• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.545-549
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• 1999

Previous studies on high impedance faults assumed that the erratic behavior of fault current would be random. In this paper we prove that the nature of the high impedance faults is indeed a deterministic chaos not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents in order to evaluate the orbital instability peculiar to deterministic chaos dynamically and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. In addition qualitative analysis such a s phase planes Poincare maps obtained from fault currents indicate that the irregular behavior is described by strange attractor.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.149-154
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• 2000

분류기법을 통해 얻어진 원격탐사 자료는 사용되기 이전에 그 정확성에 관한 신뢰도 검증을 해야 한다. 분류 정확도를 평가하기 위해서는 오분류행렬(confusion matrix)을 사용하여 정확도 평가를 하게 되는데, 이때 오분류행렬을 구성하기 위해서는 기준자료(reference data)에 대한 표본추출이 이루어져야 한다. 기준자료의 표본을 추출하는 기법간의 비교 및 표본 크기를 줄이고자 하는 연구는 많이 이루어져 왔으난, 추출된 표본들간의 거리를 줄임으로써 정확도 평가 비용을 감소시키고자 하는 연구는 미미한 실정이다. 따라서, 본 연구에서는 프랙탈 분석을 통하여 기준자료의 표본을 추출하였으며, 이를 바탕으로 기존의 표본추출 기법과 정확도 차이 및 비용효과 측면을 비교 분석하였다. 연구 결과, 프랙탈 분석을 통하여 표본을 추출하는 기법은 그 정확도 추정에 있어 기존적 표본 추출 기법과 큰 차이가 보이지 않았으며, 추출된 화소들이 가까운 거리에 군집해 있어 비용효과측면에서 보다 유리함을 확인하였다.

• Electrical & Electronic Materials
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• v.11 no.11
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

• Journal of the Mineralogical Society of Korea
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• v.22 no.4
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• pp.313-324
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• 2009

We explore the effect of particle shape and size on 3-dimensional (3D) network and pore structure of porous earth materials composed of glass beads and silica gel using NMR micro-imaging in order to gain better insights into relationship between structure and the corresponding hydrologic and seismological properties. The 3D micro-imaging data for the model porous networks show that the specific surface area, porosity, and permeability range from 2.5 to $9.6\;mm^2/mm^3$, from 0.21 to 0.38, and from 11.6 to 892.3 D (Darcy), respectively, which are typical values for unconsolidated sands. The relationships among specific surface area, porosity, and permeability of the porous media are relatively well explained with the Kozeny equation. Cube counting fractal dimension analysis shows that fractal dimension increases from ~2.5－2.6 to 3.0 with increasing specific surface area from 2.5 to $9.6\;mm^2/mm^3$, with the data also suggesting the effect of porosity. Specific surface area, porosity, permeability, and cube counting fractal dimension for the natural mongolian sandstone are $0.33\;mm^2/mm^3$, 0.017, 30.9 mD, and 1.59, respectively. The current results highlight that NMR micro-imaging, together with detailed statistical analyses can be useful to characterize 3D pore structures of various porous earth materials and be potentially effective in accounting for transport properties and seismic wave velocity and attenuation of diverse porous media in earth crust and interiors.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1850-1852
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• 2000

In this paper, new Partial Discharge (PD) detection technique using Pockels cell was proposed and considerable apparent chaotic characteristics were discussed. For this purpose, PD was generated from needle-plane electrode in air and detected by optical measuring system using Pockels cell, based on Mach-Zehnder interferometer, consisting of He-Ne laser, single mode optical fiber, 50/50 beam splitter and photo detector. A qualitative analysis was carried out by drawing Return map for the normalized time series of the detected PD signals. The results are as follows:(a) Fixed points, between 0.7 and 1.0, are appeared clearly in the right upper area of the return map as the increase in the number of obtained data.(b) Considerable periodicity have been remarked even though exact period and length can not be determined.(c) The self-similarity can be also observed inasmuch as the late paths do not follow the previous ones. Accordingly, exact quantitative analysis such as embedding dimension, fractal dimension, and Lyapunov exponents should be carried out for deducing the quantitative properties regarding PD phenomena.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.6
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• pp.965-973
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• 2021

The behavior of angelfish Pterophyllum scalare exposed to low and high temperatures was monitored by video tracking, and information such as the initial speed, changes in speed, and locations of the fish in the tank were analyzed. The water temperature was raised from 26℃ to 36℃ or lowered from 26℃ to 16℃ for 4 h. The control group was maintained at 26℃ for 8 h. The experiment was repeated five times for each group. Machine learning analysis comprising a long short-term memory model was used to train and test the behavioral data (80 s) after pre-processing. Results showed that when the water temperature changed to 36℃ or 16℃, the average speed, changes in speed and fractal dimension value were significantly lower than those in the control group. Machine learning analysis revealed that the accuracy of 80-s video footage data was 87.4%. The machine learning used in this study could distinguish between the optimal temperature group and changing temperature groups with specificity and sensitivity percentages of 86.9% and 87.4%, respectively. Therefore, video tracking technology can be used to effectively analyze fish behavior. In addition, it can be used as an early warning system for fish health in aquariums and fish farms.

• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.25-30
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• 2013

In this work, we investigate the statistical properties of gamma exposure rates using well-known analysis methods, such as Autocorrelation Function Analysis(ACF), Rescaled Range Analysis(R/S Analysis), and Detrended Fluctuation Analysis(DFA). Especially, DFA is an important method to reliably detect long-range correlations in non-stationary time series. Our data are measured by Gangneung regional radiation monitoring station over the period of 1998 to 2011. First, we find a crossover indicating two different governing regimes in fluctuations of gamma exposure rates. Within a year, they show a strong long-ranged memory while this property vanishes over the range of time period longer than one year. Second, our finding is very securely supported by a variety of analysis tools. Those tools yield many relevant exponents which satisfies the well known relation between them.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.315-319
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• 2001

A diagnosis system that provides early warnings regarding machine malfunction is very important for rolling mill so as to avoid great losses resulting from unexpected shutdown of the production line. But it is very difficult to provide e8rly w, ul1ings in rolling mill. Because dynamics of rolling mill is non-linear. This paper shows a chaotic behaviour of vibration signal in rolling mill using embedding method. Phase plane and Poincare map, FFT and histogram of vibration signal in rolling mill are implemented by qualitative analysis and Fractal dimension, Lyapunov exponent are presented by quantitative analysis.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.7
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• pp.529-535
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• 2008

The characteristics of combustion process in an internal combustion engine are affected by the mixing process between injected fuel and ambient gas. Therefore, it is necessary to understand the mixture formation process of diesel spray. In this study, the spray structure was visualized by the exciplex fluorescence method, which can provide the simultaneous 2-D images of vapor and liquid phase in inner spray. For accurate investigation, the liquid-phase images were recorded with a 35mm still camera and CCD camera. Consequentially, it could be confirmed that the high-concentration vapor phase is formed in the region of spray tip and the edge of the liquid phase where droplets exist in the evaporating diesel spray, and the formed vapor is spread by diffusion. Also, the distribution of vapor is determined by the motion of droplets that exist in the edge of the liquid phase and the spray-tip region.

• Tribology and Lubricants
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• v.34 no.1
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• pp.1-8
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• 2018

This paper presents the analysis of friction master curves for a sliding elastomer on rough granite. The hysteresis friction is calculated using an analytical model that considers the energy spent during the local deformation of the rubber due to surface asperities. The adhesion friction is also considered for dry friction prediction. The viscoelastic modulus of the rubber compound and the large-strain effective modulus are obtained from dynamic mechanical analysis (DMA). We accurately demonstrate the large strain of rubber that contacts with road substrate using the GW theory. We found that the rubber block deforms approximately to 40% strain. In addition, the viscoelastic master curve considering nonlinearity (at 40% strain) is derived based on the above finding. As viscoelasticity strongly depends on temperature, it can be assumed that the influence of velocity on friction is connected to the viscoelastic shift factors gained from DMA using the time-temperature superposition. In this study, we apply these shift factors to measure friction on dry granite over a velocity range for various temperatures. The measurements are compared to simulated hysteresis and adhesion friction using the Kluppel friction theory. Although friction results in the low-speed band match well with the simulation results, there are differences in the predicted and experimental results as the velocity increases. Thus, additional research is required for a more precise explanation of the viscoelastic material properties for better prediction of rubber friction characteristics.