• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.365-376
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• 2003

In this paper we reviewed a variety of non-Gaussian time series models, and studied the model selection criteria such as AIC and BIC to select proper models. We also considered the likelihood ratio test and applied it to analysis of Polio data set.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1396-1403
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• 2019

The radar wind profiler data contaminates with various non-atmospheric components that produce errors in moments and wind velocity estimations. This study implemented an adaptive Gaussian model to detect and remove the clutter from the radar return. This model includes DC filtering, ground clutter recognition, Gaussian fitting, and cost function to mitigate the clutter component. The adaptive model tested for the various types of clutter components and found that it is effective in clutter removal process. It is also applied for the both time series and spectrum datasets. The moments estimated using this method are compared with those derived using conventional DC-filtering clutter removal method. The comparisons show that the proposed method effectively removes the clutter and produce reliable moments.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.43.2-43.2
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• 2014

We present the three-dimensional genus topology of large-scale structure using the CMASS sample of the Final SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) data. To estimate the uncertainties in the measured genus, we very carefully construct mock CMASS surveys along the past light cone from the Horizon Run 3. We find that the shape of the observed genus curve agrees very well with the prediction of perturbation theory and with the mean topology of the mock surveys. However, comparison with simulations show that the observed genus curve slightly deviates from the theoretical Gaussian expectation. From the deviation, we further quantify the primordial non-Gaussian contribution.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.127-134
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• 2006

Based on a weakly non-Gaussian theory the occurrence probability of freak waves is formulated in terms of the number of waves in a time series and the surface elevation kurtosis. Finite kurtosis gives rise to a significant enhancement of freak wave generation in comparison with the linear narrow banded wave theory. For fixed number of waves, the estimated amplification ratio of freak wave occurrence due to the deviation from the Gaussian theory is 50% - 300%. The results of the theory are compared with laboratory and field data.

• Wind and Structures
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• v.26 no.1
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• pp.11-24
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• 2018

Full-scale measurements of wind action on the open roof structure of the WuXi grand theater, which is composed of eight large-span free-form leaf-shaped space trusses with the largest span of 76.79 m, were conducted during the passage of Typhoons HaiKui and SuLi. The wind pressure field data were continuously and simultaneously monitored using a wind pressure monitoring system installed on the roof structure during the typhoons. A detailed analysis of the field data was performed to investigate the characteristics of the fluctuating wind pressure on the open roof, such as the wind pressure spectrum, spatial correlation coefficients, peak wind pressures and non-Gaussian wind pressure characteristics, under typhoon conditions. Three classical methods were used to calculate the peak factors of the wind pressure on the open roof, and the suggested design method and peak factors were given. The non-Gaussianity of the wind pressure was discussed in terms of the third and fourth statistical moments of the measured wind pressure, and the corresponding indication of the non-Gaussianity on the open roof was proposed. The result shows that there were large pulses in the time-histories of the measured wind pressure on Roof A2 in the field. The spatial correlation of the wind pressures on roof A2 between the upper surface and lower surface is very weak. When the skewness is larger than 0.3 and the kurtosis is larger than 3.7, the wind pressure time series on roof A2 can be taken as a non-Gaussian distribution, and the other series can be taken as a Gaussian distribution.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.42.2-42.2
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• 2010

The possibility of detection of deviation from Gaussian distribution of primordial perturbations in the Cosmic Microwave Background (CMB) Radiation is very important because it can shed light on how the perturbations were created in the very early universe. We study the effect of the primordal non-Gaussianity on topological observables called Minkowski Functionals, which are functions of the temperature fluctuation field, and show that they carry distinct signatures of different types of non-Gaussianities. Then, we constrain the non-Gaussianity parameters by comparing the theoretical predictions of the Minkowski Functionals with measurements from observational data from WMAP.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• Journal of the Optical Society of Korea
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• v.19 no.2
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• pp.144-148
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• 2015

An alternative description for the Gaussian image plane (GIP) of an optical system for a given object is presented, which applies to both aberration-free and non-aberration-free systems. We extend the definition of transverse magnification (TM) to the image plane (IP) displaced from the GIP and find that the TM depends linearly on the locations of both an aperture stop placed in front of the system and the IP. Hence, we redefine the GIP as the location at which the slope of the TM variance changes sign. The definition is deterministic and self-consistent and, therefore, no other parameters or measurements are needed. The derivation of this definition using a set of paraxial ray tracings and supporting experimental data for a thick bi-convex lens system is presented.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.2
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• pp.107-117
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• 2010

An analytical subthreshold swing model is presented for symmetric double-gate (DG) MOSFETs with Gaussian doping profile in vertical direction. The model is based on the effective conduction path effect (ECPE) concept of uniformly doped symmetric DG MOSFETs. The effect of channel doping on the subthreshold swing characteristics for non-uniformly doped device has been investigated. The model also includes the effect of various device parameters on the subthreshold swing characteristics of DG MOSFETs. The proposed model has been validated by comparing the analytical results with numerical simulation data obtained by using the commercially available $ATLAS^{TM}$ device simulator. The model is believed to provide a better physical insight and understanding of DG MOSFET devices operating in the subthreshold regime.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.127-134
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• 2005

A suitable representation for the conceptual simplicity of the data in statistics and signal processing is essential for a subsequent analysis such as prediction, pattern recognition, and spatial analysis. Independent component analysis (ICA) is a statistical method for transforming an observed high-dimensional multivariate data into statistically independent components. ICA has been applied increasingly in wide fields of spectrum application since ICA is able to extract unknown components of a mixture from spectra. We focus on application of ICA for separating independent sources and predicting each composition using extracted components. The theory of ICA is introduced and an application to a metal surface spectra data will be described, where subsequent analysis using non-negative least square method is performed to predict composition ratio of each sample. Furthermore, some simulation experiments are performed to demonstrate the performance of the proposed approach.