• Atmosphere
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• v.26 no.1
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• pp.19-33
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• 2016

Water vapor in the atmosphere is an important element that generates various meteorological phenomena and modifies a hydrological cycle. In general, the Yeongdong region has a lot of snow compared to the other regions in winter due to the complex topography and an adjacent East Sea. However, the phase change from water vapor to ice cloud and further snowfall has little been examined in detail. Therefore, in this study, we investigated phase change of liquid water in terms of a quantitative budget as well as time lag of water vapor conversion to snowfall in the ESSAY (Experiment on Snow Storms At Yeongdong) campaign that had been carried out from 2012 to 2015. First, we classified 3 distinctive synoptic patterns such as Low Crossing, Low Passing, and Stagnation. In general, the amount of water vapor of Low Crossing is highest, and Low Passing, Stagnation in order. The snowfall intensity of Stagnation is highest, whereas that of Low Crossing is the lowest, when a sharp increase in water vapor and accordingly a following increase in precipitation are shown with the remarkable time lag. Interestingly, the conversion rate of water vapor to snowfall seems to be higher (about 10%) in case of the Stagnation type in comparison with the other types at Bukgangneung, which appears to be attributable to significant cooling caused by cold surge in the lower atmosphere. Although the snowfall is generally preceded by an increase in water vapor, its amount converted into the snowfall is also controlled by the atmosphere condition such as temperature, super-saturation, etc. These results would be a fundamental resource for an improvement of snowfall forecast in the Yeongdong region and the successful experiment of weather modification in the near future.

• Journal of Distribution Science
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• v.6 no.1
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• pp.5-24
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• 2008

Pharmaceutists are interested in drugstores which are selling, the sundries, cosmetics, medical devices, with drugs. Because drug stores without prescription issued by doctor have faced on finacial difficulties since speciality between doctors and pharmaceutists set us law. There are two types of drugstore which is a type of common drugstore, other is a type of traditional drugstore based on pharmaceuties in steady of big size of store based on studies, cosmetics and so on. Expansion of business for drugstore show us that most of customer are who are very sensitive in circumstance. Since 2,000 it has been expanded to large scale, so market analysts expect that volume of market will be increased to 10 times within 5 years. Drugstores have several kinds of merchandises which customers can take a choice for their demands, so most of customers the young generations. However, market customers will be changed to medium, and old generations as drugstores set freely. Furthermore everybody will enjoy in at drugstores effectively this reports that include of counter based on proposals and validities. This study show examples that have been executed successfully by the advanced countries, moreover big companies in domestic market have been expanding their market share for drugstore business. Through out change of circumstance surrounding drugstores, this report indicate how to induce the large drugstore with validities and trends. Since speciality of pharmaceutists and doctors executed, direction and a forecast of developing drugstores under change of distribution of them and may be suggested. I hope that this research will be helpful of interesting in drugstores, and also lot of distributors focuses on drugstores to develop the drugstores in future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1873-1879
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• 2014

There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

• Journal of the Korean GEO-environmental Society
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• v.11 no.3
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• pp.5-16
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• 2010

Groundwater quality monitoring wells, which is over 2,000 in South Korea, were managed to observe groundwater quality since the early 1990s. Groundwater was sampled and analyzed biannually from 781 monitoring wells located in the areas with a high possibility of pollution. The average concentrations of cyanide, mercury, phenols, hexavalent chromium, trichloroethylene, tetrachloroethylen, and 1.1.1-trichloroethane for 12 years' data of detected cases were above the groundwater quality standard, but the average concentrations of the general quality items such as pH, electric conductivity, nitrate-nitrogen, and chloride, are below the standard. To compare a quality trend for each land-use type of the monitoring site, Sen's method is used for four quality items; chloride, nitrate-nitrogen, pH, and electric conductivity. The upward trend for these items is remarkable in urbideareas and industrial complexes and this trend continues still strongly after 2001. The deviation in a trend slopes of monitoring wells becomes bigger in the mid-2000s. In conclusion, trend analysis using existing monitoring data cidebe effective to forecast the future water quality condition and the solid action to protect groundwater quality should be done in advance using a result of trend analysis.

• The Journal of Society for e-Business Studies
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• v.15 no.1
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• pp.61-87
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• 2010

This study is based on the analysis of technology innovation performance for Inno-biz. The primary purposes of this study are to help the government formulate Inno-biz related supporting policies and improve the fitness of evaluation models for Inno-biz. In this study the definition of "the outcome of technology innovation" includes technology competitiveness changes, technology forecasting as well as the outcome of technology innovation. For this analysis, 55 independent variables were used and categorized into ability of technology innovation, ability of commercialization, and ability of technology management. The results indicate that all three variable groups have positively influenced the outcome of technology innovation. Especially ability of technology innovation is highly related to technology competitiveness and business in future. The ability of commercialization enhances technology competitiveness and predictability in major business indexes; however it doesn't influence business performance in a short-term period. The ability of technology management enables businesses to forecast technology changes, but doesn't effect short-term business outcomes.

• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.359-366
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• 2002

The damages from the natural disasters, especially from the floods, have been increasing. Therefore, it is imperative to establish a BMP to diminish the damages from the floods and to enhance the welfare of the nation. Developed countries have been generating and utilizing flood risk maps to raise the alertness of the residents, and thereby achieving efficient flood management. The major objectives of this research were to develop a prototype management system for flood risk map to forecast the boundaries oi the inundation and to plot them through the integration of geographic and hydrologic database. For more efficient system development, the user requirement analysis was made. The GIS database design was done based on the results from the research work of river information standardization. A GIS database for the study area was built by using topographic information to support the hydrologic modeling. The developed prototype include several modules; river information edition module, map plotting module, and hydrologic modeling support module. Each module enabled the user to edit graphic and attribute data, to analyze and to represent the modeling results visually. Subjects such as utilization of the system and suggestions for future development were discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.126-132
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• 2015

Technology forecasting is about understanding a status of a specific technology in the future, based on the current data of the technology. It is useful when planning technology management strategies. These days, it is common for countries, companies, and researchers to establish R&D directions and strategies by utilizing experts' opinions. However, this qualitative method of technology forecasting is costly and time consuming since it requires to collect a variety of opinions and analysis from many experts. In order to deal with these limitations, quantitative method of technology forecasting is being studied to secure objective forecast result and help R&D decision making process. This paper suggests a methodology of technology forecasting based on quantitative analysis. The methodology consists of data collection, principal component analysis, and technology forecasting by logistic regression, which is one of the data mining techniques. In this research, patent documents related to autonomous vehicle are collected. Then, the texts from patent documents are extracted by text mining technique to construct an appropriate form for analysis. After principal component analysis, logistic regression is performed by using principal component score. On the basis of this result, it is possible to analyze R&D development situation and technology forecasting.

• The Journal of Engineering Geology
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• v.14 no.1
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• pp.71-80
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• 2004

The failure of cut slopes frequently occurs particularly during the thawing season and the rain season in summer. This study interpreted data collected from site to which a real-monitoring system was applied in order to analyze the causes of ground behaviors and to forecast future slope failure. As for research methods, this study analyzed the size and mechanism of failure by integrating the results of field surveys and measurements. Furthermore, it analyzed data transmitted by the monitoring system installed in the a result, three times of ground displacement occurred as well as a number of partial tension cracks. The cut slope composed of sandstone and siltstone started its initial behavior as a result of torrential downpour and the loss of support of the substructure. For quantitative analysis of the characteristics of ground behavior, this study measured 5 lateral lines. According to the result of the measurement, displacement happened little in the section to which countermeasure had been applied, but displacement of maximum 400mm happened in the section to which countermeasure had not bee applied. The analysis of data on displacement and rainfall suggested a close relationship between ground behavior and rainfall. According to the result of stability interpretation along with the change of ground saturation, stability rate appeared to be less than 1.0 when ground saturation is over 55%. Although the current trend of ground behavior is at a stable stage falling within the range of tolerance, it is considered necessary to continue monitoring and data analysis because ground displacement is highly possible with the change of temperature during the winter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.28-34
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• 2020

A reservoir is defined as an artificial facility that stores and controls water during floods and droughts. Korea has constructed and managed reservoirs all over the country to benefit farming communities. The importance of reservoirs has decreased gradually due to urbanization and the spread of tap water, but the importance of water is increasing because of the recent shortage of water and the resulting rise in the price of water resources. Therefore, this study suggests countermeasures through an analysis of the used threshold for agricultural reservoirs. To this end, the forecast of rainfall up to 2100 was first analyzed using flood estimates and RCP scenarios through rainwater data collection. The increase in the RCP 8.5 scenario, the largest increase in the probability rainfall, was calculated by adding it to the current probability rainfall, and it was predicted that the marginal height of Odong Dam would reach its limit in 2028. Therefore, as a countermeasure against this, the measures to secure effective water storage were suggested through measures, such as lowering the height of Yeosu and installing movable beams. Overall, it is expected that effective management of the reservoirs used for agriculture will be possible in the future.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.187-194
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• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.