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증례 : 출혈을 동반한 위중복증(Gastric duplication) 1예
윤정호 ( Jeong Ho Yun ),최동구 ( Dong Gu Choi ),오수용 ( Su Yong Oh ),김선숙 ( Seon Sook Kim ),박종재 ( Jong Jae Park ),김유경 ( Yoo Kyung Kim ),최덕주 ( Deok Ju Choi ),박현철 ( Hyun Chul Park ),김주현 ( Ju Hyun Kim ),박성혜 ( Sun 대한소화기학회 1997 대한소화기학회지 Vol.29 No.6
Duplications of alimentary tract are unusual congenital anomalies composed of cystic or tubular structure that is closely attached or communicated with the gastrointestinal tract. Ileum is the most common site of duplications of alimentary tract, whereas the stomach is the least common site. The majority of gastric duplication is diagnosed at infancy and a few case is diagnosed at adult. We experienced a case of cystic gastric duplication in a 45 years-old female who had presented with hematemesis. About 2×2㎝ sized, round and elevated mass was noted at posterior wall of stomach on gastrofiberscopy. It was confirmed as cystic duplication after surgery.(Korean J Gastroenterol 1997;29:836-840)
류종현(Jong-hyun Ryu),최동구(Dong Gu Choi) 한국경영과학회 2016 經營 科學 Vol.33 No.1
Generation of electricity using wind power has received considerable attention worldwide in recent years mainly due to its minimal environmental impact. However, volatility of wind power production causes additional problems to provide reliable electricity to an electrical grid regarding power system operations, power system planning, and wind farm operations. Those problems require appropriate stochastic models for the electricity generation output of wind power. In this study, we review previous literatures for developing the stochastic model for the wind power generation, and propose a systematic procedure for developing a stochastic model. This procedure shows a way to build an ARIMA model of volatile wind power generation using historical data, and we suggest some important considerations. In addition, we apply this procedure into a case study for a wind farm in the Republic of Korea, Shinan wind farm, and shows that our proposed model is helpful for capturing the volatility of wind power generation.
탈원전・탈석탄・신재생 에너지 확대 정책에 따른 신규 전원구성의 수급 안정성 평가
민대기(Daiki Min),류종현(Jong-hyun Ryu),최동구(Dong Gu Choi) 에너지경제연구원 2018 에너지경제연구 Vol.17 No.1
본 연구에서는 그동안 그 비중이 크지 않아 장기 전원구성 계획 시 심각하게 고려되지 않았던 신재생 에너지의 공급 불확실성이 전력 시장의 수급 안정성 및 적정 예비율에 미치는 영향을 명시적으로 분석할 수 있는 새로운 평가 모형을 제안하였다. 이러한 모형에 기반을 두어 우리나라 장기 전원구성 계획의 수급안정성을 평가하였다. 기존의 ‘제7차 전력수급기본계획’을 따르는 경우 신재생에너지 공급 불확실성은 계획기간 후반부인 2024년 이후부터 전력시장의 수급안정성에 문제를 일으킬 수 있다. 또한, 석탄·원자력 비중이 감소하고 신재생에너지의 비중이 증가하는 ‘제8차 전력수급기본계획‘에서는 평균 설비 예비율과 공급 예비율을 각각 20%와 18% 이상으로 ’제7차 전력수급기본계획‘에서 설정하고 있는 수준들(각각 16%와 12%)보다 높게 설정하고 있으나 목표 공급 신뢰도(0.3일/년) 수준을 만족하지 못하는 결과가 예상된다. The Korean government has recently decided to dramatically expand renewable energy technologies (RETs) while reducing the portion of nuclear and/or coal power generations. The large deployment of RETs could possibly hurt the power system reliability because of the unreliability of RETs. This paper proposes a model for analyzing the effects of unreliable RETs on the reliability of power supply and the level of reasonable reserve margin. Numerical analysis provides some interesting findings. First, the 7th basic power supply plan (the 7<SUP>th</SUP> basic plan for long-term electricity supply and demand) could fail to meet the target level of power system reliability after 2024. In addition, the power system reliability could possibly worsen in the 8<SUP>th</SUP> basic power supply plan, which reduces the portion of nuclear and coal power generation and increases RETs, even though the 8<SUP>th</SUP> basic power supply plan sets the installed reserve and capability margin as 20% and 18% respectively, which are higher than those in the 7<SUP>th</SUP> basic power supply plan, 16% and 12% respectively.
심층 Q-학습을 이용한 지능형 포트폴리오 투자전략 도출
박형준(Hyungjun Park),심민규(Min Kyu Sim),최동구(Dong Gu Choi) 대한산업공학회 2019 대한산업공학회 추계학술대회논문집 Vol.2019 No.11
Our study suggests an approach for deriving an intelligent portfolio trading strategy using deep Q-learning. In this approach, we introduce a Markov decision process model to enable an agent to learn about the financial environment and develop a deep neural network structure to approximate a Q-function. In addition, we devise three techniques to derive a trading strategy that chooses reasonable actions and is applicable to the real world. First, the action space of the learning agent is modeled as an intuitive set of trading directions that can be carried out for individual assets in the portfolio. Second, we introduce a mapping function that can replace an infeasible agent action in each state with a similar and valuable action to derive a reasonable trading strategy. Last, we introduce a method by which an agent simulates all feasible actions and learns about these experiences to utilize the training data efficiently.