This study explores modern portfolio theory by integrating the Black-Litterman portfolio with time-series clustering, specificially emphasizing K-shape clustering methodology. K-shape clustering enables grouping time-series data effectively, enhancing the ability to plan and manage investments in stock markets when combined with the Black-Litterman portfolio. Based on the patterns of stock markets, the objective is to understand the relationship between past market data and planning future investment strategies through backtesting. Additionally, by examining diverse learning and investment periods, it is identified optimal strategies to boost portfolio returns while efficiently managing associated risks. For comparative analysis, traditional Markowitz portfolio is also assessed in conjunction with clustering techniques utilizing K-Means and K-Means with Dynamic Time Warping. It is suggested that the combination of K-shape and the Black-Litterman model significantly enhances portfolio optimization in the stock market, providing valuable insights for making stable portfolio investment decisions. The achieved sharpe ratio of 0.722 indicates a significantly higher performance when compared to other benchmarks, underlining the effectiveness of the K-shape and Black-Litterman integration in portfolio optimization.

본 연구에서는 해수를 유도용액으로 사용하고 하수처리수를 공급수로 사용하는 정삼투막 공정의 유기/바이오 오염물에 의한 막오염을 저감하기 위해 폴리도파민/탄소 나노 튜브 복합 분리막을 제작하였다. 분리막은 기존 계면중합반응에 탄소 나노 튜브를 첨가하여 초박형 복합 분리막을 제조한 후, 폴리도파민으로 코팅시켜 제조하였다. 제작 된 분리막은 알긴산나트륨(Sodium alginate)용액과 미생물(Pseudomonas aeruginosa PA01) 부착 실험을 통하여 수투과도와 막오염도를 평가하였다. 그 결과, 폴리도파민/탄소 나노 튜브 복합 분리막은 복합되지 않은 분리막에 비하여 높은 수투과도와 낮은 막오염 성능을 보였다.