• Wind and Structures
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• v.16 no.6
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• pp.603-616
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• 2013

This study is aimed at formulating an empirical equation for the across-wind fluctuating moment and spectral density coefficient, which are needed to estimate the across-wind dynamic responses of tall buildings, as a function of the side ratios of buildings. In order to estimate an empirical formula, wind tunnel tests were conducted on aero-elastic models of the rectangular prisms with various aspect and side ratios in turbulent boundary layer flows. In this paper, criteria for the across-wind fluctuating moment and spectral density are briefly discussed and the results are analyzed mainly as a function of the side ratios of the buildings. Finally, empirical formulas for the across-wind fluctuating moment coefficient and spectral density coefficient according to variation of the aspect ratio are proposed.

• Progress in Superconductivity and Cryogenics
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• v.21 no.3
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• pp.6-12
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• 2019

Extended Drude model has been used to obtain information of correlations from measured optical spectra of strongly correlated electron systems. The optical self-energy can be defined by the extended Drude model formalism. One can extract the optical self-energy and the electron-boson spectral density function from measured reflectance spectra using a well-developed usual process, which is consistent with several steps including the extended Drude model and generalized Allen's formulas. Here we used a reverse process of the usual process to investigate the extended Drude analysis when an additional low-energy interband transition is included. We considered two typical electron-boson spectral density model functions for two different (normal and d-wave superconducting) material states. Our results show that the low-energy interband transition might give significant effects on the electron-boson spectral density function obtained using the usual process. However, we expect that the low-energy interband transition can be removed from measured spectra in a proper way if the transition is well-defined or well-known.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.209-222
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• 2006

Estimation of the spectral measure, covariance and spectral density functions of a strictly stationary r-vector valued time series is considered, under the assumption that some of the observations are missed. The modified periodograms are calculated using data window. The asymptotic normality is studied.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.11a
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• pp.169-172
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• 2001

There are many people who suffer from simulation sickness when immersing in virtual reality. In this study, we analyzed two photoplethysmogram(PPG) parameters - a second derivative parameter and power spectral density ratios - in order to relate PPG parameters with simulation sickness. 36 young, healthy subjects were participated in the experiment, and each subject was equipped with a PPG electrode during his or her immersion. Simulation sickness section was defined as a 7 - second section which starts from the point where a subject reported simulation sickness, and normal section as a same-length section where no physical stimuli was presented to him or her. We compared the PPG parameters of the simulation sickness sections with the normal sections, - d/a ratio is believed to have lower value during vasodilation and higher value during vasoconstriction, however, we could not find much difference in the parameter between normal and simulation sickness sections. We also compared 1 to 10Hz power spectral density ratios in normal sections with in simulation sickness section, and found that 6 density ratios among them have different value. Therefore, the density ratios might be utilized as parameters to detect simulation sickness of subjects.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.33.5-33
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• 2001

We consider here the problem of spectral estimation of multidimensional wide sense stationary (WSS) random process. A method, employing a special difference equation of correlation function, is proposed to solve the problem of multidimensional spectral estimation. In this approach, the special difference equation of correlation function is derived by modal decomposition method. Maximum likelihood estimator and Kalman filter are used to estimate the model parameters of the difference equation and the decomposed spectral residues. An algorithm is presented to estimate the multidimensional spectral density. According to the result of the simulation, these methods are feasible to estimate the spectral density of WSS process, which is realized by finite dimensional multivariable lineal system driven by white noise.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.397-404
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• 1999

For two-dimensional causal spatial autoregressive processes, we propose and illustrate a method for determining asymptotic simultaneous confidence regions using Yule-Walker, unbiased Yule-Walker and least squres estimators. The spectral density for first-order spatial autoregressive model are looked at in more detail. Finite sample properties based on simulation study we also presented.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.231-242
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• 1995

In this paper we consider kernel type estimator of the spectral density at a point in the analysis of stationary time series data. The kernel entails choice of smoothing parameter called bandwidth. A data-based bandwidth choice is proposed, and it is obtained by solving an equation similar to Sheather(1986) which relates to the probability density estimation. A Monte Carlo study is done. It reveals that the spectral density estimates using the data-based bandwidths show comparatively good performance.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.209-226
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• 2002

When predicting unsteady flow and pressure fields around a structure in a turbulent boundary layer by Large Eddy Simulation (LES), velocity fluctuations of turbulence (inflow turbulence), which reproduce statistical characteristics of the turbulent boundary layer, must be given at the inflow boundary. However, research has just started on development of a method for generating inflow turbulence that satisfies the prescribed turbulence statistics, and many issues still remain to be resolved. In our previous study, we proposed a method for generating inflow turbulence and confirmed its applicability by LES of an isotropic turbulence. In this study, the generation method was applied to a turbulent boundary layer developed over a flat plate, and the reproducibility of turbulence statistics predicted by LES computation was examined. Statistical characteristics of a turbulent boundary layer developed over a flat plate were investigated by a wind tunnel test for modeling the cross-spectral density matrix for use as targets of inflow turbulence generation for LES computation. Furthermore, we investigated how the degree of correspondence of the cross-spectral density matrix of the generated inflow turbulence with the target cross-spectral density matrix estimated by the wind tunnel test influenced the LES results for the turbulent boundary layer. The results of this study confirmed that the reproduction of cross-spectra of the normal components of the inflow turbulence generation is very important in reproducing power spectra, spatial correlation and turbulence statistics of wind velocity in LES.

• 한국전산유체공학회:학술대회논문집
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• 2006.10a
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• pp.181-184
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• 2006

High-speed flight vehicle have various cavities. The supersonic cavity flow is complicated due to vortices, flow separation and reattachment, shock and expansion waves. The general cavity flow phenomena include the formation and dissipation of vortices, which induce oscillation and noise. The oscillation and noise greatly affect flow control, chemical reaction, and heat transfer processes. The supersonic cavity' flow with high Reynolds number is characterized by the pressure oscillation due to turbulent shear layer, cavity geometry, and resonance phenomenon based on external flow conditions, The resonance phenomena can damage the structures around the cavity and negatively affect aerodynamic performance and stability. In the present study, we performed numerical analysis of cavities by applying the unsteady, compressible three dimensional Reynolds-Averaged Navier-Stokes(RANS) equations with the ${\kappa}-{\omega}$ turbulence model. The cavity model used for numerical calculation had a depth(D) of 15mm cavity aspect ratio(L/D) of 3, width to spanwise ratio(W/D) of 1.0 to 5.0. Based on the PSD(Power Spectral Density) and CSD(Cross Spectral Density) analysis of the pressure variation, the dominant frequency was analyized and compared with the results of Rossiter's Eq.