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This paper presents a new unified Chebyshev surrogate model based hybrid uncertainty analysis method for robustly assessing geometrically nonlinear responses of engineering structures involving both random and interval uncertainties.
Recently, Wang et al. (2013) developed a new method for robustly estimating the parameters of the BS distribution, whereas their method is somewhat complicated for practitioners.
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For future applications, it will be critical to carefully determine the fidelity of reprogramming and to develop methods for robustly and efficiently generating human cell types of interest.
Hence, there is an emerging need to continue and develop new computational methods for robustly inferring the flux state, while capitalizing on these other available 'omics' measurements.
Moreover, we give a design method of robustly stabilizing controllers for uncertain Takagi Sugeno fuzzy time-delay systems.
A novel method is presented for robustly simulating coupled dynamics in fluid body interactions with vorticity-based flow solvers.
A new hybrid probabilistic and interval computational method is proposed for robustly assessing both time-dependent serviceability and strength limit of concrete-filled steel tubular arch structures involving both random and interval variables.
This paper describes a method of robustly modeling road boundaries on-line for autonomous navigation.
Based on our generalized robust stability conditions, we obtain delay-dependent sufficient conditions for the closed-loop system to be robustly stable, and give a design method of robustly stabilizing controllers.
We have demonstrated that this microfluidic-assisted ChIP-Seq method works robustly for as low as 1 000 mammalian cells.
The identification of specific colon tumour-associated molecular markers and the development of robustly accurate assay method for effective disease monitoring would significantly advance the early diagnosis of recurrence and subsequently the effective treatment (Nannini et al, 2009).
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