• 한국약용작물학회지
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• 제12권2호
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• pp.129-134
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• 2004

Optimal culture conditions for efficient in vitro propagation and polysaccharide production of Orostachys japonicus were established. The highest growth yield was achieved in 1/2 MS medium, while the lowest growth yield was obtained in 4 MS medium. The patterns of polysaccharide formation were a little similar in all cases, but on MB5 medium, the po]ysaccharide contents of plant were higher than others. Among the modified nitrate levels, effective growth level were obtained in 1/4 N and 1/2 N. High contents of polysaccharide were obtained in 4 N. Different concentration of potassium and calcium did not improve the growth and polysaccharide production. The micropropagated shoots were successfully acclimatized artificial soils.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2011년도 제37회 추계학술대회논문집
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• pp.912-918
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• 2011

본 연구는 다중 접착계면에서의 초음파 전달 현상을 시스템 응답함수의 일반식을 사용하여 시뮬레이션을 수행하였고, 추진기관의 모의결함시편을 제작하여 모델링의 결과를 검증하였다. 실험 결과 추진제-라이너 미접착 결함을 초음파 펄스 반사법으로 검출할 수 있었으며, 시뮬레이션 결과와 측정된 초음파 파형이 잘 일치함을 알 수 있었다.

• Structural Engineering and Mechanics
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• 제23권3호
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• pp.233-247
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• 2006

Most codes of practice state that for large in-plane structures it is necessary to account for the spatial variability of earthquake ground motion. There are essentially three effects that contribute for this variation: (i) wave passage effect, due to finite propagation velocity; (ii) incoherence effect, due to differences in superposition of waves; and (iii) the local site amplification due to spatial variation in geological conditions. This paper discusses the procedures to be undertaken in the time domain analysis of a cable-stayed bridge under spatial variability of earthquake ground motion. The artificial synthesis of correlated displacements series that simulate the earthquake load is discussed first. Next, it is described the 3D model of the International Guadiana Bridge used for running tests with seismic analysis. A comparison of the effects produced by seismic waves with different apparent propagation velocities and different geological conditions is undertaken. The results in this study show that the differences between the analysis with and without spatial variability of earthquake ground motion can be important for some displacements and internal forces, especially those influenced by symmetric modes.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권7호
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• pp.327-333
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• 2002

In this study, we developed a snoring detection algorithm that detects snores automatically. It consists of preprocessing and snoring detection part. The preprocessing part is composed of a noise removal part using spectrum subtraction, and segmentation part, and computation part of temporal and spectral features. And the snoring detection part decides whether detected blocks are snores with BPNN(Back-Propagation Neural Network). BPNN with one hidden layer and one output layer, is trained with data of 7 subjects and tested with data of 11 subjects of total 18 subjects. The proposed algorithm showed a Sensitivity of 90.41% and a Predictive Positive Value of 84.95%.

• 한국약용작물학회지
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• 제15권5호
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• pp.315-318
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• 2007

An effective rapid propagation method was established through in vitro cultures of the medicinal plant, Cudrania tricuspidata. In vitro plantlets were obtained from in vitro germinated seeds. The various levels of cytokinins (BAP, Kinetin and TDZ) were tested on multiple shoot formation from plantlets. BAP (1.0 mg/l) treatment induced highest number of multiple shoots. Single shoot cultures gave higher initial shoot numbers than 5 shoots per culture. Among the various culture media, the shoot elongation was optimal on 2 MS basal medium without growth regulators. The IAA (2.0 mg/l) treatment induced highest number of roots. IBA (2.0 mg/l) treatment more promoted in vitro root growth than other concentrations. Rooted shoots were transferred directly to small pots with an artificial soil and successfully acclimatized.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권10호
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• 재무관리연구
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• 제19권2호
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• pp.211-231
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• 2002

본 연구의 목적은 VECM(Vector Error Correction Model)과 인공지능모형(Artificial Neural Networks)을 이용하여 우리나라 증권시장과 거시경제 변수들과의 장기적 관계에 대한 설명력을 비교해보고자 함에 있다. VECM이 APT(Arbitrage Pricing Theory)에 기초를 둔 선형동학모형이라고 한다면, 인공지능모형은 비모수적 비선형모형이라는 점에서, 두 방법론의 분석결과를 직접 비판하는 것은 의미있는 연구라고 할 수 있다. 인공지능모형을 주로 활용하는 선행연구들에 의하면, 증권시장은 시장의 특이패턴들로 인해 계량경제학적 접근인 선형 모형보다는 인공지능모형을 통해 증권시장의 움직임을 설명하고 예측하는 것이 더 바람직할 수도 있다는 것이다. 따라서, 본 연구에서는 VECM분석에서 자료의 안정성을 검증하고, 공적분 백터를 발견한 이후, 장기적 균형관계의 실증적 분석을 하였다. 그리고, 인공지능모형에서는 delta rule과 Sigmoid 함수를 이용한 GRNN(General Regression Neural Net)과 Back-Propagation등의 방법들을 활용하였다. 이러한 분석결과, Back-Propagation 모형이 다른 모든 모형들보다도 더 우수한 설명력을 보여주고 있었다. 이러한 결과들은 인공지능모형이 동태적인 선형 모형보다도 더 우수한 설명력을 제공할 수 있는 가능성을 보여주고 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.109.4-109
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• 2001

We have developed a laser ultrasonic system for visualization of elastic waves propagating on a solid surface, in order to visualize ultrasonic waves propagating on opaque media. This system can produce a series of successive images as an animation of wave propagation, because of scanning an optical heterodyne probe to measure surface transient displacements. Using this visualization technique, we observed the scattering and diffraction of ultrasonic waves around various shapes of artificial defects, and examined its application to nondestructive inspection. This imaging system provides various kinds of visualization images such as propagation image, amplitude image, arrival time image and velocity image. We have been confident that this technique is available for nondestructive inspection and materials ...

• 한국응용과학기술학회지
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• 제25권4호
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• pp.438-445
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• 2008

For recipe prediction of colorant proportion showing nonlinear behavior, we modeled the effects of colorant proportion of basic colors on the target colors and predicted colorant proportion necessary for making target colors. First, colorant proportion of basic colors and color information indicated by the instrument was applied by a linear model and a multi-layer perceptrons model with back-propagation learning method. However, satisfactory results were not obtained because of nonlinear property of colors. Thus, in this study the neuro-fuzzy model with merit of artificial neural networks and fuzzy systems was presented. The proposed model was trained with test data and colorant proportion was predicted. The effectiveness of the proposed model was verified by evaluation of color difference(${\Delta}E$).

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1375-1384
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• 2014

Flashover of power transmission line insulators is a major threat to the reliable operation of power system. This paper deals with the flashover prediction of polymeric insulators used in power transmission line applications using the novel condition monitoring technique developed by PD signal time-frequency map and neural network technique. Laboratory experiments on polymeric insulators were carried out as per IEC 60507 under AC voltage, at different humidity and contamination levels using NaCl as a contaminant. Partial discharge signals were acquired using advanced ultra wide band detection system. Salient features from the Time-Frequency map and PRPD pattern at different pollution levels were extracted. The flashover prediction of polymeric insulators was automated using artificial neural network (ANN) with back propagation algorithm (BPA). From the results, it can be speculated that PD signal feature extraction along with back propagation classification is a well suited technique to predict flashover of polymeric insulators.