• Economic and Environmental Geology
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• v.32 no.5
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• pp.503-517
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• 1999

The purpose of this study is to verfify a more effecive techique for calculating geothermal gradient. this study examines 370 data of temperature-logging having been collected since 1985. The daya are divided into three different grades grades according to the type of temperature-depth plots: 204 data show typical linear gradient (Grade A); 126 data do not explicitily show the gradient becase of various external effects such as water flow (Grade B); and the rest 40 data do not show the gradient at all (Grade D). The new technique for calculating geothermal gradient is to be required to use Greade-B data more effctiviely. This new technique includes (1) calculating the independer depth of atmospheric temperature in the earth; (2) drawing a distribution map of subsurface tempurature by using the distribution map of subsurface temperature by using Grade-A data at the independent depth; and (3) recalculating geothermal gradient of Grade-B data by using the distrbution map of subsurface temperature, borehole depth, and bottom temperature of Grade-B data by using the distribution map of subsurface temperature, borehole depth, and bottom temperature of Grade-B data. As a result, 330 data-both Grade-A and Grade-B data--can be used to draw a distribution map of hot spradient. The map clearly distinguishes anomaly areas, and helps interpret their relations to the distribution of hot springs, geology, geological structures, and geophysical anomaly areas. These new results reveal that the average of geothermal in south Korea is 25.6$^{\circ}C$/km, when calculated to the Kriging method.

• The Journal of Industrial Distribution & Business
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• v.9 no.8
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• pp.27-34
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• 2018

Purpose - This paper discussed and illustrated the most efficient method to calculate the distribution centers for a national project in China. Through demonstration of implementing the GIS, spatial analysis, and location calculation model, this paper mainly dealt with the construction distribution problem and inconvenient supply of materials problems. Research design, data, and methodology - In this paper, the research design structure based on three steps: implementing the Geographic Information System to locate the points coordination data, calculating the distribution centers of the project, and optimizing the most efficient and effective coordination. The data of the calculation is from an actual project. The methodology of this paper is summarizing the spatial analysis capabilities and digital graphic data calculation to locate logistics distribution centers, and since the illustration of the calculation is useful for locating the coordination, the result of this paper has certain reference values for the project construction. Results - This paper illustrates the steel and cement resource of every distribution point to confirm the most efficient distribution center location coordination. Conclusions - The integrated logistical management models are used to ensure the results for the purposes of our calculation. The result of the calculation is also a useful example for future Chinese national projects.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1399-1412
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• 2016

We compare many normality tests consisting of different sources of information extracted from the given data: Anderson-Darling test, Kolmogorov-Smirnov test, Cramervon Mises test, Shapiro-Wilk test, Shaprio-Francia test, Lilliefors, Jarque-Bera test, D'Agostino' D, Doornik-Hansen test, Energy test and Martinzez-Iglewicz test. For the purpose of comparison, those tests are applied to the various types of data generated from skewed distribution, unsymmetric distribution, and distribution with different length of support. We then summarize comparison results in terms of two things: type I error control and power. The selection of the best test depends on the shape of the distribution of the data, implying that there is no test which is the most powerful for all distributions.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.227-240
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• 2017

In this paper, we introduce the inverted exponentiated Weibull (IEW) distribution which contains exponentiated inverted Weibull distribution, inverse Weibull (IW) distribution, and inverted exponentiated distribution as submodels. The proposed distribution is obtained by the inverse form of the exponentiated Weibull distribution. In particular, we explain that the proposed distribution can be interpreted by Marshall and Olkin's book (Lifetime Distributions: Structure of Non-parametric, Semiparametric, and Parametric Families, 2007, Springer) idea. We derive the cumulative distribution function and hazard function and calculate expression for its moment. The hazard function of the IEW distribution can be decreasing, increasing or bathtub-shaped. The maximum likelihood estimation (MLE) is obtained. Then we show the existence and uniqueness of MLE. We can also obtain the Bayesian estimation by using the Gibbs sampler with the Metropolis-Hastings algorithm. We also give applications with a simulated data set and two real data set to show the flexibility of the IEW distribution. Finally, conclusions are mentioned.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1328-1334
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• 2015

A new system for evaluating the voltage management errors of distribution equipment is presented in this paper. The main concept of the new system is to use real distribution live-line voltage to evaluate and correct the voltage measurement data from distribution equipment. This new approach is suitable for a new Distribution Management System (DMS) which has been developed for a distribution power system due to the connection of distributed generation growth. The data from distribution equipment that is installed at distribution lines must be accurate for the performance of the DMS. The proposed system is expected to provide a solution for voltage measurement accuracy assessment for the reliable and efficient operation of the DMS. An experimental study on actual distribution equipment verifies that this voltage measurement accuracy assessment system can assess and calibrate the voltage measurement data from distribution equipment installed at the distribution line.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.241-250
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• 2010

Over the past few decades, several studies have been made on the modeling of circular data. But these studies focused mainly on the symmetrical cases including von Mises distribution. Recently, many studies with skew-normal distribution have been conducted in the linear case. In this paper, we dealt the problem of fitting of non-symmetrical circular data with wrapped skew-normal distribution which can be derived by using the principle of wrapping. Wrapped skew-normal distribution is very flexible to asymmetical data as well as to symmetrical data. Multi-modal data are also fitted by using the mixture of wrapped skew-normal distributions. To estimate the parameters of mixture, we suggested the EM algorithm. Finally we verified the accuracy of the suggested algorithm through simulation studies. Application with real data is also considered.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.43-60
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• 2018

This paper considers the use of classical and Bayesian inference methods to analyze data generated by variables whose natural behavior can be modeled using asymmetric distributions in the presence of left censoring. Our approach used a $L{\grave{e}}vy$ distribution in the presence of left censored data and covariates. This distribution could be a good alternative to model data with asymmetric behavior in many applications as lifetime data for instance, especially in engineering applications and health research, when some observations are large in comparison to other ones and standard distributions commonly used to model asymmetry data like the exponential, Weibull or log-logistic are not appropriate to be fitted by the data. Inferences for the parameters of the proposed model under a classical inference approach are obtained using a maximum likelihood estimators (MLEs) approach and usual asymptotical normality for MLEs based on the Fisher information measure. Under a Bayesian approach, the posterior summaries of interest are obtained using standard Markov chain Monte Carlo simulation methods and available software like SAS. A numerical illustration is presented considering data of thyroglobulin levels present in a group of individuals with differentiated cancer of thyroid.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.329-334
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• 2007

In this paper, a new load flow algorithm is proposed on the basis of distributed load modeling in radial distribution networks. Since the correct state data in the distribution power networks is basic for all distribution automation algorithms in the Distribution Automation System (DAS), the distribution networks load flow is essential to obtain the state data. DAS Feeder Remote Terminal Units (FRTUs) are used to measure and acquire the necessary data for load flow calculations. In case studies, the proposed algorithm has been proven to be more accurate than a conventional algorithm; and it has also been tested in a simple radial distribution system.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.313-322
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• 2015

A mixture distribution of a discrete uniform or degenerated distribution and two binomial distribution is proposed and a method of obtaining the maximum likelihood estimates of the parameters is provided. For the proposed model simulation studies were conducted to see performance of the maximum likelihood estimates and a mixture of a degenerated distribution and two binomial distributions was applied to fit a lecture evaluation data to show a good result.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.205-220
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• 2009

For modeling skewed semicircular data, we derive new family of the exponential distributions. We extend it to the l-axial exponential distribution by a transformation for modeling any arc of arbitrary length. It is straightforward to generate samples from the f-axial exponential distribution. Asymptotic result reveals two things. The first is that linear exponential distribution can be used to approximate the l-axial exponential distribution. The second is that the l-axial exponential distribution has the asymptotic memoryless property though it doesn't have strict memoryless property. Some trigonometric moments are also derived in closed forms. Maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for goodness of fit test of the l-axial exponential distribution. We finally obtain a bivariate version of two kinds of the l-axial exponential distributions.