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태양계의 물: 기원과 진화

  • Choe, Byeon-Gak;Choe, Hye-Rim
    • 한국지구과학회:학술대회논문집
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    • 2005.09a
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    • pp.3-8
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    • 2005
  • 지구는 현재 태양계에서 액체 상태의 물이 표면에 존재하는 유일한 천체이다. 하지만, 고체 또는 기체 상태의 물은 태양계의 다른 행성이나, 위성, 소행성, 혜성 등에도 풍부하게 존재하고 있다. 풍부한 액체 상태의 물은 지구 표면에서 일어나고 있는 기후의 변화, 해류의 이동, 퇴적 및 침식 작용, 화산활동과 같은 여러 지구과학적 현상에 밀접하게 관여하고 있을 뿐 아니라 생명의 탄생과 진화에도 매우 중요한 역할을 하였다. 현재 지구 표면에 액체 상태의 물이 존재할 수 있는 이유는 태양으로부터의 거리, 지구의 조성 및 크기 등과 관련된 지구 표면의 물리-화학적 조건이 액체 상태의 물이 존재할 수 있는 조건과 일치하고 있기 때문이다. 이와는 달리 지구보다 태양에 더 가깝게 위치하고 있고, 두터운 이산화탄소 대기를 갖고 있어 표면의 온도가 매우 높은 금성의 경우 H2O는 기체 상태로 존재하며, 지구보다 더 멀리 떨어져 있고 희박한 대기를 갖고 있는 화성의 경우에는 현재 H2O가 고체 즉 얼음의 형태로 존재한다. 태양계를 탄생시킨 태양계 성운에서는 압력이 너무 낮아 액체 상태의 물이 존재할 수 없으며, 고온에서는 기체 상태로 매우 낮은 저온에서는 얼음의 형태, 또는 함수 광물 내에 포함되어 존재할 수 있다. 지구와 같은 규모의 행성은 비교적 중력이 작아 태양계 성운의 기체를 거의 끌어들이지 못했다. 따라서 현재 지구에 존재하는 물은 대부분은 고체 상태로 지구에 집적되었을 것이다. 하지만 지구가 탄생한 위치에서 초기 태양계의 온도는 얼음이 형성되기에는 너무 높았기 때문에 좀 더 먼 곳에서(현재의 목성 위치보다 바깥쪽)에서 생성된 얼음 즉, 혜성이 태양계 안쪽으로 들어와 지구에 물을 공급했거나 함수광물을 포함하고 있는 소행성(예를 들어 CI chondrites와 같은 조성의)이 물을 가져왔을 것으로 생각되고 있다.서의 활성화는 어미 변환과 관련된 영역이라기보다는 산출시 관련되는 articulation, motor coordinate관련 영역으로 추정되고, 측두엽의 활성화는 형태소, 의미 관련 지식의 data base로 추정된다. 또한 우반구 전두엽 부분에서 관찰된 활성화는 억제관련 영역으로 짐작된다.러한 동물실험이 그 기초를 제공해 줄 수 있을 것이다. 또한 행동성향 및 기억의 종류에 따른 약물효과의 차이는 기억과 관련된 질병인 알츠하이머 환자에 있어 개개인에게 맞는 적절한 특징적인 치료약물이 존재할 것이라는 가능성을 제공해줄 뿐만 아니라 학습과 기억력 증진 효과를 기대해 볼 수 있을 것이라고 생각된다. 및 지역산업발전의 기획${\sim}$조정기구로서, 선진국의 지역발전기구(Regional Development Agency : RDA)인 지역전략산업기획단이 2002년도부터 산업자원부와 9개 시도에 의해 설립되어 지역네트워크의 활성화와 클러스터의 형성 촉진을 하게 되었고 2004년도에는 13개시도로 확대${\sim}$운영되고 있고, 지역특화사업(H/W)과 지역산업기술개발과제(S/W)와 함께 패케지 형태로 지원되며, 주요역할은 크게 지역산업의 정책기획 분야와 평가관리, 지역혁신역량 조사 및 DB구축 등으로 구분된다. 그중에서도 권역별, 지역별, 지역산업진흥사업 육성과 중장기 산업발전계획을 수립하기 위하여 지역혁신역량을 바탕으로 한 지역 Technology Road Map(TRM)작성사업은 전국공통의 1단계 사업으로 실시 ?榮쨉?, 2005년 3월 기준으로 9개 지역(강원, 대전, 충남, 충북, 경북, 울산, 전남, 전북, 제주) 26개 산업분야를 대상으로 23개가 완료된 상황이다. 이를 근거로 한 지역정책과 R&D 과제 및 필요 인프라의 도출이 체계적으로 구축되어 지역산업 발전을 위한

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The Impact of Bilateral Free Trade Agreements on International Trade Volume of Bulk Shipment at the Port of Korea: Focusing on Korea's FTA with Singapore, India, and United States (한·단일국가 FTA체결에 따른 우리나라 벌크물동량 영향분석 : 싱가포르, 인도, 미국을 중심으로)

  • Lee, Kyong-Han;Choi, Nayoung-Hwan
    • Journal of Navigation and Port Research
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    • v.40 no.6
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    • pp.485-494
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    • 2016
  • The primary purpose of this study is to analyze the impact and determinants of bilateral Free Trade Agreements on international total bulk shipment trade volume at the port of Korea using the Panel Gravity Model. The model estimates the aggregated panel data of exports and imports (excluding transshipment) as a dependent variable during the period from 1996 to 2015. GDP, GDP per capita, distances between bilateral countries, and FTA dummies are included as independent variables. And the economic integration of FTAs including ASEAN+3 and NAFTA3 countries were used as dummy variables. Study results show that GDP and GDP per capita have positive impacts on bulk shipment trade volume at the port of Korea. In addition, Korea's bilateral FTAs with Singapore, India and the United States have positive effects on total bulk trade volume in Korea. This is the so called trade creation effect. On the other hand, ASEAN+3 and NAFTA have negative effects on the total bulk trade. This is the so called trade diversion effect. Also, the distance between Korea and its trade partners has a negative impact. These findings provide insights for: further academic research, site operators who work in related trade and maritime sectors, and policy makers engaged in port and maritime operations. The results can be used to develop strategies for maximizing bulk port throughput.

Genetic Variation of Abies holophylla Populations in South Korea Based on ISSR Markers (ISSR 분석에 의한 전나무 집단의 유전변이)

  • Kim, Young-Mi;Hong, Kyung Nak;Lee, Jei Wan;Yang, Byeong-Hoon
    • Journal of Korean Society of Forest Science
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    • v.103 no.2
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    • pp.182-188
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    • 2014
  • Genetic diversity and genetic differentiation in six natural populations of Abies holophylla Max were investigated using ISSR marker system. From 6 ISSR primers, the average percentage of polymorphic loci was 85.6%, and the average expected heterozygosity ($H_e$) was 0.288. From the result of AMOVA, 94.4% of total genetic variation came from the differences among individuals within populations, and 5.6% was caused by those of among-populations. On the basis of Bayesian inference, genetic differentiation (${\theta}^{II}$ and $G_{ST}$) and inbreeding coefficient for all populations were 0.045, 0.038, and 0.509, respectively. The correlation between genetic distance and geographical distance was highly significant at the Mental's test (r = 0.74, P < 0.05). Six populations divided into two groups according to the results of UPGMA and PCA. One group included Namwon, Cheongdo and Mungyeong population. The other was Inje, Hongcheon and Pyeongchang population. Also, in Bayesian clustering analysis, 6 populations were divided into two clusters. But Cheongdo population was assigned into the other cluster unlike those of UPGMA or PCA. Taking the regions based on the results of the cluster analysis into consideration of AMOVA, 3.9% of genetic variation came from the regional difference. The dendrogram from UPGMA could provide the most genetically reasonable explanation for the distribution of Abies holophylla populations in South Korea.

Back-Propagation Neural Network Based Face Detection and Pose Estimation (오류-역전파 신경망 기반의 얼굴 검출 및 포즈 추정)

  • Lee, Jae-Hoon;Jun, In-Ja;Lee, Jung-Hoon;Rhee, Phill-Kyu
    • The KIPS Transactions:PartB
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    • v.9B no.6
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    • pp.853-862
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    • 2002
  • Face Detection can be defined as follows : Given a digitalized arbitrary or image sequence, the goal of face detection is to determine whether or not there is any human face in the image, and if present, return its location, direction, size, and so on. This technique is based on many applications such face recognition facial expression, head gesture and so on, and is one of important qualify factors. But face in an given image is considerably difficult because facial expression, pose, facial size, light conditions and so on change the overall appearance of faces, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact face detection which overcomes some restrictions by using neural network. The proposed system can be face detection irrelevant to facial expression, background and pose rapidily. For this. face detection is performed by neural network and detection response time is shortened by reducing search region and decreasing calculation time of neural network. Reduced search region is accomplished by using skin color segment and frame difference. And neural network calculation time is decreased by reducing input vector sire of neural network. Principle Component Analysis (PCA) can reduce the dimension of data. Also, pose estimates in extracted facial image and eye region is located. This result enables to us more informations about face. The experiment measured success rate and process time using the Squared Mahalanobis distance. Both of still images and sequence images was experimented and in case of skin color segment, the result shows different success rate whether or not camera setting. Pose estimation experiments was carried out under same conditions and existence or nonexistence glasses shows different result in eye region detection. The experiment results show satisfactory detection rate and process time for real time system.

Environmental Impact Assessment of Nuclear Power Plant Accident using Spatial Information Modeling: A Case Study of Chernobyl (공간정보 모델링을 이용한 원전 사고의 환경 영향 평가: 체르노빌 사례연구)

  • Lee, Sang-Won;Song, Ah-Ram;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.28 no.1
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    • pp.129-143
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    • 2012
  • This paper demonstrates the effectiveness of advanced spatial modeling techniques for environmental monitoring and impact assessment through a case study of Chernobyl nuclear accident occurred in 1986. Land-cover types changed after the accident are analysed by a post classification comparison method using bi-temporal Landsat TM data acquired in 1986 and 1992 near the accident site. Spatial modeling including various kriging algorithms are also applied to analyze the relationships between Cesium concentrations in soil and thyroid cancer incidence rates in Belarus, which was greatly damaged by the accident. The change detection results clearly showed the decrease of croplands and the increase of abandoned lands, and concrete structures were newly built around the nuclear plant to prevent the spread of radioactive contamination. In Belarus, high Cesium concentrations were observed in southern areas with high thyroid cancer risk estimated by Poisson kriging. Geographically weighted regression, which could account for geographic variations of independent variables including Cesium concentrations and distances from the Chernobyl nuclear power plant, was applied to extract the relationships between the independent variables and the thyroid cancer risk. The estimated risk values showed a correlation coefficient value of 0.98 with respect to the thyroid cancer risk values, which implied that the thyroid cancer risk in Belarus was affected by the accident. In conclusion, it is expected that advanced spatial modeling techniques applied in this study would be useful for environmental impact assessment and public health research.

NEAR REAL-TIME IONOSPHERIC MODELING USING A RBGIONAL GPS NETWORK (지역적 GPS 관측망을 이용한 준실시간 전리층 모델링)

  • Choi, Byung-Kyu;Park, Jong-Uk;Chung, Jeong-Kyun;Park, Phil-Ho
    • Journal of Astronomy and Space Sciences
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    • v.22 no.3
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    • pp.283-292
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    • 2005
  • Ionosphere is deeply coupled to the space environment and introduces the perturbations to radio signal because of its electromagnetic characteristics. Therefore, the status of ionosphere can be estimated by analyzing the GPS signal errors which are penetrating the ionosphere and it can be the key to understand the global circulation and change in the upper atmosphere, and the characteristics of space weather. We used 9 GPS Continuously Operating Reference Stations (CORS), which have been operated by Korea Astronomy and Space Science Institute (KASI) , to determine the high precision of Total Electron Content (TEC) and the pseudorange data which is phase-leveled by a linear combination with carrier phase to reduce the inherent noise. We developed the method to model a regional ionosphere with grid form and its results over South Korea with $0.25^{\circ}\;by\;0.25^{\circ}$ spatial resolution. To improve the precision of ionosphere's TEC value, we applied IDW (Inverse Distance Weight) and Kalman Filtering method. The regional ionospheric model developed by this research was compared with GIMs (Global Ionosphere Maps) preduced by Ionosphere Working Group for 8 days and the results show $3\~4$ TECU difference in RMS values.

A Preliminary Study for the Prediction of Leaking-Oil Amount from a Ruptured Tank (파손된 기름 탱크로부터의 유출양 산정을 위한 기초 연구)

  • Kim Wu-Joan;Lee Young-Yeon
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.4 no.4
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    • pp.21-31
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    • 2001
  • When an oil-spilling accident occurs at sea, it is of the primary importance to predict the amount of oil leakage for the swift response and decision-making. The simplest method of oil-leakage estimation is based on the hydrostatic pressure balance between oil inside the tank and seawater outside of leakage hole, that is the so-called Torricelli equilibrium relation. However, there exists discrepancy between the reality and the Torricelli relation, since the latter is obtained from the quasi-steady treatment of Bernoulli equation ignoring viscous friction. A preliminary experiment has been performed to find out the oil-leaking speed and shape. Soy-bean oil inside the inner tank was ejected into water of the outer tank through four different leakage holes to record the amount of oil leakage. Furthermore, a CFD (Computational Fluid Dynamics) method was utilized to simulate the experimental situation. The Wavier-Stokes equations were solved for two-density flow of oil and water. VOF method was employed to capture the shape of their interface. It is found that the oil-leaking speed varies due to the frictional resistance of the leakage hole passage dependent on its aspect ratio. The Torricelli factor relating the speed predicted by using the hydrostatic balance and the real leakage speed is assessed. For the present experimental setup, Torricelli factors were in the range of 35%~55% depending on the aspect ratio of leakage holes. On the other hand, CFD results predicted that Torricelli factor could be 52% regardless of the aspect ratio of the leakage holes, when the frictional resistance of leakage hole passage was neglected.

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Soil Loss and Water Runoff in a Watershed in Yeoju (소유역(小流域)에서 토양(土壤) 유실(流失) 및 물 유출양상(流出樣相))

  • Lee, Nan-Jong;Oh, Se-Jin;Jung, Pil-Kyun
    • Korean Journal of Soil Science and Fertilizer
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    • v.31 no.3
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    • pp.211-215
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    • 1998
  • Soil loss and runoff were investigated in a small watershed located in Sangeo-ri, Yeoju-eup, Yeoju-gun, Kyonggi-do. The watershed with the area of 35 ha consists of forest, grassland, uplands and mulberry. V-notch type water tank. flow-meter, automatic water sampler and rain gauge were installed at the main outlet stream. Out of $1.037.9Mg\;35ha^{-1}$ of total annual rainfall. 17.9% was lost via run-off. The total amount of soil eroded was $152.2Mg\;35ha^{-1}$, of which $78.6Mg\;35ha^{-1}$ was suspended load and $73.6Mg\;35ha^{-1}$ ha was sediment load. The soil losses under different land uses were $16.02Mg\;ha^{-1}$ for upland annual Crops. $2.69Mg\;ha^{-1}$ for mulberry field, $0.58Mg\;ha^{-1}$ for grassland and $0.55Mg\;ha^{-1}$ for forest. The predicted soil loss by Universal Soil Loss Equation was approximately 20% underestimated in forest, grassland and uplands, and 32% underestimated in mulberry field.

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Underdetermined blind source separation using normalized spatial covariance matrix and multichannel nonnegative matrix factorization (멀티채널 비음수 행렬분해와 정규화된 공간 공분산 행렬을 이용한 미결정 블라인드 소스 분리)

  • Oh, Son-Mook;Kim, Jung-Han
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.2
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    • pp.120-130
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    • 2020
  • This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.

A study on Estimating the Transfer Time of Transit Users Using Deep Neural Network Models (심층신경망 모형을 활용한 대중교통 이용자의 환승시간 추정에 관한 연구)

  • Lee, Gyeongjae;Kim, Sujae;Moon, Hyungtaek;Han, Jaeyoon;Choo, Sangho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.1
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    • pp.32-43
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    • 2020
  • The transfer time is an important factor in establishing public transportation planning and policy. Therefore, in this study, the influencing factors of the transfer time for transit users were identified using smart card data, and the estimation results for the transfer time using the deep learning method such as deep neural network models were compared with traditional regression models. First, the intervals and the distance to the bus stop had positive effects on the subway-to-bus transfer time, and the number of bus routes had a negative effect. This also showed that the transfer time is affected by the area in which the subway station exists. Based on the influencing factors of the transfer time, the deep learning models were developed and their estimation results were compared with the regression model. For model performance, the deep learning models were better than those of the regression models. These results can be used as basic data for transfer policies such as the differential application of transit allowance times according to region.