• Journal of Wetlands Research
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• v.12 no.2
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• pp.13-23
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• 2010

According to recent researches on climate change, the global warming is obvious to increase rainfall intensity. Damage caused by extreme hydrologic events due to global change is steadily getting bigger and bigger. Recently, frequently occurring heavy rainfalls surely affect the trend of rainfall observations. Probability precipitation estimation method used in designing and planning hydrological resources assumes that rainfall data is stationary. The stationary probability precipitation estimation method could be very weak to abnormal rainfalls occurred by climate change, because stationary probability precipitation estimation method cannot reflect increasing trend of rainfall intensity. This study analyzed temporal variation of trend in rainfall time series at 51 stations which are not significant for statistical trend tests. After modeling rainfall time series with maintaining observed statistical characteristics, this study also estimated whether rainfall data is significant for the statistical trend test in near future. It was found that 13 stations among sample stations will have trend within 10 years. The results indicate that non-stationary probability precipitation estimation method must be applied to sufficiently consider increase trend of rainfall.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.299-311
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• 1994

In time series data, atypical observations are not rare. Several approaches have been proposed to detect a single outlier, but the effectiveness of those procedures is in doubt when patchy outliers are present. In this paper, the atypicality in patchy outliers is interpreted as a local structural change, and a model is introduced to entertain its effect on the series. Based on this model, a statistic and a procedure are proposed for identifying those local structural changes. The performance of the proposed procedure is evaluated through simulation study and the analysis of real data sets.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.117-120
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• 2015

• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.31-41
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• 2015

This study aimed to analyze the relationship between sea surface temperature as a climatic element and catch amount of offshore and coastal fisheries in Korea using annual time series data from 1970 to 2013. It also tried to predict the future changes in catch amount of fisheries by climate change. Time series data on variables were estimated to be non-stationary from unit root tests, but one long-term equilibrium relation between variables was found from a cointegration test. The result of Granger causality test indicated that the sea surface temperature would cause directly changes in catch amount of offshore and coastal fisheries. The result of regression analysis on sea surface temperature and catch amount showed that the sea surface temperature would have negative impacts on the catch amount of offshore and coastal fisheries. Therefore, if the sea surface temperature would increase, all other things including the current level of fishing effort being equal, the catch amount of offshore and coastal fisheries was predicted to decrease.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.160-167
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• 2007

Due to the drastic growth of national economy and the development of overall territory, the shapes of national land and coastal areas are changing from day to day. To detect such changes in lands and coasts efficiently, as well as to establish an appropriate usage plan, it is necessary to secure a monitoring system for coastal areas based on the observation and analysis of the change in coastlines. Currently, looking at the field of producing national coastlines, the lengths of coastlines are inaccurate due to the vague definition of dividing coastline boundaries and insufficient observation data. The level of accuracy and reliability of previous data are also in the very low. This paper used aerial photographs with certain intervals to monitor the change in coastal areas of Songjeong, Haeundae, Kwanganri, Songdo and Dadaepo. The local area subjected for this research was limited to areas near Busan.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.143-148
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• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

• Journal of the Korean Home Economics Association
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• v.27 no.1
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• pp.111-126
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• 1989

The aim of the present study is to research into the household work time change and its structure in urban home makers by the choosen eleven studies and KBS's Data 1981, 1983, 1985, 1987. This study were proceeded under some limitations, it is choosen eleven studies that is different region: large city, medium and small town, and the household work's categories of original auther were changed. And KBS's Data was composed of general formation without personal character of home maker: FLC, number of childeren, family type, education, region. Although this study have a certain meaning of implementation, research into the household work time change and its's structure. The major findings of this study can be autlined as follows: (1) Total household work time did'nt so much changed through the choosen eleven studies compared with the last twenty years ago. In the change of each province household work time, time connected with meals and dwelling did not showed consistancy of change. But cloth laundering and mending time of 80's were declined compared with 70's. Family care time of 80's was increased, home management and buying time was declined untill '85, but again increasing trend '87. In choosen eleven studies, the household work time structure of urban home makers can be outlined: time connected with Meals>Family care>Cloth laundering and mending>Dwelling>Home management and Buying. (2) KBS's time-series data were analized as follows: a) Total household work time of '87 was declining gradually in weekday (34 minutes), sat. (41 minutes), sun (1 house and 2 minutes) compared with '81. b) The change of each province household work time: the time of cooking and sewing home management were declining gradually in its Mean time and its ratio of acters. The acter ratio of household worker in '81, '83, '85 was composed Cooking > Cleaning > Laundering > Home management > Buying > Child care > Sewing. In '87 was composed Cooking > Cleaning > Laundering > Buying > Home management > Child care > Sewing. c) The structure of household work time revealed some differences in each year and a day of the week.

• Honam Mathematical Journal
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• v.32 no.1
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• pp.101-112
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• 2010

Using some interesting convolution, we find kernels recovering the given function f. By a slight change of this convolution, we obtain an identity filter related to the Fourier series in the discrete time domain. We also introduce some techniques to decompose an impulse into several dilated pieces in the discrete domain. The detail examples deal with specific constructions of those decompositions. Also we obtain localized moving averages from a decomposition of an impulse to make hybrid Bollinger bands, that might give various strategies for stock traders.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.268-273
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• 1998

This study applies an on-line system, which employes an adaptive reconstruction technique to monitor and forecast ocean surface changes. The system adaptively generates an appropriate synthetic time series with recovering missing measurements for sequential images. The reconstruction method incorporates temporal variation according to physical properties of targets and anisotropic spatial optical properties into image processing techniques. This adaptive approach allows successive refinement of the structure of objects that are barely detectable in the observed series. The system sequentially collects the estimated results from the adaptive reconstruction and then statistically analyzes them to monitor and forecast the change in surface characteristics.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.121-132
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• 1995

In this paper we consider optimal designs of partially step-stress life testing which is deviced for k-component series systems with the considerably long life time. Test items are first run simultaneously at use condition for a specified time, and the surviving items are then run at accelerated condition until a predetermined censoring time. The optimal criterion for the change time to accelerated condition is to minimized either the generalized asymptotic variance of maximum likelihood estimators of the hazard rates at use condition and the acceleration factors or the asymptotic variance of the maximum likelihood estimators of the acceleration factors.