• JSTS:Journal of Semiconductor Technology and Science
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• 제8권3호
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• pp.264-275
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• 2008

Electron mobility has been investigated theoretically in undoped double-gate (DG) MOSFETs of different channel architectures: a relaxed-Si DG SOI, a strained-Si (sSi) DG SSOI (strained-Si-on-insulator, containing no SiGe layer), and a strained-Si DG SGOI (strained-Si-on-SiGe-on-insulator, containing a SiGe layer) at 300K. Electron mobility in the DG SSOI device exhibits high enhancement relative to the DG SOI. In the DG SGOI devices the mobility is strongly suppressed by the confinement of electrons in much narrower strained-Si layers, as well as by the alloy scattering within the SiGe layer. As a consequence, in the DG SGOI devices with thinnest strained-Si layers the electron mobility may drop below the level of the relaxed DG SOI and the mobility enhancement expected from the strained-Si devices may be lost.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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• pp.297-300
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• 2005

In this study, we proposed genetically optimized self-organizing fuzzy polynomial neural network based on information granulation and evolutionary algorithm (gdSOFPNN), develop a comprehensive design methodology involving mechanisms of genetic optimization. The proposed gdSOFPNN gives rise to a structural Iy and parametrically optimized network through an optimal parameters design available within FPN (viz. the number of input variables, the order of the polynomial, input variables, the number of membership functions, and the apexes of membership function). Here, with the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The performance of the proposed gdSOFPNN is quantified through experimentation that exploits standard data already used in fuzzy modeling.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.435-437
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• 1998

In this productive system, it needs to control the each axis motion harmoniously to perform accurately for the manufacturing, transporting and printing. Independent Axis Control usually used for this objection. However, if Independent Axis Control mismatched the parameter of each axis system or in the case of free curve tracking or the case of high speed control, there would be big contour error so that cannot achieve control objection. As a result, there is Contour Control method suggested to supply for this defect. This paper carried modeling of biaxial system and implemented Independent Axis Control & Contouring Control on straight line, circular, and coner path by simulation and experiment. If feedrate increased, contour error growed. In consequence, according to this factor, we introduced contouring controller, so we could find the fact that contour error was reduced more than that of independent axis control about each path.

• 한국안전학회지
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• 제31권3호
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• pp.162-167
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• 2016

As the simple empirical and phenomenological model applied to the analysis of leakage and explosion of chemical substances does not regard numerous variables, such as positional density of installations and equipment, turbulence, atmospheric conditions, obstacles, and wind effects, there is a significant gap between actual accident consequence and computation. Therefore, the risk management of a chemical plant based on such a computation surely has low reliability. Since a process plant is required to have outcomes more similar to the actual outcomes to secure highly reliable safety, this study was designed to apply the CFD (computational fluid dynamics) simulation technique to analyze a virtual prediction under numerous variables of leakages and explosions very similarly to reality, in order to review the computation technique of the practical safety distance at a process plant.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 하계학술대회 논문집
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• pp.369-371
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• 2007

Due to the measurement noise or system noise, the performance of photovoltaic power generation system can be degraded. If this noise is contained in the solar array voltage measurement signal, the correct operation of the maximum power point tracker can not be guaranteed. The application of the extended Kalman filter to the photovoltaic system can obtain enhanced states estimation result. The Kalman filter provides a recursive solution to optimally estimate from random noise signals. Additionally, as a consequence of Kalman filter, the unmeasurable state such as inductor current can be estimated without current sensor. The methods for system modeling and extended Kalman filter design are presented and the experimental results verify the validity of the proposed system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2929-2931
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• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.22-24
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• 1996

For two decades and more, a lot of research work on the biological effects of EMF(Electromagnetic Fields) on Human hearth have been reported. Power-frequency magnetic fields are a natural consequence of the flow of electricity. This paper deals with the modeling of electric utility facilities taking into account the line geometries. The magnetic fields profiles obtained from the computer simulation arc compared to those from measurements.

• BMB Reports
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• 제52권6호
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• pp.349-359
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• 2019

After the first research declaring the generation of human induced pluripotent stem cells (hiPSCs) in 2007, several attempts have been made to model neurodegenerative disease in vitro during the past decade. Parkinson's disease (PD) is the second most common neurodegenerative disorder, which is mainly characterized by motor dysfunction. The formation of unique and filamentous inclusion bodies called Lewy bodies (LBs) is the hallmark of both PD and dementia with LBs. The key pathology in PD is generally considered to be the alpha-synuclein (${\alpha}$-syn) accumulation, although it is still controversial whether this protein aggregation is a cause or consequence of neurodegeneration. In the present work, the recently published researches which recapitulated the ${\alpha}$-syn aggregation phenomena in sporadic and familial PD hiPSC models were reviewed. Furthermore, the advantages and potentials of using patient-derived PD hiPSC with focus on ${\alpha}$-syn aggregation have been discussed.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.223-228
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• 2021

As a consequence of sudden outbreak of COVID-19 pandemic worldwide, educational institutes around the globe are forced to switch from traditional learning systems to e-learning systems. This has led to a variety of technology-driven pedagogies in e-teaching as well as e-learning. In order to take the best advantage, an appropriate understanding of the cognitive capability is of prime importance. This paper presents an intelligent cognitive maturity recognition system for confidence-based e-learning. We gather the data from actual test environment by involving a number of students and academicians to act as experts. Then a Genetic Programming based simulation and modeling is applied to generate a generalized classifier in the form of a mathematical expression. The simulation is derived towards an optimal space by carefully designed fitness function and assigning a range to each of the class labels. Experimental results validate that the proposed method yields comparative and superior results which makes it feasible to be used in real world scenarios.

• 한국산학기술학회논문지
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• 제13권11호
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• pp.5379-5388
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• 2012

비선형 공정에 대한 퍼지 모델링에서, 퍼지 규칙은 일반적으로 입력 변수 선택, 공간 분할 수 및 소속 함수에 의해 형성된다. 비선형 공정에 대한 퍼지 규칙의 생성은 차원이 증가할수록 규칙의 수가 지수적으로 증가하는 문제를 가지고 있다. 이를 해결하기 위해, 입력 공간의 퍼지 분할에 의한 퍼지 규칙을 생성함으로써 복잡한 비선형 공정을 모델링 할 수 있다. 따라서 본 논문에서는 HCM 클러스터링 알고리즘을 이용하여 입력 공간을 분산 형태로 분할함으로써 비퍼지 추론 시스템의 규칙을 생성한다. 규칙의 전반부 파라미터는 HCM 클러스터링 알고리즘에 의한 소속행렬로 결정된다. 규칙의 후반부는 다항식 함수의 형태로 표현되며, 각 규칙의 후반부 파라미터들은 표준 최소자승법에 의해 동정된다. 마지막으로, 비선형 공정으로는 널리 이용되는 데이터를 이용하여 비선형 특성 및 성능을 평가한다. 본 실험을 통해 고차원의 비선형 시스템은 매우 적은 수의 규칙을 가지고 모델링할 수 있었다.