• Research in Mathematical Education
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• v.16 no.2
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• pp.137-154
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• 2012

Comparative studies on mathematical modeling cognition feature were carried out between 15 excellent high school third-grade science students (excellent students for short) and 15 normal ones (normal students for short) in China by utilizing protocol analysis and expert-novice comparison methods and our conclusions have been drawn as below. 1. In the style, span and method of mathematical modeling problem representation, both excellent and normal students adopted symbolic and methodological representation style. However, excellent students use mechanical representation style more often. Excellent students tend to utilize multiple-representation while normal students tend to utilize simplicity representation. Excellent students incline to make use of circular representation while normal students incline to make use of one-way representation. 2. In mathematical modeling strategy use, excellent students tend to tend to use equilibrium assumption strategy while normal students tend to use accurate assumption strategy. Excellent students tend to use sample analog construction strategy while normal students tend to use real-time generation construction strategy. Excellent students tend to use immediate self-monitoring strategy while normal students tend to use review-monitoring strategy. Excellent students tend to use theoretical deduction and intuitive judgment testing strategy while normal students tend to use data testing strategy. Excellent students tend to use assumption adjustment and modeling adjustment strategy while normal students tend to use model solving adjustment strategy. 3. In the thinking, result and efficiency of mathematical modeling, excellent students give brief oral presentations of mathematical modeling, express themselves more logically, analyze problems deeply and thoroughly, have multiple, quick and flexible thinking and the utilization of mathematical modeling method is shown by inspiring inquiry, more correct results and high thinking efficiency while normal students give complicated protocol material, express themselves illogically, analyze problems superficially and obscurely, have simple, slow and rigid thinking and the utilization of mathematical modeling method is shown by blind inquiry, more fixed and inaccurate thinking and low thinking efficiency.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.127-130
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• 1998

In this paper, we propose a method of cooperative control(T-cell modeling) and selection of group behavior strategy(B-cell modeling) based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-call respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based of clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Journal of the Korea Safety Management & Science
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• v.5 no.4
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• pp.131-145
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• 2003

A strategic plan for an immediate situation must be present in a business enterprise to deal actively and efficiently with the demand environment of new customer. The purpose of this paper is to provide research about the manufacturing strategy situations of the Korean manufacturing company. And this paper is a part of Modeling on Manufacturing Strategy. We emphasizes the importance of dynamism and complexity on the competitive environment, and classify the manufacturing strategy by trade-off model, cumulative model, sandcone model, strategic fit model, and competitiveness model.

• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.117-135
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• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.591-597
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• 2001

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control school is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.25-31
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• 2011

The purpose of power system maintenance is to prevent equipment failure. The maintenance strategy should be designed to balance costs and benefits because frequent maintenance increases cost while infrequent maintenance can also be costly due to electricity outages. This paper proposes maintenance modeling of a power distribution system using reliability centered maintenance (RCM). The proposed method includes comprehensive equipment modeling and impact analysis to evaluate the effect of equipment faults. The problem of finding the optimum maintenance strategy is formulated in terms of dynamic programming. The applied power system is based on the RBTS Bus 2 model, and the results demonstrate the potential for designing a maintenance strategy using the proposed model.

• Korean Management Science Review
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• v.12 no.2
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• pp.147-164
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• 1995

There have been two dominant paradigms in understanding and modeling an expert's decision-making behavior: output analysis and process-tracing. While the two paradigms are complementary, they have not been used yet in a combined manner. This study extends the previous research work in the two paradigms to inductive modeling research by 1) analyzing individual experts' decision strategies, 2) comparing performance of four popular inductive modeling methods, and 3) matching their performance against the type of decision strategy employed by experts.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.4
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• pp.202-208
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• 2002

In a dynamic game where the players move in a periodical sequence, each player observes the strategy of the others. So the players who move later in a game get to know the moves of others having made before them. Those who move earlier must take this into account in devising their optimal strategy. In the Poolco model, the bidding game is executed periodically. The player participating in the bidding game accumulates the information of its own and others'strategies, and payoffs through the repeated bidding process. Thereby, the players in this game would be able to map out how get the maximum profit, and get closer to the optimal strategy. This paper presents a mathematical modeling for a player to determine his or her optimal strategy at period T, based on the information acquired from the previous rounds for the periods, T-1, T-2, and so on. The proposed modeling is demonstrated with a dynamic fame theory.

• Journal of the Korean Chemical Society
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• v.63 no.6
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• pp.459-472
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• 2019

The purpose of this study was to investigate the effect of science writing for different audiences on preservice chemistry teachers' chemistry concept understanding and modeling ability in general chemistry experiment activities using Argument-based Modeling (AbM) strategy. And we also examined preservice chemistry teachers' perceptions of modeling in different audience groups. The participants of the study were 18 university students in the first grade of preservice chemistry teachers taking a general chemistry experiment course. They completed eleven topics of general chemistry experiment using argument-based modeling strategy. The understanding of chemistry concept was compared with the effect size of pre- and post-chemistry concept test scores. To find out modeling ability, we analyzed level of model by each preservice chemistry teacher. Analytical framework for the modeling ability was composed of three elements, explanation, representation, and communication. The questionnaire was conducted to check up on preservice chemistry teacher's recognition of modeling. The result of analyzing the effect of modeling for different audience on the understanding of chemistry concept and modeling ability, the preservice chemistry teachers' were found to be more effective when the level of audience was low. There was no difference in the recognition of modeling between the groups for audience. However, we could confirm that the responses of preservice chemistry teachers are changed in concrete when they have an experience in succession on modeling.

• The Journal of Society for e-Business Studies
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• v.12 no.2
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• pp.249-267
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• 2007

A variety of BPM (Business Process Management) standards to achieve interoperability among heterogeneous systems have been released. Areas of BPM standards include business process modeling, process execution and management, and monitoring and controlling. The purpose of this research is to develop an adoption strategy and guideline for implementing BPM standards. We suggest a strategy for implementing BPMN (Business Process Modeling Notation), BPEL (Business Process Execution Language), and BPQL (Business Process Query Language) and provide a specific implementation guideline for developing BPM solutions using each standard. We expect that BPM vendors can establish their own strategy for adopting BPM standards and implement BPM solutions efficiently and effectively with the help of the strategy and guideline described in this paper.