Modifications to real-time RDAHMM

Present real-time RDAHMM service just runs RDAHMM in training mode periodically on stations' real-time input, which is actually not a right way to do it.
We'll do the following modifications, which is not totally right either, but just our first step towards the right way:
For each station, collect its input data for a whole day, and build a RDAHMM model for it by running RDAHMM in training mode on the one-day's input data;
Use this model to periodically do evaluations for the station in future time; this period could vary from 10 minutes to 1 hour.

Right now we just use the model created based on one-day's data to do evaluations for all the rest time. This is obviously not completely right, and there might be the need for rebuilding the model from time to time. We'll leave an argument for specifying the period for rebuilding models to make the new implementation as general as possible, and discuss the proper period at a later time.