• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.97-108
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• 2002

The use of land at the time of investigation of groundwater quality in the rapidly urbanized Bu-chon city is classified into 5 categories based on the change process of land use. The difference in groundwater quality according to the land use and its usage period is tested by non-parametric statistical procedures. The seven constituents of water quality with the highly frequent detection in the area for this study are used for the statistical test. The shallow groundwater quality within the areas of the same land use at the time of investigation varies significantly according to the period of land usage. The concentration of KMnO$_4$consumed and hardness is significantly higher in the old residential area (of more than 20 years old) than in the younger one (of less than 10 years old). The quality of the shallow groundwater is also significantly different among the three categories with the similar period of land usage (of more than 15 years old). The concentration of No$_3$-N, hardness and total solid is significantly higher in the residential area than in the agricultural one (namely, the area used as paddy fields 2 to 5 years ago). The median concentration of these constituents is 2.2 to 3.8 times higher in the residential area than in the agricultural one. The concentration of NO$_3$-N, KMnO$_4$, consumed and Cl is significantly higher in the industrial area than in the agricultural one. The median concentration of these constituents is 5.5 to 18 times higher in the industrial area than in the agricultural one. The concentration of KMnO$_4$consumed is significantly higher in the industrial area than in the residential area. The median concentration of these constituents is 12 times higher in the industrial area than in the residential one. The spatial distribution of shallow groundwater quality in the rapidly urbanized area is closely related to the period of land usage as well as the land use, which is presumed to be attributed to the difference in the concentration and leakage rate of the contaminants leaking from damaged sewer into shallow groundwater.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.73-82
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• 2017

In this research, we tried to check the applicability of a Chow test to the linear models which are generated in the process of transportation planning or traffic flow analyses. The Chow test is a very popular statistical method which is being used to see if the coefficients from two separate linear regression models are equal or not. In order to prove the effectiveness of the Chow test, we found the linear relationships between speed and density under the situations such as driving in daytime and in nighttime on a rainy day. Based on the two months of Joong-Bu Expressway traffic data, we proved that the Chow test is useful to testify the similarity between two linear regression models. And this statistical tool seems to be able to have a very important role in traffic flow analysis or in transportation planning process. Finally, we expect the Chow test be implemented even to the non-linear regression models or to the multi-variate models.

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.799-821
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• 2016

Unmanned Aerial Vehicles (UAVs) are essential systems for Intelligence, Surveillance, and Reconnaissance (ISR) operations in current battlespace. And its importance will be getting extended because of complexity and uncertainty of battlespace. In this study, we forecast the advancement of 96 UAVs during the period of 32 years from 1982 to 2014 using TFDEA. TFDEA is a quantitative technology forecasting method which is characterized as non-parametric and non-statistical mathematical programming. Inman et al. (2006) showed that TFDEA is more accurate in forecasting compared with classical econometrics (e.g. regression). This study got 4.06% point of annual technological rate of change (RoC) for UAVs by applying TFDEA. And most UAVs in the period are inefficient according to the global SOA frontiers. That is because the countries which develop UAVs are in the middle class of technological level, so more than 60% of world UAVs markets are shared by North America and Europe which are advanced countries in terms of technological maturity level. This study could give some insights for UAVs development and its advancement. And also can be used for evaluating the adequacy of Required Operational Capability (ROC) of suggested future systems and managing the progress of Research and Development (R&D).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.322-340
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• 2021

Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.753-766
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• 2014

The future mean sea level rise (MSLR) due to climate change in major harbors of Korean Peninsula has been estimated by some statistical methods in this article. Firstly, Mann-Kendall non-parametric trend test to find some trend in the observed long-term tidal data has been performed and also Bayesian change point analysis has been used also to detect the location of change points and their magnitude quantitatively. Especially, in this study, the results from Bayesian change point analysis have been applied to combine 4 future MSLR scenario projections with local MSLR data at 5 tidal gauges. This proposed procedure including Bayesian change point analysis results can improve the step for the determination of starting years of future MLSR scenario projections with 18.6-year lunar node tidal cycle and effectively consider local characteristics at each gauge. The final results by the proposed procedure in this study have shown that the future MSLR in Jeju region (Jeju tidal gauge) is in the largest increment and also the future MSLRs in Western region (Boryeong tidal gauge) and Southern region (Busan tidal gauge) are in the second largest one. Finally, it has been shown that the future MSLRs in Southern region (Yeosu tidal gauge) and Eastern region (Sokcho tidal gauge) seem to be in the relatively smallest growth among 5 gauges.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.165-177
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• 2013

The purpose of this study was to examine the efficiency of senior welfare centers and the cause of differences among senior welfare centers in that regard, and to investigate influential factors for the differences in efficiency and the size of the influence of the factors. What methods would be effective at assessing the efficiency of senior welfare centers by taking into account their circumstances was reviewed, andpost-hoc analyses were made by using data envelopment analysis(DEA) and DAE/AP Modified prosthetic which were useful tools to evaluate relative efficiency. After 20 senior welfare centers located in Gyeonggi-do were selected, their yearly operating data of 2009 were utilized. The purpose of this study was to examine the efficiency of senior welfare centers. The evaluation data released by the Gyeonggi Welfare Foundation were analyzed by DEA, which is one of nonparametric statistics, and it was possible to obtain significant results on the regional operating efficiency of social welfare centers in 14 metropolitan cities and provinces, the causes and degree of their inefficiency and what areas one could refer to. As the data for the counties were utilized in this study, it's not quite possible to produce accurate results on the relative efficiency of senior welfare centers, but this study could be said to be of significance in that it suggested how to evaluate the overall operating efficiency of senior welfare centers in the counties involving the degree of their operating inefficiency, what improvements should be made and what reference groups there might be and provided information on the usefulness of the DEA model.