Results 11 to 20 of about 361,200 (307)

Some new rearrangements in sensitivity integrals and concerning inequalities with their application in control

Results in Control and Optimization, 2021
In this paper, we extend the sensitivity integrals for linear feedback systems via a non-analytic sensitivity function in Poisson–Jensen’s terminology. First, we sketch a generalized sensitivity integral accounting for the NMP zeros and the RHP poles of ...
Shaival H. Nagarsheth, Shambhu N. Sharma
doaj   +1 more source

Investigations of Building-Related LCC Sensitivity of a Cost-Effective Renovation Package by One-at-a-Time and Monte Carlo Parameter Variation Methods

Applied Sciences, 2022
Nearly Zero Energy Building (NZEB) is becoming a standard for new and renovated buildings throughout the European Union (EU). Through the ongoing implementation of directives related to energy efficiency and NZEB-compliant buildings, the EU commission ...
Yovko Ivanov Antonov, Kim Trangbæk Jønsson, Per Heiselberg, Michal Zbigniew Pomianowski   +3 more
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Sensitivity and Robustness Issues of Operating Envelopes in Unbalanced Distribution Networks

IEEE Access, 2022
The fast-growing uptake of distributed energy resources (DER), such as home photovoltaic (PV) and battery systems and electric vehicles, has introduced new challenges in the operation of low-voltage distribution networks (LVDNs).
Bin Liu, Julio H. Braslavsky
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Robustness versus sensitivity in non-Hermitian topological lattices probed by pseudospectra

Physical Review Research, 2022
Non-Hermitian topological systems simultaneously possess two antagonistic features: ultrasensitivity due to exceptional points and robustness of topological zero-energy modes, and it is unclear which one prevails under different perturbations.
Ioannis Komis, Dimitrios Kaltsas, Shiqi Xia, Hrvoje Buljan, Zhigang Chen, Konstantinos G. Makris   +5 more
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Supervised versus Semi-Supervised Urban Functional Area Prediction: Uncertainty, Robustness and Sensitivity

Remote Sensing, 2023
To characterize a community-scale urban functional area using geo-tagged data and available land-use information, several supervised and semi-supervised models are presented and evaluated in Hong Kong for comparing their uncertainty, robustness and ...
Rui Deng, Yanning Guan, Danlu Cai, Tao Yang, Klaus Fraedrich, Chunyan Zhang, Jiakui Tang, Zhouwei Liao, Zhishou Wei, Shan Guo   +9 more
doaj   +1 more source

Inspecting the Solution Space of Genome-Scale Metabolic Models

Metabolites, 2022
Genome-scale metabolic models are frequently used in computational biology. They offer an integrative view on the metabolic network of an organism without the need to know kinetic information in detail.
Seyed Babak Loghmani, Nadine Veith, Sven Sahle, Frank T. Bergmann, Brett G. Olivier, Ursula Kummer   +5 more
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Quantum Risk-Sensitive Estimation and Robustness [PDF]

IEEE Transactions on Automatic Control, 2009
This paper studies a quantum risk-sensitive estimation problem and investigates robustness properties of the filter. This is a direct extension to the quantum case of analogous classical results. All investigations are based on a discrete approximation model of the quantum system under consideration.
Naoki Yamamoto, Luc Bouten
openaire   +3 more sources

Robustness from flexibility in the fungal circadian clock [PDF]

, 2010
Background Robustness is a central property of living systems, enabling function to be maintained against environmental perturbations. A key challenge is to identify the structures in biological circuits that confer system-level properties such as ...
Andrew J Millar, Paul E Brown, David A Rand, Akman, Ozgur E., Rand, D. A. (David A.), Akman, Ozgur E, Brown, Paul E, Rand, David A., Ozgur E Akman, Millar, Andrew J; id_orcid, Brown, Paul E., Millar, A. J. (Andrew J.), Millar, Andrew J., Rand, David A   +13 more
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Deep-Learning-Based Dose Predictor for Glioblastoma–Assessing the Sensitivity and Robustness for Dose Awareness in Contouring [PDF]

, 2023
External beam radiation therapy requires a sophisticated and laborious planning procedure. To improve the efficiency and quality of this procedure, machine-learning models that predict these dose distributions were introduced.
Robert Poel, Daniel M. Aebersold, Poel, Robert, Amith J. Kamath, Andratschke, Nicolaus, Ekin Ermiş, Nicolaus Andratschke, Aebersold, Daniel M., Jonas Willmann, Mauricio Reyes, Willmann, Jonas, Ermis, Ekin, Reyes, Mauricio, Manser, Peter, Peter Manser, Kamath, Amith J.   +15 more
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Sensitivity analysis for causal decomposition analysis: Assessing robustness toward omitted variable bias

Journal of Causal Inference, 2023
A key objective of decomposition analysis is to identify a factor (the “mediator”) contributing to disparities in an outcome between social groups. In decomposition analysis, a scholarly interest often centers on estimating how much the disparity (e.g ...
Park Soojin, Kang Suyeon, Lee Chioun, Ma Shujie   +3 more
doaj   +1 more source