The spectrum entropy estimation method for ultrasonic backscattering signal in cancellous bones

In the application of cancellous bone ultrasound diagnosis based on backscattering method, it is of great importance to estimate fast and accurately whether the valid backscattering signal exists in the received signal. We propose a fast estimation method based on spectrum entropy method. With 984 records of adult calcaneus clinical data, we estimate the validity of the backscatter signal using this method. The results of the proposed method and the results of experience-base judgement were compared and analyzed. And two key parameters, the signal range length and the segment number of the spectrum entropy, were analyzed. The results show when the signal range length is 13 I^s and the segment number is 15 20, this method can get the best result （accuracy〉95%, sensitivity〉99%, specificity〉87%）, while taking little calculation time （1.5 ms）. Therefore, this spectrum entropy method can satisfy the accuracy and real-time requirements in the ultrasonic estimation for cancellous bone.

Denoising Nonlinear Time Series Using Singular Spectrum Analysis and Fuzzy Entropy

We present a hybrid singular spectrum analysis （SSA） and fuzzy entropy method to filter noisy nonlinear time series. With this approach, SSA decomposes the noisy time series into its constituent components including both the deterministic behavior and noise, while fuzzy entropy automatically differentiates the optimal dominant components from the noise based on the complexity of each component. We demonstrate the effectiveness of the hybrid approach in reconstructing the Lorenz and Mackey--Class attractors, as well as improving the multi-step prediction quality of these two series in noisy environments.

Maximum entropy spectral characteristics of seismic activity for great earthquakes in China

The maximum entropy spectral characteristics of seismicity in the seismic enhanced region of 11 great earthquakes is analysed in this paper to seek the difference of seismic period spectral structure between the normal and the abnormal stage of seismic activity in this paper. The results show that, during decades or even one hundred years before great earthquakes, only short periods with 6.5～24.3 years appear, and long ones disappear. Otherwise, long periods with 18.5～38.5 years exist chiefly within the normal stages. Decades years after great earthquakes, the period spectra of seismicity are generally about several or ten years. Then the characteristics of great earthquakes is explained physically by applying the strong body seismogenic model, so a method of studying and predicting great earthquakes is offered.

Area and entropy spectra of black holes via an adiabatic invariant

By considering and using an adiabatic invariant for black holes, the area and entropy spectra of static spherically- symmetric black holes are investigated. Without using quasi-normal modes of black holes, equally-spaced area and entropy spectra are derived by only utilizing the adiabatic invariant. The spectra for non-charged and charged black holes are calculated, respectively. All these results are consistent with the original Bekenstein spectra.

Theoretical Relationship between SSA and MESA with Both Application

It is theoretically demonstrated that singular spectrum analysis (SSA) is an equivalent form of Maximum Entropy Spectrum Analysis (MESA) which is essential1y a nonlinear estimation of the classical power spectrum. Both methods have respectively some different features in application as a result of the difference of description of manners. The numerical experiments show that SSA possesses some special advantage in climatic diagnosis and prediction, e.g., to steadily and accurately identify periods and investigate on domain of time in combination with frequency,which cannot be replaced by MESA. Thus SSA has extensive application in the near future.

Multi-scale morphology analysis of acoustic emission signal and quantitative diagnosis for bearing fault

Monitoring of potential bearing faults in operation is of critical importance to safe operation of high speed trains.One of the major challenges is how to differentiate relevant signals to operational conditions of bearings from noises emitted from the surrounding environment.In this work,we report a procedure for analyzing acoustic emission signals collected from rolling bearings for diagnosis of bearing health conditions by examining their morphological pattern spectrum（MPS） through a multi-scale morphology analysis procedure.The results show that acoustic emission signals resulted from a given type of bearing faults share rather similar MPS curves.Further examinations in terms of sample entropy and Lempel-Ziv complexity of MPS curves suggest that these two parameters can be utilized to determine damage modes.

黑洞经由的区域和熵系列一断热不变

By considering and using an adiabatic invariant for black holes, the area and entropy spectra of static spherically-symmetric black holes are investigated. Without using quasi-normal modes of black holes, equally-spaced area and entropy spectra are derived by only utilizing the adiabatic invariant. The spectra for non-charged and charged black holes are calculated, respectively. All these results are consistent with the original Bekenstein spectra.

Electron densitymap evaluation functions for determining the quality of protein crystal structures

Background Finding methods to judge the quality of X-ray crystallographic information is an active research topic.The quality of electron density maps reconstructed by Fourier transform is always limited by the finite resolution,the amplitude/phase error and the completeness of diffraction data.At present,the R value and effective resolution are common ways of evaluating the quality of electron density maps.Unfortunately,the current evaluation methods are only dependent on diffraction amplitude,without any phase information.Methods Advanced evaluation functions in real space are designed to estimate the electron density map quality.The electron density map definition evaluation function relies on the atomicity of the electron density distribution.We use the power spectrum electron density entropy in protein crystallography for the first time.These two functions include both structure factor amplitudes and phases via the Fourier transform of electron density map.Results We carry out tests on synthetic data sets of known structures,varying the resolution and error,and draw the quality curves of electron density maps with theoretical,noisy and experimental diffraction data by two evaluation functions at different resolutions.The curves reveal the optimum structure and resolution of proteins clearly.Conclusions The work presented here offers new methods to evaluate the qualities of the electron density maps of proteins with slight differences,and brand new indicators to select the optimum diffraction resolution of protein structures.