• Journal of Korean Society for Quality Management
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• v.26 no.4
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• pp.111-123
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• 1998

We consider the problem of modeling count data where the observation period is determined by the life time of the system under study. We assume random effects or a frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect or a frailty, the death times follow a Weibull distribution with a hazard rate. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time. A gamma distribution is assumed for the frailty model. Maximum likelihood estimators of the model parameters are obtained. A model for the time to death and the number of failures system received is constructed and consequences of the model are examined.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.828-835
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• 2019

An artificial rainfall system is used widely as a research tool for generating model experiment data. Artificial rainfall devices have been used in many studies, but studies of the rainfall distribution are not considered as important issues. To simulate various rainfall characteristics, it should be possible to simulate from low to high intensity, and the homogeneity of the rainfall distribution should be ensured. In this study, the maximum rainfall intensity was set to 130mm/hr and controlled by 10mm/hr. In addition, the aim was to secure a uniform coefficient value of 80% or more. To this end, rainfall tests were performed according to the nozzle type, diameter, position, and pump pressure. The rainfall test showed that the circular nozzle was suitable, and the nozzle size was 1.9mm and 1.4mm. The optimal pump pressure was found to be 3~6kg/㎠. The rainfall intensity tended to increase linearly with increasing pump pressure. Based on the rainfall test results, a rainfall control manual was produced with variables, such as pump pressure, nozzle type, and number of nozzles. As a result of rainfall verification, rainfall intensity showed a 3.1% error with a uniformity coefficient of 86%.

• Journal of Korean Society of Water and Wastewater
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• v.12 no.3
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• pp.99-106
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• 1998

This paper presents a procedure for determining the design rainfall depth and the design rainfall intensity at Incheon city area in Korea. In this study the eight probability distributions are considered to estimate the probable rainfall depths for 11 different durations. The Kolmogorov - Smirnov test and the Chi-square test are adopted to test each distribution. The probable rainfall intensity formulas are then determined by i) the least squares (LS) method, ii) the least median squares (LMS) method, iii) the reweighted least squares method based on the LMS (RLS), and iv) the constrained regression (CR) model. The Talbot, the Sherman, the Japanese, and the Unified type are considered to determine the best type for the Incheon station. The root mean squared (RMS) errors are computed to test the formulas derived by four methods. It is found that the Unified type is the most reliable and that all methods presented herein are acceptable for determining the coefficients of rainfall intensity formulas from an engineering point of view.

• Journal of The Korean Astronomical Society
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• v.11 no.1
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• pp.37-46
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• 1978

A hydrostatic model atmosphere of a typical umbral core is constructed on the basis of both Na I $D_2$ line profile and umbral core-to disk continuum intensity ratio. The observations were obtained by Mullan and Wyller with photoelectric means over the range from $4000{\AA}\;and\;6500{\AA}$. The computed line profile of Na I $D_2$ and the emergent continuum intensity distribution are compared with the observations. The temperature of umbral cores is found to be lower by $300^{\circ}K\;to\;500^{\circ}K$ than that of their ambient umbral region. The detailed physical structure of a working model of umbral cores is proposed.

• Convergence Security Journal
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• v.11 no.4
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• pp.85-91
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• 2011

Due to the large-scale application software syslmls, software reliability, software development has animportantrole. In this paper, software truncated software reliability growth model was proposed based on log-logistic distribution. According to fixed time, the intensity function, the mean value function, the reliability was estimated and the parameter estimation used to maximum likelihood. In the empirical analysis, Poisson execution time model of the existiog model in this area and the log-logistic model were compared Because log-logistic model is more efficient in tems of reliability, in this area, the log-logistic model as an alternative 1D the existiog model also were able to confim that you can use.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.37-43
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• 2019

The research aims to study the relationship between export performance and stock return of Vietnamese fishery companies. To conduct this study, quarterly data was collected for period from 2010-2018 of 13 fishery companies listing in Ho Chi Minh Stock Exchange (HOSE) and Ha Noi Stock Exchange (HNX). The export performance was measured by export intensity, export growth and export market coverage. In addition, interest rate, exchange rate, GDP, firm size, profitability, and financial leverage were considered as the control variables in the research model. Panel data analysis with Generalized Least Squares model was employed to estimate the predictive regression. The findings indicated that export intensity and export growth have a significant and positive relationship with stock returns. However, export market coverage has not a significant relationship with stock return at the 0.05 level. Profitability, financial leverage, and exchange rate have a positive relationship, while interest rate and GDP have no relation to stock return at the 0.05 significance level. The findings imply that investors should consider the export intensity instead of export growth and export market coverage as selecting stock of fishery exports firms to invest; managers should increase export intensity to increase company's stock price or firm market value.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.195-206
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• 2016

The remote sensing technique using SAR data have many advantages when applied to the disaster site due to its wide coverage and all-weather acquisition availability. Although a single-pol (polarimetric) SAR image cannot represent the land surface better than a quad-pol SAR image can, single-pol SAR data are worth using for disaster-induced change detection. In this paper, an automatic change detection method based on a mixture of GGDs (generalized Gaussian distribution) is proposed, and usability of the textural features and intensity is evaluated by using the proposed method. Three ALOS/PALSAR images were used in the experiments, and the study site was Norita City, which was affected by the 2011 Tohoku earthquake. The experiment results showed that the proposed automatic change detection method is practical for disaster sites where the large areas change. The intensity information is useful for detecting disaster-induced changes with a 68.3% g-mean, but the texture information is not. The autocorrelation and correlation show the interesting implication that they tend not to extract agricultural areas in the change detection map. Therefore, the final tsunami-induced change map is produced by the combination of three maps: one is derived from the intensity information and used as an initial map, and the others are derived from the textural information and used as auxiliary data.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.475-485
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• 1995

In this study, statistical analysis of fatigue data which had obtained from respective 24 fatigue crack, was examined for SiC whisker reinforced aluminium 6061 composite alloy (SiC$_{w}$/A16061) and aluminium 6061 alloy. SiC volume fraction in composite alloy is 25%. The analysis results stress intensity factor range and 0.1 mm fatigue crack initiation life for SiC$_{w}$/A16061 composite & A16061 matrix are the log-normal distribution. And regression analysis by linear model, exponential model and multiplicative model were performed to find out the relationship between fatigue crack growth rate(da/dN) and stress intensity for find out the relationship between fatigue crack growth rate(da/dN) and stress intensity factor range(.DELTA.K) in the SiC$_{w}$/A16061 composite and examine the applicability of Paris' equation to SiC$_{w}$A16061 composite. Also computer simulation was performed for fatigue life prediction of SiC$_{w}$/A16061 composite using the statistical results of this study.udy.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.94.1-94.1
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• 2013

Whistler mode chorus waves, which are observed outside the plasmasphere of the Earth's magnetosphere, play a major role in accelerating and scattering energetic electrons in the radiation belts. In this study we developed a predicting scheme of the global distribution of chorus by using the Time History of Events and Macroscale Interactions during Substorms (THEMIS) satellite data. First, we determined global spatial distributions of chorus activity, and identified fit functions that best represent chorus intensities in specific L-MLT zones. Second, we determined the specific dependence of average chorus intensity on preceding solar wind conditions (e.g., solar wind speed, IMF Bz, energy coupling degree) as well as preceding geomagnetic states (as represented by AE, for example). Finally, we combined these two results to develop the predicting functions for the global distribution and intensity of chorus. Implementing these results in the radiation belt models should improve the local acceleration effect by chorus waves.

• Journal of the Korea Safety Management & Science
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• v.22 no.1
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• pp.1-8
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• 2020

Maintenance of power distribution facilities is a significant subject in the power supplies. Fault caused by deterioration in power distribution facilities may damage the entire power distribution system. However, current methods of diagnosing power distribution facilities have been manually diagnosed by the human inspector, resulting in continuous pole accidents. In order to improve the existing diagnostic methods, a thermal image analysis model is proposed in this work. Using a thermal image technique in diagnosis field is emerging in the various engineering field due to its non-contact, safe, and highly reliable energy detection technology. Deep learning object detection algorithms are trained with thermal images of a power distribution facility in order to automatically analyze its irregular energy status, hereby efficiently preventing fault of the system. The detected object is diagnosed through a thermal intensity area analysis. The proposed model in this work resulted 82% of accuracy of detecting an actual distribution system by analyzing more than 16,000 images of its thermal images.