• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.167-172
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• 2010

EPCIS(EPC Information Service) system is a core component of EPCglobal Architecture Framework offering information of the freights, the time of awareness and the location of awareness on the EPCglobal Network. EPCIS Repository continuously stores and manages mass EPCIS Event input data from a great number of RFID devices simultaneously. The Hybrid DBMS can deal efficiently mass necessary data. This study suggest the plan which can efficiently manage EPCIS Repository using Hybrid DBMS. We offer three schema and stores EPCIS Event data to Altibase DB that can efficiently manage EPCIS Repository using Hybrid DBMS and compare the performance about three schema through simulations.

• IE interfaces
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• v.10 no.2
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• pp.15-28
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• 1997

Knowledge acquisition has been a major bottleneck in building expert systems. To ease the problems arising in knowledge acquisition, analog concept learning systems(ACLS) has been used. In this paper, in order to avoid the overfitting problem and secure a good performance, we propose the revised ACLS, which pruning methods -cost complexity, reduced error, pessimistic pruning and production rule- are incorporated into and apply them to the credit evaluation for Korean companies. The performances of the revised ACLS are evaluated in light of the prediction accuracy. To check the effect of the training data sampling on the performance, experiments are conducted using the different proportion of the training data. Experimental results show that the revised ACLS of combining cost complexity pruning with reduced error pruning performs best among original ACLS and other methods.

• Korean Journal of Computational Design and Engineering
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• v.22 no.1
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• pp.80-88
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• 2017

Product data analytics (PDA) is a data-driven analysis method that uses product data management (PDM) databases as its operational data. It aims to understand and evaluate product development processes indirectly through the analysis of product data from the PDM databases. To educate and train PDA efficiently, this study proposed an approach that employs courses for both product development and PDA in a class. The participant group for product development provides a PDM database as a result of their product development activities, and the other group for PDA analyses the PDM database and provides analysis result to the product development group who can explain causes of the result. The collaboration between the two groups can enhance the efficiency of the education and training course on PDA. This study also includes an application example of the approach to a graduate class on PDA and discussion of its result.

• Proceedings of the KAIS Fall Conference
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• 2007.11a
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• pp.81-84
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• 2007

In this thesis, we have designed the indirect adaptive controller using Dynamic Neural Units(DNU) for unknown nonlinear systems. Proposed indirect adaptive controller using Dynamic Neural Unit based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.147-149
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• 2007

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.379-381
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• 2011

Dynamic Neural Unit(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.443-445
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• 2009

Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.564-567
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• 1997

Various ropes used at the industrial fields can be used to experiment analyze tension tester development and also as an educational experiment tool. There fore the purpose of this paper is about rope tension tester development satisfying both safety and educational terms.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.481-486
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• 1999

As the manufacturing systems adapt information technology, safety control and management systems are required to adapt information technology by changing the industrial environment. This paper is presented the methodology of designing the safety control and management system based on intranetwork environment to reduce breakdown time on facility and Increase efficience of safety training and education.

• Proceedings of the KAIS Fall Conference
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• 2006.11a
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• pp.186-190
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• 2006

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.