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We address the problem of detecting non-stationary effects in time series (inparticular fractal time series) by means of the Diffusion Entropy Method (DEM).This means that the experimental sequence under study, of size $N$, is exploredwith a window of size $L << N$. The DEM makes a wise use of the statisticalinformation available and, consequently, in spite of the modest size of thewindow used, does succeed in revealing local statistical properties, and itshows how they change upon moving the windows along the experimental sequence.The method is expected to work also to predict catastrophic events before theiroccurrence.Comment: FRACTAL 2002 (Spain

FACING NON-STATIONARY CONDITIONS WITH A NEW INDICATOR OF ENTROPY INCREASE: THE CASSANDRA ALGORITHM