• Kyungpook Mathematical Journal
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• v.58 no.1
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• pp.183-202
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• 2018

${\Delta}-moves$ are closely related with a Vassiliev invariant of degree 2. For classical knots, M. Okada showed that the second coefficients of the Conway polynomials of two knots differ by 1 if the two knots are related by a single ${\Delta}-move$. The first author extended the Okada's result for virtual knots by using a Vassiliev invariant of virtual knots of type 2 which is induced from the Kauffman polynomial of a virtual knot. The arrow polynomial is a generalization of the Kauffman polynomial. We will generalize this result by using Vassiliev invariants of type 2 induced from the arrow polynomial of a virtual knot and give a lower bound for the number of ${\Delta}-moves$ transforming $K_1$ to $K_2$ if two virtual knots $K_1$ and $K_2$ are related by a finite sequence of ${\Delta}-moves$.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.1
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• pp.76-84
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• 2012

This paper presents the measurement system of arrow's point of impact using laser scan camera and describes the image calibration method. The calibration process of distorted image is primarily divided into explicit and implicit method. Explicit method focuses on direct optical property using physical camera and its parameter adjustment functionality, while implicit method relies on a calibration plate which assumed relations between image pixels and target positions. To find the relations of image and target position in implicit method, we proposed the performance criteria based polynomial theorem model that overcome some limitations of conventional image calibration model such as over-fitting problem. The proposed method can be verified with 2D position of arrow that were taken by SICK Ranger-D50 laser scan camera.

• Journal of Korean Port Research
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• v.14 no.2
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• pp.155-163
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• 2000

A discrete system has interpreted by using the network model, and PERT network is one of these methods. For the purpose of analysing the real system, it is necessary to measure the parameter of the real system. And system identification problem is to assume the parameter of a real system when we get to know the system model, the input data and output data. System identification method has been only developed to a system of which a structure has expressed a differential equation or a polynomial expression. But it has been scarcely developed yet in that case of network model. The aim of this paper is to examine a changes when new system is introduced to the present system. The changes are as follows : how the present system will be changed, when the changes will be happened. In this paper, genetic algorithm is used to assume the parameter.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.101-108
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• 1999

A discrete system has interpreted by using the network model, and PERT network is one of these methods. For the purpose of analysing the real system. it is necessary to measure the parameter of the real system. And system identification problem is to assume the parameter of a real system when we get to know the system model, the input data and output data. System identification method has been only developed to a system of which a structure has expressed a differential equation or a polynomial expression. But it has been scarcely developed yet in that case of network model. The aim of this paper is to examine a changes when new system isn introduced to the present system, The changes are as follows: how the present system will be changed, when the changes will be happened. In this paper, genetic algorithm is used to assume the parameter.