• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1304-1311
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• 2004

SMIL supports synchronization and nice screen form environments among various multimedia data. Thus it is utilized widely in the fields of internet virtual lecture, internet broadcasting, and so on. Those kinds of system which can be applied flexibly in spite of the change of environments are required continuously with important issue, and depending upon the trends the function of SMIL is upgraded step by step. In this paper main function of SMIL is analyzed and modeled depending upon object oriented methodology. Also I propose some class model which is inspired iron service combinator. Suggested class model can be tuned by user easily if he wants to optimize system environments.

• Journal of Korean Library and Information Science Society
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• v.45 no.3
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• pp.441-462
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• 2014

The purpose of this study is to analyze the concept of information commons and learning commons that has emerged in recent years, and point out the difference between the two concepts, as well as its implications for public libraries, which get lessons learned from learning commons at Japanese public libraries. To track its evolution to learning commons, the theoretical component of learning commons was analyzed. Based on the reference, a research framework for the case study of learning commons was developed. With IT technology diffusion, libraries have become information commons. However, the main mission of libraries should basically remain as learning. Because of this, libraries which function as information commons should go back to being learning commons, which are primarily places of learning. This research shows that libraries should stress its original basic mission which is learning, beyond being information commons in the Japanese library.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.691-697
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• 2010

Reliability-based topology optimization (RBTO) is to get an optimal topology satisfying uncertainties of design variables. In this study, reliability-based topology optimization method is applied to the inner reinforcement of vehicle's hood based on BESO. A multi-objective topology optimization technique was implemented to obtain optimal topology of the inner reinforcement of the hood. considering the static stiffness of bending and torsion as well as natural frequency. Performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. To evaluate the obtained optimal topology by RBTO, it is compared with that of DTO of the inner reinforcement of the hood. It is found that the more suitable topology is obtained through RBTO than DTO even though the final volume of RBTO is a little bit larger than that of DTO. From the result, multiobjective optimization technique based on the BESO can be applied very effectively in topology optimization for vehicle's hood reinforcement considering the static stiffness of bending and torsion as well as natural frequency.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.646-655
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• 2009

This paper presents a new search strategy based on models of evolution in order to solve the problem of collision-free robotic path planning. We designed the robot path planning method with genetic algorithm which has become a well-known technique for optimization, intelligent search. Considering the path points as genes in a chromosome will provide a number of possible solutions on a given map. In this case, path distances that each chromosome creates can be regarded as a fitness measure for the corresponding chromosome. The effectiveness of the proposed genetic algorithm in the path planning was demonstrated by simulation. The proposed search strategy is able to use multiple and static obstacles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.895-899
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• 2009

This paper presents a business models of the robot industry for copying with aging society that facilitates to create new business opportunities in the convergence age. In order to identify the market drivers for both convergence and aging society, the trends of them analyzed. Through constructing and analyzing market value chain, we design a set of the business model of the robot industry focused on u-health robots of a convergence service type integrated ubiquitous, health and robot. In addition, we describe the evolution path of the proposed business model in terms of technology development and market. Finally, we develop a matrix based evaluation framework to measure and assess the effectiveness of the business model.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2891-2893
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• 2005

In this paper, we introduce a new category of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multi-layer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. The conventional SOFPNN algorithm leads to a tendency to produce overly complex networks as well as a repetitive computation load by the trial and error method and/or the a repetitive parameter adjustment by designer. In order to generate a structurally and parametrically optimized network, such parameters need to be optimal. In this study, in solving the problems with the conventional SOFPNN, we introduce a new design approach of evolutionary optimized SOFPNN. Optimal parameters design available within FPN (viz. the no. of input variables, the order of the polynomial, input variables, and the no. of membership function) lead to structurally and parametrically optimized network which is more flexible as well as simpler architecture than the conventional SOFPNN. In addition, we determine the initial apexes of membership functions by genetic algorithm.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.12-14
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• 2005

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks(SOFPNN) by means of genetically optimized fuzzy polynomial neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms(GAs). The conventional SOFPNNs hinges on an extended Group Method of Data Handling(GMDH) and exploits a fixed fuzzy inference type in each FPN of the SOFPNN as well as considers a fixed number of input nodes located in each layer. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, a collection of the specific subset of input variables, and the number of membership function) and addresses specific aspects of parametric optimization. Therefore, the proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.143-153
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• 1997

At the on-line control method FLC(Fuzzy Logic Controller) is stronger to the disturbance than a classical controller and its overshoot of the initialized value is excellent. The fuzzy controller can do a proper control, though it doesn't know the mathematical model of the system or the parameter value. But to make the control rule of the fuzzy controller through an expert's experiance has a changes of the control system, the control rule is fixed, it can't adjust to the environment changes of the control system, the controller output value has a minute error and it can't convergence correctly to the desired value[1][2]. There are many ways to eliminate the minute error[3][4][5], but in this paper suggests EP-FNNIC(Fuzzy Neurla Network Intelligence Controller) intelligence controller which combines FLC with NN(Neural Network) and EP(Evolution Programming). The output characteristics of EP-FNNIC controller will be compared and analyzed with FLC. It will be showed that this EP-FN IC controller converge correctly to the desirable value without any error. The convergence speed, overshoot, rising time, error of steady state of controller of these two kinds also will be compared.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.610-616
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• 2004

In the research of biomechanical engineering, robotics and neurophysiology, to clarify the mechanism of human bipedal walking is of major interest. It serves as a basis of developing several applications such as rehabilitation tools and humanoid robots. Nevertheless, because of complexity of the neuronal system that interacts with the body dynamics system to make walking movements, much is left unknown about the details of locomotion mechanism. Researchers were looking for the optimal model of the neuronal system by trials and errors. In this paper, we applied Genetic Programming to induce the model of the nervous system automatically and showed its effectiveness by simulating a human bipedal walking with the obtained model.

• Transactions of The Korea Fluid Power Systems Society
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• v.2 no.3
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• pp.1-5
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• 2005

There are two types of solenoid actuator for force and position control of the fluid power system. One is an on-off solenoid actuator and the other is an electro-magnetic proportional actuator. They have some different characteristics for attraction force according to solenoid shape. Attraction force of the on-off solenoid actuator only depends on flux density. And the stroke-force characteristics of the proportional solenoid actuator are determined by the shape of the control cone. In this paper, steady state characteristics of the solenoid actuator for electro-hydraulic proportional valve determined by the shape of control cone are analyzed using finite element method and it is confirmed that the proportional solenoid actuator has a constant attractive force in the control region independently on the stroke position. And the shape of control cone is optimized using 1+1 evolution strategy to get a constant force. In the optimization algorithm, control cone length, thickness and taper length are used as a design parameter.