• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.84-89
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• 2007

This research was done on the basis of assumption that there is a relationship between welding parameters and geometry of the back-bead being a gap in arc welding. Multiple regression analysis was used as method for predicting the geometry of the back-bead. The analysis data and the verification data were used for the formation of multiple regression analysis. The method was used to perform the prediction of the back-bead.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.10
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• pp.582-588
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• 2002

Scalable displays generate large and high resolution images and provide an immersive environment. Recently, scalable displays are built on the networked clusters of PCs, each of which has a fast graphics accelerator, memory, CPU, and storage. However, the distributed rendering on clusters is a network bound work because of limited network bandwidth. In this paper, we present a new algorithm for reducing the network bandwidth and implement it with a conventional distributed rendering system. This paper describes the algorithm called geometry tracking that avoids the redundant geometry transmission by indexing geometry data. The experimental results show that our algorithm reduces the network bandwidth up to 42%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.161-171
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• 1993

The basin instantaneous unit hydrograph was derived by considering the network geometry and hillslope. The network geometry is quantified in a function, termed the width function, that reflects the distribution of runoff with flow distance from the outlet. The model using the derivation of the basin IUH consists of two components: the routing component of the initial distribution through the network by means of a simplified diffusion approximation and the hillslope component by means of a exponential distribution that is the probability density function of the travel time in the hillslope. The application of this method was tested on four observed flood data of Bocheong stream and Wi stream. The results show that the proposed method can be used for the analysis of the basin IUH.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.339-340
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• 2008

This paper presents a novel design of the printed hyperpolar-transformed Sierpinski Carpet (HSC) antenna. By hyperpolar transforming the Sierpinski carpet geometry, from isotropic scaling symmetry to equiangular scaling symmetry, we get improved performance rather than that of the general Sierpinski Carpet antenna. The design parameter and performance of the proposed monopole antenna are investigated by simulation. And we showed that proposed HSC geometry gives more freedom for wideband antenna design such as flare angle, (angular)scale factor.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.637-642
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• 2002

Generally, the use of robots in manufacturing industry has been increased during the past decade. GMA(Gas Metal Are) welding is an actively growing area and many new procedures have been developed for use with high strength alloys. One of the basic requirement for welding applications is to study relationships between process parameters and bead geometry. The objective of this paper is to develop a new approach involving the use of neural network and multiple regression methods in the prediction of bead geometry for GMA welding process and to develop an intelligent system that enables the prediction of bead geometry using Rapid Prototyping(RP) in order to employ the robotic GMA welding processes. This system developed using MATLAB/SIMULINK, could be effectively implemented not only for estimating bead geometry, but also employed to monitor and control the bead geometry in real time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.608-611
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• 2002

In GMAW(Gas Metal Arc Welding) process, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality. Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWB (contact- tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using negro-fuzzy algorithm. Neural networks was applied to design FL(fuzzy logic). The parameters of input membership functions and those of consequence functions in FL were tuned through the method of learning by backpropagation algorithm. Bead geometry could be reasoned from welding current, arc voltage, travel speed on FL using the results learned by neural networks.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.616-625
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• 2011

There are two representative geometry rendering methods. One is Geometry Clipmaps, another is ROAM 2.0. We propose an extended Geometry Clipmaps algorithm which does not focus on CPU operation but the GPU for faster and wider visibility area. The extended algorithm presents mesh configuration method of each level by LOD, how to configurate Mesh network between levels, mesh block method for rendering optimization using VFC, and image mapping method to get high resolution up to 1 m.

• Journal of Welding and Joining
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• v.15 no.6
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• pp.116-123
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• 1997

In GMA welding processes, bead contour and penetration patterns are criterion to estimate weld quality. Bead geometry is commonly defined with width, height and depth. When weaving is taken into account, selection of welding conditions is known to be difficult. Thus, empirical or trial-and-error method are usually introduced. This study examined the correlation of welding process variables including weaving parameters with bead geometry using srtificial neural networks(ANN). The main task of the Ann estimator is to realize the mapping characteristics from the sampled welding process variables to the actual bead geometry through training. After the neural network model is constructed, welding process variables for desired bead geometry is selected by inverse model. Experimental varification of the inverse model is conducted through actual welding.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.1
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• pp.43-48
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• 2002

This paper describes an automated computer-aided engineering (CAE) system for three-dimensional structures. An automatic finite element mesh-generation technique, which is based on fuzzy knowledge processing and computational geometry techniques, is incorporated into the system, together with a commercial FE analysis code, and a commercial solid modeler. The system allows a geometry model of interest to be automatically converted to different FE models, depending on the physical phenomena of the structures to be analyzed, i.e., electrostatic analysis, stress analysis, modal analysis, and so on. Also, with the aid of multilayer neural networks, the present system allows us to obtain automatically a design window in which a number of satisfactory design solutions exist in a multi-dimensional design parameter space. The developed CAE system is successfully applied to evaluate an electrostatic micromachines.

• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.32-39
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• 2019

A convolutional neural network (CNN) has been widely used in facial expression recognition (FER) because it can automatically learn discriminative appearance features from an expression image. To make full use of its discriminating capability, this paper suggests a simple but effective method for CNN based FER. Specifically, instead of an original expression image that contains facial appearance only, the expression image with facial geometry visualization is used as input to CNN. In this way, geometric and appearance features could be simultaneously learned, making CNN more discriminative for FER. A simple CNN extension is also presented in this paper, aiming to utilize geometric expression change derived from an expression image sequence. Experimental results on two public datasets (CK+ and MMI) show that CNN using facial geometry visualization clearly outperforms the conventional CNN using facial appearance only.