• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.120-124
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• 2003

Monoleaflet polymer artificial heart valve was known to show remarkable improvement in antithrombosis and pressure drop compared with other type of artificial valve. In this investigation of monoleaflet heart valve the vertical and horizontal deflection pattern of polymer heart valve with three types of supporting members, straight member and two curved members were analysed using the large deformation nonlinear finite element method.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.06a
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• pp.147-155
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• 1999

The film thickness and shape of elastohydrodynamic lubrication is measured by optical interferometer, which is the most precise method for EHL film measurement. However the interpretation of the image pattern from optical viscometer is not easy for two-dimensional shape. A newly developed method of image processing makes it possible to evaluate the film thickness and shape in every point of contact region with two dimensional aspects. In this study, we captured film shape of EHL film from the monochromatic incident light with the Image processing method, which uses phase shift method, and obtained the image analysis method for gray level image in order to qualitatively evaluate film shapes.

• The KSFM Journal of Fluid Machinery
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• v.17 no.5
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• pp.72-77
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• 2014

Because of overload working condition of sintering cooler, the cooler fan often suffers the break or damage of rotor blade and fixing shaft. Therefore, internal flow characteristics of a steelworks sintering cooler fan by the duct shape of the cooler fan outlet, such as duct outlet opening ratio, duct height and dividing wall shape on the duct outlet flow pattern are examined in detail. The results show that relatively short duct wall height and attachment of dividing wall shape improves flow patterns considerably.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.199-210
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• 1994

Most of clustering methods usually employ a center or predefined shape of a cluster to assign the input data into the cluster. When there is no information about data set, it is impossible to predict how many clusters are to be or what shape clusters take. (the shape of clusters could not be easily represented by the center or predefined shape of clusters) Therefore, it is difficult to assign input data into a proper cluster using previous methods. In this paper, to overcome such a difficulty a cluster is to be represented as a collection of several subclusters representing boundary of the cluster. And membership functions are used to represent how much input data bllongs to subclusters. Then the position of the nearest subcluster is adaptively corrected for expansion of cluster, which the subcluster belongs to by use of a competitive learning neural network. To show the validity of the proposed method a numerical example is illustrated where FMMC(Fuzzy Min-Max Clustering) algorithm is compared with the proposed method.

• Korean Institute of Interior Design Journal
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• v.14 no.2 s.49
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• pp.197-205
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• 2005

In estimating designed architectural buildings, many factors in various design domains such as function, structure, form, environment may be considered and then a building design might be selected or modified as final design from many possible design results. This paper proposed a method to obtain complexity values from two dimensional drawings which are floor plans or elevations. The Complexity values could be turned into esthetic values. The method has been developed based on information theory, shape pattern representation and cognitive theory. Results of measuring complexity value can make the computer evaluate and select final results produced from automatic design processes by the computer That is to say, aesthetic values based on order and chaos can be measured using complexity values and then some results having superior values can be selected as final result. Also some cognitive processes as perception of two dimensional drawings are discussed using shape representations. Aesthetic values could be varied in terms of shape properties such as size, individualities and knowledge as well as order and chaos.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.19-19
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• 2000

This paper introduces a new scheme for neural network classifier which can describe the shape of patterns in clustered group by using a self-organizing teeming algorithm. The prototype based neural network classifier can not describe the shape of group and it has low classification performance when the data groups are complex. To improve above-mentioned problem, new neural scheme is introduced. This proposed neural network algorithm can be regarded as the extension of self-organizing feature map which can describe The experimental results shows that the proposed algorithm can describe the shape of pattern successfully.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.205-209
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• 1994

The main purpose of this study is constructing new velocity fields on the base of shape function used in finite element method and showing the possibility of application it to metal forming processes. Utilizing the 8-node quadratic rectangular element, we expressed the velocity within the deformation region by interpolating the velocity of each nodal points. And the upper-bound formulation from this velocity fields was derived. In order to confirm the validity of this method we applied it to axisymmetic combined extrusion problem. the results of load show that this method is on better agreement with experiment than the conventional UBET, and also the flow pattern and profile of extruded part are reasonable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3685-3700
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• 2015

To avoid influences caused by pose, illumination and facial expression variations, we propose a robust three-step algorithm based on ASM and POEM for facial landmark localization. Firstly, Model Selection Factor is utilized to achieve a pose-free initialized shape. Then, we use the global shape model of ASM to describe the whole face and the texture model POEM to adjust the position of each landmark. Thirdly, a second localization is presented to discriminatively refine the subtle shape variation for some organs and contours. Experiments are conducted in four main face datasets, and the results demonstrate that the proposed method accurately localizes facial landmarks and outperforms other state-of-the-art methods.

• Journal of International Society for Simulation Surgery
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• v.2 no.1
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• pp.7-9
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• 2015

Purpose In the many face-related application such as head pose estimation, 3D face modeling, facial appearance manipulation, the robust and fast facial feature extraction is necessary. We present the facial feature extraction method based on shape regression and feature selection for real-time facial feature extraction. Materials and Methods The facial features are initialized by statistical shape model and then the shape of facial features are deformed iteratively according to the texture pattern which is selected on the feature pool. Results We obtain fast and robust facial feature extraction result with error less than 4% and processing time less than 12 ms. The alignment error is measured by average of ratio of pixel difference to inter-ocular distance. Conclusion The accuracy and processing time of the method is enough to apply facial feature based application and can be used on the face beautification or 3D face modeling.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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• pp.53-58
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• 2003

Wear debris can be collected from the lubricants of operating machinery and its morphology is directly related to the fiction condition of the interacting materials from which the wear particles originated in lubricated machinery. But in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefore, if the shape characteristics of wear debris is identified by computer image analysis and the neural network, The four parameter (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction. It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We resented how the neural network recognize wear debris on driving condition.