• Journal of the Korean Mathematical Society
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• v.46 no.1
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• pp.1-12
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• 2009

Motivated by XTR cryptosystem which is based on an irreducible polynomial $x^3-cx^2+c^px-1$ over $F_{p^2}$, we study polynomials of the form $F(c,x)=x^3-cx^2+c^qx-1$ over $F_{p^2}$ with $q=p^m$. In this paper, we establish a one to one correspondence between the set of such polynomials and a certain set of cubic polynomials over $F_q$. Our approach is rather theoretical and provides an efficient method to generate irreducible polynomials over $F_{p^2}$.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.249-253
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• 2004

When we decide the software quality on the basis of the software measurement, the transitive property which is a requirement for an equivalence relation is not always satisfied. Therefore, we propose a scheme for classifying the software quality that employs a tolerance relation instead of an equivalence relation. Given the experimental data set, the proposed scheme generates the tolerant classes for elements in the experiment data set, and generates the tolerant ranges for classifying the software quality by clustering the means of the tolerance classes. Through the experiment, we showed that the proposed scheme could product very useful and valid results. That is, it has no problems that we use as the criteria for classifying the software quality the tolerant ranges generated by the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.16-16
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• 2000

This paper describes a new structure re create a pseudo Gaussian function network (PGFN). The activation function of hidden layer does not necessarily have to be symmetric with respect to center. To give the flexibility of the network, the deviation of pseudo Gaussian function is changed according to a direction of given input. This property helps that given function can be described effectively with a minimum number of center by PGFN, The distribution of deviation is represented by level set method and also the loaming of deviation is adjusted based on it. To demonstrate the performance of the proposed network, general problem of function estimation is treated here. The representation problem of continuous functions defined over two-dimensional input space is solved.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.4
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• pp.36-43
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• 1992

This paper presents a hierarchical real-time operation control and monitoring scheme of the FMS/CIM center which has been implemented at the Automation and Systems Research Institute of Seoul National University. The hierarchical structure of the whole scheme consists of three lavers. The upper layer is in charge of on-line scheduling, computer network control, shop-floor monitoring and command generation for AGV dispatching, machining, assembly, inspection, set-up, etc. The middle layer has six modules, which are installed in the FMS host computer with the upper layer and run on the multi-tasking basis. Each module is connected to one of six cell controllers distributed in the FMS model plant and transfers operation command down to each cell controller through the Ethernet/TCP-IP local area network. The lower layer is comprised of six cell control software modules for machining cell, assembly cell, inspection cell, set-up stations. AS/RS and AGV. Each cell controller reports the status of the manufacturing facilites to the middle layer as well as ecxecuting the appropriate sequence control of the manufacturing processes.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.143-145
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• 2001

In this paper, we present the modeling and resonance frequency of M/G set simulator, which is designed for SSR(Subsynchronous Resonance) phenomenon. Resonance frequency analysis is performed by modeling and simulation. This simulation is preparation for experiments. So, simulation scenario is constructed in basis of detail experiments and simulation is performed by Matlab.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.05a
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• pp.180-184
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• 2009

A novel set of experimental test tooling for measuring pulling and holding forces for drawbeads on binders inclined at a wide range of angles is introduced. A mechanical design featuring a single load cell, a male-female draw bead set, translation and rotation degrees of freedom, and a screw-driven clamping system has been incorporated into a standard tensile test machine. On a real time basis, restraining and holding force data with respect to draw-in displacement may be directly downloaded into a PC for data processing. The proposed experimental system represents a significant breakthrough in drawbead simulation technology due to its relatively low cost, clever design, and versatility. The system is shown to yield excellent experimental data suitable for verifying theory and numerical model predictions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.112-119
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• 2009

Telecare, one of the e-healthcare services with lCT, is a promising technology which aims to monitor the state of patients and then provide the medical services appropriately in remote sites. Virtual telecare team based on the concept of virtual collaborative teams which consist of a patient, a doctor, and a telecare team, operates on a temporary basis in need. Reputation, which means the degree of a patient's belief to a doctor in consideration, is the most important factor to make the virtual telecare team trustable. In this paper, we propose the fuzzy reputation model of a virtual telecare team, which is a reputation-based trust model based on fuzzy set theory. An illustrative example is also given in order to show the applicability of the model to the concept of a virtual telecare team.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.63-74
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• 1991

An expert scheduling system on real time basis for computer-aided manufacturing systems has been developed. In developing expert scheduling system, the most time-consuming job is to obtain rules from expert schedulers. An efficient process of obtaining rules directly form the schedules produced by expert schedulers is proposed. By the process, a set of complete and minimal set of rules is obtained. During a real time scheduling, when given information on possible values of elements, the rules produce possible values of decision elements, where logical explanations of the result may be offered in terms of chaining rules. The learning and scheduling processes have been simulated with an automated manufacturing line engaged in the production of circuit boards.

• The KIPS Transactions:PartA
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• v.8A no.1
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• pp.56-62
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• 2001

This paper presents a neural network based variable structure control scheme for nonlinear systems. In this scheme, a set of local variable structure control laws are designed on the basis of the linear models about preselected representative points which cover the range of the system operation of interest. From the combination of the set of local variable structure control laws, neural networks infer the approximate control input in between the operating points. The neural network based variable structure control alleviates the effects of model uncertainties, which cannot be compensated by the control techniques using feedback linearization. It also relaxes the discontinuity in the system’s behavior that appears when the control schemes based on the family of the linear models are applied to nonlinear systems. Simulation results of a ball and beam system, to which feedback linearization cannot be applied, demonstrate the feasibility of the proposed method.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.873-876
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• 2000

The information-theoretic approach to face recognition is based on the compact coding where face images are decomposed into a small set of basis images. Most popular method for the compact coding may be the principal component analysis (PCA) which eigenface methods are based on. PCA based methods exploit only second-order statistical structure of the data, so higher- order statistical dependencies among pixels are not considered. Independent component analysis (ICA) is a signal processing technique whose goal is to express a set of random variables as linear combinations of statistically independent component variables. ICA exploits high-order statistical structure of the data that contains important information. In this paper we employ the ICA for the efficient feature extraction from face images and show that ICA outperforms the PCA in the task of face recognition. Experimental results using a simple nearest classifier and multi layer perceptron (MLP) are presented to illustrate the performance of the proposed method.