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Spectral analysis techniques have been used in various biomedical applications including speech detection, diagnosis of various types of diseases, gesture recognition, and many others. Existing spectral methods work well in detecting specific sounds or voices. However, it is difficult and/or expensive to classify various types of sounds with different frequencies, such as music, noise, and the human voice. This is because such sounds may not be easily separable in frequency by human perception, and there are many human sounds with similar frequencies. Therefore, it is desirable to develop a method to classify human sounds into various classes in order to analyze various types of human sounds. In this paper, we aim to classify various types of human sounds by a statistical approach. The classification method used is the quadratic discriminant analysis (QDA). The goal of this study is to classify different types of sound sources using the QDA. The experiments were conducted with real-time machine noise analysis. In addition, the results show that the classification function using the QDA sound source is effective for the analysis of different types of human sounds. Classification based on spectra can be used to classify various types of sounds to their sources.
A wide range of sophisticated numerical tools are often required to address the problems involved in molecular dynamics simulations. In the current paper, we demonstrate the usability of the software package CheMMPI 2 for the determination of the friction ân coefficient from the trajectories in molecular dynamics simulations. The implemented methods were validated by generating reference data sets using the standard Langevin equation of motion. The methods were then applied to the simulation trajectories obtained from Gromacs 5.0.4 simulations of the GTP and GDP bound complexes of the switch I region of the ternary BSA - GTP - Arf1 system. The performance was evaluated by a close examination of the ân values obtained from nonlinear fitting to the Langevin equation of motion. The grand canonical Monte Carlo (GCMC) as well as the isothermal-isobaric ensemble (NPT) simulations were performed to validate the accuracy of the codes in comparison to the reference data sets generated using the standard Langevin equation of motion. An estimate of the uncertainty of the ân value from the trajectory is then included. d2c66b5586