Automated structural design methods for reinforced concrete (RC) beam members have been widely studied with various techniques to date. Recently, artificial intelligence has been actively applied to various engineering fields. In this study, machine learning (ML) is adopted to make automated structural design model for RC beam members. Among various machine learning methods, a supervised learning was selected. When a supervised learning is applied to development of ML-based prediction model, datasets for training and test are required. Therefore, the datasets for rectangular and t-shaped RC beams was constructed by commercial structural design software of MIDAS. Five supervised learning algorithms, such as Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost) were used to develop the automated structural design model. Design moment (Mu), design shear force (Vu), beam length, uniform load (wu) were used for inputs of structural design model. Width and height of the designed section, diameter of top and bottom bars, number of top and bottom bars, diameter of stirrup bar were selected for outputs of structural design model. Performance evaluation of the developed structural design models was conducted using metrics sush as root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), and coefficient of determination (R2). This study presented that random forest provides the best structural design results for both rectangular and t-shaped RC beams.

본 연구에서는 기 선발한 Enterobacter asburiae ObRS-5 균주를 1×108 cfu mL-1 농도로 고추에 관주 처리했을 때 Phytophthora capsici에 의한 고추역병을 74.6% 방제하는 효과가 있었다. E. asburiae ObRS-5 균주에 의한 고추역병 방제 메커니즘을 확인하기 위해 고추의 PR1, PR4 및 PR10 유전자를 특이적으로 증폭하는 프라이머를 이용하여 quantitative PCR을 수행하였다. 그 결과 E. asburiae ObRS- 5 균주를 처리한 고추에서 대조구와 비교하여 상기 세 가지 유전자의 발현이 모두 높은 수준을 유지하였다. 또한 E. asburiae ObRS-5 균주는 고추의 생육을 억제하지 않으면서 ISR 반응을 유도하는 것으로 나타났다. 이러한 결과를 통하여 P. capsici이 침입할 때 E. asburiae ObRS-5 균주가 매개 하는 ISR 메커니즘을 통해 Phytophthora 역병의 제어가 가능한 것으로 사료된다.

We report the effect of the chain length of carboxylic acid on the photoluminescence(PL) of /ZnS nanocrystals. /ZnS nanocrystals with emission wavelength ranging from 566 nm through 583 nm were synthesized with zinc acetate and carboxylic acids with various chain length. In this study, /ZnS nanocrystals prepared using long chain carboxylic acid showed more improved PL intensity. The origin of strong photoluminescence of the nanocrystals prepared with zinc acetate and long chain carboxylic acid was ascribed to improved size distribution due to strong reactivity between long chain carboxylic acid and zinc acetate.