• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.89-96
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• 2015

In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

• Structural Engineering and Mechanics
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• v.77 no.3
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• pp.355-368
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• 2021

The time-varying mean (TVM) component of non-stationary wind speeds is commonly extracted utilizing empirical mode decomposition (EMD) in practice, whereas the accuracy of the extracted TVM is difficult to be quantified. To deal with this problem, this paper proposes an approach to identify and extract the optimal TVM from several TVM results obtained by the EMD. It is suggested that the optimal TVM of a 10-min time history of wind speeds should meet both the following conditions: (1) the probability density function (PDF) of fluctuating wind component agrees well with the modified Gaussian function (MGF). At this stage, a coefficient p is newly defined as an evaluation index to quantify the correlation between PDF and MGF. The smaller the p is, the better the derived TVM is; (2) the number of local maxima of obtained optimal TVM within a 10-min time interval is less than 6. The proposed approach is validated by a numerical example, and it is also adopted to extract the optimal TVM from the field measurement records of wind speeds collected during a sandstorm event.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.335-347
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• 2013

There are various types of real world signals. For example, an electrocardiogram(ECG) represents myocardium activities (contraction and relaxation) according to the beating of the heart. ECG can be expressed as the fluctuation of ampere ratings over time. A signal is a composite of various types of signals. An orchestra (which boasts a beautiful melody) consists of a variety of instruments with a unique frequency; subsequently, each sound is combined to form a perfect harmony. Various research on how to to decompose mixed stationary signals have been conducted. In the case of non-stationary signals, there is a limitation to use methodologies for stationary signals. Huang et al. (1998) proposed empirical mode decomposition(EMD) to deal with non-stationarity. EMD provides a data-driven approach to decompose a signal into intrinsic mode functions according to local oscillation through the identification of local extrema. However, due to the repeating process in the construction of envelopes, EMD algorithm is not efficient and not robust to a noise, and its computational complexity tends to increase as the size of a signal grows. In this research, we propose a new method to extract a local oscillation embedded in a signal by utilizing the second derivative.

• Progress in Superconductivity
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• v.5 no.1
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• pp.26-30
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• 2003

Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.557-586
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• 2009

Although energy demand management policy attracts attention internationally and domestically, the importance of local government in this policy is not so much as central government. But local government can do a role with regard to this policy because it is close to energy consumers not like central government. So local energy plan should be based on the understanding local energy consumption characteristics to activate local energy demand management policy. This paper tries to analyze energy characteristics of 16 local governments by decomposing energy consumption into population, production and intensity factors. The result of index decomposition analysis shows that energy intensity improvement has offset the increase of energy consumption caused by economic growth in the metropolitan cities, while it couldn't offset in the other provinces because of industrialization based on the manufacturing. In conclusion, this paper suggests that it will be necessary to switch to low energy society by carrying out concrete energy efficiency improvement projects in the metropolitan cities while it will be helpful to make a local development plan for low energy intensive industrialization in the other provinces.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.394-394
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• 2023

The world's sustainable growth is being severely hampered by the inefficient use of water resources. Despite the widely acknowledged importance of trade in global and regional water and food security, societal reliance on local production as well as international trade remains inadequately assessed. Therefore, using South Korea as a case study, this study fills in this research gap by applying the virtual water concept, the logarithmic mean divisia index (LMDI) method, and the Tapio decoupling model. The virtual water concept was used to estimate South Korea's net virtual water trade for major grain crops from 1992 to 2017. Then, the LMDI method was utilized to assess the driving factors causing changes in net virtual water trade. Lastly, the Tapio decoupling model was used to investigate the decoupling relationships between economic growth and the driving factors of net virtual water trade. Results showed that South Korea remains a net importer of virtual water flows with respect to grain crops, with an average import of 16,559.24 million m³ over the study period. In addition, the change in net virtual water trade could be attributed to water intensity effect, product structure effect, economic effect, and population effect. However, water intensity and economic effects were the major decisive factors for decrease and increase in net virtual water trade respectively, while the population and product structure effects had minor positive influences on the net virtual water trade. Furthermore, water intensity and economic growth showed a strong decoupling in most periods, while the decoupling state between product structure and economic growth was observed as expansive negative decoupling. Likewise, population size and economic growth showed a weak decoupling in most periods. The results reveal South Korea's status as it concerns the virtual water trade of grain crops, thus providing valuable insights into the sustainability of trade activities for the management of local water resources.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1643-1649
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• 2000

When markers attached to body segment are captured by camera, they generally have many noises due to intrinsic biomechanical characteristics. In this study, one technique to reduce these noises is suggested, which constructs a local coordinates of the markers using time-mean lengths of the measured markers and calculates a linear transformation matrix of the interesting body using least square error technique. This matrix is decomposed into two matrices of rotation and flexibility. Suggested method does well for 3 markers or more, and shows consistent results without regard to choice of reference axis.

• Wind and Structures
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• v.31 no.2
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• pp.165-183
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• 2020

The first step of performance-based design for transmission lines is the determination of wind fields as well as wind loads, which are largely depending on local wind climate and the surrounding terrain. Wind fields in a mountainous area are very different with that in a flat terrain. This paper firstly investigated both mean and fluctuating wind characteristics of a typical mountainous wind field by wind tunnel tests and computational fluid dynamics (CFD). The speedup effects of mean wind and specific turbulence properties, i.e., turbulence intensity, power spectral density (PSD) and coherence function, are highlighted. Then a hybrid simulation framework for generating three dimensional (3D) wind velocity field in the mountainous area was proposed by combining the CFD and proper orthogonal decomposition (POD) method given the properties of the target turbulence field. Finally, a practical 220 kV transmission line was employed to demonstrate the effectiveness of the proposed wind field generation framework and its role in the performance-based design. It was found that the terrain-induce turbulence effects dominate the performance-based structural design of transmission lines running through the mountainous area.

• Journal of The Korean Astronomical Society
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• v.47 no.5
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• pp.167-178
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• 2014

We search for misclassified type 1 AGNs among type 2 AGNs identified with emission line flux ratios, and investigate the properties of the sample. Using 4 113 local type 2 AGNs at 0.02 < z < 0.05 selected from Sloan Digital Sky Survey Data Release 7, we detected a broad component of the $H{\alpha}$ line with a Full-Width at Half-Maximum (FWHM) ranging from 1 700 to $19090km\;s^{-1}$ for 142 objects, based on the spectral decomposition and visual inspection. The fraction of the misclassified type 1 AGNs among type 2 AGN sample is ~3.5%, implying that a large number of missing type 1 AGN population may exist. The misclassified type 1 AGNs have relatively low luminosity with a mean broad $H{\alpha}$ luminosity, log $L_{H\alpha}=40.50{\pm}0.35\;erg\;s^{-1}$, while black hole mass of the sample is comparable to that of the local black hole population, with a mean black hole mass, log $M_{BH}=6.94{\pm}0.51\;M_{\odot}$. The mean Eddington ratio of the sample is log $L_{bol}/L_{Edd}=-2.00{\pm}0.40$, indicating that black hole activity is relatively weak, hence, AGN continuum is too weak to change the host galaxy color. We find that the O III lines show significant velocity offsets, presumably due to outflows in the narrow-line region, while the velocity offset of the narrow component of the $H{\alpha}$ line is not prominent, consistent with the ionized gas kinematics of general type 1 AGN population.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.61.1-61.1
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• 2016

Black hole (BH) mass is a fundamental quantity to understand BH growth, galaxy evolution, and connection between them. Thus, obtaining accurate and precise BH mass estimates over cosmic time is of paramount importance. The rest-frame UV CIV ${\lambda}1549$ broad emission line is commonly used for BH mass estimates in high-redshift AGNs (i.e., $2{\leq}z{\leq}5$) when single-epoch (SE) optical spectra are available. Achieving correct and accurate calibration for CIV-based SE BH mass estimators against the most reliable reverberation-mapping based BH mass estimates is thus practically important and still useful. By performing multi-component spectral decomposition analysis to obtained high-quality HST UV spectra for the updated sample of local reverberation-mapped AGNs including new HST STIS observations, CIV emission line widths and continuum luminosities are consistently measured. Using a Bayesian hierarchical model with MCMC sampling based on Hamiltonian Monte Carlo algorithm (Stan NUTS), we provide the most consistent and accurate calibration of CIV-based BH mass estimators for the three line width characterizations, i.e., full width at half maximum (FWHM), line dispersion (${\sigma}_{line}$), and mean absolute deviation (MAD), in the extended BH mass dynamic range of log $M_{BH}/M_{\odot}=6.5-9.1$.