• Journal of Korean Society on Water Environment
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• v.34 no.1
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• pp.10-25
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• 2018

This study was conducted to estimate the habitat suitability of 17 benthic macroinvertebrate taxa in the Hwayang stream. Habitat Suitability Index (HSI) of benthic macroinvertebrates from the Hwayang stream was developed based on three physical habitat factors which include current velocity, water depth, and the substrate. The Weibull model was used as a probability density function to analyze the distribution of individual abundance by physical factors. The number of species and the total individual abundance increased along with the increase in current velocity. By means of Canonical Correspondence Analysis (CCA), the relative importance of each factor was determined in the following order: current velocity, water depth, and the mean diameter. The results depicted that, the most influential factor in the growth of benthic macroinvertebrates in the Hwavang system was current velocity. After comparing the analyzed results from the Hwayang stream with the resukts from the Gapyeong stream, the integrated HSI was drawn. The results indicated that current velocity and substrate had similar distributions of HSI in the two streams. This was due to the addition of unmeasured data from previous surveys, or the fact that benthic macroinvertebrates adapted to deeper waters in the Hwayang Stream. Most taxa showed a clear preference for a fast current velocity, deep water depth and coarse substrate except Baetiella, Epeorus, (mayflies), and Hydropsyche (caddisfly).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.693-700
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• 2004

The probabilistic fracture mechanics(PFM) is a useful analytical tool to assess the integrity of reactor pressure vessel(RPV) at the event of pressurized thermal shock(PTS). In PFM, the probabilities of flaw initiation and propagation are estimated by comparing the applied stress intensity factor with the fracture toughness calculated by the simulation of various stochastic variables. It is known that the results of PFM analyses are dependent on the choice of the stochastic parameters and assumptions. Of the various variables and assumptions, we investigated the effects of the RT$_{NDT}$ shift equations, fracture toughness curves, and flaw distributions on the PFM results for the three PTS transients. The results showed that the combined effects of the RT$_{NDT}$ shift equations and fracture toughness curves are complicated and dependent on the characteristics of the transients, the chemistry of the materials, the fast neutron fluence, and so on.

• Journal of The Korean Astronomical Society
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• v.17 no.1
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• pp.1-14
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• 1984

Analyses of an integrated form $N(\tau)={\int}_{\tau}^{\infty}n(\tau)d{\tau}$ of the distribution of cluster ages, rather than its differential form $n(\tau)$, demonstrate that the observed distribution has clusters older than about 500 million years in a significant excess over theoretical model distributions. Considerations on cluster disruption processes show that a single disruption time-scale, frequently employed by current theoretical models, is no longer an adequate parameter for describing survival probability of clusters over wide age range, because different initial conditions of these clusters produce corresponding spreads in their lifetimes. To take into account for the spread in initial conditions, we have introduced an age-dependent disruption time, and deduced its age-dependence from the present-day age distribution of clusters. Results show a distinct two-stage variation: The newly introduced disruption time stays constant at about 50 million years for clusters younger than about 100 million years, while for clusters older than that it increases monotonically with the cluster age. This leads us to conclude that clusters experience different types of disrupting causes as they get old.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.251-260
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• 2009

In this study, we propose a new estimation method based on autocovariance for selecting optimal estimators of the regression coefficients in the simple linear regression model. Although this method does not seem to be intuitively attractive, these estimators are unbiased for the corresponding regression coefficients. When the exploratory variable takes the equally spaced values between 0 and 1, under mild conditions which are satisfied when errors follow an autoregressive moving average model, we show that these estimators have asymptotically the same distributions as the least squares estimators. Additionally, under the same conditions as before, we provide a self-contained proof that these estimators converge in probability to the corresponding regression coefficients.

• Progress in Superconductivity
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• v.11 no.1
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• pp.52-56
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• 2009

Temperature distributions and thermal stresses were calculated and analyzed to investigate the effect of the artificial holes to the transient behaviors of the superconductors which was cooled in liquid nitrogen. Three dimensional finite element method was used to calculated the transient temperature and thermal stresses in the superconductors. The cooling speed of the superconductors with holes is faster than those without holes. Because the thermal stresses calculated in the superconductors can be relaxed by the distributed holes, the volume of the peak tensile stress decreases during the cooling in liquid nitrogen. If optimal metal, which can maintain the relaxation of thermal stresses, is used to fill and reinforce the artificial holes, the probability of failure of the superconductors may be decreased by the decrease of volume of peak tensile stress.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.119-130
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• 2010

Reconstruction analysis of traffic accident is done by analyzing diverse data such as the road, accident traces and damage on the automobile. Most data can be a variable in the process of analysis, and measurement error of the data occurs from the investigator, tool and the given environment. Therefore, accident analysis always has some risks of measurement uncertainty. This research quantify the uncertainty in traffic accident analysis by conducting repetitive measurement experiments for variables with high probability of uncertainly such as length (i.e. geometric structure of the road, tire marks) and coefficient of friction. This paper also suggests an analysis result for the uncertainly of photographic observation of automobile crush measurement. These statistical distributions can help determine appropriate ranges for the input data in order to estimate the accident reconstruction uncertainty.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.119-125
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• 1999

This paper gives an overview of the various approaches to designing statistical pattern recognition scheme based on Bayes discrimination rule and the artificial neural networks for rotating machine condition classification. Concerning to Bayes discrimination rule, this paper contains the linear discrimination rule applied to classification into several multivariate normal distributions with common covariance matrices, the quadratic discrimination rule under different covariance matrices. Also we discribes k-nearest neighbor method to directly estimate a posterior probability of each class. Five features are extracted in time domain vibration signals. Employing these five features, statistical pattern classifier and neural networks have been established to detect defects on rotating machine. Four different cases of rotation machine were observed. The effects of k number and neural networks structures on monitoring performance have also been investigated. For the comparison of diagnosis performance of these two method, their recognition success rates are calculated form the test data. The result of experiment which classifies the rotating machine conditions using each method presents that the neural networks shows the highest recognition rate.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.649-654
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• 2005

Shallow slope failures in residual soil during periods of prolonged infiltration are common over the world. One of the key factors that dominate slope stability is hydrological response associated with infiltration. Hence, the soil-water profile during rainfall infiltration into unsaturated soil must me examined to evaluate slope stability. However, the hydraulic response of unsaturated soil is complicated by inherent uncertainties of the soil hydraulic properties. This study presents a methodology for assessing the effects of parameter uncertainty of hydraulic properties on the response of a analytical infiltration model using first-order reliability method. The unsaturated soil properties are considered as uncertain variables with means, standard deviations, and marginal probability distributions. Sensitivities of the probabilistic outcome to the basic uncertainties in the input random variables are provided through importance factors.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1605-1614
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• 2013

This paper presents a probabilistic methodology for small signal stability analysis of power system with correlated wind sources. The approach considers not only the stochastic characteristics of wind speeds which are treated as random variables with Weibull distributions, while also the wind speed spatial correlations which are characterized by a correlation matrix. The approach based on the 2m+1 point estimate method and Cornish Fisher expansion, the orthogonal transformation technique is used to deal with the correlation of wind farms. A case study is carried out on IEEE New England system and the probabilistic indexes for eigenvalue analysis are computed from the statistical processing of the obtained results. The accuracy and efficiency of the proposed method are confirmed by comparing with the results of Monte Carlo simulation. The numerical results indicate that the proposed method can actually capture the probabilistic characteristics of mode properties of the power systems with correlated wind sources and the consideration of spatial correlation has influence on the probability of system small signal stability.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.269-296
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• 2006

With the concern of the potential problems which can be observed in terms of the power supply of renewable energies, we need to analyze the impact of additional power generation capacities of renewable energy sources on peak load. Each renewable energy sources are dependent upon wind speed, solar radiation, head differences caused by lunar calendar. Considering that these exogenous renewable energy sources follow their own stochastic distributions, we analyze the probability distribution of the impact of each renewable energy power supply on peak load. As a conclusion, we note that traditional tools used for the analysis of power supply such as capacity factors are no longer appropriate for the analysis of renewable energy sources in that perspective.