Search results for "uncertainty."
showing 10 items of 972 documents
Robust output feedback control of non-collocated low-damped oscillating load
2021
For systems with order of dynamics higher than two and oscillating loads with low damping, a non-collocation of the sensing and control can deteriorate robustness of the feedback and, in worst case, even bring it to instability. Furthermore, for a contactless sensing of the oscillating mechanical load, like in the system under investigation, the control structure is often restricted to the single proportional feedback only. This paper proposes a novel robust feedback control scheme for a low-damped fourth-order system using solely the measured load displacement. For reference tracking, the loop shaping design relies on a band reject filter, while the plant uncertainties are used as robustne…
Managing hepatitis C in liver transplant patients with recurrent infection
2009
Tim Zimmermann1, Gerd Otto2, Marcus Schuchmann11Department of Internal Medicine, 2Transplantation Surgery, University of Mainz, GermanyAbstract: Hepatitis C virus (HCV) reinfection after liver transplantation (LT) and recurrent hepatitis C often lead to recurrent cirrhosis (RC). RC is one of the most frequent complications resulting in organ failure and early death after LT in HCV-positive patients with reported 5-year rates from 20% to 40%. As HCV-cirrhosis is one of the leading indications for LT, the therapeutic management is a central issue. To date, the best available therapy is a combination of pegylated interferon + ribavirin in patients with established recurrent hepatitis C proven …
Sensitivity and uncertainty analysis of an integrated ASM2d MBR model for wastewater treatment
2018
Abstract An integrated membrane bioreactor (MBR) model was previously proposed and tested. The model provides a comprehensive and detailed description of the nitrogen biological removal processes with respect to up-to-date literature. This paper presents a sensitivity and uncertainty analysis aimed at identifying the key factors affecting the variability of the model predictions. The Standardized Regression Coefficients (SRC) method was adopted for the sensitivity analysis. The uncertainty analysis was employed by running Monte Carlo simulations by varying only the value of the key factors affecting the model outputs. The sensitivity analysis combined with the uncertainty analysis applied h…
The Integrated Nested Laplace Approximation for fitting Dirichlet regression models
2022
This paper introduces a Laplace approximation to Bayesian inference in Dirichlet regression models, which can be used to analyze a set of variables on a simplex exhibiting skewness and heteroscedasticity, without having to transform the data.These data, which mainly consist of proportions or percentages of disjoint categories, are widely known as compositional data and are common in areas such as ecology, geology, and psychology. We provide both the theoretical foundations and a description of how Laplace approximation can be implemented in the case of Dirichlet regression.The paper also introduces the package dirinla in the R-language that extends the RINLA package, which can not deal dire…
Covariate-informed latent interaction models: Addressing geographic & taxonomic bias in predicting bird-plant interactions
2023
Reductions in natural habitats urge that we better understand species' interconnection and how biological communities respond to environmental changes. However, ecological studies of species' interactions are limited by their geographic and taxonomic focus which can distort our understanding of interaction dynamics. We focus on bird-plant interactions that refer to situations of potential fruit consumption and seed dispersal. We develop an approach for predicting species' interactions that accounts for errors in the recorded interaction networks, addresses the geographic and taxonomic biases of existing studies, is based on latent factors to increase flexibility and borrow information acros…
Entry under uncertainty: Limit and most-favored-customer pricing
2015
Abstract In the absence of uncertainty, an incumbent that attempts to prevent entry of rival firms can have no incentive to offer a most-favored-customer (MFC) clause because it could lead to higher post-entry prices. Our analysis suggests that this is not necessarily the case under uncertainty. In the presence of uncertainty, the incumbent can set a limit price that affects the entry decision. Limit pricing involves a pre-entry price different from the static monopoly price, which leads to a signaling cost. We show that part of this cost can be distributed over several periods by means of consumer refunds from the MFC clause. If the discount factor is not very high, the incumbent adopts th…
The migrant crisis in the Mediterranean Sea: Empirical evidence on policy interventions
2021
Abstract This paper presents a novel set of empirical evidence to explore several hypotheses regarding the migrant crisis in the Mediterranean Sea. The political instability in transit countries, such as Libya, that made pre-existent repatriation policies ineffective, called for several search-and-rescue operations in the Mediterranean, which in turn have been wrongly accused of fostering illegal immigration and increasing deaths at sea. The empirical results show that the main determinants of the departures are several root causes at the departing African countries, underlining the importance of fighting human smuggling networks. The paper suggests a change in migration studies’ perspectiv…
Measurement uncertainty impact on simplified load flow analysis in MV smart grids
2018
This work is focused on the measurement uncertainty impact on load flow analysis in medium voltage (MV) distribution networks. In more detail, the paper presents the uncertainty evaluation of a simplified load flow algorithm, which is based on the load power measurements at each secondary substation and one voltage measurement at the slack bus (i.e. the voltage at the MV bus bars of the primary substation). To reduce the costs of the monitoring system, the load flow algorithm makes use of LV load power measurements for all the substations except those of MV users, where MV transducers are usually already installed. The uncertainties on the algorithm input quantities (load powers and slack b…
The analytic hierarchy process with stochastic judgements
2014
The analytic hierarchy process (AHP) is a widely-used method for multicriteria decision support based on the hierarchical decomposition of objectives, evaluation of preferences through pairwise comparisons, and a subsequent aggregation into global evaluations. The current paper integrates the AHP with stochastic multicriteria acceptability analysis (SMAA), an inverse-preference method, to allow the pairwise comparisons to be uncertain. A simulation experiment is used to assess how the consistency of judgements and the ability of the SMAA-AHP model to discern the best alternative deteriorates as uncertainty increases. Across a range of simulated problems results indicate that, according to c…
Multivariate nonparametric tests in a randomized complete block design
2003
AbstractIn this paper multivariate extensions of the Friedman and Page tests for the comparison of several treatments are introduced. Related unadjusted and adjusted treatment effect estimates for the multivariate response variable are also found and their properties discussed. The test statistics and estimates are analogous to the traditional univariate methods. In test constructions, the univariate ranks are replaced by multivariate spatial ranks (J. Nonparam. Statist. 5 (1995) 201). Asymptotic theory is developed to provide approximations for the limiting distributions of the test statistics and estimates. Limiting efficiencies of the tests and treatment effect estimates are found in the…