• The Korean Journal of Nuclear Medicine
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• v.37 no.3
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• pp.162-170
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• 2003

The probabilistic anatomical maps are used to localize the functional neuro-images and morphological variability. The quantitative indicator is very important to inquire the anatomical position of an activated legion because functional image data has the low-resolution nature and no inherent anatomical information. Although previously developed MNI probabilistic anatomical map was enough to localize the data, it was not suitable for the Korean brains because of the morphological difference between Occidental and Oriental. In this study, we develop a probabilistic anatomical map for Korean normal brain. Normal 75 blains of T1-weighted spoiled gradient echo magnetic resonance images were acquired on a 1.5-T GESIGNA scanner. Then, a standard brain is selected in the group through a clinician searches a brain of the average property in the Talairach coordinate system. With the standard brain, an anatomist delineates 89 regions of interest (ROI) parcellating cortical and subcortical areas. The parcellated ROIs of the standard are warped and overlapped into each brain by maximizing intensity similarity. And every brain is automatically labeledwith the registered ROIs. Each of the same-labeled region is linearly normalize to the standard brain, and the occurrence of each legion is counted. Finally, 89 probabilistic ROI volumes are generated. This paper presents a probabilistic anatomical map for localizing the functional and structural analysis of Korean normal brain. In the future, we'll develop the group specific probabilistic anatomical maps of OCD and schizophrenia disease.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.2 s.4
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• pp.43-53
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• 1994

GSIS(geo-spatial information system), particularly when utilized in hazard management decision, is one of hazard analysis tool. Data of GSIS input from digitizing or scanning of map or aerial photos. This paper focuses upon the hazard prediction in GSIS and RS analysis to assess map, aerialphotos, satellite imagery and soil map. This study found computation of hazard area analysis. the results is formed as raster data model of quadtree. Authors knew more accurate results of overlay. This paper shows building up integrated data base as well as search of hazard area in aerial photographs.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.1-17
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• 1997

Geographic Information Systems(GIS) are very useful for spatial analysis and policy in local government administration. Recognizing the value of GIS, Chungnam province authorities put a spur on the introduction and development of it. But they have some difficulty in this process because of technical restraint, expertise shortage and budget limit. This study has surveyed current achievement and conditions for GIS development and presented general framework and subordinate tasks to build up GIS. First of all, there are a few prior conditions to guarantee the success of GIS: First, we should set up reasonable long-term plan and follow systematic procedures according to the plan. Second, it is essential to clarify what initiatively manage to whole business and so we should make up GIS-Board as an institutional center for this job. Third, we must research how to take advantage of already existing NGIS(National Geographic Information System), so that we may eliminate redundancy of investment. We can save a lot of finance and human resources through it. Fourth, we must focus on the importance of accurate mapping by utilizing new technology like GPS(Global Positioning System). Fifth, we should arrange efficient training program to constantly produce excellent human resources for GIS.

• Annual Conference of KIPS
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• 2004.11a
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• pp.653-656
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• 2004

교육인적자원부의 ${\ulcorner}$초${\cdot}$중등학교 정보통신기술 교육 운영지침${\lrcorner}$에 따르면 각 교과 수업 시간에 ICT 활용 교육이 $10\%$이상 반영되도록 적극 권장하고 있다. 이에 따라 각급 학교에서는 전통적인 학습 지도안과 ICT 활용 교수-학습 과정안의 두 가지 형태를 병행하여 사용하고 있으나 작성 도구와 형식이 다양하여 교사들 상호간의 문서 공유와 재사용성이 떨어지며 웹 상에서 정확한 검색이 어렵다. 본 논문에서는 한국교육학술정보원에서 제시하고 있는 ICT 활용 교수-학습 과정안의 모형을 토대로 공통 DTD를 설계하고 데이터베이스와 연동하여 표준화된 XML 문서를 생성함으로써 교사들 상호간의 공유 및 재사용성을 높이고 정확한 검색이 이루어지도록 하였다. 또한 유선 인터넷 서비스와 동시에 무선 인터넷 환경에서도 WML을 이용하여 모바일 서비스가 가능하도록 구현되어 있어 보다 향상된 교수-학습 환경을 제공할 수 있다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.523-533
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• 2014

It has been spent too much time to figure out the incident route when we are facing computer security incident. The incident often recurs moreover the damage is expanded because critical clues are lost while we are wasting time with hesitation. This paper suggests to build a Digital Evidence Map (DEM) in order to find out the incident cause speedy and accurately. The DEM is consist of the log chain which is a mesh relationship between machine data. And the DEM should be managed constantly because the log chain is vulnerable to various external facts. It could help handle the incident quickly and cost-effectively by acquainting it before incident. Thus we can prevent recurrence of incident by removing the root cause of it. Since the DEM has adopted artifacts in data as well as log, we could make effective response to APT attack and Anti-Forensic.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.37-45
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• 2008

Increased demand for the latest spatial information, it is necessary to study the complement current map updating systems for responding the diverse environment of the national territory information. This study suggests the way to update 1/5,000 digital maps with the application of as-built drawings based on current systems. This study compares current as-built drawings with digital maps, and consider intra and international related cases and regulations. This study also selects case areas based on different types of as-built drawings and updates digital maps with the application of as-built drawings. After the consideration of systems and regulations related to as-built drawings, the research results, including the improvement and the application of as-built drawings, are presented. It is expected that the foundation to provide more rapid and accurate geographic information can be achieved from the research result.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.481-490
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• 2018

Recently, the spatiotemporal patterns of flood disasters have become more complex and unpredictable due to climate change. Flood hazard map including information on flood risk level has been widely used as an unstructured measure against flooding damages. In order to product a high-precision flood hazard map by combination of hydrologic and hydraulic modeling, huge digital information such as topography, geology, climate, landuse and various database related to social economic are required. However, in some areas, especially in developing countries, flood hazard mapping is difficult or impossible and its accuracy is insufficient because such data is lacking or inaccessible. Therefore, this study suggests a method to delineate large scale flood-prone area based on topographic factors produced by linear binary classifier and ROC (Receiver Operation Characteristics) using globally-available geographic data such as ASTER or SRTM. We applied the proposed methodology to five different countries: North Korea Bangladesh, Indonesia, Thailand and Myanmar. The results show that model performances on flood area detection ranges from 38% (Bangladesh) to 78% (Thailand). The flood-prone area detection based on the topographical factors has a great advantage in order to easily distinguish the large-scale inundation-potent area using only digital elevation model (DEM) for ungauged watersheds.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.1
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• pp.55-60
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• 2011

The most basic algorithm in SLAM(Simultaneous Localization And Mapping) technique of mobile robots is EKF(Extended Kalman Filter) SLAM. However, it requires prior information of characteristics of the system and the noise model which cannot be estimated in accurate. By this limit, Kalman Filter shows the following behaviors in a highly uncertain environment: becomes too sensitive to internal parameters, mathematical consistency is not kept, or yields a wrong estimation result. In contrast, $H_{\infty}$ filter does not requires a prior information in detail. Thus, based on a idea that $H_{\infty}$ filter based SLAM will be more robust than the EKF-SLAM, we propose a framework of $H_{\infty}$ filter based SLAM and show that suggested algorithm shows slightly better result man me EKF-SLAM in a highly uncertain environment.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.29-36
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• 2011

The main purpose of this paper is to make a map showing canopy cover by using airborne Lidar data based on region. Watershed algorithm was applied to elevation data to conduct segmentation, and then canopy cover was estimated through the regions extracted. In the process of transforming point data to raster, we solved the problems about overestimation and underestimation by using frequency method. Also, canopy cover map could be produced with various scales by differing level of segmentation and it provides more accurate and precise information than ones of ordinary public forest map.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.