• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.86-93
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• 2006

The TAM(Topographic Attentive Mapping) network based on a biologically-motivated neural network model is an especially effective one for pattern analysis. It is composed of of input layer, category layer, and output layer. Fuzzy rule, for input and output data are acquired from it. The TAM network with three pruning rules for reducing links and nodes at the layer is called fuzzy TAM network. In this paper, we apply fuzzy TAM network to pattern analysis of core competency model for subcontractors of construction companies and show its usefulness.

• Journal of Welding and Joining
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• v.13 no.3
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• pp.77-88
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• 1995

A prediction method for determining the welding residual stress by artificial neural network is proposed. A three-dimensional transient thermomechanical analysis has been performed for the CO$_{2}$ arc welding using the finite element method. The first part of numerical analysis performs a three-dimensional transient heat transfer analysis, and the second part then uses the results of the first part and performs a three-dimensional transient thermo-elastic-plastic analysis to compute transient and residual stresses in the weld. Data from the finite element method are used to train a backpropagation neural network to predict the residual stress. Architecturally, the fully interconnected network consists of an input layer for the voltage and current, a hidden layer to accommodate the ailure mechanism mapping, and an output layer for the residual stress. The trained network is then applied to the prediction of residual stress in the four specimens. It is concluded that the accuracy of the neural network predicting method is fully comparable with the accuracy achieved by the traditional predicting method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.437-443
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• 2007

In this paper, we propose the power-aware test framework for Network-on-Chip, which is based on embedded processor and on-chip network. First, the possibility of using embedded processor and on-chip network isintroduced and evaluated with benchmark system to test the other embeddedcores. And second, a new generation method of test pattern is presented to reduce the power consumption of on-chip network, which is called don't care mapping. The experimental results show that the embedded processor can be executed like the automatic test equipments, and the test time is reduced and the power consumption is reduced up to 8% at the communication components.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.160-163
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• 1995

An optimal EEG and artifact classifier is proposed using neural network operating characteristics. The neural network operating characteristics are two dimensional parametric representations of the right and false identification probabilities of the network classifier. Since the EEG and EP signals acquired from multi -channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG), the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. Using the neural-network based classification, human expert's efforts and time can be substantially reduced. From experiments, the neural-network based classification performs as good as human experts: variation of decisions between the neural network and human expert appears even smaller than that between human experts.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.705-709
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• 1995

The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

• International Journal of Korean Welding Society
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• v.1 no.2
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• pp.51-60
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• 2001

A prediction method for determining the welding residual stress by artificial neural network is proposed. A three-dimensional transient thermo-mechanical analysis has been performed for the $CO_2$ arc welding using the finite element method. The first part of numerical analysis performs a three-dimensional transient heat transfer analysis, and the second part then uses the results of the first part and performs a three-dimensional transient thermo-elastic-plastic analysis to compute transient and residual stresses in the weld. Data from the finite element method are used to train a back propagation neural network to predict the residual stress. Architecturally, the fully interconnected network consists of an input layer for the voltage and current, a hidden layer to accommodate the failure mechanism mapping, and an output layer for the residual stress. The trained network is then applied to the prediction of residual stress in the four specimens. It is concluded that the accuracy of the neural network predicting method is fully comparable with the accuracy achieved by the traditional predicting method.

• International Journal of Contents
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• v.2 no.4
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• pp.1-7
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• 2006

The goal of Ambient Intelligence (AmI) is to build a smart environment for users where they are supported in some of their activities by many interaction mechanisms. The diversity of AmI characteristics requires special support from Operating Systems (OSes). In this paper, in order to support a conscious choice of an operating system for any specific AmI application, features requested by AmI systems were characterized and defined considering various applications. Then, characteristics of existing Operating Systems have been investigated in the context of AmI application support to relate their key characteristics to the typical requirements of AmI systems. Qualitative mapping table between AmI characteristics and as features has been proposed with an illustration of how to use it. As no as completely covers the range of characteristics required by AmI systems, challenging issues are summarized for the development of a new as and a product line of OSes.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.43-48
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• 2003

This study presents the detailed methods for university facilities mapping using GPS and totalstation. In the control survey by GPS network adjustment, the level of significance for the height value of fourth order triangulation stations was estimated about loom. The accuracy analysis of height determination by totalstation for the traverse points showed that the RMSE came out 9mm to the basis of direct leveling, so it indicated that trigonometric leveling by totalstation was correct comparatively. For GPS/RTK method, the result of accuracy analysis about traverse points showed that the RMSE came out 33㎜ in horizontal location to the basis of totalstation's outcome and 15㎜ in height value to the basis of direct leveling. In the construction survey, GPS/RTK surveying is quicker and more economical than totalstation surveying in the feasible areas of GPS surveying, but there were many impossible areas lot GPS/RTK surveying by the obstacles like a building.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.415-420
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• 2005

Mathematical modeling and simulation of biochemical reaction networks gained a lot of attention recently since it can provide valuable insights into the interrelationships and interactions of genes, proteins and metabolites in a reaction network. A number of attempts have been made for modeling and storing biochemical reaction networks without their dynamical properties but unfortunately storing and efficiently querying of the dynamic (mathematical) models are not yet studied extensively. In this paper, we present a novel nested relational data schema to store a pathway with its dynamic properties. We then show how to make the mapping between this dynamic pathway schema with the corresponding static pathway representation.

• Journal of the Korean Society for information Management
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• v.15 no.3
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• pp.95-112
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• 1998

This study is to investigate the problems in mapping between MARC data and Dublin core metadata, and to evaluate metadata as a source of cataloging. In addition resource description framework and its XML syntax for processing metadata in different format were analyzed in the view from encoding and transporting metadata in the network environments.