• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.1-9
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• 2010

Recently, 3D stereoscopic display such as 3D stereoscopic cinemas and 3D stereoscopic TV is getting a lot of interest. In general, a stereo image can be used in 3D stereoscopic display. In other hands, for 3D auto stereoscopic display, the elemental images should be generated through visualization from every camera in a lens array. Since a lens array consists of several cameras, it takes a lot of time to generate the elemental images with respect to 3D virtual space, specially, if a large bio-medical volume data is in the 3D virtual space, it will take more time. In order to improve the problem, in this paper, we construct an octree for a given bio-medical volume data and then propose a method to generate the elemental images through efficient rendering of the Octree data using GPU. Experimental results show that the proposed method can obtain more improvement comparable than conventional one, but the development of more efficient method is required.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.419-426
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• 2022

In this paper, we propose a method to improve the accuracy of 3D human pose estimation model in various move motions. Existing human pose estimation models have some problems of jitter, inversion, swap, miss that cause miss coordinates when estimating human poses. These problems cause low accuracy of pose estimation models to detect exact coordinates of human poses. We propose a method that consists of detection and correction methods to handle with these problems. Deep learning-based outlier detection method detects outlier of human pose coordinates in move motion effectively and rule-based correction method corrects the outlier according to a simple rule. We have shown that the proposed method is effective in various motions with the experiments using 2D golf swing motion data and have shown the possibility of expansion from 2D to 3D coordinates.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.81-95
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• 2009

The CDB(Constraint Database) model is a new paradigm for massive spatial data processing such as GIS(Geographic Information System). This paper will identify the limitation of the schema structure and query processing through prior spatial database research and suggest more efficient processing mechanism of constraint data model. We presented constraint model concept, presentation method, and the examples of query processing. Especially, we represented TIN (Triangulated Irregular Network) as a constraint data model which displays the height on a plane data and compared it with prior spatial data model. Finally, we identified that we were able to formalize spatial data in a simple and refined way through constraint data modeling.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.281-283
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• 2014

국제수로기구는 항해안전과 수로정보 활용 증진을 위해 S-57 표준을 한계점을 개선하고 최신 GIS 표준을 반영하여 S-100 표준을 개발한 바 있다. 해사안전과 관련된 각 국제기구와 표준그룹에서는 S-100 표준을 기반으로 다양한 수로데이터 제품표준(S-10X) 개발을 논의 중에 있으며 가시적인 결과를 도출하고 있으므로, 이를 기반으로 하는 차세대 ECDIS에서는 기존의 자료 구조와 주요 기능의 변경이 예상되고 있다. 한편, 국제해사기구에서 추진하고 있는 e-Navigation 전략에서 e-Nav 정보표준(CMDS) 개발 시작점으로 S-100이 선정됨에 따라, S-100의 핵심 개념이 e-Nav 정보엔진 설계에 반영될 것으로 예상되므로, 본 연구에서는 S-10X 사례 분석을 통한 e-Navigation 정보엔진 구조를 설계하고자 하였다. 현행 전자해도 시스템 구조를 분석하여 주요 특징을 정리 하였으며, 각 국제기구에서 논의하고 있는 S-10X 표준 내역을 분석하여 e-Navigation 정보엔진에서 고려되어야 하는 자료의 유형과 종류를 벡터형 데이터, 그리드형 데이터, TIN형 데이터, 이미지형 데이터로 정리 하였고, 이를 토대로 e-Navigation 정보엔진 구조설계안을 도출하였다.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.33.1-33.1
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• 2010

태양전파폭발위치관측기(KSRBL)는 단일 안테나 전파분광기로써 미 뉴저지공과대학과의 협력으로 2009년 8월에 한국천문연구원에 개발 설치되었다. 1 MHz 스펙트럼 분해능과 1초의 시간 분해능을 가지고 있고 관측할 수 있는 주파수 대역은 245, 410 MHz 와 0.5-18 GHz에 이르는 광대역이다. 또한 태양 전면 $0.03^{\circ}$ 각거리 안의 오차 범위 내에 태양 폭발 위치를 감지할 수 있다. 전파 관측은 LabVIEW와 IDL 프로그램에 의해 미리 짜여진 관측 스케줄에 따라 매일 자동으로 진행된다. 하루에 생성되는 원시데이터는 90 GB 정도이며, 태양이 지고나면 원시데이터는 적분과정을 통해 용량이 6 GB 정도로 줄어들게 된다. 이렇게 처리된 파일은 바로 데이터 서버에 자동 전송된다. 또한 KSRBL 관측일지 홈페이지를 웹기반으로 개발하였으며 조만간 이를 데이터 전송과 연계하여 전파 폭발이 감지될 경우 원시데이터도 데이터 서버에 자동 전송되도록 할 예정이다. 2010년 1월에서 2월 8일 사이 5개의 전파 폭발이 관측되었고 태양활동이 점차 활발해짐에 따라 관측횟수는 더욱 늘어날 전망이다. 관측된 사례들에 대해 다른 전파 및 X선 관측과 비교분석하였다.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.12
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• pp.569-576
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• 2013

Cloud computing has been receiving increasing attention recently. Despite this attention, security is the main problem that still needs to be addressed for cloud computing. In general, a cloud computing environment protects data by using distributed servers for data storage. When the amount of data is too high, however, different pieces of a secret key (if used) may be divided among hundreds of distributed servers. Thus, the management of a distributed server may be very difficult simply in terms of its authentication, encryption, and decryption processes, which incur vast overheads. In this paper, we proposed a efficiently data storage and recovery scheme using XOR and RAID in Hadoop environment.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.593-605
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• 2022

The purpose of this study is to investigate the personalized treacmill exercise analysis using a smart mirror based on Kinect sensor. To evaluate the performance of the development system, 10 health males were used to measure the range of the hip joint, knee joint, and ankle joint using a smart mirror when walking on a treadmill. For the validity and reliability of the development system, the validity and reliability were analyzed by comparing the human movement data measured by the Kinect sensor with the human movement data measured by the infrared motion capture device. As a result of validity verification, the correlation coefficient r=0.871~0.919 showed a high positive correlation, and through linear regression analysis, the validity of the smart mirror system was 88%. Reliability verification was conducted by ICC analysis. As a result of reliability verification, the correlation coefficient r=0.743~0.916 showed high correlation between subjects, and the consistency for repeated measurement was also very high at ICC=0.937. In conclusion, despite the disadvantage that Kinect sensor is less accurate than the motion capture system, Kinect is it has the advantage of low price and real-time information feedback. This means that the Kinect sensor is likely to be used as a tool for evaluating exercise prescription through human motion measurement and analysis.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.363-373
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• 2023

Forest biomass surveys are regularly conducted to assess and manage forests as carbon sinks. LiDAR (Light Detection and Ranging), a remote sensing technology, has attracted considerable attention, as it allows for objective acquisition of forest structure information with minimal labor. In this study, we propose a method for estimating overstory and understory biomass in forest stands using backpack laser scanning (BPLS) and unmanned aerial vehicle laser scanning (UAV-LS), and assessed its accuracy. For overstory biomass, we analyzed the accuracy of BPLS and UAV-LS in estimating diameter at breast height (DBH) and tree height. For understory biomass, we developed a multiple regression model for estimating understory biomass using the best combination of vertical structure metrics extracted from the BPLS data. The results indicated that BPLS provided accurate estimations of DBH (R² =0.92), but underestimated tree height (R² =0.63, bias=-5.56 m), whereas UAV-LS showed strong performance in estimating tree height (R² =0.91). For understory biomass, metrics representing the mean height of the points and the point density of the fourth layer were selected to develop the model. The cross-validation result of the understory biomass estimation model showed a coefficient of determination of 0.68. The study findings suggest that the proposed overstory and understory biomass survey methods using BPLS and UAV-LS can effectively replace traditional biomass survey methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.965-971
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• 2011

As the liver cancer in our country cancerous occurrence frequency to be the gastric cancer in the common cancer, If the case which will be discovered in early rising the treatment record was considered seriously about under the early detection. The system which it sees with the system for the early detection of the liver cancer reacts the blood of the control group other than the patient who is confirmed as the liver cancer and the liver cancer to the biochip and aptamer protein biochip profiles mechanical studying leads and it is a system which it classifies. 1149 each other it reacted blood samples of the control group other than the liver cancer patient who is composed of the total 85 samples and the liver cancer which is composed of 310 samples to the biochip which is composed with different oligo from the present paper and it was a data which it makes acquire worker the neural network it led and it analyzes the classification efficiency of the result 95.38 ~ 97.95% which it was visible.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.421-428
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• 2014

Like Alzheimer's disease, Parkinson's Disease(PD) is one of the most common neurodegenerative brain disorders. PD results from the deterioration of dopaminergic neurons in the brain region called the substantia nigra. Currently there is no cure for PD, but diagnosing in its early stage is important to provide treatments for relieving the symptoms and maintaining quality of life. Unlike many diagnosis methods of PD which use a single biomarker, we developed a diagnosis method that uses both biochemical biomarkers and imaging biomarkers. Our method uses ${\alpha}$-synuclein protein levels in the cerebrospinal fluid and diffusion tensor images(DTI). It achieved an accuracy over 91.3% in the 10-fold cross validation, and the best accuracy of 72% in an independent testing, which suggests a possibility for early detection of PD. We also analyzed the characteristics of the brain fiber pathways of Parkinson's disease patients and normal elderly people.