Distance-based clustering methods categorize samples by optimizing a global criterion, finding ellipsoid clusters with roughly equal sizes. In contrast, density-based clustering techniques form clusters with arbitrary shapes and sizes by optimizing a local criterion. Most of these methods have several hyper-parameters, and their performance is highly dependent on the hyper-parameter setup. Recently, a Gaussian density Distance (GDD) approach was proposed to optimize local criteria in terms of distance and density properties of samples. GDD can find clusters with different shapes and sizes without any free parameters. However, it may fail to discover the appropriate clusters due to the interfering of clustered samples in estimating the density and distance properties of remaining unclustered samples. Here, we introduce Adaptive GDD (AGDD), which eliminates the inappropriate effect of clustered samples by adaptively updating the parameters during clustering. It is stable and can identify clusters with various shapes, sizes, and densities without adding extra parameters. The distance metrics calculating the dissimilarity between samples can affect the clustering performance. The effect of different distance measurements is also analyzed on the method. The experimental results conducted on several well-known datasets show the effectiveness of the proposed AGDD method compared to the other well-known clustering methods.

The paper presents a Fast Fourier Transform (FFT) based Power Spectral density (PSD) filter for denoising the PMU signal received from the smart power system network to identify the low frequency Oscillation modes (LFO). Small disturbances are introduced during normal operation of power system causes low frequency oscillations and may hinder the power system transfer capabilities of a system. The traditional signal processing method cannot extract the information from ambient signals effectively during noisy measurement. In this paper, the performance of the Prony analysis with reduced sampling rate is analysed for the PMU data with noiseless and noise environment. It is observed that, the performance of the Prony approach is not satisfactory under noisy measurement data.  In the present work FFT-PSD is used to denoise the noisy measurement signal and identify the nature of the decrement factor of the low frequency oscillatory modes. The accuracy of the estimated decrement factors of modes are verified with eigenvalues to validate the proposed method. The performance of proposed method is compared with signal processing method for IEEE New England power system and found effective and suitable during noisy PMU measurements.

This paper describes the power Spectral density matrix of manipulator tip displacement to stochastic excitation of the base. The dynamic equations for an articulated manipulator subjected to a vertically stochastic excitation are derived by Lagrangian method. Then the equations are linearized with respect to a small displacement in a fixed configuration.Sensitivity of the power Spectral density of tip motion to the manipulator configuration and structural damping are investigated. Finally, simulation results are presented for a 2R Planner robot manipulator under vertical base excitation

Objective: To examine the efficiency of both the Zeta and density gradient centrifugation (DGC) methods for the selection of normal chromatin sperm by TUNEL, sperm chromatin dispersion (SCD), acridine orange and chromomycin A3 (CMA3).Materials and Methods: The study was performed on 63 patients. Semen analysis was carried out according to WHO criteria. Semen samples were divided into three equal portions. One portion was used as the control, the second portion was used for the Zeta method and the third portion underwent DGC method. All portions were evaluated for sperm morphology (Diff Quick staining), protamine deficiency (CMA3) and DNA integrity (SCD, AO and TUNEL). Coefficients of correlation and student’s t test were carried out using SPSS 11.5.Results: The mean percentage of abnormal sperm, protamine deficiency and DNA fragmentation in the Zeta and DGC methods were significantly decreased as compared to the control group (p<0.005). In addition, the DGC method was higher in comparison to the Zeta method in the selection of sperm with normal morphology (p<0.005). The Zeta method was higher in comparison to the DGC method in the selection of sperm with intact DNA (p<0.005).Conclusion: Both Zeta and DGC methods were effective in the selection of sperm with better quality in terms of normal morphology, normal protamine content and DNA integrity. Therefore, we suggested that the combined Zeta and DGC method should be used for selection of normal sperm.

In recent years, a new approach called transmissibility based operational modal analysis has been propounded. The new approach is able to identify the modal parameters of structural systems based on the transmissibility functions, where, unlike conventional methods of operational modal analysis, there is no limiting assumption about the input excitations. In this paper, an effective form of transmissibility called power Spectral density transmissibility is used in order to identify the dynamic characteristics of a 5DOF system. The dynamic system that is modeled using MATLAB/Simulink is excited by the different earthquakes such as El Centro, Northridge and Loma Prieta, and white Gaussian noise is also added to its responses with different signal to noise ratios. The modal parameters (natural frequencies and mode shapes) of the numerical model are calculated and extracted based on the singular values and vectors obtained from singular value decomposition of the power Spectral density transmissibility matrix. This matrix, unlike the Fourier Spectral transmissibility matrix, can be created based on the transferring outputs obtained from just one loading condition; therefore, there is no need to use the outputs of multiple loading conditions, so that it is possible to identify the dynamic characteristics with only one dynamic test. In this research, the modal identification results are evaluated through comparison with the values obtained from exact solution of the system. The comparison shows that the modal parameters extracted from the system responses with different noise levels have a good agreement with the exact values.

Introduction: Purkinje Cell (PC) output displays a complex firing pattern consisting of high frequency sodium spikes and low frequency calcium spikes, and disruption in this firing behavior may contribute to cerebellar ataxia. Riluzole, neuroprotective agent, has been demonstrated to have neuroprotective effects in cerebellar ataxia. Here, the Spectral analysis of PCs firing in control, 3-acetylpyridine (3-AP), neurotoxin agent, treated alone and riluzole plus 3-AP treated were investigated to determine changes in the firing properties. Difference in the power spectra of tonic and burst firing was assessed. Furthermore, the role of calcium-activated potassium channels in the power spectra was evaluated.Methods: Analysis was performed using Matlab. Power Spectral density (PSD) of PCs output were obtained. Peak frequencies were extracted from the spectrum and statistical comparisons were done. In addition, a multi-compartment computational model of a Purkinje cell was used.This computational stimulation allowed us to study the changes in the power Spectral density of the PC output as a result of alteration in ion channels.Results: Spectral analysis showed that in the spectrum of tonic and burst firing pattern only high sodium frequency and low calcium frequency was seen, respectively. In addition, there was a significant difference between the frequency components of PCs firing obtained from normal, ataxia and riluzole treated rats. Results indicated that sodium firing frequency of normal, ataxic and treated PCs occurred in approximate frequency of 22.53±5.49, 6.46±0.23, and 31.34±4.07 Hz, respectively; and calcium frequency occurred in frequency of 4.22±2.02, 1.52±1.19, and 3.88±1.37 Hz, respectively. The simulation results demonstrated that blockade of calcium activated potassium channels in the PC model changed the PSD of the PC model firing activity.This change was similar to PSD changes in ataxia condition.Conclusion: These alterations in the spectrum of PC output may be a basis for developing possible new treatment strategies to improve cerebellar ataxia.