In this context, this paper proposes a methodology whose aim is to support the timetabling planning process by providing an accurate estimation of train dwell times at stations, so as to increase timetabling robustness and hence rail service reliability.
Prognostics and Health Management is an engineering discipline that is gaining an increasing interest as it aims at improving the safety and the reliability of systems while reducing maintenance costs by providing an accurate estimation about the remaining useful life RUL and current health status of the equipment.
In contrast to conventional pilot-assisted channel estimation, the proposed algorithms make a more efficient use of cooperative diversity by providing a joint estimation of all the channel matrices thanks to the use of a tensor modeling of the end-to-end system.
In contrast to conventional pilot-assisted LS channel estimation, where the channel matrices are estimated separately in consecutive stages, our proposed algorithms make a more efficient use of cooperative diversity by providing a joint estimation of all the channel matrices.
In order to prevent the rejection of good Solution Concepts or to screen out unfeasible ones, we proposed an approach to assist the designers in increasing confidence in the Solution Concept by providing a rapid estimation and/or exploration of the feasibility of a tested Solution Concept.
Furthermore, the calculation of confidence intervals for impact numbers can add to the interpretation of study results by providing a measure of estimation uncertainty.
This procedure is intended to complement the likelihood approach developed by Handcock and Gile (2010) by providing a practical means of estimation when the size of the complete network is unknown and/or the complete network is very large.
The toolbox meets the increasing need of the fMRI community to more comprehensively understand the effects of complex processing strategies by providing a ground truth that estimation methods may be compared against.
Data from transgenic rodent systems may play an important role in the extension of the parallelogram approach to genetic risk estimation by providing a link between cancer and genetic risk estimates.
It shows that the best-fit GDP function, by extrapolation, could provide an estimation of specific BEs in the highly noisy region of the distribution (the left part of the distribution.
