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Early warning and intelligent decisions have proved to be important tools to handle the unprecedented events (wildcards) that might emerge in the future. Relying on forecasting techniques only are not enough to shape the future, since they depend only on the historical shape and they generate one image of the future. The Futures Methodologies are capable of overcoming the constraints imposed on the...
In the algorithms of setting checkpoint intervals, it is significant to minimize the time and space overhead for enhancing computational efficiency. Under the existence of dynamic checkpoint intervals, a novel dynamic checkpoint intervals algorithm, named MDCI, based on hidden semi-Markov model has been proposed, which adopts random time series analysis method. The method not only decreases the computing...
In this talk the author will outline some of the recent work undertaken by the Oxford Brookes Vision Group, a common theme underlying much of the research is to cast vision problems in terms of combinatorial optimization which provides a rich a deep theory for understanding them, with many new and exciting results.
This correspondence describes an efficient Bayesian framework for localization of moving terminals (MTs) in wideband wireless networks. In a previous paper, the authors have presented a grid-based technique, based on a hidden Markov model, that used the power delay profiles of the received signals to track the MT position. This grid-based Bayesian method has proved its efficacy in reducing localization...
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