• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.390-394
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• 2009

The semantic web-based social network is highly useful in a variety of areas. In this paper we make diverse analyses of the FOAF-based social network, and propose an expert recommendation system. This system presents useful method of ontology-based social network using SparQL, RDFS inference, and visualization tools. Then we apply it to real social network in order to make various analyses of centrality, small world, scale free, etc. Moreover, our system suggests method for analysis of an expert on specific field. We expect such method to be utilized in multifarious areas - marketing, group administration, knowledge management system, and so on.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.102-106
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• 1997

Grinding has difficulty in satisfying the qualitative knowledge based on the skilled expert as well as quantitative data for all user. Design of grinding database is based on the frame-based model for utilizing the empirical and qualitative knowledge. Inthis paper, basic strategy to develop the grinding database by frame-based model, which is strongly dependent upon experience and intuition, frame-base model, which is strongly dependent upon experience and intuition, is described. Design of grinding database is based on the frame-based model for utilizing the ambiguous knowledge and inference is accomplised by the object-oriented paradigm system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1202-1206
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• 2004

In the future, a machine-tool will be more improved in the form of a knowledge evolution based device. In order to develop the knowledge evolution based machine-tool, this paper proposes the structure of knowledge evolution and the scheme of a dialogue agent among agent-based modules such as a sensory module, a dialogue module, and an expert system. The dialogue agent has a role of interfacing with another machine for cooperation. To design of the dialogue agent module in M2M(Machine To Machine) environment, FIPA-OS and ping agent based on FIPA-OS are analyzed in this study. Through this, it is expected that the dialogue agent module can be more efficiently designed and the knowledge evolution based machine-tool can be hereafter more easily implemented.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.271-276
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• 1997

Verification is a process aimed at demonstrating whether a system meets it's specified requirements. As expert systems are used in various applications, the knowledge base verification of systems fakes an important position. The conventional Petri net approach that has been studied recently in order to verify the knowledge base is found that it is inadequate to verify the knowledge base of large and complex system, such as alarm processing system of nuclear power plant. Thus, we propose an improved method that models the knowledge base as enhanced colored Petri net. In this study. we analyze the reachability and the error characteristics of the knowledge base and apply the method to verification of simple knowledge base.

• IE interfaces
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• v.3 no.2
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• pp.1-11
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• 1990

In this study, we will present a knowledge-based consulting system, called THYCONS, for diagnosing thyroid disorders. It has been developed to make the knowledge and expertise of the human expert more widely available, therefore achieving a high-quality diagnosis. Frames will be used to represent the medical knowledge of thyroid disorders, and several rules are attached in each slot of a frame. The uncertainty of diagnostic processes is manipulated by the subjective Bayesian method under the assumption that the pieces of evidence are conditionally independent. Searching for the group of diagnostic tests to be carried out and their optimum sequences will be established in order to infer a more correct diagnosis on the basis of maximum information gain with cost and time restrictions. Additionally. differential diagnosis will be carried out based on the information gained.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 1995.10a
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• pp.85-93
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• 1995

Recently, the development of Artificial Intelligence(AI) and Expert System has caused some interest in the possibility of developing an intelligent CAD system. However, these development and possibility are in an extremenly early stage for Architectural design. In this study, the design process of Residence being recognized as a Constraints-satisfied model, a part of these constraints used in the Architectural design of Residence are being systematized and sorted by the design process. Those regulations and planning items to be considered in the basic planning stage are being systematized as a knowledge base system. The possibility of this knowledge-based system as an effective design tool is studied and an integrated form of Architectural design system is proposed.

• Journal of the military operations research society of Korea
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• v.23 no.2
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• pp.120-134
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• 1997

This paper illustrates the process of developing and configuring the prototype computer-assisted analysis system named as Work-Expert for analyzing occupational stress. A Work-Expert was developed to allow the nonexperts or line manager to utilize the existing knowledge in the area of occupational stress estimation, and to provide intelligent and computer-aided problem solving. The purpose of the system development is for future prediction and problem solving. Creating preventive measures, such as early detection of stress, proper placement and promotion of employees, job enlargement, employee identification, employee involvement, communication, and training of managers will be possible by using this system effectively.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.390-395
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• 2004

A semiconductor manufacturing process is the complicate and dynamic process, and consists of many sub-processes. An etching process is the most important process in the semiconductor fabrication. In this paper, the decision support system based upon data mining and knowledge discovery is an important factor to improve the productivity and yield. The proposed decision support system consists of a neural network model and an inference system based on fuzzy logic Firstly, the product results are predicted by the neural network model constructed by the product patterns that represent the quality of the etching process. And the product patters are classified by expert's knowledge. Finally, the product conditions are estimated by the fuzzy inference system using the rules extracted from the classified patterns. Prediction of product qualities can be linked to each input and process variables. We employ data mining and intelligent techniques to find the best condition of the etching process. The proposed decision support system is efficient and easy to be implemented for the process management based upon expert's knowledge.

• Journal of the Korean Society for Marine Environment & Energy
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• v.4 no.4
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• pp.61-69
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• 2001

Recently, according to the rapid development of computer and electronic technology, most crude oil carriers adopt automated cargo handling system. But an excessive automation makes system so complicate that it could increase the Possibility of accidents due to human error. Although a cargo handling process is done by an expert, the potential of accidents by human factor lies through the whole cargo handling procedure and the current automated system lacks of the functionality to prevent a mis-operation and diagnose the abnormal status of the system. Because the oil concerned accident could be almost a disaster, the primary goal of system development should not be a fully automated system but be a perfectly safe system. This paper deals with the analysis and design of an expert system which can provide mariner with the operational guidance and the facility of crisis management by monitoring system's abnormal condition and human's mis-operation.