• Journal of Environmental Impact Assessment
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• v.15 no.3
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• pp.207-215
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• 2006

The purpose of this paper is to analyze the spatial distribution and change of the frequency of Yellow Sand days and to examine their relationship with atmospheric circular characteristics at the surroundings of the Korean peninsula. Yellow Sand days data are used by intensity, Siberian High Index and monthly mean temperature of the Northern Hemisphere. In the Middle-western region, the occurrence frequency of Yellow Sand days was higher during the study period (1973-2004). Also, the occurrence frequency of Yellow Sand days increased to latter half 16 years compared with the first half 16 years, and be clearer in Middlewest regions. Yellow Sand days frequency increased, and the trend was distinct in the Jungbu region during the study period. Increasing trend of Yellow Sand days frequency was significant for the recent 22 years. Yellow Sand days had a negative relationship with Siberian High Index in February and March. Therefore, Siberian High Index became weaker in the spring, and possibility for the occurrence of Yellow Sand days was generating larger. Yellow Sand days had a positive relationship in monthly mean temperature of the Northern Hemisphere. Especially, the case of the strong Yellow Sand days is significant. Recently, global warming might be affecting the occurrence of strong Yellow Sand days.

• Convergence Security Journal
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• v.6 no.3
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• pp.145-153
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• 2006

Infinite failure NHPP models for a record value satisfies mode proposed in the literature exhibit either monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, propose comparative study of software reliability model using Erlang distribution, Rayleigh and Gumbel distribution. Equations to estimate the parameters using maximum likelihood estimation of infinite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing distribution, we used to the special pattern. Analysis of failure data set using arithmetic and Laplace trend tests, goodness-of-fit test, bias tests is presented.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.1-9
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• 2014

The inverse Rayleigh model distribution and Rayleigh distribution model were widely used in the field of reliability station. In this paper applied using the finite failure NHPP models in order to growth model. In other words, a large change in the course of the software is modified, and the occurrence of defects is almost inevitable reality. Finite failure NHPP software reliability models can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the inverse Rayleigh and Rayleigh software reliability growth model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, were employed. In order to insurance for the reliability of data, Laplace trend test was employed. In many aspects, Rayleigh distribution model is more efficient than the reverse-Rayleigh distribution model was proved. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can helped.

• Journal of Distribution Science
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• v.21 no.5
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• pp.101-111
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• 2023

Purpose: The purpose of this paper is to examine the effect of the VKOSPI index on short-term stock returns after a large-scale stock price shock of individual stocks of firms in the distribution industry in Korea. Research design, data, and methodology: This study investigates the effect of the change of the VKOSPI index or investor mood on abnormal returns after the event date from January 2004 to July 2022. The significance of the abnormal return, which is obtained by subtracting the rate of return estimated by the market model from the rate of actual return on each trading day after the event date, is determined based on T-test and multifactor regression analysis. Results: In Korea's distribution industry, the simultaneous occurrence of a bad investor mood and a large stock price decline, leads to stock price reversals. Conversely, the simultaneous occurrence of a good investor mood and a large-scale stock price rise leads to stock price drifts. We found that the VKOSPI index has strong explanatory power for these reversals and drifts even after considering both company-specific and event-specific factors. Conclusions: In Korea's distribution industry-related stock market, investors show an asymmetrical behavioral characteristic of overreacting to negative moods and underreacting to positive moods.

• Journal of the Korean Geographical Society
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• v.41 no.3 s.114
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• pp.361-372
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• 2006

The purpose of this paper is to analyze temporal trends and spatial distribution of frost occurrence days using 54 weather stations under the Korea Meteorological Administration during the recent 30years ($1971{\sim}2000$). The frost occurrence days in the middle inland area was more than in the coastal area, but the period of free-frost days in the coastal area was longer than that in the middle inland. In the southern and eastern coastal areas, the frost day was more than in the western coastal area. The distribution of the first frost day was similar to that of the last frost day. The first frost day in the coastal area appeared a month later than that in the middle inland. The last frost day in the coastal area appeared $20{\sim}25$ days later than that in the middle inland. At most of stations which the first frost day was getting delayed and the last frost day earlier, the frost occurrence days showed a decreasing trend. However, in some stations, the frost occurrence day was increasing. As the frost days in October, March and April at some stations showed an increasing trend, the damage due to the frost might be increased in some areas in South Korea.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.2
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• pp.112-120
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• 2010

In this paper time series wave data measured continuously for 24 hours during a storm in Yura Sea Area are used to investigate statistical characteristics of nonlinear waves. The exceedance probability of wave height is compared using the Rayleigh distribution and the Edgeworth-Rayleigh (ER) distribution. Wave data which show stationary state for 10 hours contain 4600 waves approximately. The Gram-Chalier distribution fits the probability of wave elevation better than the Gaussian distribution. The Rayleigh ($H_{rms}$) distribution follows the exceedance probability of wave height in general and predicts the probability of freak waves well. The ER distribution overpredicts the exceedance probability of wave heights and the occurrence of freak waves. If wave data measured for 30 minute period which contains 250 waves are used, the ER distribution can predict the occurrence probability of freak waves well. But it overpredicts the probability of overall wave height If no freak wave occurs, the Rayleigh ($H_{rms}$) distribution agrees well with wave height distribution for the most of wave height ranges. The wave height distribution of freak waves of which height are less than 10 m shows similar tendency compared with freak waves greater than 10 m. The value of $H_{max}/H_{1/3}$ is related to the kurtosis of wave elevation. It seems that there exists threshold value of the kurtosis for the occurrence of freak waves.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.2
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• pp.227-234
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• 2010

When a weapon system is developed, climate elements such as temperature, rainfall, and so on have an effect on development costs and a developing period. Therefore, effects of environment and climate must be examined throughly before the design of weapon systems and be applied to their developments. And so, operational and storage requirements for weapon systems are determined and are applied to related tests through analyzing not only environmental factors such as vibration, shock, and so on, but also climate factors. In this paper, the distribution and the frequency of occurrence of rainfall were analyzed and were suggested as a good guide to determine standards of tests for weapon systems when it's raining.

• Journal of Plant Biology
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• v.33 no.3
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• pp.159-168
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• 1990

The occurrence and distribution of cellular slime molds in major deciduous forests of South Korea were investigated. Ten species were isolated from the soils collected at ten sampling areas and cultured in hay infusion agar with E. coli. These include: Dictyostelium minutum Raper, Dictyostelium mucoroides Brefeld, Dictyostelium lacteum Van Tiegham, Dictyostelium polycephalum Raper, Dictyostelium fasciculutum Traub, Hohl and Cavender, Dictyostelium sp. Polysphondylium pallidum Olive, Polyshpondylium violaceum Brefeld, Copromyxellar sp. and Guttulinopsis vulgaris Olives. Among these species, Dictyostelium sp. and Copromyxellar sp. could not be identified. D. minutum and D. mucoroides occurred the most frequently in almost all the deciduous forests investigated in this study. Dictyostelium sp., D. fasciculutum and Copromyxella sp. occurred only in the north of the central region, but D. lacteum and D. polycephalum were found only in the south of that region. This indicates that distribution of these species may be affected by climate. The number of isolates per sampling site ranged from 2 to 6, averaging 4.3.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.509-521
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• 1994

This study is an effort to develop computer simulation model that produce precipitation patterns from stochastic model. A stochastic model is formulated for the process of daily precipitation with considering the sequences of wet and dry days and the precipitation amounts on wet days. This study consists of 2 papers and the process of precipitation occurrence is modelled by an alternate renewal process (ARP) in paper (I). In the ARP model for the precipitation occurrence, four discrete distributions, used to fit the wet and dry spells, were as follows; truncated binomial distribution (TBD), truncated Poisson distribution (TPD), truncated negative binomial distribution (TNBD), logarithmic series distribution (LSD). In companion paper (II) the process of occurrence is developed by Markov chain. The amounts of precipitation, given that precipitation has occurred, are described by a Gamma. Pearson Type-III, Extremal Type-III, and 3 parameter Weibull distribution. Daily precipitation series model consists of two models, A-Wand A-G model, by combining the process of precipitation occurrence and a continuous probability distribution on the precipitation of wet days. To evaluate the performance of the simulation model, output from the model was compared with historical data of 7 stations in the Nakdong and Seomjin river basin. The results of paper (1) show that it is possible to design a model for the synthetic generation of IX)int precipitation patterns.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.9-24
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• 2009

We compare the relation among the annual distribution of sunspots: coronal mass ejections (CMEs) and geomagnetic storms and North-South asymmetry during solar cycle 23. For this purpose, we calculate correlation coefficients between (i) annual distribution and N-S asymmetry of CMEs - sunspots (ii) distribution of CMEs - occurrence number of geomagnetic storms (iii) distribution of sunspots - occurrence number of geomagnetic storms. We find that (i) the annual distribution of total CMEs has good correlation with distribution of annual average of sunspots but poor correlation with N-S asymmetry of sunspots, N-S asymmetry of CMEs has good correlation with N-S asymmetry of sunspots: (ii) total and N-S asymmetry of CMEs have poor correlation with occurrence number of geomagnetic storms, it's, however, well correlated with the classified groups of CMEs (Ap, Dst and an indices vs. fast CMEs($\upsilon$ > $1000kms^{-1}$), Dst index vs. Halo CMEs), and (iii) sunspot numbers and area are correlated with occurrence number of geomagnetic storms. We conclude that annual distribution of CMEs and sunspots have well correlated with geomagnetic storms, N-S asymmetry of CMEs and sunspots have poor correlated with the geomagnetic storms.