• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.175-186
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• 2003

Mobile clients like a PDA need a cache and a spatial index to search and access map data efficiently. When a server transmits spatial objects to a mobile client which has a low storage capacity, some of them can be duplicated in a cache of the mobile client. Moreover, the cost for strong added data in the cache and reconfiguring spatial index is very high in the mobile client with low computing power. The scheme for processing duplicated objects and disturbing tasks of the mobile client which has low computing power is needed. In this paper, we classfy the method for strorng duplicated objects and present the scheme for the both caching objects and reconfiguring a spatial index of cached objects using the clipping technique. We propose the caching system based on an agent in order to distribute the overhead of a mobile client as well as to provide efficiently map services. We design and implement it, and evaluate the performance.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.125-137
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• 2004

In case of using image sequence taken from a moving camera along a road in an urban area, general video mosaicing technique based on a single baseline cannot create 2-D image mosaics. To solve the drawback, this paper proposed a new image mosaicing technique through 3-D multi-baselines that can create image mosaics in 3-D space. The core of the proposed method is that each image frame has a dependent baseline, an equation of first order, calculated by using ground control point (GCP) of optical flows. The proposed algorithm consists of 4 steps: calculation of optical flows using hierarchical strategy, calculation of camera exterior orientation, determination of multi-baselines, and seamless image mosaics. This paper realized and showed the proposed algorithm that can create efficient image mosaics in 3-D space from real image sequence.

• Korea Real Estate Review
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• v.24 no.1
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• pp.7-14
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• 2014

This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.

• Journal of Environmental Health Sciences
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• v.45 no.5
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• pp.487-496
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• 2019

Objective: The purpose of this study was to create soil contamination maps using QGIS (Quantum Geographic Information System) and suggest selection methods for soil pollution sources for preferential investigation in a soil contamination survey. Method: Data from soil contamination surveys over five years in Gyeonggi-do Province, South Korea (2013-2017) were used for making soil contamination maps and analyzing the density of survey points. By analyzing points exceeding the concern level of soil contamination, soil pollutant sources for priority management were identified and selection methods for preferred survey points were suggested through a study of the model area. Results: A soil contamination survey was conducted at 1,478 points over five years, with the largest number of surveys conducted in industrial complex and factory areas. Soil contamination maps for copper, zinc, nickel, lead, arsenic, fluoride, and total petroleum hydrocarbons were made, and most of the survey points were found to be below concern level 1 for soil contamination. The density of the survey points is similar to that of densely populated areas and factory areas. The analysis results of points exceeding the criteria showed that soil pollutant sources for priority management were areas where ore and scrap metals were used and stored, traffic-related facilities areas, industrial complex and factory areas, and areas associated with waste and recycling. According to the study of the model area, the preferred survey points were traffic-related facilities with 15 years or more since their construction and factories with a score of 10 or more for soil contamination risk. Conclusion: Soil contamination surveys should use GIS for even regional distribution of survey points and for the effective selection of preferred survey points. This study may be used as guidelines to select points for a soil contamination survey.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.6
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• pp.426-432
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• 2021

Injection molding is used in many industrial fields such as home appliances, vehicle parts, and electronic device parts because various resins can be molded, leading to mass production of complex shapes. Generally, the empirical prediction method is used to set the initial processing conditions of injection molding. However, this approach requires a lot of cost and its presented solution is not accurate. In this paper, injection molding was simulated through the Moldflow^TM in order to manufacture the spacer for gas insulated switch. Through the simulation, the flow of the resin with respect to the diameter of the inlet was analyzed. It was found that the process was possible at a higher resin temperature as the diameter of the inlet increased. In addition, through thermal analysis during injection of the resin, it was confirmed that a stagnation phenomenon occurred at the insert portion during injection molding, and the temperature of the resin was higher than that of the mold. As in this paper, if the spacer is manufactured by optimizing the injection hole and the temperature of the injection process based on simulation, it is expected that the spacer can be manufactured with high productivity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.119-127
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• 2019

In this study, we investigated the application of deep learning to the manufacturing process of traffic and road signs which are constituting the road layer in map production with 1 / 1,000 digital topographic map. Automated classification of road traffic sign images was carried out through construction of training data for images acquired by using transfer learning which is used in image classification of deep learning. As a result of the analysis, the signs of attention, regulation, direction and assistance were irregular due to various factors such as the quality of the photographed images and sign shape, but in the case of the guide sign, the accuracy was higher than 97%. In the digital mapping, it is expected that the automatic image classification method using transfer learning will increase the utilization in data acquisition and classification of various layers including traffic safety signs.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.185-195
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• 2018

In the Seoul Metropolitan City, the PM(pariculate matter) application used by the citizens provides the PM concentration of the nearest monitoring stations located on the PM monitoring stations. Currently, the selecting method of the PM monitoring network considered by the Ministry of Environment is based on considering the monitoring station distribution and population density only. In this study, we analyzed the distance between PM monitoring station and the administrative center point in addition to the above considerations. The number of test sites was verified and the range of coverage of each monitoring stations was indicated by using the Voronoi algorithm and hexagon grid. The spatial position problem of the PM monitoring station was suggested by spatial data analysis. The variables of spatial data analysis are single-family houses, apartments, $1^{st}$ class neighborhood, $2^{nd}$ class neighborhood, garbage disposal plant, hazardous material disposal facility, factory, and the density map. The analysis result of the selection criterion considering the additional variables for new PM monitoring stations was presented, in addition to the selection criteria provided by the Ministry of Environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.525-534
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• 2018

Camera calibration is the process of determining the parameters such as the focal length of a camera, the position of a principal point, and lens distortions. For this purpose, images of checkerboard have been mainly used. When targets were automatically recognized in checkerboard image, the existing studies had limitations in that the user should have a good understanding of the input parameters for recognizing the target or that all checkerboard should appear in the image. In this study, a methodology for automatic target recognition was proposed. In this method, even if only a part of the checkerboard image was captured using rectangles including eight blobs, four each at the central portion and the outer portion of the checkerboard, the index of the target can be automatically assigned. In addition, there is no need for input parameters. In this study, three conditions were used to automatically extract the center point of the checkerboard target: the distortion of black and white pattern, the frequency of edge change, and the ratio of black and white pixels. Also, the direction and numbering of the checkerboard targets were made with blobs. Through experiments on two types of checkerboards, it was possible to automatically recognize checkerboard targets within a minute for 36 images.

• Journal of Korean Society of Rural Planning
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• v.25 no.3
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• pp.59-66
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• 2019

This study saw developed to build a landscape monitoring methodology by simulation of landscape effect prediction. A Visual landscape planning and management system has been introduced and implemented by each ministry so as to solve the problems of visual landscape destruction due to recognition on the value of natural landscape of beautiful territory and various development projects. At present, this system emphasizes the importance of the visual and perceptual aspect of the landscape however, there is a lack of techniques required for comprehensively predicting, evaluating, and managing it. Furthermore, sustainable landscape management after the completion of development projects has been inadequately carried out, as the focus has been only on consultation in the planning process of the development project in institutional performance. The viewpoint for judging the change in the visual landscape of the development plan and development project should be selected as the effective point where the development project is expected to result in a remarkable landscape change. As for the method of selecting effective viewpoints, the main viewpoints are selected by analyzing the visible area of the target viewpoint. When selecting the viewpoint centered on the viewpoint target, it was judged that it is possible to reduce the procedure of selecting and checking the existing preliminary viewpoints and widening the effective visible range. The proposed visual landscape monitoring is expected to be able to solve the existing institutional problems, and to be used when the implementers and authors of the development projects review the effects on the landscape.

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.105-112
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• 2019

Due to abnormal high temperature, electric power demand has exceeded the backup power reserved for emergency case, hence, resulting in a major power outage. In today's overcrowded cities, the unexpected disruption in energy supply and demand is a major threat to the enormous economic damage and urban malfunctions. Existing methods for estimating the demand of the emergency power source do not lend themselves to predict the actual demand in the spatial dimension of the city. In addition, the reserve power is arbitrarily distributed in the case of emergency. This paper presents a method that predicts the emergency power demand using the spatial distribution of emergency power demand by applying the daily energy consumption intensity and emergency power demand according to urban spatial information and building use.