http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
An Algorithm Study on Petri Nets based Accordion Keyboard Instruments Music for Flexible Play
Jaeyoung Lim,Jongkun Lee 대한전자공학회 2009 ITC-CSCC :International Technical Conference on Ci Vol.2009 No.7
The existing musical enumeration and process were decided by repetition, synchrony, order, system, time, language and other elements, but especially, they seem to be insufficient in analyzing and utilizing the problems when an accordion, a keyboard musical instrument, is performed. Petri Net is a tool which allows to describe and process musical objects within both analysis /composition and performing environments. This paper express a relation that bass, bellow, high-tone of Accordion Keyboard Music Instruments used Petri net. Bass is connected left-finger and bellow is connected harmony and emotion of Accordion music, Keyboard of high-tone is connected right-finger. It is very interesting that bass, bellow, keyboard can be synthesized by locating circuit followed by adding opportunity.
Deeper Integrative Neural Network Analysis for Multi-level Omics Data
Jayeon Lim,Junsang Cho,JaeYoung Kim,Jiyeon Kim,SungHwan Kim 계명대학교 자연과학연구소 2019 Quantitative Bio-Science Vol.38 No.2
Recently, various machine learning methods have emerged for analyzing and interpreting the ever-expanding genetic data. In addition, new analytical tools for machine learning using statistical models, are being developed. Lim et al. [1] proposed the integrative deep learning to find the differentially expressed (DE) biomarkers using deep neural network with a single hidden layer. This method consists of the input layer, a hidden layer, the consolidation layer, and the output layer. They found that integrative deep learning method is stable and robust for analysis of the variation in the simulation datasets. In this study, we expanded the integrative deep learning method by including an additional hidden layer. The present expanded method consists of the input layer, two hidden layers, the consolidation layer and the output layer. The purpose of this study is to investigate the effect of the additional hidden layers on the performance of the previous method (integrative deep learning). We conducted a simulation study and compared the results with those from deep neural network with one hidden layer.
임재영(Jaeyoung Lim),김대식(Daesik Kim) 한국추진공학회 2016 한국추진공학회 학술대회논문집 Vol.2016 No.12
항공용 가스터빈에서의 배출물 규제가 강화됨에 따라 환형 연소 시스템에서도 희박 예혼합 방식의 채택이 늘어나면서 연소불안정에 대한 관심이 증가하고 있다. 본 연구에서는 환형 시스템에서 열음향 문제를 모델링하기 위하여 자체 3D 유한요소해석을 모델 개발을 통하여 음향장을 해석하였고, 다양한 음향 모드를 벤치마크 연소기의 실험 결과와 비교/검증하였다. 또한 연소실의 횡방향 음향 모드와 노즐로부터의 축방향 섭동 간의 커플링 메커니즘을 규명하였다. 해석 결과, 연소실의 횡방향 모드는 노즐의 음향 경계 조건의 영향을 크게 받게 되고, 노즐에서의 압력 분포 역시 연소실의 압력장과 밀접한 관련이 있는 것으로 나타났다. Due to the enhanced emission regulations in aero-engines, an annular gas turbine combustor has increasingly adapted lean premixed technology, and also has a critical issue in combustion instability. The current study developed in-house 3D FEM code in order to model thermoacoustic problems in the annular system and compared the acoustic field calculation results with measured ones from a benchmakr combustor. In addition, the coupling mechanism between the transverse mode in the combustor and the longitudinal mode was investigated. As a result, it was found that the transverse waves in the combustor were strongly affected by the nozzle acoustic impedances, as well, the pressure distributions were closely related with the combustor acoustic pressure field.
음향 경계 조건이 가스터빈 연소기에서의 연소불안정에 미치는 영향
임재영(Jaeyoung Lim),김대식(Deasik Kim),김성구(Seong-Ku Kim),차동진(Dong Jin Cha) 한국추진공학회 2015 한국추진공학회지 Vol.19 No.4
This study predicts the basic characteristics of combustion instabilities in a gas turbine lean premixed combustor using ASCI3D code which is a FEM(Finite Element Method)-based Helmholtz solver. The prediction results show the good agreement with the measured data in modeling the overall combustion instability features, however, the code is found to overpredict the unstable conditions. As one of the efforts to improve the model accuracy, the effects of acoustic boundary conditions on the instability growth rate are analyzed. As a result, it is shown that the acoustic reflection coefficient has a great impact on the instability and the prediction accuracy can be enhanced by defining the precise acoustic conditions.