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See detailUnbekanntere Seiten von Fremdenfeindlichkeit und wie man damit umgeht. Neuere Forschungsbefunde und Praxisanregungen
Willems, Helmut UL; Wahl, Klaus

in Themenheft Diskurs - Studien zu Kindheit, Jugend, Familie und Gesellschaft (2001), (2),

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See detailUnbiased H∞ filtering for a class of stochastic systems with time-varying delay
Li, Yumei UL; Guan, Xinping; Luo, Xiaoyuan

in The 21st annual international conference on Chinese control and decision conference (2009)

This paper presents the unbiased H∞ filter design for a class of stochastic systems with time-varying delay. The aim is to design an unbiased filter assuring exponential stability in mean square and a ... [more ▼]

This paper presents the unbiased H∞ filter design for a class of stochastic systems with time-varying delay. The aim is to design an unbiased filter assuring exponential stability in mean square and a prescribed H∞ performance level for the filtering error system. Based on the application of the descriptor model transformation and free weighting matrices, delay-dependent sufficient conditions for stochastic systems with time-varying delay are proposed respectively in terms of linear matrix inequalities(LMIs). Numerical examples demonstrate the proposed approaches are effective and are an improvement over existing methods. [less ▲]

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See detailUnbiased H∞ Infinite Filtering for Stochastic Systems with Data Packet Losses
Li, Yumei UL; Zhao, Bin; Guan, Xinping

in Advanced Materials Research (2011), 204-210

This paper presents the unbiased H∞ filter design for stochastic systems with data packet losses. By constructing unbiased filter, the complexity and computational burden of the real-time filtering ... [more ▼]

This paper presents the unbiased H∞ filter design for stochastic systems with data packet losses. By constructing unbiased filter, the complexity and computational burden of the real-time filtering process are reduced greatly. Delay-dependent sufficient conditions for stochastic system with data packet losses are proposed in terms of linear matrix inequalities (LMIs). Numerical example demonstrates the proposed approaches are effective. [less ▲]

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See detailUncertain demand and supply in energy markets
Zanaj, Skerdilajda UL

Scientific Conference (2016)

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See detailUncertainty avoidance, risk tolerance and corporate takeover decisions
Frijns, Bart; Gilbert, Aaron; Tourani Rad, Ali Reza et al

in Journal of Banking and Finance (2013), 37

In this paper, we examine the role of national culture in corporate takeover decisions, by arguing that managerial risk tolerance (a combination of risk aversion and risk perception), at the national ... [more ▼]

In this paper, we examine the role of national culture in corporate takeover decisions, by arguing that managerial risk tolerance (a combination of risk aversion and risk perception), at the national level, is a cultural trait and affects the expected net synergies CEOs require. We propose a theoretical framework that links CEO risk tolerance to the expected net synergies. We empirically show that CEOs of firms located in countries with lower levels of risk tolerance, measured by Hofstede’s (1980, 2001) uncertainty avoidance score, require higher premiums on takeovers, and show that uncertainty avoidance plays a greater role in relatively large takeovers. Additional testing reveals that CEOs from high uncertainty avoiding nations engage less in cross-border/cross-industry takeovers, suggesting that uncertainty avoidance captures more the CEO’s risk perception than his/her risk aversion. [less ▲]

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See detailUncertainty of absolute gravity measurements
Van Camp, Michel; Williams, Simon D. P.; Francis, Olivier UL

in Journal of Geophysical Research (2005), 110(B05406), 1-9

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See detailUncertainty propagation in stochastic fractional order processes using spectral methods: A hybrid approach
Duong, Pham UL

in Communications in Nonlinear Science & Numerical Simulation (2012), 17(11), 4262-4273

Stochastic spectral methods are widely used in uncertainty propagation thanks to its ability to obtain highly accurate solution with less computational demand. A novel hybrid spectral method is proposed ... [more ▼]

Stochastic spectral methods are widely used in uncertainty propagation thanks to its ability to obtain highly accurate solution with less computational demand. A novel hybrid spectral method is proposed here that combines generalized polynomial chaos (gPC) and operational matrix approaches. The hybrid method takes advantage of gPC’s efficient handling of large parameter uncertainties and overcomes its limited applicability to systems with relatively highly correlated inputs. The hybrid method’s use of operational matrices allows analyses of systems with low input correlations without suffering its restriction to small parameter uncertainties. The hybrid method is aimed to propagate uncertainties in fractional order systems with random parameters and random inputs with low correlation lengths. It is validated through several examples with different stochastic uncertainties.Comparison with Monte Carlo and gPC demonstrates the superior computational efficiency of the proposed method. [less ▲]

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See detailUncertainty Quantification - Sensitivity Analysis / Biomechanics
Hauseux, Paul UL; Hale, Jack UL; Bordas, Stéphane UL

Presentation (2017, February)

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See detailUncertainty quantification and global sensitivity analysis of complex chemical process using a generalized polynomial chaos approach
Duong, Pham UL

in Computers & Chemical Engineering (2016), 90(7), 23-30

Uncertainties are ubiquitous and unavoidable in process design and modeling. Because they can significantly affect the safety, reliability and economic decisions, it is important to quantify these ... [more ▼]

Uncertainties are ubiquitous and unavoidable in process design and modeling. Because they can significantly affect the safety, reliability and economic decisions, it is important to quantify these uncertainties and reflect their propagation effect to process design. This paper proposes the application of generalized polynomial chaos (gPC)-based approach for uncertainty quantification and sensitivity analysis of complex chemical processes. The gPC approach approximates the dependence of a process state or output on the process inputs and parameters through expansion on an orthogonal polynomial basis. All statistical information of the interested quantity (output) can be obtained from the surrogate gPC model. The proposed methodology was compared with the traditional Monte-Carlo and Quasi Monte-Carlo sampling-based approaches to illustrate its advantages in terms of the computational efficiency. The result showed that the gPC method reduces computational effort for uncertainty quantification of complex chemical processes with an acceptable accuracy. Furthermore, Sobol’s sensitivity indices to identify influential random inputs can be obtained directly from the surrogated gPC model, which in turn further reduces the required simulations remarkably. The framework developed in this study can be usefully applied to the robust design of complex processes under uncertainties. [less ▲]

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See detailUncertainty quantification for soft tissue biomechanics
Hauseux, Paul UL; Hale, Jack UL; Bordas, Stéphane UL

Poster (2016, December)

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See detailUncertainty Quantification in Finite Element Models:Application to SoftTissue Biomechanics
Hauseux, Paul UL; Hale, Jack UL; Bulle, Raphaël UL et al

Scientific Conference (2018, July 23)

We present probabilistic approaches aiming at the selection of the best constitutive model and to identify their parameters from experimental data. These parameters are always associated with some degree ... [more ▼]

We present probabilistic approaches aiming at the selection of the best constitutive model and to identify their parameters from experimental data. These parameters are always associated with some degree of uncertainty. It is therefore important to study how this statistical uncertainty in parameters propagates to a safety-critical quantity of interest in the output of a model. Efficient Monte Carlo methods based on variance reduction techniques (Sensitivity Derivatives Monte Carlo methods [Hauseux et al. 2017] and MultiLevel Monte Carlo [Giles 2015] methods) are employed to propagate this uncertainty for both random variables and random fields. Inverse and forward problems are strongly connected. In a bayesian setting [Matthies et al. 2017], developing methods that reduce the number of evaluations of the forward model to an absolute minimum to achieve convergence is crucial for tractable computations. Numerical results in the context of soft tissue biomechanics are presented and discussed. [less ▲]

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See detailUncertainty quantification of dry woven fabrics: A sensitivity analysis on material properties
Akmar, Ilyani; Lahmer, Tom; Beex, Lars UL et al

in Composite Structures (2014), 116

Based on sensitivity analysis, we determine the key meso-scale uncertain input variables that influence the macro-scale mechanical response of a dry textile subjected to uni-axial and biaxial deformation ... [more ▼]

Based on sensitivity analysis, we determine the key meso-scale uncertain input variables that influence the macro-scale mechanical response of a dry textile subjected to uni-axial and biaxial deformation. We assume a transversely isotropic fashion at the macro-scale of dry woven fabric. This paper focuses on global sensitivity analysis; i.e. regression- and variance-based methods. The sensitivity of four meso-scale uncertain input parameters on the macro-scale response are investigated; i.e. the yarn height, the yarn spacing, the yarn width and the friction coefficient. The Pearson coefficients are adopted to measure the effect of each uncertain input variable on the structural response. Due to computational effectiveness, the sensitivity analysis is based on response surface models. The Sobol’s variance-based method which consists of first-order and total-effect sensitivity indices are presented. The sensitivity analysis utilizes linear and quadratic correlation matrices, its corresponding correlation coefficients and the coefficients of determination of the response uncertainty criteria. The correlation analysis, the response surface model and Sobol’s indices are presented and compared by means of uncertainty criteria influences on MataBerkait-dry woven fabric material properties. To anticipate, it is observed that the friction coefficient and yarn height are the most influential factors with respect to the specified macro-scale mechanical responses. [less ▲]

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See detailUncertainty Quantification of Exponential Synchronization for a Novel Class of Complex Dynamical Networks with Hybrid TVD Using PIPC
Pan, Lin UL; Voos, Holger UL; Li, Yumei UL et al

in Control and Decision Conference (CCDC), 2015 27th Chinese (2015, May 23)

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See detailUncertainty Quantification of Group Synchronization and Control of a New Class of Adaptive Complex Dynamical Network with Brownian Motion and Time-varying Delay
Pan, Lin UL; Voos, Holger UL; Darouach, Mohamed

in Control Conference (CCC), 2014 33rd Chinese (2014, July 28)

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See detailUnconventional Monetary Policies and the European Central Bank's Problematic Democratic Legitimacy
Högenauer, Anna-Lena UL; Howarth, David UL

in Zeitschrift für öffentliches Recht (2016), 71(2), 124

Prior to the international fi nancial crisis, the ECB’s policies were shaped by the interpretation that its mandate was primarily to ensure low infl ation. Since the outbreak of the sovereign debt crisis ... [more ▼]

Prior to the international fi nancial crisis, the ECB’s policies were shaped by the interpretation that its mandate was primarily to ensure low infl ation. Since the outbreak of the sovereign debt crisis in early 2010, the ECB has adopted a range of policies which have pushed its role well beyond that interpretation. This article presents the argument that ECB policy-making since the start of 2010 undermines the democratic legitimacy of the ECB. The problems stem from three developments: the stretching – and arguably breach – of the ECB’s mandate; the increasing politicization of the ECB’s decisions and policies; and the extent to which the ECB’s policies undermine the transparency of both its own monetary policy and national macroeconomic policies. [less ▲]

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See detailUnconventional superconductivity in the extended Hubbard model: Weak-coupling renormalization group
Wolf, Sebastian; Schmidt, Thomas UL; Rachel, Stephan

in Physical Review. B, Condensed Matter and Materials Physics (2018)

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See detailUNCRPD Article 27: sheltered workshops and inclusion; a point of discussion
Limbach-Reich, Arthur UL

Scientific Conference (2015)

Detailed reference viewed: 57 (1 UL)