• Journal of the Korean Geographical Society
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• v.43 no.4
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• pp.526-543
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• 2008

Based on the social network analysis(SNA), this study examines the structural and spatial characteristics of the actor networks of the manufacturing industries for the elderly. In the field of economic geography, former researches on network have mainly focused on the network governance. However, this study focused on the social network analysis. Centrality indexes are used to analyze the topological structure of actor networks of firms and organizations. In order to investigate the spatial structure of actor networks, not only the regional distribution of actors but also the correlation between centrality index and distance are analyzed. Network matrixes among actors are transformed to network matrixes among regions using block modeling method to reveal the spatial characteristics of the actor networks. In spite of the importance of the Capital Region, networks in the non-Capital Region like Chungnam and Pusan were showed high network density. This suggested that some kinds of policy project operating in the non-Capital Region had the influence on this network in the initial stage of industry.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.117-122
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• 1994

In this paper, we discuss the modeling of flexible manipulators. In the modeling of flexible manipulators, there are two approaches: one is based on the distributed-parameter modeling and the other on the lumped-parameter modeling. The former has been applied to control and analysis of simple manipulator requiring precision, while the latter has been applied to multi-link spatial manipulator, because of the model's simplicity. We have already proposed the lumped-parameter modeling method for simple manipulator, and investigate that model of how much degree of precision we can get. The experiments and simulations are performed, comparing these results, the approximate performance of our modeling method is discussed.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.16-41
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• 2020

Geospatial input setting to represent the reality of spatial distribution or quantitative property within model has become a major interest in earth system simulation. Many studies showed the variation of grid resolution could lead to drastic changes of spatial model results because of insufficient surface property estimations. Hence, in this paper, the authors proposed Monte Carlo Integration (MCI) to apply spatial probability (SP) in a spatial-sampling framework using a three-dimensional point cloud (3DPC) to keep the optimized spatial distribution and area/volume property of buildings in urban area. Three different decision rule based building identification results were compared : SP threshold, cell size, and 3DPC density. Results shows the identified building area property tend to increase according to the spatial sampling grid area enlargement. Hence, areal building property manipulation in the sampling frameworks by using decision rules is strongly recommended to increase reliability of geospatial modeling and analysis results. Proposed method will support the modeling needs to keep quantitative building properties in both finer and coarser grids.

• Journal of Korean Association for Spatial Structures
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• v.7 no.2 s.24
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• pp.115-124
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• 2007

The initial shape is arrived at by a self-formation process, which accomplishes a form in the natural world, or is determined analytically by considering the equilibrium of initial stress only. Therefore, the self-formation process, which accomplishes a form in the natural world is grasped and the types of modeling techniques available to find the shapes of soft structures are well investigated and classified. To establish a form-finding modeling techniques, the models of string, soap film, fabric, rubber, plaster, and etc. are used. These modeling techniques can be used as a method of understanding the characteristics of structures when the material of model shows similar characteristics. Generally, the model test confirms the structure based on numerical analysis, at the same time it is important preceding process to develop such a program. With the above process, the relationship between model test and numerical analysis becomes a feedback process. Therefore, in this study, two examples which have been accomplished from such a technique are investigated and considered according to modeling process.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1047-1051
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• 2004

The design storm is a crucial element in urban drainage design and hydrological modeling. The total rainfall depth of a design storm is usually estimated by hydrological frequency analysis using historic rainfall records. The different geostatistical approaches (ordinary kriging, universal kriging) have been used as estimators and their results are compared and discussed. Variogram parameters, the sill, nugget effect and influence range, are analysis. Kriging method was applied for developing contour maps of design storm depths In bocheong stream basin. Effect to utilize weather radar data and grid-based basin model on the spatial variation characteristics of storm requires further study.

• Korean Journal of Geomatics
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• v.1 no.1
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• pp.85-93
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• 2001

Geospatial database, which is the basis for Geo-Spatial Information Systems, is produced by conventional mapping methods. Recently, with increased demand for digital forms of the geospatial database, studies are carried out to automate its production. The automated mapping system is composed of the image acquisition subsystem, positioning subsystem, point referencing subsystem and the visualization subsystem. The image acquisition subsystem is the most important part of the overall production line because it is the starting point and will affect all subsequent processes. This paper presents a software analysis and design of the image acquisition subsystem. The design was carried out using the Unified Modeling Language which is a modeling method used extensively in the software engineering field.

• Spatial Information Research
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• v.17 no.3
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• pp.277-285
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• 2009

Each system should have a suitable data model about their purpose for efficiently managing, analyzing, and manipulating data. And the usable range of application is determined by the data model, and suitable data models are being developed for each application. In GIS, diversity spatial data model is being developed too. The accuracy and update of the spatial data would be important for applying efficient application as well as the data modeling is important as constructing the spatial data structure. Therefore, the purposes of this research are to 1)compare domestic spatial data models with oversea spatial data models about their geometry model, topology model and visualizing method of 3D spatial data 2)to compare the features of the data model by analyzing each data structures. We 3)compare and analyze features of each spatial data models via the quantitative analysis of each spatial data models.

• Journal of Korea Spatial Information System Society
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• v.10 no.1
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• pp.51-63
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• 2008

Previous studies for routing In USN (Ubiquitous Sensor Networks) appear to be unreliable due to the dependence on non-spatial data and the lack of map overlay analysis. Multiple spatial parameters and radio propagation modeling techniques were integrated to derive RSSI (Received Signal Strength Indicator) value between route nodes and produce a highly reliable path map. It was possible to identify area-wide patterns of USN route subject to many different Influences (e.g. the specific effects of radio blocking factors such as the visible area, road area, cell duplicated area, and building density), which cannot be acquired by traditional non-spatial modeling. The quantitative evidence concerning the USN route for individual cell as well as entire study area would be utilized as major tools to visualize paths in real-time and to select alternative path when failure or audition of route node occurs.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.461-471
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• 2012

The purpose of this paper is to visualize the housing market dynamics with ESDA (Exploratory Spatial Data Analysis) using MATLAB toolbox, in terms of the modeling housing market dynamics in the Busan Metropolitan City. The data are used the real housing price transaction records in Busan from the first quarter of 2006 to the second quarter of 2009. Hedonic house price model, which is not reflecting spatial autocorrelation, has been a powerful tool in understanding housing market dynamics in urban housing economics. This study considers spatial autocorrelation in order to improve the traditional hedonic model which is based on OLS(Ordinary Least Squares) method. The study is, also, investigated the comparison in terms of $R^2$, Sigma Square(${\sigma}^2$), Likelihood(LR) among spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), and SAC(General Spatial Models). The major finding of the study is that the SAR, SEM, SAC are far better than the traditional OLS model, considering the various indicators. In addition, the SEM and the SAC are superior to the SAR.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.589-593
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• 2013

Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.