• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.36 no.5 s.108
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• pp.11-20
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• 2004

In this work the Model Algorithmic Control (MAC) method is applied to control the grade change operations in paper mills. The neural network model for the grade change operations is identified first and the impulse model is extracted from the neural network model. Results of simulations for MAC control of grade change operations are compared with plant operation data. The major contribution of the present work is the application of MAC in the industrial plants based on the identification of neural network models. We can confirm that the proposed MAC method exhibits faster responses and less oscillatory behavior compared to the plant operation data in the grade change operations.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2003.11a
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• pp.272-290
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• 2003

In this study a model for the drying process in paper production plants was developed based on the mass and heat balances around drying cycles. Relationships for the heat transfer coefficients between the web and the air as well as between the drying cylinder and the web were extracted from the closed-loop plant operation data. It was found that the heat transfer coefficients could be represented effectively in terms of moisture content, basis weight and reel velocity. The effectiveness of the proposed model was illustrated through numerical simulations. From the comparison with the operation data, the proposed model represents the paper plant being considered with sufficient accuracy.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.5
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• pp.53-61
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• 2003

In this study a model for the drying process in paper production plants was developed based on the mass and heat balances around drying cycles. Relationships for the heat transfer coefficients between the web and the air as well as between the drying cylinder and the web were extracted from the closed-loop plant operation data. It was found that the heat transfer coefficients could be represented effectively in terms of moisture content, basis weight and reel velocity. The effectiveness of the proposed model was illustrated through numerical simulations. From the comparison with the operation data, the proposed model represents the paper plant being considered with sufficient accuracy.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.449-452
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• 2004

The life of power transformer is basically dependent on the aging deterioration of insulating paper. Analysis of insulating paper for its DP value or tensile strength requires removal of a few strips of paper but direct measurement of this properties is not practical for in-service transformers. For this reason furfural analysis by HPLC has gained increasing favor as a means of estimating degradation of insulating papers in power transformers and this paper reports on the analysis of data on the concentration of furfural in oil samples from about 50 power transformers and the case study. The data showed that furfural content can estimate more accurately aging characteristics compared to concentration of CO, $CO_2$. We expect that these results can be useful to predict the aging characteristics and life diagnosis of power transformers and further the study must be continued.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2004.11a
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• pp.212-220
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• 2004

In this work the Dynamic Matrix Control method is applied to control the grade change operations in paper mills. Paper process trained by neural network regards a real-plant. The model obtained with operation data is used to achieve DMC. Results of simulations for DMC control of grade change operations are compared with plant operation data response. From the comparison, we can see that the proposed DMC method exhibits faster response for the grade change of paper and achieves stable steady-state.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.15-25
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• 1999

We propose an extended relational data model which can represent the reliability of data. In this paper, the reliability of data is defined as the reliability of the source, from which the data originated. We represent the reliability of data at the level of attribute values, instead of tuples, then define the selection, product and join operators.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.141-146
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• 2001

XML is fast emerging as the dominant standard to represent and exchange data in the Web. As the amount of data available in the Web has increased dramatically in recent years, the data resides in different forms ranging from semi-structured data to highly structured data in relational database. As semi-structured data will be represented by XML, XML will increase the ability of semi-structured data. In this paper, we propose an idea for extracting schema in XML document using DTD.

• Journal of the Korea Computer Industry Society
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• v.10 no.3
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• pp.73-78
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• 2009

This paper designed Object-orientid Meta_data operation module that introducted new Meta_class basis the Meta_Classfication model. In order to implement this Data model, we have introducted heurilistic class to traditional object-orinted database. And we designed Meta_data operation module for Inplemetated Meta_data that basis on the heurilistic classficasion model using stored Meta_data in extened object-oriend data model.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1353-1359
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• 2010

Basic objective in cluster analysis is to discover natural groupings of items. In general, clustering is conducted based on some similarity (or dissimilarity) matrix or the original input data. Various measures of similarities between objects are developed. In this paper, we consider a clustering of huge categorical real data set which shows the aspects of time-location-activity of Korean people. Some useful similarity measure for the data set, are developed and adopted for the categorical variables. Hierarchical and nonhierarchical clustering method are applied for the considered data set which is huge and consists of many categorical variables.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.329-332
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• 2000

Research interests on temporal data have been almost focused on data models. There has been relatively less research in the area of temporal data management. In this paper, we propose two data migration strategies based on time-segmented storage structure: the migration strategy by Time Granularity, the migration strategy by LST-GET. We describe the criterion for data migration and moving process. We simulated the performance of the migration strategy by Time Granularity in order to compare it with non-segmentation method. We compared and analyzed two data migration strategies for temporal data.