• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.57
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• pp.11-20
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• 2000

In dynamic management environment, CEO must make an efficient decision with information & knowledge management systems based on IT(Information Technology). As a key component to cope with this current, we suggest the business performance analysis system based on KDD(Knowledge Discovery in Databases). We consider the theoretical model that is composited both Value-Added in respect of stakeholder and Economic Value-Added in respect of shareholder. Additionally we use DBMS and data mining method using Genetic Algorithms as physical model. To demonstrate the performance of the business performance analysis system, we analyse a domestic motors industry. The empirical case is based on the financial data of KISFAS(Korea Investors Services Financial Analysis System) database. The samples included in the study consist of H motors/S motors industry over the 16-year from 1981 to 1996.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.127-136
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• 2020

This paper presents an environment for rule-based English-Korean machine translation system, which supports the translation domain adaptation and the continuous translation quality improvement. For the purposes, corpus is essential, from which necessary information for translation will be acquired. The environment consists of a corpus construction part and a translation knowledge extraction part. The corpus construction part crawls news articles from some newspaper sites. The extraction part builds the translation knowledge such as newly-created words, compound words, collocation information, distributional word representations, and so on. For the translation domain adaption, the corpus for the domain should be built and the translation knowledge should be constructed from the corpus. For the continuous improvement, corpus needs to be continuously expanded and the translation knowledge should be enhanced from the expanded corpus. The proposed web-based environment is expected to facilitate the tasks of domain adaptation and translation system improvement.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1150-1159
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• 2000

This paper presents an automatic text categorization model that improves the accuracy by combining statistical and knowledge-based categorization methods. In our model we apply knowledge-based method first, and then apply statistical method on the text which are not categorized by knowledge-based method. By using this combined method, we can improve the accuracy of categorization while categorize all the texts without failure. For statistical categorization, the vector model with Inverted Category Frequency (ICF) weighting is used. For knowledge-based categorization, Phrasal Patterns and Keyword Sets are introduced to represent sentence patterns, and then pattern matching is performed. Experimental results on new articles show that the accuracy of categorization can be improved by combining the tow different categorization methods.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.59-70
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• 1999

This paper deals with automated computer-aided process planning by which designers can determine operation sequences even if they have little experience in the design of press working products. The computer-aided process planning in hot forging, deep drawing and blanking requires many kinds of technical and empirical skills based on investigation and collection of the knowledge of their processes. An approach to the CAPP system is based on the knowledge-based rules and the process knowledge base consisting of process planning rules is built. The methodology adopted to develop the system is elaborated in this paper. This system has been written in AutoLISP on the AutoCAD with a personal computer and provides powerful capabilities for process planning of hot forging, cold forging, deep drawing and blanking products.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.633-639
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• 2001

This paper proposes a knowledge-based expert system. which is assembled into hardware organized with sensor module. AID converter, USB. data acquisition PC and software composed of monitoring and diagnosis module combined with a frame-based method using Sohre's chart and a rule-based method. Vibration signals using various sensors are acquired by AID converter. transferred into PC and processed to obtain a continuous monitoring of the machine status displayed into several plots. Through combining frame-base which covers wide vibration causes with rule-base which gives relatively specified diagnosis results, high accuracy of fault diagnosis can be guaranteed and knowledge base can be easily extended by adding new causes or symptoms. Some examples using experimental data show the good feasibility of the proposed algorithm for condition monitoring and diagnosis of industrial rotating machinery.

• IE interfaces
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• v.2 no.2
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• pp.51-62
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• 1989

A computer-aided simulation modeling system has been developed to allow the automatic construction of complete discrete simulation models for queueing systems. Three types of knowledge are used in the specification and construction of a simulation modeling: Knowledge of queueing system, simulation modeling, and a target simulation language. This knowledge has been incorporated into the underlying rule base in the form of extraction and construction rule, and implemented via the expert system building tool, OPS5. This paper suggested a knowledge based approach for automatic programming to enable a user who lacks modeling knowledge and simulation language expertize to quickly build executable models.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.10a
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• pp.197-206
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• 1995

In structural design procedure, The procedure of member selection manages complex data relationship and reflects structural expert's knowledge. It is a difficult problem to construct an effective system with the conventional l programming technique. Knowledge_based s!'stem is a software system capable of supporting the explicit representation of expert's knowledge in member selection process through member data and reasoning mechanisms. This study describes useful methodology for structuring knowledge and representing relation between member data and knowledge. And this study shows the application of this member for member selection in the steel structural design.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.309-310
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.970-973
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• 1995

The proposal of this paper is the constructing of knowledge database with manufacturing information. This database contains characteristics of workpiece materials, cutting tools, NC machines, manufacturing processes, and work conditions. And all shape in the system are feature models such base plate, step, hole, pocket, boss, and slot. These information generate a final decision for machining process by the expert system.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.149-156
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• 2003

Recently, the importance of plant maintenance(PM) was highly raised to provide efficient plant operation which highly affects the productivity. For this reason, a number of engineering methodologies, such as riskbased inspection(RBI), fitness for service guidelines(FFS), plant lifecycle management(PLM), have been applied to improve the plant operation efficiency. Also, a network-based business operation system, which is called ERP(Enterprise Resource Planning), has been introduced in the field of plant maintenance. However, there was no attempt to connect engineering methodologies to the ERP PM system. In this paper, a knowledge-based information system for the plant operation of steel making company has been proposed. This system, which is named as K-VRS(Knowledge-based Virtual Reality System), provides a connection between ERP plant maintenance module and knowledge-based engineering methodologies, and thus, enables network-based highly effective plant maintenance process. The developed system is expected to play a great role for more efficient and safer plant maintenance.