• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.725-735
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• 2006

This paper deals with the problem of self-learning cooperative motion control for the pushing task of a humanoid robot in the sagittal plane. A model with 27 linked rigid bodies is developed to simulate the system dynamics. A simple genetic algorithm(SGA) is used to find the cooperative motion, which is to minimize the total energy consumption for the entire humanoid robot body. And the multi-layer neural network based on backpropagation(BP) is also constructed and applied to generalize parameters, which are obtained from the optimization procedure by SGA, in order to control the system.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.697-704
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• 2006

The paper is concerned with $H_{\infty}$ filtering for descriptor systems. A necessary and sufficient condition is established in terms of linear matrix inequalities(LMIs) for the existence of normal filters such that the error systems are admissible and the transfer function from the disturbance to the filtering error output satisfies a prescribed $H_{\infty}$-norm bound constraint. When these LMIs are feasible, an explicit parameterization expression of all desired normal filter is given. All these results are yielded without decomposing the original descriptor systems, which makes the filter design procedure simple and direct. Finally, a numerical example is derived to demonstrate the applicability of the proposed approach.

• Journal of Mechanical Science and Technology
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• v.15 no.4
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• pp.413-421
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• 2001

A simple procedure to add and remove material simultaneously along the boundary is developed to optimize the shape of a two dimensional elastic problems and to minimize the maximum von Mises stress. The results for the two dimensional infinite plate with a hole, are close to the theoretical results of an elliptical boundary and the stress concentration is reduced by half for the fillet problem. The proposed shape optimization method, when compared with existing derivative based shape optimization methods has many features such as simplicity, applicability, flexibility, computational efficiency and a much better control on stresses on the design boundary.

• Bulletin of the Korean Mathematical Society
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• v.41 no.1
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• pp.125-135
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• 2004

One of the intriguing and fundamental algorithmic graph problems is the computation of the strongly connected components of a directed graph G. In this paper we first introduce a simple procedure for determining the location of the nonzero elements occurring in $B^{-1}$ without fully inverting B, where EB\;{\equiv}\;(b_{ij)\;and\;B^T$ are diagonally dominant matrices with $b_{ii}\;>\;0$ for all i and $b_{ij}\;{\leq}\;0$, for $i\;{\neq}\;j$, and then, as an application, show that all of the strongly connected components of a directed graph G can be recognized by the location of the nonzero elements occurring in the matrix $C(G)\;=\;(D\;-\;A(G))^{-1}$. Here A(G) is an adjacency matrix of G and D is an arbitrary scalar matrix such that (D - A(G)) becomes a diagonally dominant matrix.

• Journal of Theoretical and Applied Mechanics
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• v.3 no.1
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• pp.1-15
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• 2002

Reduction methods for large structural systems have been reviewed. Mai emphasis is put on the dynamic reduction. Recently, the computing resources and technologies have been expanded so fast that the huge matrices Invoked In the analysis of structural system can be processed without serious difficulties. For most users, however, the computer facilities are limited and the system reductions in some forms are required. The reduction procedure in static problems is simple and straightforward. The major task is the book-keeping in computations. In dynamic problems and structural optimization. however. the problem is much more complicated. The problem is, in general, nonlinear and hence the exact solution is not available. Therefore, approximate solutions are sought in an iterative manner. A proper convergence criterion needs to be employed in order to get an accurate solution efficiently. Several research works have been reported fer the structural optimization combined with system reductions.

• Journal of Ginseng Research
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• v.10 no.1
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• pp.21-26
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• 1986

Polyacetylenes (conjugated poly-ynes) were Isolated from the roots of Panax Ginseng C.A. Meyer by the low pressure preparative liquid chromatography and characterized by spectral analyses. The advantages of the isolation method are the simplicity of the isolation procedure and the much higher yield of poly-ynes compared to the old method.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.43-50
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• 1998

The cause of software crisis is that software quality and productivity can not meet the requirement of software market. In order to resolve the software crisis, there are many approaches to be proposed. Software reuse is one of the high potential approaches to improve software quality and productivity. Some high-tech countries (like USA, Japan) have proposed and studied the topics of software reuse in 1970 and got several results. In software development procedure, the products of detailed design and implement phases are simple, definite and suitable for reuse. In this paper, the necessary documents of reusable software component will be proposed, and how to select and evaluate the software components with high reuse potential and high quality will be discussed and recommended.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.19 no.2
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• pp.149-155
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• 1997

Ridge expansion osteotomy(REO) technique is a simple and more conservation method to widen a narrow alveolar ridge in the maxilla. This method is superior to drilling method in soft and narrow maxillary alveolar ridge and allows the surgeon to widen the ridge in routine office procedure. Therefore, it is the treatment of choice to implant the maxilla with narrow alveolar ridge. This article presents clinical cases and discusses the advantages, rationale and surgical protocol of REO technique.

• Nuclear Engineering and Technology
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• v.41 no.5
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• pp.739-746
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• 2009

This paper introduces facility operation modeling and simulation based primarily on a discrete event system modeling scheme. Many modern industrial facilities are so complex that their operational status cannot be estimated by simple calculations. In general, a facility can consist of many processes and transfers of material between processes that may be modeled as a discrete event system. This paper introduces the current status of studies on operation modeling and simulation for typical nuclear facilities, along with some examples. In addition, this paper provides insights about how a discrete event system can be applied to a model for a nuclear facility. A headend facility is chosen for operation modeling and the simulation, and detailed procedure is thoroughly described from modeling to an analysis of discrete event results. These kinds of modeling and simulation are very important because they can contribute to facility design and operation in terms of prediction of system behavior, quantification of facility capacity, bottleneck identification and efficient operation scheduling.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.323-335
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• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.