• Journal of Biosystems Engineering
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• v.30 no.5 s.112
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• pp.268-273
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• 2005

This study was conducted to investigate the specificities of four fulcrum types for geo-statistical analysis of elevation within rice paddy field. In Korea, the spaces between inter-rows and between hills for rice transplanting are 30cm and 11cm to 14cm, respectively. So, the size and shape of fulcrum for field elevation measurement should be considered according to the inter-row and the hill spaces. Four kinds of fulcrum were chosen such as round-shape with 2.5cm diameter, circular-shape with 10cm diameter, 10cm (one third of inter-row space) by 24cm (double of hill space) rectangular-shape, and 20cm (two-thirds of inter-row space) by 24cm rectangular-shape. The resulting descriptive statistics couldn't determine the best fulcrum type to measure the rice paddy field elevation. But the results of geo-statistical analysis could determine the best fulcrum type. In the case of 10cm by 24cm rectangular-shape fulcrum, Nugget and range, meaning measurement error and/or noise, and limit of spatial connection, respectively, were minimum; Q value meaning weight of spatial structure and $r^2$ value were minimum, and residual sum of squares was minimum. It means that 10cm by 24 cm rectangular-shape fulcrum could best describe the rice paddy field elevation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.907-915
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• 2018

With the increase of metal usage in various industries, metal pollution and ecological toxicity in the environmental system have become a significant concern. A geo-statistical index has been widely used to determine contamination level with normalization through a background value. In this study, geo-statistical indexes such as an enrichment factor, accumulation index, and potential ecological risk index were used to assess metal pollution in soil at locations associated with shipbuilding manufacturing industries. Metal contamination, especially of Cu and Pb, was observed in some samples located closer to manufacturing sites. Enrichment factor and accumulation (IGEO) values were indicative of concerning levels of soil contamination in specific samples, and the soil contamination could be induced by anthropogenic sources. In further study, after more detailed sampling for soil and potential pollution sources, high interpretation techniques such as Pb isotope analysis and X-ray analysis will be needed to investigate source identification.

• Journal of the Korean Geotechnical Society
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• v.27 no.7
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• pp.59-68
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• 2011

Subsurface Investigation results always reflect a level of soil uncertainty, which sometimes requires statistical corrections of the data for the appropriate engineering decision. This study suggests a closed-form framework to extract the outlying data points from the testing results using the statistical geo-spatial information analyses with outlier analysis and kring-based crossvalidation. The suggested analysis method is conducted to soil stratification using the borehole data in Yeouido.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.40-48
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• 2005

This paper will specify geo-objects and geo-fields of the geo-ecological contamination source and implement the system for evaluating an ocean Environmental contamination based on the spatial statistical analysis. In order to produce the grade of fishery that can evaluate the ocean effect, we will analysis the degree of the spatial correlation by semi-veriogram and predicate the elevation raster of spatial data using ordinary kriging method. This paper is to estimate the grade of fishery contamination region and produce the ratio of the area according to the fishery grade. Therefore, we can contribute to produce fishery grade that evaluates the ocean effect by means of deciding an efficient fishery environment.

• The Journal of Engineering Geology
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• v.22 no.2
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• pp.207-221
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• 2012

A statistical analysis of time series of water level at 27 groundwater monitoring wells was conducted to analyze the surface water-groundwater connectivity in the wide alluvial plains surrounding the Nakdong River, Korea. Change in groundwater level is strongly related to river water level, yielding an average cross-correlation coefficient of 0.601, which is much higher than that between rainfall and groundwater level (0.125). Principal component analysis of groundwater level indicates that wells in the study area can be classified into two groups: wells in Group A are located close to a river, have water levels closely related to river level, and generally show a large increase in groundwater level during heavy rainfall. On the other hand, wells in Group B located far from a river are relatively less related to river level. Including hydrologic and statistical analyses, geochemical analysis and temperature monitoring are additionally required to reveal the relationship between surface water level and groundwater level, and to assess the possibility of groundwater flooding.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.74-84
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• 2009

GIS based new postal marketing method is presented in this paper with spatiotemporal mining to cope with domestic mail volume decline and to strengthening competitiveness of postal business. Market segmentation technique for socialogy of population and spatiotemporal prediction of consumer propensity to purchase through spatiotemporal multi-dimensional analysis are suggested to provide meaningful and accurate marketing information with customers. Internal postal acceptance & external statistical data of local districts in the Seoul Metropolis are used for the evaluation of geo-lifestyle clustering and spatiotemporal cube mining. Successfully optimal 14 maketing clusters and spatiotemporal patterns are extracted for the prediction of consumer propensity to purchase.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• v.10 no.2
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• pp.349-352
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• 2005

• Journal of Korean Society of Environmental Engineers
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• v.32 no.12
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• pp.1102-1110
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• 2010

Tidal mudflat is a reservoir for diverse microbial resources. Microbial diversity in tidal mudflat sediment can be easily influenced by various human activities. It is necessary to take representative samples to monitor microbial diversity in tidal mudflat sediments. In this study, we analyzed the microbial diversity and chemical characteristics of vegetation and non-vegetation tidal mudflat regions in the Kangwha tidal mudflat using geo-statistics and data-mining. According to the geo-statistical analysis, most correlation range values for the vegetation region were smaller than those for the non-vegetation region, which suggested that the shorter number and interval of sampling are required for the vegetation tidal mudflat environment due to its higher degree of chemical and biological complexity and heterogeneity. The data-mining analysis suggested that the organic content and nitrate were the major environmental factors influencing microbial diversity in the vegetation region while pH and sulfate were the major influencing factors in the non-vegetation region. Using the geo-statistical and data-mining integration approach, we proposed a guideline for determining the sampling interval and number to monitor microbial diversity in tidal mudflat.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.61.1-61.1
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• 2013

In this study we apply Support Vector Machine (SVM) to the prediction of geo-effective halo coronal mass ejections (CMEs). The SVM, which is one of machine learning algorithms, is used for the purpose of classification and regression analysis. We use halo and partial halo CMEs from January 1996 to April 2010 in the SOHO/LASCO CME Catalog for training and prediction. And we also use their associated X-ray flare classes to identify front-side halo CMEs (stronger than B1 class), and the Dst index to determine geo-effective halo CMEs (stronger than -50 nT). The combinations of the speed and the angular width of CMEs, and their associated X-ray classes are used for input features of the SVM. We make an attempt to find the best model by using cross-validation which is processed by changing kernel functions of the SVM and their parameters. As a result we obtain statistical parameters for the best model by using the speed of CME and its associated X-ray flare class as input features of the SVM: Accuracy=0.66, PODy=0.76, PODn=0.49, FAR=0.72, Bias=1.06, CSI=0.59, TSS=0.25. The performance of the statistical parameters by applying the SVM is much better than those from the simple classifications based on constant classifiers.

• Geomechanics and Engineering
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• v.12 no.4
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• pp.723-738
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• 2017

Rock is a heterogeneous material, which introduces complexity in the analysis of rock slopes, since both the existing discontinuities within the rock mass and the intact rock contribute to the degradation of strength. Rock failure is often catastrophic due to the brittle nature of the material, involving the sliding along structural planes and the fracturing of rock bridge. This paper proposes an advanced discretization method of rock mass based on block theory. An in-house software, GeoSMA-3D, has been developed to generate the discrete fracture network (DFN) model, considering both measured and artificial joints. Measured joints are obtained from the photogrammetry analysis on the excavation face. Statistical tools then facilitate to derive artificial joints within the rock mass. Key blocks are searched to provide guidance on potential reinforcement measures. The discretized blocky system is subsequently implemented into a discontinuous deformation analysis (DDA) code. Strength reduction technique is employed to analyze the stability of the slope, where the factor of safety can be obtained once excessive deformation of slope profile is observed. The combined analysis approach also provides the failure mode, which can be used to guide the choice of strengthening strategy if needed. Finally, an illustrated example is presented for the analysis of a rock slope of 20 m height inclined at $60^{\circ}$ using combined GeoSMA-3D and DDA calculation.