• Journal of KIISE
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• v.43 no.8
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• pp.893-901
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• 2016

In Internet of Things (IoT) environments, users are required to search for IoT devices necessary to access services for accomplishing their tasks. As IoT technologies advance, a user task will utilize various types of IoT-based services that are deployed in an IoT environment. Therefore, to accomplish a user task effectively, the services that utilize IoT devices need to be found in a certain geographical region. In addition, the service discovery needs to be accomplished in a stable manner while considering dynamically changing IoT environments. To deal with these issues, we propose two service discovery methods that consider geographic cohesiveness of services in IoT environments. We compare the effectiveness of the proposed methods against a traditional service discovery algorithm that does not consider geographic cohesiveness.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.3-10
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• 2014

Digital maps are made by experts who digitize the data from aerial image and field survey. And the digital maps are updated every 2 years in National Geographic Information Institute. Conventional Digitizing methods take a lot of time and cost. And geographic information needs to be modified and updated appropriately as geographical features are changing rapidly. Therefore in this paper, we modify the digital map updates the road information for rapid high-resolution aerial orthophoto taken at different times were performed HSI color conversion. Road area of the cassification was performed the region growing methods. In addition, changes in the target area for analysis by applying the CVA technique to compare the changed road area by analyzing the accuracy of the proposed extraction.

• Journal of the Speleological Society of Korea
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• no.90
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• pp.35-56
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• 2009

The purpose of this paper is to analyze the implementation of the karst infrastructure systems for the u-cave. IT based u-cave represents spatial information derived fields, such as geographical distribution of the cave boundaries, physical configuration of the cave locations and formation characteristics of the karst history. These three aspects relate to karst infrastructure systems, cave monitoring center and spatial database implementation. In terms of the IT based u-cave infrastructure implementation systems, the u-cave depends on IT contents and spatial features. uIT contents are strongly related to IT839 strategy due to the national agenda is "u-Korea". Cave should contribute to u-cave construction through the spatial analyses methods including USN, RFID, LiDAR, ELD, and GIS technologies. For these methods various cave functions will guide to u-cave's distribution, location, and characteristics of karst. The infrastructure consists of landforms and speleothem facilities, underground related facilities, environmental protection systems, and cave planning. These six units of the cave infrastructures have spatial databases that consist of spatial configuration, such as 4-D in order to draw the spatial distribution of the limestone and lava caves. IT based u-cave system infrastructure implementation should deal with IT convergence to generate fusion affects.

• Spatial Information Research
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• v.19 no.6
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• pp.55-65
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• 2011

All of area we live in has its own geographic names. Even small size of rock under the water has its own name. They are called "marine geographic names". Marine geographic names can be classified two categories. One is a proper name; the other is an attribute name. Rocks, reefs and banks referred in the introduction, belong to the category of the attribute name. And there are certain standards to name marine geographic things. In this study, we conducted a case research with the aims to figure out how we name and use those three features that we consider dangerous factors for marine navigation. This study also focused on differences between the methods used to classify attributes of marine geographic names in the past and today. In addition, it reviewed and analyzed marine geographic names used by Korea Hydrographic and Oceanographic Administration (KHOA) on its own Nautical charts and conducted a case research on marine geographic names notified by Korean Committee on Marine Geographic Names. Based on research and analysis, this study presents future methods regarding marine geographic names standardization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10A
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• pp.784-795
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• 2009

An accurate positioning estimation in the wireless sensor networks (WSN) is very important in which each sensor node is aware of neighbor conditions. The multi-hop positioning estimation technique is considered as one of the suitable techniques for the WSN with many low power devices. However geographical holes, where there is no sensor node, may severely decrease the positioning accuracy so that the positioning error can be beyond the tolerable range. Therefore in this paper, we analyze error factors of DV-hop and hole effect to obtain node's accurate position. The proposed methods include boundary node detection, distance level adjustment, and unreliable anchor elimination. The simulation results show that the proposed method can achieve higher positioning accuracy using the hole detection and enhanced distance calculation methods compared with the conventional DV-hop.

• Journal of the Korean Institute of Landscape Architecture
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• v.13 no.1
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• pp.109-121
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• 1985

A study on the image identification of urban streetscape is valuable for illuminating identity that is not yet fully approached in the field of environmental design. This analysis of urban streetscape for image identification allows us to make a more detailed exploration of an important approaching methods in dealing with the structural characteristics of identity. As a matter of fact, the earlier indirect studies on this image identification were made by environmental designers, such as architectural and urban designer in the field of environmental perception and came to its environmental cognition & environmental pattern research with assistances by such researchers as K. Lynch A. Rapoport & Christopher Alexander. Through its environmental perception research, we can see its structural characteristics that is aesthetic & visual structural contents of physical environmental elements. And we can see its cognitive characteristics through the environmental cognitive research, that is continuity, territoriality, identity of place, uniqueness or individuality, meaning & symbolism. Through its environmental pattern research, we can see its physical, socio - economic, cultural and symbolic pattern identification contents, that is physical form of the city, style of the street, pattern of streetscape, socio- economic & geographical locality, arid life cycle, life style, common style of the behavior, cultural pattern of the activity, socio - cultural expression of the symbol. In these process, we can set up a set of the environmental design criterias from those three integral studies for identity. And for an environmental research, Tongsung-Ro around the CBD (central business district) in Taegu City was selected for a case study, because this streetscape is suitable for that approaching methods in this study.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5223-5227
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• 2016

Background: Cervical cancer is the second most common cancer among women in many populations. While the Pap smear is a well established screening test it suffers from both false-positive and false-negative results in diagnosis of cancers and precancerous states. In this study, immunocytochemistry of the P16 biomarker and HPV-PCR were compared for their diagnostic potential. Materials and methods: In the study, we obtained pairs of specimens from 45 women with cervical dysplasia. One sample was placed in a liquid-based solution, and processed for staining of sections with antibodies to P16. HPV-PCR was performed on the other and the results obtained were analyzed by T-test using SPSS v. 15. Results: Using HPV-PCR 71% of the samples were found to be infected with either HPV 16 or HPV 18, and the rate of infection did not have a statistically significant relationship with higher grades of dysplasia (p= 0.253). In contrast, with immunocytochemistry evaluation of P16, 64% of the specimens were positive, but the percentage of positive results significantly increased with higher grades of dysplasia (p= 0.0001). Conclusion: Employment of the P16 marker as an optional test might be preferable over HPV-PCR for cervical dysplasia in our geographical region.

• Journal of The Korea Institute of Healthcare Architecture
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• v.27 no.2
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• pp.39-48
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• 2021

Purpose: The study aims to demonstrate regional diagnosis methods and results combined with geographical information to expand the physical infrastructure related to community care services. To this end, the physical infrastructure for the core elements of community care was analyzed in terms of the fulfilment and access of facilities to derive the underserved elements and regions. Methods: Utilizes GIS network analysis techniques that can derive physical infrastructure service areas. Underserved elements are derived by comparing and analyzing the service area for each core element. Next, the underserved regions for each core element are derived through the overlapping of the set service area and the diagnosis population. Results: Among the physical infrastructure by core elements for community care, the housing support element was considerably weak, and the nursing care facility compared to health care was also analyzed to be weak. In addition, underserved regions by dong in Mapo-gu were deduced and presented for each diagnosed population. Implications: The discovery of underserved elements and underserved regions is meaningful as a diagnostic process that can derive the physical infrastructure that needs to be expanded urgently for the realization of community care and determine the priority projects and targets of the projects.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.135-142
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• 2022

Recently, with the development of data processing technology and the increase of computational power, methods to solving social problems using Artificial Intelligence (AI) are in the spotlight, and AI technologies are replacing and supplementing existing traditional methods in various fields. Meanwhile in Korea, heavy rain is one of the representative factors of natural disasters that cause enormous economic damage and casualties every year. Accurate prediction of heavy rainfall over the Korean peninsula is very difficult due to its geographical features, located between the Eurasian continent and the Pacific Ocean at mid-latitude, and the influence of the summer monsoon. In order to deal with such problems, the Korea Meteorological Administration operates various state-of-the-art observation equipment and a newly developed global atmospheric model system. Nevertheless, for precipitation nowcasting, the use of a separate system based on the extrapolation method is required due to the intrinsic characteristics associated with the operation of numerical weather prediction models. The predictability of existing precipitation nowcasting is reliable in the early stage of forecasting but decreases sharply as forecast lead time increases. At this point, AI technologies to deal with spatio-temporal features of data are expected to greatly contribute to overcoming the limitations of existing precipitation nowcasting systems. Thus, in this project the dataset required to develop, train, and verify deep learning-based precipitation nowcasting models has been constructed in a regularized form. The dataset not only provides various variables obtained from multiple sources, but also coincides with each other in spatio-temporal specifications.

• Journal of the Korean Geographical Society
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• v.44 no.2
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• pp.122-145
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• 2009

Terrain parameters calculated from digital elevation models (DEM) have become increasingly important in current spatially distributed models of earth surface processes. This paper investigated how the ability of upslope area for predicting the spatial distribution of soil properties varies depending on the selection of spatial resolutions of DEM and algorithms. Four soil attributes from eight soil-terrain data sets collected from different environments were used. Five different methods of calculating upslope area were first compared for their dependency on different grid sizes of DEM. Multiple flow algorithms produced the highest correlation coefficients for most soil attributes and the lowest variations amongst different DEM resolutions and soil attributes. The high correlation coefficient remained unchanged at resolutions from 15 m to 50 m. Considering decreasing topographical details with increasing grid size, we suggest that the size of 15-30 m may be most suitable for soil-landscape analysis purposes in our study areas.