• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.213-215
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• 2007

This paper introduces an emotional behavior decision model for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of emotional model and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented the proposed emotional behavior decision model and verified its performance.

• Korean System Dynamics Review
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• v.1 no.1
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• pp.57-79
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• 2000

Most model constructs in organization studies are descriptive in nature, and the conclusions relating to the model behavior over time are speculative. The usefulness of System Dynamics as a methodology for modeling and testing dynamic behavioral hypotheses in organizational behavioral studies is presented, and how to construct a System Dynamics model using simulation software(VENSIM) is shown, The well-know March and Simon motivation model is used to demonstrate the step by step application of System Dynamics to model of this type. The dynamic behavior of the model, both transient and steady state, is obtained, Even though the paper has focused on one model in the area of individual behavior, the approach is general and can be applied to other areas of organizational behavior as will. The usefulness of System Dynamics as a methodology for theory building is identified as well.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.476-479
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• 2008

Understanding the dynamics of proteins is essential to gain insight into biological functions of proteins. The protein dynamics is delineated by conformational fluctuation (i.e. thermal vibration), and thus, thermal vibration of proteins has to be understood. In this paper, a simple mechanical model was considered for understanding protein's dynamics. Specifically, a mechanical vibration model was developed for understanding the large protein dynamics related to biological functions. The mechanical model for large proteins was constructed based on simple elastic model (i.e. Tirion's elastic model) and model reduction methods (dynamic model condensation). The large protein structure was described by minimal degrees of freedom on the basis of model reduction method that allows one to transform the refined structure into the coarse-grained structure. In this model, it is shown that a simple reduced model is able to reproduce the thermal fluctuation behavior of proteins qualitatively comparable to original molecular model. Moreover, the protein's dynamic behavior such as collective dynamics is well depicted by a simple reduced mechanical model. This sheds light on that the model reduction may provide the information about large protein dynamics, and consequently, the biological functions of large proteins.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.209-234
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• 2007

Recently, balanced scorecard is widely used in the public sector as well as in the private sector. Balanced scorecard system of a particular hospital is a very useful tool in the sense that it shows various measures for the management including the traditional financial measures. However, since it does not show the impact of action items, managers have to analyze his potential decisions. On the other hand, a system dynamics model for the management of a hospital can be used to predict future management status. In this paper, a balanced scorecard system with a system dynamics model is developed for a small sized hospital, and the feasibility and applicability of the system have been tested. It turns out the combination of the balanced scorecard and system dynamics technique can be comprised each other. The balanced scorecard system can take advantage of the data forecasted by the system dynamics model including the implementation of action items taken today. On the other hand, the key performance indicators and action items from the balanced scorecard system provide guidelines the scope and direction of the system dynamics model. The additional efforts of developing a system dynamics model are well compensated by the additional colorful functionalities of the system. This paper also covers the future research areas for the combined system to be more effectively developed.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.760-768
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• 2007

This paper introduces an emotional behavior decision model based on linear system for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of intelligent service robots and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear dynamic system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented a cyber robot and an emotional head robot using 3D character for verifying the performance of the proposed emotional behavior decision model.

• Korean System Dynamics Review
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• v.6 no.1
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• pp.33-70
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• 2005

This study explores the process of corporate corruption via a percolation-based system dynamics model. The preliminary model is an agent-based model constructed in the terms of the corruption networking between ego and other. In the model, the agents behave depending on percolation rules, which represent (1) passing on the corruption opportunities and (2) accepting it. To describe the percolation process in the networks, we develop a further complicated model by combining the basic model with the Bethe lattice. Through the complicated model, we suggest (1) the dynamics of the systemic corporate corruption, (2) 4 patterns of the corruption, and (3) the institutionalization of the corruption. These simulation results provide theoretical and practical implications.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.497-500
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• 2002

When one is interested in the dynamics of a mechanical system with electric motors, the force generated by the motor is generally considered as only an applied torque or force independent of mechanical state variables such as velocity. For a system operated in non-steady dynamic conditions, however, the usual analysis approach may fail to predict some characteristics in the dynamic behaviors because of electromechanical coupling effects. In this paper, we propose dynamics analysis model in which dc motor dynamics with the electromechanical coupling effects are embedded to mechanical dynamics models. The do motor is modeled based on its equivalent circuit model and included in the dynamics solving algorithm which we developed before, called generalized recursive dynamics formula. The developed dynamic analysis model is effective and realistic for analysis of electromechanical dynamics of a system with do motors. The developed model is evaluated by constructing and simulating the flexible antennas of an artificial satellite driven by do motors.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.61-83
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• 2009

This study developed a variable demand traffic assignment model by stable dynamics. Stable dynamics, suggested by Nesterov and do Palma[19], is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with the user equilibrium model, which is based on the arc travel time function in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on congestion. It is therefore expected to be a useful analysis tool for transportation planners. In this study, we generalize the stable dynamics into the model with variable demands. We suggest a three stage optimization model. In the first stage, we introduce critical travel times and dummy links and determine variable demands and link flows by applying an optimization problem to an extended network with the dummy links. Then we determine link travel times and path flows in the following stages. We present a numerical example of the application of the model to a given network.

• Korean System Dynamics Review
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• v.14 no.3
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• pp.75-103
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• 2013

The purpose of this study is to use system dynamics to establish the relation among each variable through the construction process of Community Planning Model, and examine what changes policy scenarios per alternative cause in Community Planning through policy simulation of the constructed model. Therefore, this study extracted chief variables of Community Planning Projects through precedent researches related to Community Planning, and extracted variables were prepared as causal map to examine in what causal cycle feedback structure within Community Planning they can be explained. Next, Community Planning Model was constructed based on the prepared causal map. The model was verified by specialists' interviews and simulation of example areas. This study, which aimed to construct Community Planning Model using system dynamics, has a significance in that it prepared the foundation to provide useful methodology in monitoring the progress of project or establishing the plan of future Community Planning Projects.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.133-142
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• 2019

In physics-based character animation, trajectory optimization has been widely adopted for automatic motion synthesis, through the prediction of an optimal sequence of future states of the character based on its system dynamics model. In general, the system dynamics model is neither in a closed form nor differentiable when it handles the contact dynamics between a character and the environment with rigid body collisions. Employing smoothed contact dynamics, researchers have suggested efficient trajectory optimization techniques based on numerical differentiation of the resulting system dynamics. However, the numerical derivative of the system dynamics model could be inaccurate unlike its analytical counterpart, which may affect the stability of trajectory optimization. In this paper, we propose a novel method to derive the closed-form derivative for the system dynamics by properly approximating the contact model. Based on the resulting derivatives of the system dynamics model, we also present a model predictive control (MPC)-based motion synthesis framework to robustly control the motion of a biped character according to on-line user input without any example motion data.