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HMM (Hidden Markov Model) is a statistical-signal based model, and MFCC (Mel frequency Cepstrum Coefficient) is one kind of characteristic parameters, both of which are widely used in speech recognition. This paper studies MFCC-HMM bird songs recognition technology. Firstly, it collected bird songs through web crawler. Then, bird audios were preprocessed and MFCC features were extracted. Through differential methods calculation, improved MFCC feature parameters are obtained, which are fed into the HMM model to classify different kinds of bird songs. Experimental results show that the MFCC-HMM model achieve a recognition rate of 90.47% among the six kinds of birds.

A class of compound negative binomial-binomial risk model is investigated in this work. Based on this model, the adjusting coefficients are discussed by using the martingale analysis method. Then, the expression of the final bankruptcy probability and the Lundberg inequality are derived of insurance company under the condition that the initial reserve is u.

We put the queuing theory into hospital queuing system to analysis the process of outpatient department, build up queuing models by means of engineering application softwareMatlab. Therefore, hospitals will not blindly increase facilities causing a waste of resources, and patients will spend less time waiting. Hospitals and patients achieve 'win-win'.