• The Korean Society of Law and Medicine
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• v.18 no.1
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• pp.37-60
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• 2017

Ownership is the bundle of rights that allow a person or institute to use and control an object. As the biomedical science is advanced, we should consider whether human biological material should be recognized as property. Whether separated parts of the human body can be objects of ownership is a different issue. Many thought that separated parts of the human body could not be objects of ownership. This idea is primarily based on this thought: even if a piece of human biological material is separated from a person, it still relates to that person, and if treated as a thing, human dignity may be harmed. However, some commentators have admitted separated parts of the human body into the realm of property. Though a person owns his/her body or body parts, this does not mean that he/she can do anything he/she desires. There are many natural and social limitations to exercise the ownership of human biological material as discussed above. Human dignity is the core consideration whether or not we recognize that ownership of human biological material biomedical research and knowledge.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.149-163
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• 2015

In this study, we conducted study on the confirmation of thermal-hydraulic safety for Mast assembly with Computational Fluid Dynamics(CFD) analysis. Before performing the natural convection analysis for the Mast assembly by using CFD code, we validated the CFD code against two benchmark natural convection data for the evaluation of turbulence models and confirmation of its applicability to the natural convection flow. From the first benchmark test which was performed by Betts et al. in the simple rectangular channel, we selected standard k-omega turbulence model for natural convection. And then, calculation performance of CFD code was also investigated in the sub-channel of rod bundle by comparing with PNL(Pacific Northwest Laboratory) experimental data and prediction results by MATRA and Fluent 12.0 which were performed by Kwon et al.. Finally, we performed main natural convection analysis for fuel assembly inside the Mast assembly by using validated turbulence model. From the calculation, we observed stable natural circulation flow between the mast assembly and pool side and evaluated the thermal-hydraulic safety by calculating the departure from nucleate boiling ratio.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.1
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• pp.29-36
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• 2004

This study deals with an analysis on the sinking resistance for the model purse seine, in the case of different netting material and sinkers. The experiment was carried out using rune simplified model seines of knotless nettings. Dimension of model seines 420cm for corkline and 85cm for seine depth, three groups of models rigged 25, 45 and 60g with the same weighted sinkers in water were used. These were named PP-25, PA-25, PES-25, PP-45, PA-45, PES-45, PP-60, PA-60 and PES-60 seine. The densitie($\rho$) of netting materials were 0.91g/cm$cm^3$, 1.14g/cm$cm^3$ and 1.38g/cm$m^3$. Experiments carried out in the observation channel in a flume tank under still water conditions. Sinking motion was recorded by the one set of TV-camera for VTR, and reading coordinate carried out by the video digitization system. Differential equations were derived from the conservation of momenta of the model purse seines and used to determine the sinking speeds of the depths of leadline and the other portions of the seines. An analysis carried out by simultaneous differential equations for numerical method by sub-routine Runge-Kutta-Gill The results obtained were as follows : 1. Average sinking speed of leadline for the model seines rigged 60g with the same weighted sinkers in water was fastest for 12.2cm/sec of PES seine, followed by 11.4cm/sec of PA and 10.7cm/sec of PP seines. 2. The coefficient of resistance for netting of seine was estimated to be $K_D=0.09(\frac{\rho}{\rho_w})^4$ 3. The coefficient of resistance for netting bundle of seine was estimated to be $C_R=0.91(\frac{\rho}{\rho_w})$ 4. In all seines, the calculated depths of leadline closely agreed with the measured ones, each 25g, 45g, 60g of weighted sinkers were put into formulas meas.=1.04cal., meas.=0.99cal. and meas.=0.98 cal.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.417-418
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• 2018

미국 국립가뭄경감센터 (National Drought Mitigation Center, NDMC)는 다양한 가뭄지수를 통합하여 미국 전역의 가뭄진행상황을 모니터링하고 가뭄대응정책 수립을 위한 주요 의사결정정보로 활용하고 있다. 대표적으로 1999년에 개발되어 현재까지 운영 중인 미국가뭄모니터 (United States Drought Monitor, USDM)는 미국 전역에 대하여 가뭄단계를 표시한 지도 (U.S. Drought Monitor map)를 매주 생성하여 제공하고 있다 (http://droughtmonitor.unl.edu/). 가뭄지표(drought index)는 가뭄의 현황과 시공간적인 전개 과정을 분석하고 정량적 가뭄심도 평가 및 가뭄대응계획 수립을 위한 도구로써 다양하게 개발되어 활용되고 있다. 가뭄의 정도를 정량화하기 위하여 개발된 다수의 가뭄지수는 대상과 평가방법에 따라 가뭄을 표현하는 특성이 서로 다르다. 하나의 가뭄지수로는 가뭄특성을 온전히 표현하기 어렵기 때문에, 최근에는 단일 가뭄지수에 의존하기 보다는 다수의 가뭄지수를 이용하되, 여러 가뭄지수 간의 특징을 고려하여 각 가뭄지수가 갖는 장단점을 상호 보완하여 사용하기를 권고하고 있다. USDM은 파머가뭄심도지수 (Palmer Drought Severity Index, PDSI), Soil Moisture Model (NOAA Climate Prediction Center, CPC), 미 지리조사국의 하천유량 주간보고 (USGS Weekly Streamflow), 표준강수지수 (Standardized Precipitation Index, SPI) 등의 주요 가뭄판단지표를 선정하고, 가뭄판단의 기준으로써 각 가뭄지수의 가뭄심도 (drought severity) 및 백분위수 (percentiles)로 등급을 구분하였다. 가뭄등급은 '정상 상태 (none)'를 포함하여 '비정상적인 건조 (abnormally dry, D0)'에서 최악의 가뭄상태를 의미하는 '이례적인 가뭄상태 (exceptional, D4)'에 이르는 6 단계로 구분하고, 정상상태를 제외한 5 단계의 통합가뭄단계로 표시한다. 우리나라에서는 기상청, 수자원공사, 농어촌공사에서 기상/수문/농업관련 가뭄지수의 위험지도를 실시간으로 제공하고 있으며, 각 지표별로 상이한 기준으로 가뭄을 판단하고 있다. 각각의 가뭄지표에 대한 가뭄판단기준은 해당 국가의 장기적으로 축적된 자료를 활용하여 가뭄단계 및 가뭄판단기준의 재설정에 대한 연구가 필요하다. 본 연구에서는 SPI, SC-PDSI, 표준강수증발산지수 (Standardized Precipitation Evapotranspiration Index, SPEI), Evaporative Demand Drought Index (EDDI), 유효가뭄지수 (Effectvie Drought Index, EDI)의 다양한 가뭄지수를 활용하여 USDM의 가뭄심도 및 가뭄판단기준을 적용하고자한다.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.841-850
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• 2019

The purpose of this study is to strengthen the capability of rapid mapping for disaster through improving the positioning accuracy of mapping and fusion of multi-sensing point cloud data derived from Unmanned Aerial Vehicles (UAVs) and disaster investigation vehicle. The positioning accuracy was evaluated for two procedures of drone mapping with Agisoft PhotoScan: 1) general geo-referencing by self-calibration, 2) proposed geo-referencing with optimized camera model by using fixed accurate Interior Orientation Parameters (IOPs) derived from indoor camera calibration test and bundle adjustment. The analysis result of positioning accuracy showed that positioning RMS error was improved 2~3 m to 0.11~0.28 m in horizontal and 2.85 m to 0.45 m in vertical accuracy, respectively. In addition, proposed data fusion approach of multi-sensing point cloud with the constraints of the height showed that the point matching error was greatly reduced under about 0.07 m. Accordingly, our proposed data fusion approach will enable us to generate effectively and timelinessly ortho-imagery and high-resolution three dimensional geographic data for national disaster management in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.267-277
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• 2019

Photogrammetry and computer vision are identical in determining the three-dimensional coordinates of images taken with a camera, but the two fields are not directly compatible with each other due to differences in camera lens distortion modeling methods and camera coordinate systems. In general, data processing of drone images is performed by bundle block adjustments using computer vision-based software, and then the plotting of the image is performed by photogrammetry-based software for mapping. In this case, we are faced with the problem of converting the model of camera lens distortions into the formula used in photogrammetry. Therefore, this study described the differences between the coordinate systems and lens distortion models used in photogrammetry and computer vision, and proposed a methodology for converting them. In order to verify the conversion formula of the camera lens distortion models, first, lens distortions were added to the virtual coordinates without lens distortions by using the computer vision-based lens distortion models. Then, the distortion coefficients were determined using photogrammetry-based lens distortion models, and the lens distortions were removed from the photo coordinates and compared with the virtual coordinates without the original distortions. The results showed that the root mean square distance was good within 0.5 pixels. In addition, epipolar images were generated to determine the accuracy by applying lens distortion coefficients for photogrammetry. The calculated root mean square error of y-parallax was found to be within 0.3 pixels.