• 접착 및 계면
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• 제14권1호
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• pp.21-27
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• 2013

셀룰로오스계 레이온섬유 또는 레이온직물은 좁은 온도범위의 안정화공정 동안에 열분해가 매우 빠르게 진행된다. 그러므로 레이온계 탄소섬유를 제조하는데 있어 안정화단계는 매우 중요한 핵심공정이다. 따라서 본 연구에서는 셀룰로오스계 레이온직물의 중량감소, 화학조성, 미세구조 및 texture 변화에 미치는 등온 안정화공정과 초음파세척의 영향을 조사하였다. $200{\sim}240^{\circ}C$ 영역에서 행한 등온 안정화공정의 온도는 레이온직물을 안정화 소요시간, 탄소함량, 산소함량, 셀룰로오스 구조 변화 그리고 직물 texture에 큰 영향을 주었다. 등온 안정화공정 전에 물을 이용한 초음파세척은 레이온직물의 안정화공정 시간을 단축하고, 안정화 후 직물의 탄소함량을 증가하고, 산소함량을 감소시키며, XRD 분석 패턴을 변화시키는데 역할을 하는 것으로 조사되었다. 또한 초음파세척은 등온 안정화공정시 발생하는 레이온직물의 빠른 중량감소 현상을 더디게 하고, 열수축을 감소시켜, 직물의 급격한 물리적 변화의 완화에도 기여하는 것으로 사료된다.

• 정보저장시스템학회논문집
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• 제6권2호
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• pp.74-78
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• 2010

In this paper, 2-axis driving mechanism, which uses voice coil motor (VCM), is proposed to measure the friction force. The proposed VCM actuator consists of two parts; structural part and magnetic circuit part. Structural part is simplified to perform the friction experiments. Magnetic circuit part is composed of two parts. The experiments are accomplished by changing the mass of moving part. Through the experiments, optimal dimension is selected. Finally, the experimental results are verified and the optimal case is applied to the 2-axis driving mechanism, optical image stabilization actuator.

• 한국자기공명학회논문지
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• 제23권3호
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• pp.67-72
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• 2019

Caveolae are small plasma membrane invaginations that play many roles in signal transduction, endocytosis, mechanoprotection, lipid metabolism. The most important protein in caveolae is the integral membrane protein, caveolin, which is divided into three families such as caveolin 1, caveolin 2, and caveolin 3. Caveolin 1 and 3 are known to incorporate palmitate through linkage to three cysteine residues. Regulation of the protein palmitoylation cycle is important for the cellular processes such as intracellular localization of the target protein, membrane association, conformation, protein-protein interaction, and activity. However, the detailed aspect of individual palmitoylation has not been studied. In the present work, the role of each lipid modification at three cysteines was studied by NMR. Our results suggest that each lipid modification at the natively palmitoylation site has its own roles. For example, lipidations to C106 and C129 are play a role in structural stabilization, however, interestingly, lipid modification to C116 interrupts the structural stabilization.

• Journal of Advanced Marine Engineering and Technology
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• 제25권2호
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• pp.383-394
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• 2001

The stabilization control of inverted pendulum (IP) system is difficult because of its nonlinearity and structural unstability. In this paper, an Evolving Neural Network Controller (ENNC) without Error Back Propagation (EBP) is presented. An ENNC is described simply by genetic representation using an encoding strategy for types and slope values of each active functions, biases, weights and so on. By an evolutionary programming which has three genetic operation; selection, crossover and mutation, the predetermine controller is optimally evolved by updating simultaneously the connection patterns and weights of the neural networks. The performances of the proposed ENNC(PENNC)are compared with the one of conventional optimal controller and the conventional evolving neural network controller (CENNC) through the simulation and experimental results. And we showed that the finally optimized PENNC was very useful in the stabilization control of an IP system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 춘계학술대회논문집
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• pp.488-493
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• 2005

In gun stabilization systems, the torque comes from the unbalance mass of gun and the base acceleration is an important source of disturbance which degrades stabilization performance. Fatigue of gear train is another important factor affecting structural safety problems. In this paper, a feedback control gain is designed by optimal control weighting to difference between motor and gun velocity, and a feedforward controller using FXLMS algorithm is adopted to investigate those problems. Experimental results show that the feedforward compensator based on FXLMS can reduce the disturbance effects. The directional convergence property according to initial conditions of the FXLMS is also shown through experiments.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1327-1334
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• 1999

The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.551-558
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• 2008

This paper deals with the real-time stable walking for a humanoid robot, ISHURO-II, on uneven terrain. A humanoid robot necessitates achieving posture stabilization since it has basic problems such as structural instability. In this paper, a stabilization algorithm is proposed using the ground reaction forces, which are measured using FSR (Force Sensing Resistor) sensors during walking, and the ground conditions are estimated from these data. From this information the robot selects the proper motion pattern and overcomes ground irregularities effectively. In order to generate the proper reaction under the various ground situations, a fuzzy algorithm is applied in finding the proper angle of the joint. The performance of the proposed algorithm is verified by simulation and walking experiments on a 24-DOFs humanoid robot, ISHURO-II.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3013-3015
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions, At the same time, the fine tunings of their gain parameters are also troublesome, Thus, in this paper, an Evolving Neural Network ControlleY(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm (RVEGA) was presented for stabilization of an IP system with nonlinearity, This proposed ENNC was described by a simple genetic chromosome. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2001년도 춘계학술대회 논문집
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• pp.243-248
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• 2001

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Thus, in this paper, an Evolving Neural Network Controller(ENNC) without Error Back Propagation(EBP) is presented. An ENNC is described simply by genetic representation using an encoding strategy for types and slope values of each active functions, biases, weights and so on. By an evolutionary programming which has three genetic operation; selection, crossover and mutation, the predetermine controller is optimally evolved by updating simultaneously the connection patterns and weights of the neural networks. The performances of the proposed ENNC(PENNC) are compared with the ones of conventional optimal controller and the conventional evolving neural network controller(CENNC) through the simulation and experimental results. And we showed that the finally optimized PENNC was very useful in the stabilization control of an IP system.

• KDI Journal of Economic Policy
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• 제14권1호
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• pp.37-60
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• 1992

본고(本稿)에서는 실질(實質)GNP, 총통화(總通貨), GNP디플레이터, 전산업명목임금(全産業名目賃金)으로 구성된 체계에서의 구조적(構造的) 벡터자기회귀모형(自己回歸模型)을 추정하였다. 구조적(構造的) 요인(要因)으로는 총수요(總需要)(DEMAND), 총통화(總通貨)(SUPPLY), 안정화정책(安定化政策)(STBLZTN), 그리고 임금충격(賃金衝擊)(WAGE)을 추정, 복원하였다. 모형내(模型內)의 모든 변수(變數)는 단위근(單位根)을 하나씩 보유하고 있고, 4변수간에 공적분(共積分)이 존재함도 확인되었다. 구조요인(構造要因)을 복원한 뒤에는 이를 이용하여 충격반응분석(衝擊反應分析)을 행해 각 요인의 동태적인 효과를 살펴보았다. 추정결과는 대체적으로 표준적인 케인즈모형(模型)과 부합하였으나 때때로 한국경제(韓國經濟)에만 독특한 현상도 발견되었다.