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Susana Gomez, Benjamin Ivorra and Angel M. Ramos

problems by considering, as a study case, wind and sea currents data from the Prestige hazard. These problems are designed to study the efficiency of the optimal trajectories considering the objective function formulations (3) or (4) and several values for the power of the pump. Our main objective here is to show the advantage of using optimal trajectories for the cleaning ship. We note that this methodology can be applied for the design of any other cleaning method based on trajectory planning. 3.2.1 Cleaning Scenarios for Different Pumping Power Ships We

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Linli Zhu, Yu Pan and Jiangtao Wang

Informatics, 6, No 1, 34-46. 10.1166/jmihi.2016.1579 Gopi V. P. Palanisamy P. Wahid K. A. Babyn P. Cooper D. 2016 Iterative Computed Tomography Reconstruction from Sparse-View Data, Journal of Medical Imaging and Health Informatics 6 1 34 46 10.1166/jmihi.2016.1579 [26] J. Dowell and P. Pinson, (2016), Very-Short-Term Probabilistic Wind Power Forecasts by Sparse Vector Autoregression , IEEE Transactions on Smart Grid, 7, No 2, 763-770. 10.1109/TSG.2015.2424078 Dowell J. Pinson P. 2016 Very-Short-Term Probabilistic Wind Power Forecasts by Sparse Vector Autoregression

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Rosa Donat and Sergio López-Ureña

1 Introduction Uncertainty Quantification (UQ) is the science that studies the quantification and the reduction of uncertainties in real applications with an intensive computational component. An example would be the computation of the fuel consumption of a car. Suppose we know how to compute the consumption as a function of some parameters (car and wind velocity, wheel condition, car weight, etc.), but we do not know the exact value of these parameters because they are random variables. Hence, the fuel consumption is also a random variable. UQ studies