• BMB Reports
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• v.41 no.6
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• pp.444-447
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• 2008

Trypanothione reductase is an important target enzyme for structure-based drug design against Leishmania. We used homology modeling to construct a three-dimensional structure of the trypanothione reductase (TR) of Leishmania infantum. The structure shows acceptable Ramachandran statistics and a remarkably different active site from glutathione reductase(GR). Thus, a specific inhibitor against TR can be designed without interfering with host (human) GR activity.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.276-283
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• 2007

It has been shown that the structure identification of a neuro-fuzzy model improves their accuracy performances in a various modeling problems. In this paper, we claim that the structure identification of a neuro-fuzzy model can also reduce the degree of inconsistency of its fuzzy rulebase. Thus, the resulting neuro-fuzzy model serves as more like a structured knowledge representation scheme. For this, we briefly review a structure identification method of a neuro-fuzzy model and propose a systematic method to measure inconsistency of a fuzzy rulebase. The proposed method is applied to problems or fuzzy system reproduction and nonlinear system modeling in order to validate our claim.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.219-232
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• 1998

A lot of difficulties exist in analyzing the structure of a system owing to the complex and organic relations in the systems we face in reality. Focuses have been put on the research of optimal solution in a defined structure, however, on the assumption that the structure of the system has been already defined. With the grasping of the structure as the most prior condition, ISM(Interpretive Structural Modeling) and FSM(Fuzzy Structural Modeling) are suggested as solutions in this paper. ISM uses the systematic application of some elementary notions of graph theory and boolean algebra, FSM uses Fuzzy conception for representing relationship between elements. In FSM, the entries in the relation matrix are taken to value on the interval [0,1] by virtue of a fuzzy binary relation. Numeric examples are used as the actual application as follows.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.4
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• pp.61-70
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• 1996

This paper deals with consciousn~s structure by means of human subjective judgement. Fuzzy structural modeling which is a modeling method for consciousness structure have the large number of pairwise comparigon by human subjective judgement, is difficplt to check the consistency index which denotes the precision for human judgement. To improve these points, we set the structure of consciousness by fuzzy structural modeling method using the concept of pairwise compariqon matrix in AHP. The efficiency of this method is showed by means of the consciousness structure graph to the qyality system construction.

• Journal of Korean Association for Spatial Structures
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• v.17 no.3
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• pp.65-73
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• 2017

Recently, the trend is emerging a variety of irregular tall buildings. It is important to design the building for lateral load according to this trend. Fluid Structure Interaction(FSI) simulation can be performed to understand the vibrations of the structure against dynamic wind loads. In order to make the physical characteristics of the actual structure and the analytical model the same, we studied core inserting equivalent stiffness modeling method. As a result of this analysis, the stiffness of the structure can be set similar to that of the two axes of the structure, and turbulence can be reproduced through the acceleration tendency.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.635-639
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the modeling of chaotic nonlinear systems. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the modeling performance for chaotic nonlinear systems and compare it with those of the FNN and the WFM.

• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.730-744
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• 2002

A Web-Based Information System(WBIS), a typical structure of recently information systems, should be dynamically restructured in order to satisfy user's need and make a profit. Thus, we should analyze and modelize the navigational structure of WBIS and utilize it by modeling the navigational structure of behavior of user through log-file as system restructuring. In this paper, we propose the modeling method for navigational structure and user behavior to restructure WBIS including shopping mall. Also, we suggest the structural model, state transition model, Petri net model and analysis method and analyze and implement modeling algorithm for user behavior to analyze log-file of it. Then, we propose some restructuring heuristic and apply the methods to the example of WBIS.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.2 s.146
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• pp.258-267
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• 2006

The present piping modeling method requires detailed inputs from a designer to generate a piping model, and thus it takes much time for the designer to perform such task. Moreover, the piping model has no relation with that of hull structure. Thus, it is time-consuming and requires much effort if design changes arise. In this study, a method that generates quickly many pipes using a pipe tray and a conversion method that converts automatically the pipes into objects related with the hull structure are proposed. A piping modeling system based on the proposed methods is developed. The applicability of the developed system is demonstrated by applying it to the generation of the piping model of a deadweight 300,000ton VLCC(Very Large Crude oil Carrier). The results show that the developed system can quickly generate the piping model in relation with the hull structure.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.405-410
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• 2002

In this paper, fuzzy system modeling using new hierarchical structure is suggested for the complex and uncertain system. The proposed modeling technique Is to decompose the fuzzy rule base structure into the above-rule base and the sub-rule base. By applying hierarchical fuzzy rules, they can be used efficiently and logically. Also, hieratical fuzzy rules can improve the accuracy and the transparency of structure in the fuzzy system. The genetic algorithm is applied for optimization of the parameters and the structure of the fuzzy rules. To show the effectiveness of the proposed method, fuzzy modeling of the complex nonlinear system is provided.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.