• 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

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.801-802
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1467-1470
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• 2003

In order to enhance the productivity of design and manufacture of injection molds, various computer-aided systems have been developed and introduced to mold manufacturers. The customized 3-D CAD systems for mold design is one of the most representative computer-aided system. However, these systems usually do not provide a convenient way to access and manage design knowledge implemented in them. To overcome this shortage, knowedge-based engineering systems have been developed, and now they are imbedded as modules of commercial CAD systems. In this paper, we introduced a 3-D design system for standard mold base based on Knowledge Fusion, a commercialized KBE system imbedded in Unigraphics. By introducing KBE system, design knowledge can be exposed to the users and modified by the end-users.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.613-614
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• 2006

Design data, information, and knowledge have complex associations with each other. Systems related with the management of the data, information, and knowledge are various, and the representations are numerous. Therefore it is difficult to construct a knowledge based design system with a full association knowledge for supporting the design tasks. In this research, OWL based ontology model for an excavator design is developed for the representation of the relationships. Also an ontology model is used to develop the knowledge based excavator design system.

• Journal of Information Technology Applications and Management
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• v.18 no.1
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• pp.75-100
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• 2011

For decades, thousands of corporation introduced knowledge management systems to respond knowledge-based society. However, it seems that the systems merely focusing on knowledge accumulation and its sharing have been bounded by many restrictions in terms of new knowledge creation based on the life cycle of knowledge management systems. Moreover, recently, a variety of knowledge management activities regarding organization, systems, and process is emphasized as a strategic asset for a corporation to create core knowledge. Therefore, this study adopted the Csikszentmihalyi's flow theory to investigate the factors affecting knowledge creation and the success factors of knowledge management systems in virtual space. Prior studies argued that flow experience should be a prerequisite for creative knowledge creation. In that vein, this research revealed the causal relationships for flow experience between the determinants of clear goal, immediate feedback, congruence of challenge and skill. Additionally, it empirically examined how flow experience affected the exploratory behavior of knowledge creation.

• Journal of the military operations research society of Korea
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• v.23 no.2
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• pp.45-71
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• 1997

There has been considerable research recently on uncertainty handling in the fields of artificial intelligence and knowledge-based system. Various numerical and non-numerical methods have been proposed for representing and propagating uncertainty in knowledge-based system. The Bayesian method, the Dempster-Shafer's Evidence Theory, the Certainty Factor model and the Fuzzy Set Theory are most frequently appeared in the knowledge-based system. Each of these four methods views uncertainty from a different perspective and propagates it differently. There is no single method which can handle uncertainty properly in all kinds of knowledge-based systems' domain. Therefore a knowledge-based system will work more effectively when the uncertainty handling method in the system fits to the system's environment. This paper proposed a framework for selecting proper uncertainty handling methods in knowledge-based system with respect to characteristics of problem domain and cognitive styles of experts. A schema with strategic/operational and unstructured/structured classification is employed to differenciate domain. And a schema with systematic/intuitive and preceptive/receptive classification is employed to differenciate experts' cognitive style. The characteristics of uncertainty handling methods are compared with characteristics of problem domains and cognitive styles respectively. Then a proper uncertainty handling method is proposed for each category.

• Korean Journal of Computational Design and Engineering
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• v.10 no.1
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• pp.49-60
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• 2005

Existing CAD systems have configured geometry data and it is necessary to extend the configured geometry into a knowledge-based system. An intelligent CAD system emerged to provide such a knowledge-based system. However the intelligent CAD system has a limited product model to represent various knowledge models. This paper presents a model, called extended intelligent CAD model, which can extend the product model of the intelligent CAD system into further detailed knowledge model. The extended intelligent CAD model includes a whole design process knowledge and an efficiency of the model has been verified via a knowledge based wiper design system. The model can improve the functionality and efficiency of the existing CAD systems.

• Korean Journal of Adult Nursing
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• v.28 no.1
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• pp.83-94
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• 2016

Purpose: The purpose of this study was to explore how knowledge management of hospital and nurses' beliefs and competences on evidence-based practice can affect evidence-based decision making. Methods: In this descriptive study, a total of 184 nurses who were working in the five general hospitals participated. The data were collected through a self-administered questionnaire in September, 2014. Data were analyzed using descriptive statistics, independent t-test, one-way ANOVA, Pearson correlation coefficient, and step-wise multiple regression with SPSS/WIN Statistics 21.0 program. Results: Evidence-based decision making was correlated with EBP beliefs (r=.55, p<.001), EBP competence (r=.57, p<.001), and knowledge management (r=.50, p<.001). Hierarchical regression analysis showed that EBP beliefs (${\beta}=.18$, p=.005), EBP competence (${\beta}=.37$, p<.001), organizational knowledge management (${\beta}=.27$, p<.001) explained 48.6% of evidence based decision making (p<.001). Conclusion: The study results indicated that evidence-based practice competences, organizational knowledge management, and evidence-based practice beliefs were important factors on evidence-based decision making. In order to improve evidence-based practice among nurses through organizational knowledge management, EBP beliefs and competence at individual level need to be considered and incorporated into any systemic training of EBP.

• Knowledge Management Research
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• v.3 no.1
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• pp.93-106
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• 2002

Knowledge management is a recent area in business administration that deals with how to leverage knowledge as a key asset and resource in modern organizations. Also, Knowledge systems are the single most important industrial and commercial offspring of the discipline called artificial intelligence. A Case Based Reasoning(CBR) system solves new problems by recalling adapting previous solutions. This paper presents the results of a recent empirical study. Furthermore this study proposes a CBR Methodology designed to manage knowledge of Hana company under e-business.

• Journal of Information Technology Services
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• v.6 no.1
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• pp.1-15
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• 2007

An objective and valid knowledge activity indicator (KAI) is essential for encouraging knowledge activity in public institution. However, knowledge activity of public institution is inherently different from one of private corporation and, therefore, new method to find aggregated knowledge mileage considering public organizational culture and structure is to be developed. Therefore, this paper shows how to develop KAI of public institution based on three steps. First, knowledge activities were categorized as knowledge creation, knowledge sharing, and knowledge value increasing. Several knowledge indicators and hierarchical knowledge structure were developed for each knowledge categories. Second, personal knowledge mileage was calculated using AHP method considering whole organization's opinion. Finally, these approaches to find KAI were applied to "P" public institution as case studies. The results shows that KAI developed in this paper was very effective in grouping knowledge workers based on knowledge activities.