermediates. Our results raise concerns that a cross-border tax mechanism will not suffice to bring about competitiveness of hydrogen-based steel production in Europe because the cost tends to remain higher than the cost of steel production in e.g. China. Steel is a classic example for a good used mainly as intermediate for other products. Therefore, a cross-border tax mechanism for steel will increase the price of products produced in the EU that require steel as an input. This can in turn adversely affect competitiveness of these sectors. Hence, the effects of higher steel costs on European exports should be borne in mind and could require the cross-border adjustment mechanism to also subsidize exports.
Unternehmen sind in der Regel überzeugt, dass sie die Bedürfnisse ihrer Kunden in den Mittelpunkt stellen. Aber in der direkten Interaktion mit dem Kunden zeigen sie häufig Schwächen. Der folgende Beitrag illustriert, wie durch eine konsequente Ausrichtung der Wertschöpfungsprozesse auf die zentralen Kundenbedürfnisse ein Dreifacheffekt erzielt werden kann: Nachhaltig erhöhte Kundenzufriedenheit, gesteigerte Effizienz und eine Differenzierung im Wettbewerb.
Kundenanforderungen an Netzwerke haben sich in den vergangenen Jahren stark verändert. Mit NFV und SDN sind Unternehmen technisch in der Lage, diesen gerecht zu werden. Die Provider stehen jedoch vor großen Herausforderungen: Insbesondere Produkte und Prozesse müssen angepasst und agiler werden, um die Stärken von NFV und SDN zum Kundenvorteil auszuspielen.
Die Durchführung einer systematischen Literaturrecherche ist eine zentrale Kompetenz wissenschaftlichen Arbeitens und bildet daher einen festen Ausbildungsbestandteil von Bachelor- und Masterstudiengängen. In entsprechenden Lehrveranstaltungen werden Studierende zwar mit den grundlegenden Hilfsmitteln zur Suche und Verwaltung von Literatur vertraut gemacht, allerdings werden die Potenziale textanalytischer Methoden und Anwendungssysteme (Text Mining, Text Analytics) dabei zumeist nicht abgedeckt. Folglich werden Datenkompetenzen, die zur systemgestützten Analyse und Erschließung von Literaturdaten erforderlich sind, nicht hinreichend ausgeprägt. Um diese Kompetenzlücke zu adressieren, ist an der Hochschule Osnabrück eine Lehrveranstaltung konzipiert und projektorientiert umgesetzt worden, die sich insbesondere an Studierende wirtschaftswissenschaftlicher Studiengänge richtet. Dieser Beitrag dokumentiert die fachliche sowie technische Ausgestaltung dieser Veranstaltung und zeigt Potenziale für die künftige Weiterentwicklung auf.