• Title/Summary/Keyword: 계산 복잡도 감소

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Evaluating the Dosimetric Characteristics of Radiation Therapies according to Head Elevation Angle for Head and Neck Tumors (두 경부 종양 치료 시 거상각도에 따른 치료기법 별 선량특성 평가)

  • Cheon, Geum-Seong;Kang, Seong-Hee;Kim, Dong-Su;Kim, Tae-Ho;Suh, Tae-Suk
    • Progress in Medical Physics
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    • v.27 no.1
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    • pp.14-24
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    • 2016
  • Since the head and neck region is densely located with organs at risk (OAR), OAR-sparing is an important issue in the treatment of head and neck cancers. This study-in which different treatment plans were performed varying the head tilt angle on brain tumor patients-investigates the optimal head elevation angle for sparing normal organs (e.g. the hippocampus) and further compares the dosimetric characteristics of different types of radiation equipment. we performed 3D conformal radiation therapy (3D-CRT), intensity-modulated radiation therapy (IMRT), and tomotherapy on 10 patients with brain tumors in the frontal lobe while varying the head tilt angle of patients to analyze the dosimetric characteristics of different therapy methods. In each treatment plan, 95% of the tumor volume was irradiated with a dose of 40 Gy in 10 fractions. The step and shoot technique with nine beams was used for IMRT, and the same prescription dose was delivered to the tumor volume for the 3D-CRT and tomotherapy plans. The homogeneity index, conformity index, and normal tissue complication probability (NTCP) were calculated. At a head elevation angle of $30^{\circ}$, conformity of the isodose curve to the target increased on average by 53%, 8%, and 5.4%. In 3D-CRT, the maximum dose received by the brain stem decreased at $15^{\circ}$, $30^{\circ}$, and $40^{\circ}$, compared to that observed at $0^{\circ}$. The NTCP value of the hippocampus observed in each modality was the highest at a head and neck angle of $0^{\circ}$ and the lowest at $30^{\circ}$. This study demonstrates that the elevation of the patients' head tilt angle in radiation therapy improves the target region's homogeneity of dose distribution by increasing the tumor control rate and conformity of the isodose curve to the target. Moreover, the study shows that the elevation of the head tilt angle lowers the NTCP by separating the tumor volume from the normal tissues, which helps spare OARs and reduce the delivered dose to the hippocampus.

Simulation of Soil Moisture in Gyeongan-cheon Watershed Using WEP Model (WEP 모형을 이용한 경안천 토양수분 모의)

  • Noh, Seong-Jin;Kim, Hyeon-Jun;Kim, Cheol-Gyeom;Jang, Cheol-Hee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.720-725
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    • 2006
  • 토양수분은 식물의 생장 및 가용수자원 산정 등에 있어서 중요한 요소로서 토양층 상부의 수 m내에 존재하는 수분의 양을 일컫는다. 토양수분과 토양수분의 공간적 시간적 특징들은 증발, 침투, 지하수 재충전, 토양침식, 식생 분포 등을 지배하는 중요한 요소이다. 강우 등으로 인한 지면과 지표하에서의 순간적인 포화공간의 형성 및 유출의 생성 등을 포함하는 과정과 증발산 등은 모두 비포화대(vadose zone) 혹은 토양층에서의 토양수분의 함량에 크게 의존하게 된다(이가영 등(2005)). 분포형 수문모형은 유역을 격자단위로 세분화하여 매개변수를 부여하고, 증발산, 침투, 지표면유출, 중간유출, 지하수유출, 하도 흐름 등 여러 가지 수문요소를 해석하는 종합적인 수문모형이다. 지표면에 내린 강우가 증발, 침투, 유출될 지는 토양수분의 함량에 크게 의존하게 되며, 따라서 토양수분에 대한 적절한 모의가 분포형 수문모형의 정확도를 좌우하는 핵심이라 할 수 있다. 본 연구에서는 분포형 수문모형인 WEP 모형을 경안천 유역(유역면적: $575km^2$, 유로연장: 49.3㎞)에 적용하여 토양수분의 시공간분포를 모의하였다. 지점별 토양수분 모의결과, 토양 매개변수의 최대, 최소값 내에서 적절히 모의됨을 확인하였으나, 관측값이 없어 실질적으로 타당한지 여부는 검증하지 못하였다. 토양수분비율, 연간 증발산량, 지표면 유출량 공간분포를 비교한 결과, 토양수분비율이 연간 증발산량 모의에 직접적인 영향을 주는 것을 확인할 수 있었다. 일부격자에서는 토양수분이 지나치게 높게 모의되었는데, 지하수위와 관련있는 것으로 보이며, 구축된 자료가 부족한 지하대수층에 대한 정보부족이 토양수분 계산에도 영향을 준 것으로 보인다. 본 연구는 WEP 모형의 토양수분 해석능력에 대한 시험적용에 그 의의가 있으며, 향후 토양 및 지표하 매개변수 정보가 충분히 갖추어지고, 토양수분 관측결과 있는 대상유역에 대한 적용이 요구된다.-Moment 방법에 의해 추정된 매개변수를 사용한 Power 분포를 적용하였으며 이들 분포의 적합도를 PPCC Test를 사용하여 평가해봄으로써 낙동강 유역에서의 저수시의 유출량 추정에 대한 Power 분포의 적용성을 판단해 보았다. 뿐만 아니라 이와 관련된 수문요소기술을 확보할 수 있을 것이다.역의 물순환 과정을 보다 명확히 규명하고자 노력하였다.으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가 설정한 투자기간보다 더욱 긴 분석기간의 주식가격정보에 의하여 최대한 발휘될 수 있음을 확인하였다.(M1), 무역적자의

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Experimental Study on Helical Turbine Efficiency for Tidal Current Power Plant (조류 발전용 헬리컬 수차의 효율에 대한 실험적 연구)

  • Han, Sang-Hun;Lee, Kwang-Soo;Yum, Ki-Dai;Park, Woo-Sun;Park, Jin-Soon;Yi, Jin-Hak
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.530-534
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    • 2006
  • 조류발전은 조류 유속이 빠른 곳에 수차발전기를 설치하여 해수의 운동에너지로부터 전기를 생산하는 발전방식이다. 2001년부터 해양연구원에서는 울돌목의 우수한 조류발전 개발 여건을 바탕으로 조류에너지 실용화 기술을 개발하고 있다. 본 연구에서는 조류발전 시스템에 사용되는 헬리컬 수차의 효율을 현장실험을 바탕으로 판단하고자 하였다. 현장실험을 위하여 지름 2.2 m, 높이 2.5 m의 수차를 제작하고, 울돌목 협수로의 한 쪽 면에 쟈켓구조물을 설치하여 수차를 거치한다. 수차가 회전함에 따라 회전봉에 일정 마찰을 주어 토크와 RPM을 측정하고, 함께 측정된 유속자료를 이용하여 수차를 효율을 산정한다. 유속-수차효율, TSR(수차의 날개속도와 유속의 비)-수차효율의 상관관계로 실험결과를 고찰하였다. 1중 날개 수차인 경우에 유속 1.4에서 2.6 m/s 사이에서 최대효율이 30 - 35 % 정도였고, 2중 날개 수차에 대한 실험에서는 유속 1.4에서 2.6 m/s 사이에서 최대수차효율이 25 - 35 % 사이임을 알 수 있었다. TSR과 최대수차효율의 상관관계는 실험 case별로 조금씩 다르다. 전체적으로 1중 날개의 경우가 최대수차효율에서 2중 날개보다 TSR 값이 조금 큰 경향을 나타냄을 알 수 있다. 이것은 1중 날개가 2중 날개보다 가벼워 좀 더 큰 RPM을 발생시켜서 나타난 현상으로 생각된다. 현재의 실험결과들을 이용하여 TSR과 최대수차효율을 상관관계를 나타내는 모델식을 도출하였다. 현장시험결과를 종합하면, 현장조류발전 시설이 최소 600 kW의 전력이 생산되기 위해서는 지름 3 m, 높이 3.6 m 인 수차 3개가 하나의 축에 설치되어야하는 것으로 계산되었다. 정격유속이 4.8 m/s이고 수차의 지름이 3m 라면, 최적 전력발생시의 RPM은 1중 날개의 경우 79이고 2중 날개의 경우는 63정도임을 추정할 수 있었다.촬영하여 실시간으로 전송하기 때문에 홍수시 하천 상황에 대한 모니터링 목적으로 사용될 수 있다. 영상수위계는 우물통 등을 이용하는 기존 방법과 비교하여 구조물이 필요 없어 설치 비용이 저렴하고, 영상에 의한 하천 모니터링 기능을 자체적으로 가지고 있기 때문에 효율적이라고 할 수 있다.따른 4개의 평가기준과 26개의 평가속성으로 이루어진 2단계 기술가치평가 모형을 구축하였으며 2개의 개별기술에 대한 시범적용을 실행하였다.하는 것으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전

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Estimation of Fractional Urban Tree Canopy Cover through Machine Learning Using Optical Satellite Images (기계학습을 이용한 광학 위성 영상 기반의 도시 내 수목 피복률 추정)

  • Sejeong Bae ;Bokyung Son ;Taejun Sung ;Yeonsu Lee ;Jungho Im ;Yoojin Kang
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.1009-1029
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    • 2023
  • Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R2 of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R2 of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

A Study on the Forest Yield Regulation by Systems Analysis (시스템분석(分析)에 의(依)한 삼림수확조절(森林收穫調節)에 관(關)한 연구(硏究))

  • Cho, Eung-hyouk
    • Korean Journal of Agricultural Science
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    • v.4 no.2
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    • pp.344-390
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    • 1977
  • The purpose of this paper was to schedule optimum cutting strategy which could maximize the total yield under certain restrictions on periodic timber removals and harvest areas from an industrial forest, based on a linear programming technique. Sensitivity of the regulation model to variations in restrictions has also been analyzed to get information on the changes of total yield in the planning period. The regulation procedure has been made on the experimental forest of the Agricultural College of Seoul National University. The forest is composed of 219 cutting units, and characterized by younger age group which is very common in Korea. The planning period is devided into 10 cutting periods of five years each, and cutting is permissible only on the stands of age groups 5-9. It is also assumed in the study that the subsequent forests are established immediately after cutting existing forests, non-stocked forest lands are planted in first cutting period, and established forests are fully stocked until next harvest. All feasible cutting regimes have been defined to each unit depending on their age groups. Total yield (Vi, k) of each regime expected in the planning period has been projected using stand yield tables and forest inventory data, and the regime which gives highest Vi, k has been selected as a optimum cutting regime. After calculating periodic yields and cutting areas, and total yield from the optimum regimes selected without any restrictions, the upper and lower limits of periodic yields(Vj-max, Vj-min) and those of periodic cutting areas (Aj-max, Aj-min) have been decided. The optimum regimes under such restrictions have been selected by linear programming. The results of the study may be summarized as follows:- 1. The fluctuations of periodic harvest yields and areas under cutting regimes selected without restrictions were very great, because of irregular composition of age classes and growing stocks of existing stands. About 68.8 percent of total yield is expected in period 10, while none of yield in periods 6 and 7. 2. After inspection of the above solution, restricted optimum cutting regimes were obtained under the restrictions of Amin=150 ha, Amax=400ha, $Vmin=5,000m^3$ and $Vmax=50,000m^3$, using LP regulation model. As a result, about $50,000m^3$ of stable harvest yield per period and a relatively balanced age group distribution is expected from period 5. In this case, the loss in total yield was about 29 percent of that of unrestricted regimes. 3. Thinning schedule could be easily treated by the model presented in the study, and the thinnings made it possible to select optimum regimes which might be effective for smoothing the wood flows, not to speak of increasing total yield in the planning period. 4. It was known that the stronger the restrictions becomes in the optimum solution the earlier the period comes in which balanced harvest yields and age group distribution can be formed. There was also a tendency in this particular case that the periodic yields were strongly affected by constraints, and the fluctuations of harvest areas depended upon the amount of periodic yields. 5. Because the total yield was decreased at the increasing rate with imposing stronger restrictions, the Joss would be very great where strict sustained yield and normal age group distribution are required in the earlier periods. 6. Total yield under the same restrictions in a period was increased by lowering the felling age and extending the range of cutting age groups. Therefore, it seemed to be advantageous for producing maximum timber yield to adopt wider range of cutting age groups with the lower limit at which the smallest utilization size of timber could be produced. 7. The LP regulation model presented in the study seemed to be useful in the Korean situation from the following point of view: (1) The model can provide forest managers with the solution of where, when, and how much to cut in order to best fulfill the owners objective. (2) Planning is visualized as a continuous process where new strateges are automatically evolved as changes in the forest environment are recognized. (3) The cost (measured as decrease in total yield) of imposing restrictions can be easily evaluated. (4) Thinning schedule can be treated without difficulty. (5) The model can be applied to irregular forests. (6) Traditional regulation methods can be rainforced by the model.

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Estimation of GARCH Models and Performance Analysis of Volatility Trading System using Support Vector Regression (Support Vector Regression을 이용한 GARCH 모형의 추정과 투자전략의 성과분석)

  • Kim, Sun Woong;Choi, Heung Sik
    • Journal of Intelligence and Information Systems
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    • v.23 no.2
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    • pp.107-122
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    • 2017
  • Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.