• Cross-Cultural Studies
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• v.26
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• pp.321-351
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• 2012

This paper attempts to clarify the similarity found in Seo Jungjoo's two books of poems, Seo Jungjoo Shiseon and Shillacho, and thereby to establish the continuity between Seo's early poetry and his mid-period poetry. This attempt arises from the realization that unfamiliar poetic material, background, and narration are merely surface features, and that in fact his early concerns nevertheless persist in terms of his poetic imagination and his Weltanschauung. Furthermore, this continuity seems to originate from shamanistic spiritual chaos that is consubstantially interrelated with the spirit of his deceased lover. After chaos and confusion subsided, the poet's endeavor to discover the lineal origin of his personal shamanism shows itself in Seo Jungjoo Shiseon, and we witness the embodiment of such endeavor in Shillacho. His interest in the skies as it is expressed in my poem, and Shilla as it is intimated by Gwanghwamun are sublimated in saso yeonjag and the words of Queen Seondeog into shamanic wisdom that served as the norm for both spiritual life and physical life in ancient times, and the wisdom is carried on further into the present in Seo's own times. Moreover, the star and the bell sound that were presented as signs of desirable Weltanschauung in Sangrigwawon are transformed into the symbols of shamanic wisdom, and into the inner magic formula that contributes to achieving the wisdom. This analysis offers as its result the evidence embedded in his poems that shows, first, that the two books correspond to merely two separate stages of his poetic concern, and second, that his early poetic concern persists, though transformed through a peculiar manner, into his mid-period poems.

• Journal of Wetlands Research
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• v.21 no.3
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• pp.236-243
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• 2019

Hydrologic time series has been analyzed and forecasted by using classical linear models. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. Daily streamflow series at St. Johns river near Cocoa, Florida, USA showed an interesting result of a low dimensional, nonlinear dynamical system but daily inflow at Soyang reservoir, South Korea showed stochastic property. Based on the chaotic dynamical characteristic, DVS (deterministic versus stochastic) algorithm is used for short-term forecasting, as well as for exploring the properties of the system. In addition to the use of DVS algorithm, a neural network scheme for the forecasting of the daily streamflow series can be used and the two techniques are compared in this study. As a result, the daily streamflow which has chaotic property showed much more accurate result in short term forecasting than stochastic data.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.1
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• pp.125-134
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• 2014

6 sigma is a management innovation strategy which improves most of all managerial processes including transactional and project based operations such as marketing, purchasing, accounting, and construction. Even though 6 sigma is trying to solve problems from the customer's viewpoint in the scientific manner, project leader feels some difficulties in implementation because of several reasons. Especially the difficulties are prevalent in construction site. This paper investigates the cause of the difficulties through questionnaires, analyzes the investigation results, and verifies the critical success factors of 6 sigma implementation. Factor analysis has been usually employed in reducing quantity of data and summarizing information chaos. In this study, several variables from questionnaires are grouped into just only four factors by the process of factor analysis. The critical success factors are extracted as project management system, implementation mechanism, site condition, and project ownership. Some ideas for each individual success factor are suggested, which are expected to be useful in successful implementation of 6 Sigma in construction site.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1691-1696
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• 2013

In this paper, an analysis of behavior is performed in the circular hybrid energy harvesting device. This analysis of behavior is to confirm with or without an existence of nonlinear system because its system is required to produce the more energy. To do this, first of all the phase portrait is reconstructed through Taken's embedding method, and then Poincare map is organized by using phase portrait and finally Lyapunov exponent is analyzed.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.2
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• pp.116-127
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• 2007

Background and Purpose: Acording to chaos theory, irregular signals of electroencephalogram can interpretated by nonlinear method. Chaotic nonlinear dynamics in EEG can be studied by calculating the correlation dimension. The aim of this study is to analyze EEG by correlation dimension and do Correlation Analysis of correlation dimension and cold-heat score Method: EEG raw data were measured during 15 minutes and choosed 40 seconds. We calculated correlation dimension and used surrogate data method for checking nonlinear data. After then do correlation analysis Result and Conclusion: Correlation dimension of channel 7 and channel 8 are showed significant correlation with cold score.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.2
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• pp.68-83
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• 2007

Background and Purpose: According to chaos theory, irregular signals of electroencephalogram can interpretated by nonlinear method. Chaotic nonlinear dynamics in EEG can be studied by calculating the correlation dimension. The aim of this study is to analyze EEG by correlation dimension and do Correlation Analysis of correlation dimension and K-POMS factors score. Method: EEG raw data were measured during 15 minutes and choosed 40 seconds. We calculated correlation dimension and used surrogate data method for checking nonlinear data. After then do correlation analysis. Result and Conclusion: Correlation dimension of channel 6, channel 7 and channel 8 are showed significant correlation with vigor factor.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.3
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• pp.169-176
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• 2000

The partial discharge(PD) signal, may seems to be stochastic and merely random, was investigated using the method to discern between chaos and random signal, e.g. correlation integral, Lyapunov characteristic exponents and etc. For the purpose of obtaining experimental data, partial discharge detecting system via computer aided acoustic sensor, detect PD signal from the insulating system, was used. While this method is very different from typical statistical analysis from the point of view of a nonlinear analysis, it can provide better interpretable criterion according to the time evolution with a degradation process in the same type insulating system.

• Structural Engineering and Mechanics
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• v.75 no.3
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• pp.311-325
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• 2020

In applying the spectral stochastic finite element methods to the frequency response analysis, the conventional methods are known to give unstable and inaccurate results near the natural frequencies. To address this issue, a new sensitivity based stabilized formulation for stochastic frequency response analysis is proposed in this paper. The main difference over the conventional spectral methods is that the polynomials of random variables are applied to both numerator and denominator in approximating the harmonic response solution. In order to reflect the resonance behavior of the structure, the denominator polynomials is constructed by utilizing the natural frequency sensitivity and the random mode superposition. The numerator is approximated by applying a polynomial chaos expansion, and its coefficients are obtained through the Galerkin or the spectral projection method. Through various numerical studies, it is seen that the proposed method improves accuracy, especially in the vicinities of structural natural frequencies compared to conventional spectral methods.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.975-979
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• 2001

In connection with the monitoring of the insulation degradation of large power apparatus in order to predict their expected service failures, a statistical treatment, such as phase resolved partial discharge analysis (PRPDA), has been established for the on-line monitoring system during the past decades. However, this method has shown some inconveniences to identify the nature of the PD source in power apparatus. In this regard, a novel approach based on the chaotic analysis (CAPD) is proposed describing the fundamental ideas, outcomes and different viewpoints from the conventional PRPDA. As a model for the possible defects causing sudden failures in service, three types of specimen are prepared. And partial discharge signals, originated from those samples, are measured and analyzed by means of CAPD. Throughout this work, it seems that the correlation between the consecutive PD pulses, depending on the nature of PD, could be clarified by CAPD. Thereffre, it could be considered that the nature of PD source can be identified more distinctively when the CAPD is combined with PRPDA.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.