• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1083-1086
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• 1996

Cold rolling mill process in steel works uses stands of rolls to flatten a strip to a desired thickness. At cold rolling mill process, precalculation determines the mill settings before a strip actually enters the mill and is done by an outdated mathematical model. A corrective neural network model is proposed to improve the accuracy of the roll force prediction. Additional variables to be fed to the network include the chemical composition of the coil, its coiling temperature and the aggregated amount of processed strips of each roll. The network was trained using a standard backpropagation with 4,944 process data collected from no.1 cold rolling mill process from March 1995 through December 1995, then was tested on the unseen 1,586 data from Jan 1996 through April 1996. The combined model reduced the prediction error by 32.8% on average.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.63-66
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• 1996

Cold rolling mill process in steel works uses stands of rolls to flatten a strip to a desired thichness. At Pohang Iron and Steel Company (POSCO) in Pohang, Korea, precalculation determines the mill settings before a strip actually enters the mill and is done by an outdated mathematical model. A corrective neural network model is proposed to improve the accuracy of the roll force prediction. Additional variables to be fed to the network include the chemical composition of the coil, its coiling temperature and the aggregated amount of processed strips of each roll. The network was trained using a standard backpropagation with 2,277 process data collected form POSCO from March 1995, then was tested on the unseen 200 data from the same period. The combined model reduced the prediction error by 55.4% on average.

• KSCI Review
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• v.14 no.2
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• pp.185-197
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• 2006

A star schema consists of a central fact table, which is surrounded by one or more dimension tables. Each row int the fact table contains a multi-part primary key(or a composite foreign key) along with one or more columns containing various facts about the data stored in the row Each of the composit foreign key components is related to a dimensional table. The combination of keys in the fact table creates a composite foreign key that is unique to the fact table record. The composite foreign key, however, is rarely unique to the fact table record in real-world applications, particularly in financial applications. In order to make the composite foreign key be the determinant in real-world application, some precalculation might be performed in the SQL relational database, and cached in the OLAP database. However, there are many drawbacks to this approach. In some cases, this approach might give users the wrong results. In this paper, an approach to fact table modeling and related MDX query composing, which can be used in real-world applications without performing any precalculation and gives users the correct results, is proposed.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.177-188
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• 2007

A star schema consists of a central fact table, which is surrounded by one or more dimension tables. Each row in the fact table contains a multi-part primary key(or a composite foreign key) along with one or more columns containing various facts about the data stored in the row. Each of the composit foreign key components is related to a dimensional table. The combination of keys in the fact table creates a composite foreign key that is unique to the fact table record. The composite foreign key, however, is rarely unique to the fact table retold in real-world applications, particularly in financial applications. In order to make the composite foreign key be the determinant in real-world application, some precalculation might be performed in the SQL relational database, and cached in the OLAP database. However, there are many drawbacks to this approach. In some cases, this approach might give users the wrong results. In this paper, an approach to fact table modeling and related MDX query composing, which can be used in real-world applications without performing any precalculation and gives users the correct results, is proposed.

• Journal of IKEEE
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• v.15 no.4
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• pp.354-362
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• 2011

One of the unsolved problems in Artificial Neural Networks is related to the capacity of a neural network. This paper presents a CoreNet which has a multi-leveled input and a multi-leveled output as a 2-layered artificial neural network. I have suggested an equation for calculating the capacity of the CoreNet, which has a p-leveled input and a q-leveled output, as $a_{p,q}=\frac{1}{2}p(p-1)q^2-\frac{1}{2}(p-2)(3p-1)q+(p-1)(p-2)$. With an odd value of p and an even value of q, (p-1)(p-2)(q-2)/2 needs to be subtracted further from the above equation. The simulation model 1(3)-1(6) has 3 levels of an input and 6 levels of an output with no hidden layer. The simulation result of this model gives, out of 216 possible functions, 80 convergences for the number of implementable function using the cot(x) input leveling method. I have also shown that, from the simulation result, the two diverged functions become implementable by precalculating the weight values. The simulation result and the precalculation of the weight values give the same result as the above equation in the total number of implementable functions.

• Journal of the Korean Institute of Navigation
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• v.2 no.1
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• pp.15-34
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• 1978

This paper deals with the study of the effective reflecting area of the land targets for the improvement of the map of the Radar Simulator, through the analysis of the pictures on P.P.I Scope. It is very important to anticipate the effective refiecting area of land marks, either forinterpretation of radar scope or for simulating accurately the radar scope, but has seldom been studied theoretically or experimentarily, especially on the stand point of simulating the radar scope. Most of the maps of Radar Simulator in use are made without consideration of the effective reflecting area of land marks, so that the P.P.I. Scope of the Radar Simulator may show much different pictures from the actual shore line and other targets. This paper has derived the following conclusiions by experimental procedures. 1. The effective area of the land target greatly varies according to the gradient of the contours, roughness and material of the land surfaces, so that simulator maps of uniformly coated land taret practically used now many be effectively improved by varying the intensity of the land marks proposed in this paper. 2. The intensity of the land targets on the P.P.I. is also related much to the distance from the radar, so that the precalculation of this effect may results in a much simulated P.P.I. picture improved. 3. If the ambient condition is constant, the intensity of the picture increases as the height of the targets is increased.