• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.310-314
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• 2008

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. This novel method uses the support vector machines (SVM) with its function approximation property. It works together with RLS (Recursive least-squares) algorithm. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1463-1466
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• 1987

The problem of generating minimal area CMOS functional cell layout can be converted to that of decomposing the transistor connection graph into a minimum number of subgraphs, each having a pair of Euler paths with the same sequence of input labels on the N-graph and P-graph, which are portions of the graph corresponding to NMOS and PMOS parts respectively. This paper proposes a heuristic algorithm which yields a nearly minimal number of Euler paths from the path representation formula which represents the give a logic function. Subpath merging is done through a list processing scheme where the pair of paths which results in the lowest cost is successively merged from all candidate merge pairs until no further path merging and further reduction of number of subgraphs are possible. Two examples were shown where we were able to further reduce the number of interlaces, i.e., the number of non-butting diffusion islands, from 3 to 2, and from 2 to 1, compared to the earlier work [1].

• Structural Engineering and Mechanics
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• 제49권3호
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• pp.411-425
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• 2014

This paper presents the processing of nonlinear features associated with a damage event by quadratic time-frequency distributions for damage identification in a frame structure. A time-frequency distribution is a function which distributes the total energy of a signal at a particular time and frequency point. As the occurrence of damage often gives rise to non-stationary, nonlinear structural behavior, simultaneous representation of the dynamic response in the time-frequency plane offers valuable insight for damage detection. The applicability of the bilinear time-frequency distributions of the Cohen class is examined for the damage assessment of a frame structure from the simulated acceleration data. It is shown that the changes in instantaneous energy of the dynamic response could be a good damage indicator. Presence and location of damage can be identified using Choi-Williams distribution when damping is ignored. However, in the presence of damping the Page distribution is more effective and offers better readability for structural damage detection.

• 제어로봇시스템학회논문지
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• 제10권9호
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• pp.755-762
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• 2004

In this research, EOG(Electrooculogram) signal was analyzed to predict the subject's intention using a fuzzy classifier. The fuzzy classifier is built automatically using the EOG data and evolutionary algorithms. An assistant robot manipulator in redundant configuration has been developed, which operates according to the EOG signal classification results. For automatic fuzzy model construction without any experts' knowledge, an evolutionary algorithm with the new representation scheme, design of adequate fitness function and evolutionary operators, is proposed. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts. It is shown that the fuzzy classifier built by the proposed algorithm can classify the EOG data efficiently. Intelligent motion planner that consists of several neural networks are used for control of robot manipulator based upon EOG classification results.

• 한국CDE학회논문집
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• 제11권2호
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• pp.88-96
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• 2006

This paper introduces an approach to ontology-based framework for knowledge management in a product development domain. The participants in a product life cycle want to share the product knowledge without any heterogeneity. However, previous knowledge management systems do not have any conceptual specifications of their knowledge. We suggest the three levels of knowledge framework. First level is an axiom, which specifies the semantics of concepts and relations. Second level is a product development knowledge map. It defines the common domain knowledge which domain experts agree with. Third level is a specialized knowledge for domain, which includes three knowledge types; expert knowledge, engineering function and data-analysis-based knowledge. We propose an ontology-based knowledge framework based on the three levels of knowledge. The framework has a uniform representation; first order logic to increase integrity of the framework. We implement the framework using prolog and test example queries to show the effectiveness of the framework.

• 산업기술연구
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• 제13권
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• pp.25-31
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• 1993

This paper presents an analysis of microwave device component. An H-Plane waveguide component with arbitrary shape is analyzed using finite element method(FEM) cooperated with boundary element method(BEM). The finite element method(FEM) is applied to the junction region and the boundary element method(BEM) to the waveguide region. For the application of BEM in the waveguide structure, a ray representation of the waveguide Green's function is used. The proposed technique was applied to the analysis of the waveguide inductive junction to compare the numerical result with the result of the mode matching technique. The comparison showed good agreements between the two results. Transmitted powers were also computed in T-junction waveguides for the various shape of the junction area.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.1019-1024
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• 2007

그래픽스 분야에서 다양한 재질을 사실감 있게 표현하려는 연구가 활발히 진행되고 있는 가운데, 다양한 재질의 반사특성을 측정하는 방법들이 시도되고 있다. 본 연구에서는 디지털 카메라를 이용하여 영상 기반 양방향 반사 분포함수(BRDF: Bidirectional Reflectance Distribution Function)를 획득할 수 있는 측정 시스템을 구축하였다, 이를 통한 BRDF 모델은 경험적(empirical)혹은 물리(physical)기반의 모델에 비해 보다 사실성 높은 표현이 가능하다. 영상 기반으로 양방향 반사 분포함수를 생성하는 과정에서 노출시간을 달리한 여러 장의 영상을 가지고 HDR(High Dynamic Range) 영상을 생성하였다. 또한 원색재현을 위해 표준광원을 사용하고 컬러차트와 회귀분석을 통해 컬러 보정을 수행하였다. 본 연구에서는 플라스틱이나 금속재질같이 불투명한 등방성(isotropic) 재질을 사용하였고, 이러한 재질의 BRDF데이터를 통해 산업제품에서 많이 사용되는 재질의 모델을 보다 실감나게 렌더링(rendering)할 수 있다.

• 한국주거학회논문집
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• 제1권2호
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• pp.1-11
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• 1990

A study of domestic furniture arrangements may reveal the living style relevant to the room as conceived and coded by occupants and the effects of the physical environment on the structure of behavior settings. The purpose of this study was to investigate, through analizing the furniture usage and behavior as a non-reactive and activity oriented behavioral measures, the occupants` domestic habits as a living style using MDS. MDS(multidimensional scaling technique) is a statistical technique for creating a spatial representation of data. It Is a particularly appropriate technique for analizing qualitative data such as the furniture usage and behavior because it takes into account all of the relationships between items. For the MDS analysis, the furniture usage and behavior examined by housing types based on 114 households in Seoul. The result of spatial configuration by MDS has three dimensions : recogn;lion of room function, pattern of room organization, understanding of room meaning. The effect of housing types for dimensions is identical but configuration of furniture items is different.

• 대한전기학회논문지:전력기술부문A
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• 제48권9호
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• pp.1055-1063
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• 1999

This paper present a conceptual possibilistic approach using fuzzy set theory to manage the uncertainties in the given reliability input date of the practical power system. In this paper, an algorithm is introduced to calculate the possibilstic reliability indices according to the degree of uncertainty in the given data. The probability distribution function can be transformed into an appropriate possibilstic representation using the probability-Possibility Consistency principle(PPCP) algorithm. In this the algorithm, the transformation is performation by making a compromise between the transformation consistency and the human updating experience. Fuzzy classifcation theory is applied to reduced the number of load data. The fuzzy classification method determines the closeness of load data points by assigning them to various clusters and then determening the distance between the clusters. The IEEE-RTS with 32-generating units is used to demonstrate the capability of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1002-1005
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• 1991

It is important to express the specific growth rate of a fermentation reaction as a function of substrate and product concentration in developing bioprocess automation techniques such as modeling of the reactor and controlling it via an advanced control scheme. Typical methods of identification utilize graphical representation of the rate constant data or nonlinear regression with an appropriate noise filter. But the former method fails when the data are erroneous and the latter are mathematically complicated to apply in the field. Neural network is another candidate for the identification from time series data since it is insensitive to the random data error and easy to implement. In this study, we will develop a neural network method of specific growth rate estimation from the time series state variable data and test the performance.