• Proceedings of the Korean System Dynamics Society
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• 2004.08a
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• pp.63-85
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• 2004

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.4
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• pp.414-420
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• 1997

An intelligent speed control system for marine diesel engines is presented. The approach adopt¬ed is to use a conventional PID controller for normal operation and a feedforward controller for adaptive control. The feedforward controller is a neural network. The neural network is the inverse dynamics model of the plant, which is being trained on line. The parametric model of the diesel engine is represented in a linear second-order system, with a first-order combustion part and a revolution part each at a normal operating point. The time delay in the control of the com¬bustion part is approximated to the first-order system. The tuned PID parameters are set based on the model for normal operating point. To obtain the inverse dynamics of the diesel engine system, two neural networks are used, one for inverse, the other for forward dynamics. The former is posi¬tioned across the plant to learn its inverse dynamics during operation, and the latter is placed in series with the controlled plant. Simulation results are presented to illustrate the applicability of the proposed scheme to intelligent adaptive control of diesel engines.

• The Journal of Information Systems
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• v.16 no.4
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• pp.177-194
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• 2007

This study is intended to identify critical success factors(CSF) of real-time enterprises(RTE) by using a policy leverage method of system dynamics. Since RTE is a new theoretical system that unifies existing theories or concepts in business management and information technology, it is not proper to employee a traditional statistical method. To obtain our research goal, causal maps of system dynamics are employed to abstract and arrange RTE information from previous studies. By using the commonness of policy leverage and critical success factors, CSFs for the RTE are deduced by substituting the leverage points on causal maps with necessary success factors to solve the problems. Since this is a new approach to identify success factors. it has some restrictions. Unlike the statistical methods, this approach explains only the directions of causalities and correlations. For the future research, a simulation tool of system dynamics can be employed to discover how each CSF is correlated to the successful implementation of RTE.

• Korean System Dynamics Review
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• v.4 no.2
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• pp.131-151
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• 2003

Traffic congestion stems from the widespread desires of people to purse certain goals that inevitably overload existing roads every day. he a transportation policy, congestion toll system has been implemented in Seoul, since 1996. The growing concerns on whether the system would achieve sustained results in the future motivated us to investigate the effectiveness of this policy. Developing and running the congestion toll simulation model, we find that this policy is not an effective policy in the long m. The paper indicates the power of system dynamics approach as a tool for evaluating complex policy like a congestion toll, and suggest that city transportation policy maker should approach the problem with systems thinking and analyze the effectiveness of policy on the basis of understanding the dynamic relationships among subsystems.

• Korean System Dynamics Review
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• v.3 no.2
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• pp.49-68
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• 2002

The intent of this study is to develop system dynamics model for assessment of organizational and human factors in nuclear power plant which can contribute to secure the nuclear safety. Previous studies are classified into two major approaches. One is engineering approach such as ergonomics and probability safety assessment(PSA). The other is social science approach such like sociology, organization theory and psychology. Both have contributed to find organization and human factors and to present guideline to lessen human error in NPP. But, since these methodologies assume that relationship among factors is independent they don't explain the interactions among factors or variables in NPP. To overcome these limits, we have developed system dynamics model which can show cause and effect among factors and quantify organizational and human factors. The model we developed is composed of 16 functions of job process in nuclear power, and shows interactions among various factors which affects employees' productivity and job quality. Handling variables such like degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plant in the organization side. Through simulation, user can get insight to improve safety in plants and to find managerial tools in the organization and human side. Analyzing pattern of variables, users can get knowledge of their organization structure, and understand stands of other departments or employees. Ultimately they can build learning organization to secure optimal safety in nuclear power plant.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.115-140
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• 2007

Changes in material use, energy use and emissions profiles of steel industry are the result of complex interrelationships among a multitude of technological and economic drivers. To better understand and guide such changes requires that attention is paid to the time-varying consequences that technology and economic influences have on an industry's choice of inputs and its associated outputs. We briefly review the range of policy issues in our paper and assess the impact that climate-change policies may have on energy use and carbon emissions in Korea steel industry. We then present the models of Korea steel industry's energy and product flow regarding environmental regulations by using system dynamics simulation methodology(SD). Time series data and engineering information are combined to endogenously specify changes in technologies, fuel mix, and production processes within dynamic simulation model. Through a various scenario, ramifications that the convention of climate change would to steel industry is analyzed, and based on the study results, strategies against environment changes is contemplated in various perspectives to contribute to minimize the risks concerning the uncertain future and to be conducive to Korea steel industry's sustainable development.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.382-393
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• 2006

Mechanical system dynamics plays an important role in the area of computational structural biology. Elastic network models (ENMs) for macromolecules (e.g., polymers, proteins, and nucleic acids such as DNA and RNA) have been developed to understand the relationship between their structure and biological function. For example. a protein, which is basically a folded polypeptide chain, can be simply modeled as a mass-spring system from the mechanical viewpoint. Since the conformational flexibility of a protein is dominantly subject to its chemical bond interactions (e.g., covalent bonds, salt bridges, and hydrogen bonds), these constraints can be modeled as linear spring connections between spatially proximal representatives in a variety of coarse-grained ENMs. Coarse-graining approaches enable one to simulate harmonic and anharmonic motions of large macromolecules in a PC, while all-atom based molecular dynamics (MD) simulation has been conventionally performed with an aid of supercomputer. A harmonic analysis of a macroscopic mechanical system, called normal mode analysis, has been adopted to analyze thermal fluctuations of a microscopic biological system around its equilibrium state. Furthermore, a structure-based system optimization, called elastic network interpolation, has been developed to predict nonlinear transition (or folding) pathways between two different functional states of a same macromolecule. The good agreement of simulation and experiment allows the employment of coarse-grained ENMs as a versatile tool for the study of macromolecular dynamics.

• Korean System Dynamics Review
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• v.17 no.3
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• pp.121-143
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• 2016

The purpose of this study to analyze the effect of Mindfulness on the Therapeutic Relationship using System Dynamics. The biggest factor in psychotherapy's treatment outcome is the Therapeutic Relationship including the quality of the therapist (empathy, therapeutic presence) and therapy alliance. Mindfulness practice can facilitate the therapeutic relationship. In order to analyze the therapeutic relationship, I measure FFMQ(Five Facet Mindfulness Questionnaire), Empathy, Therapeutic presence and Therapy alliance. Participants consist of 55 mental health professionals (doctor, psychologist, psychiatrist, counselor, social worker). The result of the study will be explained. First, with the causal loop diagram research, I analyze how mindfulness can influence the quality of therapist and therapy alliance. The result of literature research indicate that mindfulness increase therapist's empathy, congruence, therapeutic presence, flow, therapy alliance. And then mindfulness reinforces the ability of therapeutic relationship. Secondly, through the real data research and simulation analysis, mindfulness practicing period (year and hour a day) of therapist is studied. The result of the therapist experiencing mindfulness practice period is over 5 years and the daily hours of practice is 2 - 2.5 hours in order to enhance the therapeutic relationship. After reviewing the result of the research it is important to understand the practicing period and daily practice of mindfulness. With daily practice and time, the level of mindfulness will increase and influence positively the therapeutic relationship between therapist and client.

• Journal of the Korean Home Economics Association
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• v.43 no.7 s.209
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• pp.53-65
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• 2005

We analyzed the dynamics of the family system and the economic well-being by utilizing the socio-demographic objective economic and subjective economic factors of urban employed housewives. The survey was conducted in Seoul and three other major cities. The subjects consisted of employed housewives in these areas who were currently cohabiting with their spouses and had at least one child. The preliminary and main survey questionnaires were distributed between November 12, 2001 and February 27, 2002, and 254 survey questionnaires were collected and analyzed We applied the frequency, average, percentage, Cronbach's $\alpha$, simple regression and multiple regression analysis by using SPSS/PC WIN. The findings were as follows. First, the mean score of the availability of life information was 3.21. Second, when the stability of husband occupation increased, the dynamics of family system worked very well. Third, the dynamics of family system didn't have any influence on the economic well-being.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.11
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• pp.931-938
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• 2002

Combustion dynamics of a dry low NOx gas turbine have been measured by utilizing a dynamic pressure measurement system. The software part of the measurement system, implemented with a commercial general-purpose DASYLab version 5.6 code, basically acquires combustion dynamics signals, performs the FFT analysis, and displays the results. The gas turbine often experiences momentary combustion instability, especially when its combustion mode changes. It is found that the measurement system developed in the study may outperform the other commercial dynamic pressure measurement system. The developed system currently serves to monitor the combustion dynamics of the gas turbine.