• Journal of the Korean earth science society
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• v.32 no.5
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• pp.494-503
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• 2011

During the last three decades, earth science has been re-conceptualized as an interdisciplinary discipline entitled Earth System Science (ESS), which is based on knowledge of the physical earth system and human impact on the earth. While there is increasing effort to teach earth as a system in K-12 education, teachers' preparedness of to teach earth system is still in its infancy. This article focuses on reviewing the literature of teachers' knowledge of earth systems and of how teachers' knowledge of subject matter affects their teaching practice and pedagogical content knowledge (PCK). First, the study investigated a literature of PCK in general as well as in science teaching. Then this study duscuss what teachers' subject matter knowledge (SMK) is and what it means to be in teaching earth system science. Third, a literature of teachers' knowledge of earth system was reviewed. Finally, a number of suggestions and implications are made as to what teacher education program should do to better prepare future teachers to teach earth systems.

• STI Policy Review
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• v.8 no.2
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• pp.23-48
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• 2017

This article advocates for a Mode 3 science policy. Compared to the university research-based Mode 1 knowledge production system and the knowledge application-centric Mode 2 innovation system, Mode 3 can be defined as a system that integrates both Mode 1 and Mode 2-type knowledge production models. In this article, based on the major characteristics of the Mode 3 scientific knowledge production system, I agree with the advocates of Mode 3 that constructing a knowledge society requires an inclusive form of knowledge production and innovation system through the democratization of knowledge production as well as the promotion of social values. Moreover, the mechanisms for creating accountable innovation in the Mode 3 system should be given more attention from the science research and policy communities to make public policy for scientific and technological innovation more reflective of social changes. Similar to the ways that the Mode 1 and Mode 2 scientific knowledge production approaches have influenced the development of science policy models, the Mode 3 scientific knowledge production approach, or Mode 3 science, also has the potential to shape a new science policy model. I will refer to this as Mode 3 science policy. In an effort to conceptualize the democracy- and society-centric Mode 3 science policy model, I will articulate science policy strategies in four science policy domains in South Korea from the context of the Mode 3 science approach. These include (1) evaluation of publicly-funded research activities, (2) valorization of scientific knowledge (that is, enhancement of the value of scientific knowledge through governmental action), (3) development of a science policy decision-making support system, and (4) anticipatory foresight of science, technology and society. When adopting and implementing a Mode 3 science framework, one progressive change is to increase socially desirable innovation such as responsible innovation.

• Korean Management Science Review
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• v.20 no.1
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• pp.1-23
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• 2003

Knowledge Management System is defined as an Information system to support the integrated knowledge management process for maximizing value of the knowledge assets in organizations. From that point of view, the system performance - the usage level of the system and user satisfaction - can be an available measure of the knowledge management system success. Many previous research were focused on the application of a new technological component for knowledge management processes or the construction of the overall system architecture in spite of the importance of the system performance. The purpose of this study is to Identify the factors affecting the knowledge management system performance. To do this, we conducted an exploratory case studies of eight companies. We applied theories of information system success to knowledge management system and investigated some specific strategic components as additional affecting factors. Finally, we proposed research model and ex propositions regarding the factors affecting the knowledge management system performance. The implication of the findings and future research directions were discussed.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.288-291
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• 2003

For the purpose of building the more efficient knowledge learning system, it is very important to make a good structure of the knowledge system first of all. The well designed knowledge system can make the stored knowledge to be easily accessed for knowledge acquisition and extraction. Expert knowledge can also play a good role for controlling. Accordingly, in this paper we propose the Hierarchical modular system with expert knowledge gating mechanism. This system consists of the mechanisms for knowledge acquisition, constructing the associative memory, knowledge inference and extraction according to the expert knowledge gating mechanism. We applied this system to the medical diagnostic area for classifying Virus(coxackie virus, echovirus, cold), Rhinitis(Nonallergic, allergic) and tested with symptom data

• Journal of Korean Library and Information Science Society
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• v.16
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• pp.129-157
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• 1989

Through this study, some considerations to be taken into account in order to construct the user model for the user friendly system which can provide each individuals user armed with varied intellectual level with the relevant information, can be summarized as follows : (1) The user' ability to use the system and users' subject knowledge, the distribution of the users' level knowledge should be considered for the decision of the typed of interaction between the users and the system. (2) the knowledge of the user models should include the following kinds of knowledge inharmony with one another, 1. Standard user knowledge which represents a general characteristic of user group, 2. individual user knowledge which represents an individual's unique characteristic, 3. Long-term user knowledge which represents the education level and subject background of users, 4. short-term user knowledge which represents the purpose of information science and information need by users (3) As knowledge generation technique, both the implicit method and explicit method should be a n.0, pplied, observation of the system during the interaction, and explicit method generates the knowledge by the user's answering the questions already made by the system. (4) The frame technique as the knowledge representation for the user-modelling in which user-knowledge is represented in a limited situation and in a qualitative aspects, can be recommended. The frame is adequated for the explanation of structured situation, and for the processing the present situation by inferring the previous experiences.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.18.1-18
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• 2001

• Journal of Korean Academy of Nursing
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• v.44 no.1
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• pp.64-74
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• 2014

Purpose: This study was done to develop and implement the Nursing KMS (knowledge management system) in order to improve knowledge sharing and creation among clinical nurses in outpatient departments. Methods: This study was a methodological research using the 'System Development Life Cycle': consisting of planning, analyzing, design, implementation, and evaluation. Quality Function Deployment (QFD) was applied to establish nurse requirements and to identify important design requirements. Participants were 32 nurses and for evaluation data were collected pre and post intervention at K Hospital in Seoul, a tertiary hospital with over 1,000 beds. Results: The Nursing KMS was built using a Linux-based operating system, Oracle DBMS, and Java 1.6 web programming tools. The system was implemented as a sub-system of the hospital information system. There was statistically significant differences in the sharing of knowledge but creating of knowledge was no statistically meaningful difference observed. In terms of satisfaction with the system, system efficiency ranked first followed by system convenience, information suitability and information usefulness. Conclusion: The results indicate that the use of Nursing KMS increases nurses' knowledge sharing and can contribute to increased quality of nursing knowledge and provide more opportunities for nurses to gain expertise from knowledge shared among nurses.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.77-104
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• 1995

Intelligent Decision System support the decision analysis process in the managerial problems with decision analytic knowledge as well as domain specific knowledge. Influence Diagram has been one of the major knowledge representation in the intelligent decision system. In the development of intelligent decision system, knowledge acquisition is also known to be difficult. This paper suggests a developing tool using an influence diagram and Verbal Protocol Analysis which facilitates knowledge acquision for intelligent decision system. An ennvironmental decision making problem is used as an illustrative example and validation of the suggested developing tool is discussed. The suggested tool is very flexible to be expanded or applied to similar problems.