• The Bulletin of The Korean Astronomical Society
• /
• v.36 no.1
• /
• pp.38.1-38.1
• /
• 2011

Bright rims are one of the most unknown part of a filament nowadays. Many models tried to explain the environments, but there is no commonly acceptable model. Many survey observations have been performed to find various characteristics of the bright rim statistically, but there was only one spectroscopic observation to understand phenomena of the bright rim. We observed a bright rim on June 25, 2010 using FISS installed in NST, Big Bear Solar observatory. FISS can obtain a couple of wavebands data simultaneously with short time cadence and fine resolution(~ 0.1", expected) with Adaptive Optics. By applying the cloud model, we found source function, optical thickness, temperature and non-thermal velocity of the region from the spectra of Ha and CaII 8542 lines. We discuss the physical implication of these measurements on the nature of bright rims of filaments.

• KIEE International Transactions on Electrophysics and Applications
• /
• v.5C no.3
• /
• pp.138-142
• /
• 2005

In this paper, we compared recognition rates between NN(neural networks) and clustering method as a scheme of off-line PD(partial discharge) diagnosis which occurs at the stator coil of traction motor. To acquire PD data, three defective models are made. PD data for classification were acquired from PD detector. And then statistical distributions are calculated to classify model discharge sources. These statistical distributions were applied as input data of two classification tools, BP(Back propagation algorithm) and ANFIS(adaptive network based fuzzy inference system) pre-processed FCM(fuzzy c-means) clustering method. So, classification rate of BP were somewhat higher than ANFIS. But other items of ANFIS were better than BP; learning time, parameter number, simplicity of algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.38 no.11
• /
• pp.888-895
• /
• 1989

A novel model reference adaptive control (MRAC) scheme for electrical servo drives is proposed, in which the control input is synthesized without any parameter identification mechanism and a PI controller is inserted ahead of the plant to reduce the steady state chattering. The proposed scheme is shown to be asymptotically stable in the case where the load torque disturbance satisfies a certan condition. An application to a permanent magnet synchronous motor drive shows that the output error between the plant and the reference model tends to zero and the chattering is greatly reduced.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07b
• /
• pp.868-870
• /
• 2005

본 논문은 포즈가 취해진 얼굴의 정확한 특징점 추출을 위하여 적응적인 평균 모양 방법을 이용한 ASM(Active Shape Model)을 제안한다. ASM은 사람 얼굴의 모양을 모델링하기 위하여 통계학상의 모양 모델을 이용한다. 통계학상의 모양 모델의 평균 모양은 입력 영상의 얼굴 포즈와 관계없이 하나로 고정되어 있으며, 이는 모양 모델 제한 조건 검사 및 복원과정에서 잘못된 결과를 만드는 원인이 된다. 이러한 문제를 해결하기 위하여 입력 영상의 얼굴 모양에 적응적인 평균 모양을 제안하며, 실험을 통해 제안한 방법이 고정된 평균 모양 방법의 문제를 해결하고 특징점 추출 성능을 향상시킴을 보였다.

• Proceedings of the KIEE Conference
• /
• 1999.07g
• /
• pp.2929-2931
• /
• 1999

In this paper, an adaptive fuzzy inference and HCM(Hard C-Means) clustering method are used for on-line fuzzy modeling of nonlinear and complex system. Here HCM clustering method is utilized for determining the initial parameter of membership function of fuzzy premise rules and also avoiding overflow phenomenon during the identification of consequence parameters. To obtain the on-line model structure of fuzzy systems. we use the recursive least square method for the consequent parameter identification. And the proposed on-line identification algorithm is carried out and is evaluated for sewage treatment process system.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2085-2087
• /
• 2003

A new interacting multiple model (IMM) method based on intelligent input estimation (IIE) is proposed for tracking a maneuvering target. In the proposed method, the acceleration level of each sub-filter is determined by IIE using the fuzzy system, which is optimized by the genetic algorithm (GA). The tracking performance of the proposed method is compared with those of the input estimation (IE) technique and the adaptive interacting multiple model (AIMM) method in computer simulations.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.221-223
• /
• 1993

The Hopfield model is defined as an adaptive dynamic system. In this paper we propose a modified neural network which is capable of solving linear programming problems and a set of linear equations. The model is directly implemented from the given system, and solves the problem without calculating the inverse of the matrices. We get the better stability results by the addition of scaling property and by using the nonlinearities in the linear programming neural networks.

• Genomics & Informatics
• /
• v.3 no.3
• /
• pp.63-67
• /
• 2005

Adaptive responses to diverse microbial pathogens might be limited in relatively few types. Host cell responses to pathogens are believed to be patterned or stereotyped along with species or class. We tried to compose the host response to Mycoplasma in terms of cellular gene expression. Although gene expression profile of two host HeLa and 293 cells were quite different each other, 30 genes were differentially expressed by mycoplasma infection in both of HeLa and 293 cells. Six of them (PR48, MADH4, MKPX, CRK, RBM7, NEK3) were related to cell cycle or proliferation. Another category of genes like IL1 HY1, KLRF1, TNFSF14, GBP1 were host defense to elicit immune responses. With this set of genes, we establish the prediction model for mycoplasma contamination.

• Journal of the korean Society of Automotive Engineers
• /
• v.13 no.1
• /
• pp.35-45
• /
• 1991

A linear quarter model of a vehicle suspension system is built and simulated. Especially the so-called sensitivity analysis is conducted in order to show its applicability to design problems, and sensitivity function is determined in the frequency domain. The change of frequency response function is predicted, which depends on the design parameter variation and the property is verified by computer simulation. Typical performance measures, namely, sprung mass acceleration, suspension deflection, and tire deflection are examined. The vehicle model is analyzed for ist performance sensitivity as a function of the system's feedback gains. The variable feedback gains are selected as the spring and damping coefficients. Frequency response, RMS response, and performance index of the performance evaluation variables are considered and three-dimensional and contour plots of response surfaces are formed to examine output sensitivity to suspension feedback. Performance trade-offs over the entire frequency spectrum are identified from the FRF, and that between ride quality and handling characteristics are examined from the RMS responses.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.321-322
• /
• 2007

본 논문에서는 로봇과 인간의 인터액션을 위해 인간 몸의 실루엣 및 액티브 스켈레톤 추출 기법을 제안한다. 연속된 이미지 정보로 부터 얻어진 옷영역등의 정보에서 background subtraction를 이용한 adaptive fusion을 통해 추출된 인간 몸의 실루엣을 바탕으로 active contour와 가상 신체 모델인 skeleton model을 응용하여 작은 움직임에 보다 강한 active skeleton model을 이용하여 인간 몸의 특징 점 위치를 추출하는 방법을 한다.