• 한국육종학회지
• /
• 제40권1호
• /
• pp.1-7
• /
• 2008

An attempt was made to link rice embryo proteins to DNA sequences and to understand their functions. One hundred of the 700 spots detected on the embryo 2-DE gels were microsequenced. Of these, 28% of the embryo proteins were matched to DNA sequences with known functions, but 72% of the proteins were unknown in functions as previously reported (Woo et al. 2002). In addition, twenty-four protein spots with 100% of homology and nine with over 80% were matched to ESTs (expressed sequence tags) after expanding the amino acid sequences of the protein spots by Database searches using the available rice EST databases at the NCBI (http://www/ncbi.nlm.nih.gov/) and DDBJ (http://www.ddbj.nig.ac.jp/). The chromosomal location of some proteins were also obtained from the rice genetic map provided by Japanese Rice Genome Research Program (http://rgp.dna.affrc.go.jp). The DNA sequence databases including EST have been reported for rice (Oryza sativa L.) now provides whole or partial gene sequence, and recent advances in protein characterization allow the linking proteins to DNA sequences in the functional analysis. This work shows that proteome analysis could be a useful tool strategy to link sequence information and to functional genomics.

• Nuclear Engineering and Technology
• /
• 제51권4호
• /
• pp.987-995
• /
• 2019

Steam jet condensation is of great importance to pressure suppression containment and automatic depressurization system in nuclear power plant. In this paper, the condensation processes of sonic steam jet in a quiescent subcooled pool are recorded and analyzed, more precise understanding are got in direct contact condensation. Experiments are conducted at atmospheric pressure, and the steam is injected into the subcooled water pool through a vertical nozzle with the inner diameter of 10 mm, water temperature in the range of $25-60^{\circ}C$ and mass velocity in the range of $320-1080kg/m^2s$. Richardson number is calculated based on the conservation of momentum for single water jet and its values are in the range of 0.16-2.67. There is no thermal stratification observed in the water pool. Four condensation regimes are observed, including condensation oscillation, contraction, expansion-contraction and double expansion-contraction shapes. A condensation regime map is present based on steam mass velocity and water temperature. The dimensionless steam plume length increase with the increase of steam mass velocity and water temperature, and its values are in the range of 1.4-9.0. Condensation heat transfer coefficient decreases with the increase of steam mass velocity and water temperature, and its values are in the range of $1.44-3.65MW/m^2^{\circ}C$. New more accurate semi-empirical correlations for prediction of the dimensionless steam plume length and condensation heat transfer coefficient are proposed respectively. The discrepancy of predicted plume length is within ${\pm}10%$ for present experimental results and ${\pm}25%$ for previous researchers. The discrepancy of predicted condensation heat transfer coefficient is with ${\pm}12%$.

• 한국항공우주학회지
• /
• 제47권1호
• /
• pp.66-74
• /
• 2019

달 표면 전체에 걸쳐 열물성치를 확보하는 대신 단위 면적당 열질량을 이용하여 달 표면온도를 정확히 예측할 수 있는 개선된 집중계(Lumped System Model, LSM) 해석방법을 제시하였다. 최근에 발표된 연구에 기초하여 표토층 최상단의 단위 면적당 열 질량이 균일하다고 가정하고, 하부면 전도열유속 방정식을 이론적인 근거 하에 도입함으로써 DLRE 측정온도와 상당한 정도 잘 일치하는 달 표면의 온도지도를 구하였다. LSM 온도예측은 태양복사가 약한 황혼, 새벽 및 고위도 지역을 제외하면 DLRE 측정과 잘 일치하며, 이러한 지역에서의 온도 불일치는 하부 전도열유속 모델의 한계에 기인한다. 표면 지형과 열물성치가 매우 불균일한 지역에서 나타나는 비정상온도 영역을 제외하고 LSM 분석으로 생성된 달 표면 온도지도는 DLRE 측정 결과와 유사하다.

• 융합정보논문지
• /
• 제12권5호
• /
• pp.100-106
• /
• 2022

종단연구는 동일 대상에 대하여 반복적으로 측정한 종단자료를 기반으로 하는 연구방법을 말한다. 대부분의 종단분석 방법은 예측이나 추론에 적합하고, 탐색적 목적으로 사용하기에는 적합하지 않은 경우가 많다. 본 연구에서는 종단자료를 분석하는 탐색적 방법을 제시한다. 이 방법은 자기조직화지도기법을 사용하여 종단자료를 군집화 하여 최선의 군집 수를 정한 후 종단궤적을 찾는 방법이다. 제안한 방법론은 고용정보원의 종단자료에 적용되었으며, 총 2,610개의 샘플에 대하여 분석을 하였다. 방법론을 적용한 결과 패널 별로 시계열적으로 군집 화되는 결과를 얻었다. 이는 종단자료를 사전에 클러스터링하고 다층 종단분석을 하는 것이 더욱 효과적이라는 사실을 나타낸다.

• Geomechanics and Engineering
• /
• 제27권6호
• /
• pp.551-560
• /
• 2021

Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

• Nuclear Engineering and Technology
• /
• 제54권5호
• /
• pp.1825-1834
• /
• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• 지적과 국토정보
• /
• 제51권2호
• /
• pp.141-150
• /
• 2021

미세먼지는 사람의 건강에 많은 영향을 미치는 물질로서 이와 관련하여 다양한 연구가 이루어지고 있다. 미세먼지의 인체 영향으로 인해 서울시 모니터링 네트워크에서 측정된 과거 데이터를 활용하여 미세먼지를 예측하려는 다양한 연구가 진행되고 있다. 본 연구는 2019년 5월 서울시의 미세먼지를 중점으로 진행하였으며, 학습에 사용한 변수는 SO₂, CO, NO₂, O₃와 같은 대기오염물질 데이터를 활용하였다. 예측모델은 Adaboost에 기반하여 구축하였고, 훈련모델은 PM₁₀과 PM_2.5로 구분하였다. 에러 메트릭스를 통한 예측모델의 정확도 평가 결과로 Adaboost가 시도되었다. 대기오염물질은 초미세먼지와 더 높은 상관성을 보이는 것으로 나타났지만, 보다 효과적인 분포등급을 제시하기 위해서는 많은 양의 데이터를 학습하고, PM₁₀과 PM_2.5의 공간분포 등급을 효과적으로 예측하기 위해서 교통량 등의 추가적인 변수를 활용할 필요성이 있다고 판단된다.

• Asian Journal of Business Environment
• /
• 제13권2호
• /
• pp.9-20
• /
• 2023

Purpose: This study aims to map the spatial distribution of poverty using nighttime light satellite images as a proxy indicator of economic activities and infrastructure distribution in D.I Yogyakarta, Indonesia. Research design, data, and methodology: This study uses official poverty statistics (National Socio-economic Survey (SUSENAS) and Poverty Database 2015) to compare satellite imagery's ability to identify poor urban areas in D.I Yogyakarta. National Socioeconomic Survey (SUSENAS), as poverty statistics at the macro level, uses expenditure to determine the poor in a region. Poverty Database 2015 (BDT 2015), as poverty statistics at the micro-level, uses asset ownership to determine the poor population in an area. Pearson correlation is used to identify the correlation among variables and construct a Support Vector Regression (SVR) model to estimate the poverty level at a granular level of 1 km x 1 km. Results: It is found that macro poverty level and moderate annual nighttime light intensity have a Pearson correlation of 74 percent. It is more significant than micro poverty, with the Pearson correlation being 49 percent in 2015. The SVR prediction model can achieve the root mean squared error (RMSE) of up to 8.48 percent on SUSENAS 2020 poverty data.Conclusion: Nighttime light satellite imagery data has potential benefits as alternative data to support regional poverty mapping, especially in urban areas. Using satellite imagery data is better at predicting regional poverty based on expenditure than asset ownership at the micro-level. Light intensity at night can better describe the use of electricity consumption for economic activities at night, which is captured in spending on electricity financing compared to asset ownership.

• Journal of Ecology and Environment
• /
• 제46권1호
• /
• pp.54-61
• /
• 2022

Background: In South Korea, African swine fever virus (ASFV) has spread among wild boars through Gangwon-do to Dangyang-gun, Chungcheongbuk-do on the southern border of Gangwon-do. To prevent the spread of ASFV to African swine fever (ASF)-free areas, it is necessary to identify areas with a high probability of finding ASFV-infected carcasses and to reduce the density of wild boars in those areas. In this study, we described the propagation trend of ASFV among wild boars, constructed the habitat suitability maps for ASFV-infected carcasses, and suggested areas with a high probability of finding ASFV-infected carcasses and an important route of ASFV transmission. Results: Despite the active quarantine policies in Korea to prevent the spread of ASFV through wild boars, there was no significant difference in the monthly average of number of ASFV-infected carcasses observed between 2020 and 2021. The ASFV-infected carcasses were found more in winter and spring (January to April). Since the first ASF outbreak in wild boars on October 2, 2019, the maximum width of ASFV-infected carcass distribution area was 222.7 km for about 26 months till November 20, 2021. The habitat suitability map, based on GPS coordinates of ASFV-infected wild boar carcasses, shows that highly detectable areas of ASFV-infected carcasses were sporadically dispersed in western and southwestern parts of Gangwon-do, and ranged from north to south of the province along the Baekdudaegan Mountains, whereas poorly detectable areas ranged along the north to the south in the middle parts of the province. Conclusions: Our suitability model, based on the GPS coordinates of ASFV-infected carcasses, identifies potential habitats where ASFV-infected carcasses are likely to be found and ponential routes where ASFV is likely to spread. Among ASF-free areas, the areas with high suitability predicted in this study should be given priority as survey areas to find ASFV-infected carcasses and hunting areas to reduce wild boar populations.

• 대한토목학회논문집
• /
• 제28권6D호
• /
• pp.915-922
• /
• 2008

불투수층은 자연적인 침투를 허용하지 않는 인위적인 토지피복상태로, 도시화율을 추정하거나 도시의 환경변화 정도를 분석하기 위한 척도로 사용되어 왔다. 수문학적인 관점에서 불투수층은 단기 유출현상에 큰 영향을 끼치는 요소로 급속한 도시화로 인해 불투수층의 영향이 더욱 커짐에 따라 불투수층의 추정에 대한 필요성이 증가하고 있다. 따라서 본 연구에서는 불투수층을 추정하기 위해 중랑천 유역을 대상지역으로 선정하고, $30m{\times}30m$ 공간해상도의 Landsat-7 ETM+ 영상과 $1m{\times}1m$의 고해상도 위성영상을 구축하였으며 tasselled cap 변환과 식생지수(NDVI) 변환을 수행하여 다양한 예측변수를 고려하였다. 수집된 학습자료에 분류 및 회귀트리를 적용하여 불투수층 추정모델을 구성하였고, 이를 지도화하여 중랑천 유역의 불투수층을 나타냈다.