전단자극 시 나트륨-칼슐 교환체 활성에 의한 횡방향 심방 근세포 Ca2+ 웨이브의 발생

김준철, 왕준, 손민정, 김경희, 우선희 충남대학교 약학대학 의약품개발연구소 2017 藥學論文集 Vol.32 No.-

In the present study, we investigated possible mechanism for the triggered global CaH wave from local Ca2+ wave in atrial myocytes under shear stress. Shear stress was applied onto single cells isolated from rat atria and two-dimensional confocal Ca2+ imaging was performed to measure Ca2+ signal. Shear stress of 16 dyn/cm2 induced local Ca2+ wave, which was followed by a rapid transverse global Ca2+ wave inhibition of Na + -ci+ exchange using KB-R7943 suppressed the occurrence of rapid transverse wave ob served under shear stress, but not the shear-induced local wave. in the presence of this chemical local wave was developed to global wave under shear stress which results in slower time to peak of peripheral and central CaH transients. As the preceding local Ca"+ wave signal was higher, the latency of the occurrence of transverse global wave was shorter, suggesting Ca2+ dependence of transverse Ca2+ wave. The results sug-gest that shear stress may activate Na+ -Ca2+ exchange via local CaZ+ wave, triggering the rapid global Ca2+ wave

On-line 학습 신경회로망을 이용한 열간 압연하중 예측

손준식,이덕만,김일수,최승갑 한국공작기계학회 2005 한국생산제조학회지 Vol.14 No.1

In the face of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term learning and short-term learning was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

방사형기저함수망을 이용한 열간 사상압연의 압연하중 예측에 관한 연구

손준식,이덕만,김일수,최승갑 한국공작기계학회 2003 한국공작기계학회 추계학술대회논문집 Vol.2003 No.-

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analysis the performance of applied neural network, the comparison with the measured rolling force and the predicted results using two different neural networks - RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

방사형기저함수망을 이용한 표면 비드폭 예측에 관한 연구

손준식,김인주,김일수,김학형 한국공작기계학회 2004 한국공작기계학회 추계학술대회논문집 Vol.2004 No.-

Despite the widespread use in the various manufacturing industries, the full automation of the robotic CO₂ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an Radial basis function network model to predict the weld top-bead width as a function of key process parameters in the robotic CO₂ welding. and to compare the developed model and a simple neural network model using two different training algorithms in order to verify performance. of the developed model.

방사형기저함수망을 이용한 열간 사상압연의 압연하중 예측에 관한 연구

손준식,이덕만,김일수,최승갑 한국공작기계학회 2004 한국생산제조학회지 Vol.13 No.6

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analyze the performance of applied neural network, the comparison with the measured rolling force and the predicted results using two different neural networks-RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

Monte Carlo 시뮬레이션을 이용한 이온 주입시의 점결함 분포의 계산

손명식,이준하,변기량,황호정 중앙대학교 기술과학연구소 1995 기술과학연구소 논문집 Vol.25 No.-

이온 주입시의 점결함 분포를 간접적으로 계산하기 위해 단결정 실리콘에서의 3차원 이온 주입 시뮬레이터인 TRICSI (TRansport Ions in Crystal Slilicon) Monte Carlo 코드를 확장하여 Boron 이온 주입시의 에너지와 dose에 따른 불순물(particle) 및 점결함 분포(point defect)를 계산하였다. 결함 분포는 Modified Kinchin-Pease equation을 단결정 실리콘에 적용하여 displacement damage에 의해 발생한 Frenkel Pair(vacancy-interstitial)분포를 계산하였으며 이온 주입시의 웨이퍼 온도에 의한 Frenkel Pair 소멸 효과는 고려하지 않았다. 계산 결과는 3차원 각면으로의 2차원 투영 불순물 농도로 표현하고 주입된 dose와 에너지에 다른 마스크 주입시의 에너지 및 dose 의존성 도펀트 분포와 이에 따른 damage 분포를 이해하는 데 중요한 정보가 될 것으로 기대된다. We extended our ion implantation simulator, TRICSI (TRansport lons in Crystal Slilicon) Monte Carlo(MC) code, and indirectly calculated particle and its generating point defect distributions depending on energy and dose during boron implantation into <100> single0crystal silicon. The point defect distribution of Frenkel Pair(vacancy-interstitial) was abtained by applying the modified Kinchin-Pease equation, which usually uses in MC simulation in amorphous target, to MC simulation in crystalline silicon. We did not considered the annihilation of Frenkel Pairs due to wafer temperature. The calculated results were projected onto each free-dimensional plane, presented as two-dimensional concentration profile on it. The particle concentration profile was presented with typical open mask structure. We expect that these results help understand the dopant and its generating damage distributions depending on energy and dose during boron implantation.

금속기지 복합재료의 제조 및 성형시에 발생하는 열적잔류응력의 정량적 평가 및 예측에 관한 이론적 연구 : (Case 1:Two-Dimensional In-Plane Fiber Distribution) (제1보:강화재가 2차원 평면상태로 분포하는 경우)

손봉진,이준현 韓國非破壞檢査學會 1997 한국비파괴검사학회지 Vol.17 No.2

단섬유강화금속복합재료는 최근 항공기, 자동차산업에 있어서 관심의 대상이 되고 있는 재료중의 하나이나 재료의 제조 및 성형주에 재료내의 기지재 및 강화재의 열팽창계수의 차이로 인해 재료 내부에 발생되는 열적잔류응력으로 이한 재료 특성의 변화로 실제적인 재료 적용상에 많은 문제점들이 보고되고 있다. 이와같은 금속복합재료의 잔류응력의 평가에는 몇가지 비파괴적 방법이 적용되고 있으나 그 측정에 많은 어려움이 보고되고 있다. 따라서 금속복합재료의 보다 실제적인 응용을 위하여는 이와같은 열적잔류응력을 평가하기 위한 이론적 모델의 확립이 요구된다. 본 연구에 있어서는 비방향성을 가진 강화재가 2차원 평면 상태로 기지재내에 존재하는 단섬유강화금속복합재료에 있어서 재료에 균일한 온도 변화가 주어질 때 기지재와 강화재의 열팽창계수의 차로 인해 재료 내부에 발생하는 열적잔류응력을 평가, 예측하기 위한 이론적 탄성 모델을 확립하고자 한다. 본 연구에서 해석하고자 하는 이론 모델은 Eshelby의 등가 개재물 방법을 토대로 하고 있으며 과거 제안되고 있는 모델을 포함하는 보다 일반성을 가지는 해석 모델로서, 이 해석 모델을 이용하여 열적잔류응력에 미치는 강화재의 체적률, 종횡비, 분포 상태, 분포cut-off 각도들에 대한 각 인자의 영향을 검토하였다. 그 결과 강화재의 체적률, 종횡비, cut-off각도들이 강화재의 분포 상태보다도 금속복합재료의 열적잔류응력에 미치는 영향이 현저함을 알 수 있었다. Although discontinuously reinforced metal matrix composite(MMC) is one of the most promising materials for applications of aerospace, automotive industries, the thermal residual stresses developed in the MMC due to the mismatch in coefficients of thermal expansion between the matrix and the fiber under a temperature change has been pointed out as one of the serious problem in practical applications. There are very limited nondestructive techniques to measure the residual stress of composite materials. However, many difficulties have been reported in their applications. Therefore it is important to establish analytical model to evaluate the thermal residual stress of MMC for practical engineering application. In this study, an elastic model is developed to predict the average thermal residual stresses in the matrix and fiber of a misoriented short fiber composite. The thermal residual stresses are induced by the mismatch in the coefficient of the thermal expansion of the matrix and fiber when the composite is subjected to a uniform temperature change. The model considers two-dimensional in-plane fiber misorientation. The analytical formulation of the model is based on Eshelby's equivalent inclusion method and is unique in that it is able to account for interactions among fibers. This model is more general than past models to investigate the effect of parameters which might influence thermal residual stress in composites. The preset model is to investigate the effects of fiber volume fraction, distribution type, distribution cut-off angle, and aspect ratio on thermal residual stress for in-plane fiber misorientation. Fiber volume fraction, aspect ratio, and distribution cut-off angle are shown to have more significant effects on the magnitude of the thermal residual stresses than fiber distribution type for in-plane misorientation.

작은 피질하 병변에 대한 정위적 개두술 및 경-구 접근법

손병철,김문찬,이관성,박춘근,홍용길,강준기 대한신경외과학회 1999 Journal of Korean neurosurgical society Vol.28 No.12

GMA용접에서 유전자 알고리즘을 이용한 비드높이 예측 모델 개발에 관한 연구

손준식,김일수,장경천,이동길 한국공작기계학회 2006 한국공작기계학회 추계학술대회논문집 Vol.2006 No.-

Gas metal arc welding process has been chosen as a metal joining technique due to the wide range of usable applications, cheap consumables and easy handling. Three main indicators such as arc voltage, welding speed and welding current have a big influence in the quality welding. Since all these factors affect the quality of the welded joining parts, the effect of these parameters was investigated experimentally. In this paper, an attempt has been made to develop the predicted models (quadratic and cubic) for bead height using genetic algorithm. Performance of the developed models were proved to be compared to the regression equation.

건설기업의 지식경영적용상의 특성과 성패요인에 관한 연구

손정욱,윤준선,백준홍 대한건축학회 2003 대한건축학회 학술발표대회 논문집 - 계획계/구조계 Vol.23 No.1

Many construction E&C companies have recognized lack of productivity in the execution project. For improvement of productivity in construction industry, they have applied KM to construction industry. As a result, the application of KM in Korea is transition period. There is many difficulty for the KM but advantage also. In this study, consider KM and find difficulty and advantage for application to the Korean construction industry, finally categorize critical success factor of KM.