• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.180-180
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• 2015

Weather radar has been widely used in measuring precipitation and discharge and predicting flood risks. The radar rainfall estimate has one of the essential problems in terms of uncertainty and accuracy. Previous study analyzed radar errors to reduce its uncertainty or to improve its accuracy. Furthermore, a recent analyzed the effect of radar error on rainfall-runoff using spatial error model (SEM). SEM appropriately reproduced radar error including spatial correlation. Since the SEM does not take the time dependence into account, its time variability was not properly investigated. Therefore, in the current study, we extend the SEM including time dependence as well as spatial dependence, named after Spatial-Temporal Error Model (STEM). Radar rainfall events generated with STEM were tested so that the peak runoff from the response of a basin could be investigated according to dependent error. The Nam River basin, South Korea, was employed to illustrate the effects of STEM on runoff peak flow.

• Journal of the Korean Mathematical Society
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• v.49 no.6
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• pp.1163-1174
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• 2012

This paper examines a temperature dependent Stokes flow in a semi-infinite cylinder. Under appropriate initial and boundary conditions the author establishes exponential decay of solutions in energy norm with distance from the finite end of the cylinder.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.225-231
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• 2014

When a spatial regression model that uses kernel density values as a dependent variable is applied to retail business data, a unique model cannot be selected because kernel density values change following kernel bandwidths. To overcome this problem, this paper suggests how to use the point pattern analysis, especially the L-index to select a unique spatial regression model. In this study, kernel density values of retail business are computed by the bandwidth, the distance of the maximum L-index and used as the dependent variable of spatial regression model. To test this procedure, we apply it to meeting room business data in Seoul, Korea. As a result, a spatial error model (SEM) is selected between two popular spatial regression models, a spatial lag model and a spatial error model. Also, a unique SEM based on the real distribution of retail business is selected. We confirm that there is a trade-off between the goodness of fit of the SEM and the real distribution of meeting room business over the bandwidth of maximum L-index.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• Molecules and Cells
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• v.43 no.7
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• pp.591-599
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• 2020

Complex cell-to-cell communication underlies the basic processes essential for homeostasis in the given tissue architecture. Obtaining quantitative gene-expression of cells in their native context has significantly advanced through single-cell RNA sequencing technologies along with mechanical and enzymatic tissue manipulation. This approach, however, is largely reliant on the physical dissociation of individual cells from the tissue, thus, resulting in a library with unaccounted positional information. To overcome this, positional information can be obtained by integrating imaging and positional barcoding. Collectively, spatial transcriptomics strategies provide tissue architecture-dependent as well as position-dependent cellular functions. This review discusses the current technologies for spatial transcriptomics ranging from the methods combining mechanical dissociation and single-cell RNA sequencing to computational spatial re-mapping.

• Korean Institute of Interior Design Journal
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• v.15 no.6 s.59
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• pp.120-130
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• 2006

This study is about objectified spatial composition. The Interior Design field has grown and established its major trends dependent upon other related field of study. With this perspective in mind, esthetics on Interior Design has to be treated in similar manner. In modem architects or fine artists have defined the terminology 'objectification' theoretical principle where by unable to distinguish between 'object's type' and 'objects', Presently, the term 'objectified' became a trend word. In order to confront misconception of the idea of 'objectification', some people define as reflection of this complex society. There are five types in expression of objectified spatial composition in Interior Design. Which are free form spatial composition through artistry of artists, fantastic spatial composition by polysemous collision, symbolic spatial composition from the metaphorical of form, aggregate spatial composition by geometric collision and geometric superimposition, and cultural spatial composition. Therefore, this study aims to help understanding of tendency in various space expressions in Interior Design through searching how to express type of objectified spatial composition in Interior Design from 2000 through 2005.

• The Korean Journal of Ecology
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• v.23 no.3
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• pp.241-253
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• 2000

The degree to which microenvironmental factors are linked to spatial patterns of vegetational factors within ecosystems has important consequences for our understanding of how ecosytems are structured and for conservation of rare species in ecosystems. We studied this relationships between the spatial patterns of microenvironmental factors and vegetational factors in temperate hardwood forest in Mt. Jumbong Biological Reserve Area, Korea. To do this, environmental and vegetational factors from 196 micropoints in a 0.49 ha plot were investigated. Most of all environmental factors and vegetational factors showed the variations among micropoints. Microtopographic factors, litter depth, soil moisture content and relative light intensity at this site were spatially dependent at a scale of 14∼62 m. Coverage of tree and shrub layer and species diversity of herb layer in autumn were spatially dependent at a scale of < 15 m. Species richness and species diversity of herb layer in spring and species richness of herb layer in autumn were spatially dependent at a scale of 28∼48 m. Multiple regression analysis showed that spatial patterns of species richness and species diversity of herb layer in spring and autumn were affected by litter depth, slope, subtree layer, shrub, Sasa borealis etc. The best predictor for the spatial patterns of species richness and species diversity of herb layer at this site was the spatial pattern of litter depth. Species richness and species diversity of herb layer showed strongly negative correlation with litter depth. We estimate that the spatial pattern of litter depth at this site were affected by direction of wind, microtopography and spatial pattern of shrub layer.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1320-1326
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• 2002

In a one-dimensional heat conduction domain with heated and insulated walls, an integral approach is proposed to estimate time-dependent boundary heat flux without internal measurements. It is assumed that the expression of the heat flux is not known a priori. Hence, the present inverse heat conduction problem is classified as a function estimation problem. The spatial temperature distribution is approximated as a third-order polynomial of position, whose four coefficients are determined from the heat fluxes and the temperatures at both ends at each measurement. After integrating the heat conduction equation over spatial and time domain, respectively, a simple and non-iterative recursive equation to estimate the time-dependent boundary heat flux is derived. Several examples are introduced to show the effectiveness of the present approach.

• Korean Journal of Optics and Photonics
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• v.13 no.5
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• pp.408-413
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• 2002

We demonstrated a polarization dependent type 2$\times$2 optical switch, using a binary reflection type SLM. Reflection type FLC was used as a half wave retardation plate. Two inputs were controlled by each SLM for the desired output direction. In conclusion, in the "1" state the average optical loss was 6.6 ㏈, and in the "0" state the average optical loss was 14.6 ㏈, and measured the switching speed as 75 $mutextrm{s}$. By using this method, a polarization dependent type 2$\times$2 optical switch can be demonstrated and the possibility of a 4-port WDM optical switch also verified.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.95-100
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• 2010

This paper proposes a new spatial regularization of Fisher linear discriminant analysis (LDA) to reduce the overfitting due to small size sample (SSS) problem in face recognition. Many regularized LDAs have been proposed to alleviate the overfitting by regularizing an estimate of the within-class scatter matrix. Spatial regularization methods have been suggested that make the discriminant vectors spatially smooth, leading to mitigation of the overfitting. As a generalized version of the spatially regularized LDA, the proposed regularized LDA utilizes the non-uniformity of spatial correlation structures in face images in adding a spatial smoothness constraint into an LDA framework. The region-dependent spatial regularization is advantageous for capturing the non-flat spatial correlation structure within face image as well as obtaining a spatially smooth projection of LDA. Experimental results on public face databases such as ORL and CMU PIE show that the proposed regularized LDA performs well especially when the number of training images per individual is quite small, compared with other regularized LDAs.