• Journal of the Korean Geotechnical Society
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• v.25 no.12
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• pp.13-25
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• 2009

In this paper, a numerical procedure of probabilistic slope stability analysis that considers the spatial variability of soil properties is presented. The procedure extends the deterministic analysis based on the limit equilibrium method of slices to a probabilistic approach that accounts for the uncertainties and spatial variation of the soil parameters. Making no a priori assumptions about the critical failure surface like the Random Finite Element Method (RFEM), the approach saves the amount of solution time required to perform the analysis. Two-dimensional random fields are generated based on a Karhunen-Lo$\grave{e}$ve expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty caused by the spatial heterogeneity on the stability of slope. The results show that the proposed method can efficiently consider the various failure mechanisms caused by the spatial variability of soil property in the probabilistic slope stability assessment.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1748-1753
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• 2003

3D-PTV measurement was conducted on the wake of a sphere. The Reynolds number is 1130 with the diameter(d=30mm). The measurement system consisted of three CCD cameras, an image grabber, an Ar-Ion laser and a host computer. An eigenvalue analysis was introduced for the analysis on the wake. Statistical turbulent properties were quantitatively clarified using the time-consecutive instantaneous three-dimensional vectors obtained by the 3D-PTV system. The spatial distributions of the sphere wake showed strong relations with spiral motions of the vortcies shedded from the surface of the sphere.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.245-257
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• 2022

Water quality characteristics and their spatial variations in the Nakdong River were statistically analyzed by multivariate techniques including correlation analysis, CA, and FA/PCA based on water quality parameters for 17 sites over 2017-2019, yielding PI values for primary factors. Site 10 indicated the highest parameter concentrations, and results of pearson's correlation analysis suggest that non-biodegradable organic matter had been distributed on the site. Five clusters were identified in order of descending pollution levels: I (Ib > Ia) > II (IIa > IIb) > III. Spatial variations started from sub-cluster Ib in which Daegu city and Geumho-river are joined. T-P, PO4-P, SS, COD, and TOC corresponded to VF 1 and 2, which were found to be principal components with strong influence on water quality. Sub-cluster Ib was strongly influenced by NO3-N and T-N compared to other clusters. According to the PIs, water quality pollution deteriorated due to non-biodegradable organic matter, nitrogen- and phosphorus-based nutrient salts in the middle and lower reaches, illustrating worsening water pollution due to inflows of anthropogenic sources on the Geumho-river, i.e., sewage and wastewater, discharged from Site 10, at which there is a concentration of urban, agricultural, and industrial areas.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.2
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• pp.71-77
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• 2007

Advance of neuroimaging technique has greatly influenced recent brain research field. Among various neuroimaging modalities, positron emission tomography has played a key role in molecular neuroimaging though functional MRI has taken over its role in the cognitive neuroscience. As the analysis technique for PET data is more sophisticated, the complexity of the method is more increasing. Despite the wide usage of the neuroimaging techniques, the assumption and limitation of procedures have not often been dealt with for the clinician and researchers, which might be critical for reliability and interpretation of the results. In the current paper, steps of voxel-based statistical analysis of PET including preprocessing, intensity normalization, spatial normalization, and partial volume correction will be revisited in terms of the principles and limitations. Additionally, new image analysis techniques such as surface-based PET analysis, correlational analysis and multimodal imaging by combining PET and DTI, PET and TMS or EEG will also be discussed.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.161-175
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• 2022

Oscillatory magnetic fields produced in the brain due to neuronal activity can be measured by the sensor. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution, which gives information about the brain's functional activity. Potential utilization of high spatial resolution in MEG is likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in some diseases under resting state or task state. This review is a comprehensive report to introduce statistical models from MEG data including graphical network modelling. It is also meaningful to note that statisticians should play an important role in the brain science field.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.557-558
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• 2013

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.87-97
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• 2024

This study analyzed the water shortage hotspot areas in South Korea using spatial clustering analysis for water shortage estimates in 2030 of the Master Plans for National Water Management. To identify the water shortage cluster areas, we used water shortage data from the past maximum drought (about 50-year return period) and performed spatial clustering analysis using Local Moran's I and Getis-Ord Gi*. The areas subject to spatial clusters of water shortage were selected using the cluster map, and the spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The results indicated that one cluster (lower Imjin River (#1023) and neighbor) in the Han River basin and two clusters (Daejeongcheon (#2403) and neighbor, Gahwacheon (#2501) and neighbor) in the Nakdong River basin were found to be the hotspot for water shortage, whereas one cluster (lower Namhan River (#1007) and neighbor) in the Han River Basin and one cluster (Byeongseongcheon (#2006) and neighbor) in the Nakdong River basin were found to be the HL area, which means the specific area have high water shortage and neighbor have low water shortage. When analyzing spatial clustering by standard watershed unit, the entire spatial clustering area satisfied 100% of the statistical criteria leading to statistically significant results. The overall results indicated that spatial clustering analysis performed using standard watersheds can resolve the variable spatial unit problem to some extent, which results in the relatively increased accuracy of spatial analysis.

• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.291-298
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• 2005

This paper is an analysis of the Category Individual Residence urban spatial structure along the National Route 20 (Koushu-Kaido), one of the major roads in Japan, and the degree of differences between locations and its changes between the points of time. The analysis was based on the GIS technique. Whilst, previous studies were based on municipal boundaries or mesh units as sources of data, GIS allowed the use of variable geographical units, Roadside zone, Inner zone, North zone, South zone, Blocks. As an example to apply the technology of GIS, 1986's sand 1991's building polygon data of the Urban Planning Bureau of Tokyo Metropolitan Government are used. The layers referred to the analyses is the building polygons with the amount of stories, building area, floor area and the material of the building. Two statistical analysis are executed; one is the test of the regional equality about the number of story of building, building area, floor area and fireproof building ratio.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.21-30
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• 2014

Lately, new influentials have secured a large number of volunteers on social networks due to vitalization of various social media. There has been considerable research on these influential people in social networks but the research has limitations on location information of Location Based Social Network Service(LBSNS). Therefore, the purpose of this study is to propose a spatial detection methodology and application plan for influentials who make comments about diverse social and cultural issues in LBSNS using spatial statistical analysis methods. Twitter was used to collect analysis object data and 168,040 Twitter messages were collected in Seoul over a month-long period. In addition, 'politics,' 'economy,' and 'IT' were set as categories and hot issue keywords as given categories. Therefore, it was possible to come up with an exposure index for searching influentials in respect to hot issue keywords, and exposure index by administrative units of Seoul was calculated through a spatial joint operation. Moreover, an influential index that considers the spatial dependence of the exposure index was drawn to extract information on the influential areas at the top 5% of the influential index and analyze the spatial distribution characteristics and spatial correlation. The experimental results demonstrated that spatial correlation coefficient was relatively high at more than 0.3 in same categories, and correlation coefficient between politics category and economy category was also more than 0.3. On the other hand, correlation coefficient between politics category and IT category was very low at 0.18, and between economy category and IT category was also very weak at 0.15. This study has a significance for materialization of influentials from spatial information perspective, and can be usefully utilized in the field of gCRM in the future.

• Journal of Wetlands Research
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• v.14 no.2
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• pp.243-254
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• 2012

Recently, the use of radar rainfall data that can help tracking of the development and movement of rainfall's spatial distribution is drawing much attention in hydrology. The reliability of existing radar rainfall compared to gauge rainfall data on the ground has not yet been confirmed and so we have difficulties to apply the radar rainfall in hydrology. The radar rainfall for the applications in hydrology are adjusted merging method derived from gage. This study uses the Mean-Field Bias (MFB) and Statistical Objective Analysis (SOA) as correction methods to create adjusted grid-based radar rainfall data which can represent the temporal and spatial distribution of rainfall. This study used a storm event occurred in August 2010 for the adjustment of radar rainfall. In addition, the grid-based distributed rainfall-runoff model (Vflo), which enables more detailed examinations of spatial flux changes in the basin rather than the lumped hydrological models, has been applied to Gamcheon river basin which is a tributary of Nakdong River located in south-eastern part of the Korean peninsular and the basin area is $1005km^2$. The simulated runoff was compared with the observed runoff in an attempt to evaluate the usability of radar rainfall data and the reliability of the correction methods. The error range of peak discharge using each correction method was within 20 percent and the efficiency of the model was between 60 and 80 percent. In particular, the SOA method showed better results than MFB method. Therefore, the SOA method could be used for the adjustment of grid-based radar rainfall and the adjusted radar rainfall can be used as an input data of rainfall-runoff models.