• Journal of Arbitration Studies
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• v.24 no.3
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• pp.33-46
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• 2014

Amiable composition is a means of dispute resolution based on the arbitrator's authority to base his decision on equity. Although this method has been used frequently in the last decades of the 20th Century, the number of the published awards by amiable compositeur arbitrators is getting lower and lower. The reason(s) for unpopularity of amiable composition should be sought in its very nature, in its relationships with other institutions such as arbitration in law, equity, ex aequo et bono arbitration, other means of dispute resolution and in its role in the development of the rules specific to international commerce. A brief look at the history of law shows that the concept of equity comes to the scene every time that the rigidity of the rules of law challenges the justice. This has been the case in the 20th Century with respect to international commercial law which was deprived of specific rules. The role of amiable composition has been to contribute to the development of the rules specific to international commerce. The progressive codification of such rules in the last decades is also owed to amiable composition, which has accomplished its mission in the evolution of these rules.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.5-8
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• 2000

In this paper, we propose new algorithms for the partition of input space and the generation of fuzzy control rules. The one consists of Shannon and extended fuzzy entropy function, the other consists of adaptive fuzzy neural system with back propagation teaming rule. The focus of this scheme is to realize the optimal fuzzy rule base with the minimal number of the parameters of the rules, reducing the complexity of the system. The proposed algorithm is tested with the time series prediction problem using Mackey-Glass chaotic time series.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.207-210
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• 2003

In this paper, we explore a new data mining capability that is based on Quantitative Attribute and Time Series. Our solution procedure consists of two steps. First, We derive an algorithm to contain the Quantitative Attribute into a set of candidate item. Second, We redefine the concepts of confidence and support for composite association rules. It is shown that proposed methode is very advantageous and can lead to prominent performance improvement.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1262-1265
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• 1993

The paper discusses the problem of controlling systems with a very high number of input variables effectively by fuzzy If . . . then rules. The basic idea is the partition of the state space into domains, which step can be done even iteratively several times, and every domain has its own sub rule base referring to a considerably lower number of variables than the original space. In this manner the number of necessary rules is drastically reduced and time complexity of the control algorithm remains acceptable.

• IE interfaces
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• v.8 no.3
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• pp.249-257
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• 1995

Expert system is an effective approach for quality system to be automated and thus to be an essential integrating mechanism in any move towards CIM(Computer Integrated Manufacturing). A quality control expert system is introduced and its relationship to CIM is illustrated in a case study. Process control expert system developed by Kim and Sin[6] has been improved via ODBC(Open DataBase Connectivity) for efficient information network, graph representation using Windows API for rapid response and some new rules for identification of patterns in control charts.

• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.7-34
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• 2009

Structures of stories, paragraphs, and sentences and inferences applied to indexing and searching were studied to construct the full-text and sentence retrieval system for storytelling. The system designed the database of stories, paragraphs, and sentences and the knowledge-base of inference rules to aid to write the story. The Knowledge-base comprised the files of story frames, paragraph scripts, and sentence logics made by mark-up languages like SWRL etc. able to operate in semantic web. It is necessary to establish more precise indexing language represented the sentences and to create a mark-up languages able to construct more accurate inference rules.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.103-110
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• 1998

In case of traditional Rule-Based Reasoning(RBR) and Case-Based Reasoning(CBR), although knowledge is reasoned either by one of them or by the integration of RBR and CBR, there is a problem that much time should be consumed by numerous rules and cases. In order to improve this time-consuming problem, in this paper, a new type of reasoning technique, which is a kind of integration of reduced RB and CB, is to be introduced. Such a new type of reasoning uses Rough Set, by which we can represent multi-meaning and/or random knowledge easily. In Rough Set, solution is to be obtained by its own complementary rules, using the process of RB and CB into equivalence class by the classification and approximation of Rough Set. and then using reduced RB and CB through the integrated reasoning.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.11
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• pp.562-568
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• 2001

In this paper, we described the export system to monitor and diagnose 765KV power apparatus. To develop this expert system, we studied the knowledge bases and data bases for 765KV transformer and GIS. In order to make the reliable inference of knowledge base and the good MMI(Man Machine Interface), the data bases were consisted of the tables of power apparatus information, limit level value, measured input data, inference result and diagnosis result. The knowledge base had various rules to infer the conditions of transformer and GIS. We applied both the forward chaining and backward chaining methods to these rules of system for good inferences. This paper describes the applied methods for expert system. Also, this developed system was tested with dissolved gas analyzing result and the result was shown.

• Journal of the Korean Geographical Society
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• v.43 no.5
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• pp.761-774
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• 2008

Integration of GIS data and human expert knowledge into digital image processing has long been acknowledged as a necessity to improve remote sensing image analysis. We propose inductive machine learning algorithm for GIS data integration and rule-based classification method for land cover classification. Proposed method is tested with a land cover classification of a Landsat ETM+ multispectral image and GIS data layers including elevation, aspect, slope, distance to water bodies, distance to road network, and population density. Decision trees and production rules for land cover classification are generated by C5.0 inductive machine learning algorithm with 350 stratified random point samples. Production rules are used for land cover classification integrated with unsupervised ISODATA classification. Result shows that GIS data layers such as elevation, distance to water bodies and population density can be effectively integrated for rule-based image classification. Intuitive production rules generated by inductive machine learning are easy to understand. Proposed method demonstrates how various GIS data layers can be integrated with remotely sensed imagery in a framework of knowledge base construction to improve land cover classification.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.06a
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• pp.47-56
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• 1998

Designing Trim die block is a complicated and time-consuming process heavily resting on the experience of the designer. To reduce design time and human errors, a knowledge base is used to automated the design process. In this paper, a framework of the Rule-based CAD System is presented for trim die block design consisting of a rule-base, design process control module and geometric modeler (CATIA). The rule-base includes design rules and know-how of design specialist. CATIA is used as the overall CAD environment and rule-base and design control modules are developed by C++ language with an interface to CATIA. Using the rule-base, the designer can explore alternating designs fast by changing design parameters and the part-list is automatically created which avoids miscommunication.