• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.395-402
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• 2010

The seriousness of a traffic accident appears relatively higher on the curve sections compared with the straight sections due to a change in speed caused by a change in the driver's sight. In particular, the visual distortion phenomenon, one of the dangerous factors taking place on the curve sections, appears different according to the road's geometric design. Although it is a genuinely principal design factor which should be necessarily considered in designing a road, the previous researches on establishing the design standards for it have been insufficiently conducted. As a result, the establishment of the road design standards for the curve sections considering the sight distortion phenomenon is desperately required. This research examined the previous researches on the driver's behaviors, the driver's sight characteristics and the perceived curve radius on the curve sections, and developed the theoretical model of perceived curve radius to which a mathematical technique is applied in consideration of the visual distortion phenomenon on the two-lane curve sections in a local area. In addition, after the theoretical visual distortion was calculated on the basis of the theoretical model of perceived curve radius, the range of error on the theoretical recognition radius model formula was verified through comparing it with the previous researches' experiential visual distortion level and analyzing both of them. As a result, it was observed that as the curve radius practically increases in the theoretical recognition curve radius, the range of error tends to go down, which reflects well the characteristics of the curve sections on the road. Based on this research, it is expected that this research will be helpful to eliminate the safety defects when designing the curve sections and contribute to develop the road design standards considering human factors in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.23-31
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• 2000

Iterative curve evolution techniques are powerful methods for image segmentation. Classical methods proposed curve evolutions which guarantee close contours at convergence and, combined with the level set method, they easily handled curve topology changes. In this paper, we present a new geometric active contour model based on level set methods introduced by Osher & Sethian for detection of object boundaries or shape and we adopt anisotropic diffusion filtering method for removing noise from original image. Classical methods allow only one-way curve evolutions : shrinking or expanding of the curve. Thus, the initial curve must encircle all the objects to be segmented or several curves must be used, each one totally inside one object. But our method allows a two-way curve evolution : parts of the curve evolve in the outward direction while others evolve in the inward direction. It offers much more freedom in the initial curve position than with a classical geodesic search method. Our algorithm performs accurate and precise segmentations from noisy images with complex objects(jncluding sharp angles, deep concavities or holes), Besides it easily handled curve topology changes. In order to minimize the processing time, we use the narrow band method which allows us to perform calculations in the neighborhood of the contour and not in the whole image.

• Bulletin of the Korean Mathematical Society
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• v.44 no.3
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• pp.429-438
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• 2007

In this paper, we study the position vectors of a spacelike W-curve (or a helix), i.e., curve with constant curvatures, with spacelike, timelike and null principal normal in the Minkowski 3-space $\mathbb{E}_1^3$. We give some characterizations for spacelike W - curves whose image lies on the pseudohyperbolical space $\mathbb{H}_0^2$ and Lorentzian sphere $\mathbb{S}_1^2$ by using the positions vectors of the curve.

• Korean Journal of Computational Design and Engineering
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• v.15 no.2
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• pp.115-123
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• 2010

We present an efficient algorithm for computing the Hausdorff distance between two planar curves. The algorithm is based on an efficient trimming technique that eliminates the curve domains that make no contribution to the final Hausdorff distance. The input curves are first approximated with biarcs within a given error bound in a pre-processing step. Using the biarc approximation, the distance map of an input curve is then approximated and stored into the graphics hardware depth-buffer by rendering the distance maps (represented as circular cones) of the biarcs. We repeat the same procedure for the other input curve. By sampling points on each input curve and reading the distance from the other curve (stored in the hardware depth-buffer), we can easily estimate a lower bound of the Hausdorff distance. Based on the lower bound, the algorithm eliminates redundant curve segments where the exact Hausdorff distance can never be obtained. Finally, we employ a multivariate equation solver to compute the Hausdorff distance efficiently using the remaining curve segments only.

• Korean Journal of Hydrosciences
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• v.4
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• pp.21-32
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• 1993

The estimates of both runoff depth and peak runoff by the basin runoff curve numbers, which are CN-II for antecedent moisture condition- II and CN -III for antecedent moisture condition-III, obtained from hydrological soil-cover complexes of 26 watersheds are investigated by making use of the observed curve numbers, which are median curve number and optimum curve number, computed from 250 rainfall-runoff records. For gaged basins the median curve numbers are recommended for the estimation of both runoff depth and peak runoff. For ungaged basin, found is that for the estimate of runoff depth CN-II is adequate and for peak runoff CN-II is suitable. Also investigated is the variation of the runoff curves during storms. By the variable runoff curve numbers, the prediction of runoff depth and peak runoff can be improved slightly.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.679-683
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• 2005

The technique which connects Generalized Regression Neural Networks Model(GRNNM) with Genetic Algorithm (CA) is used to derive rating curve in the river basin. GRNNM architecture consists of 4 layers ; input, hidden, summation and output layer. GA method is applied to estimate the optimal smoothing factor when GRNNM is trained. The derivation of rating curve using GRNNM is considered different kinds of hydraulic characteristics such as water stage, area and mean velocity and is applied two stage stations; Sunsan and Jungam. Furthermore, it is compared with conventional curve-fitting method. Through the training and validation performance, the results show that GRNNM is much superior as compared to the conventional curve-fitting method.

• Tribology and Lubricants
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• v.14 no.4
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• pp.114-120
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• 1998

The T-curve, wear and erosion behaviors of two different silicon carbides, i.e., the fine grained SiC and the in situ-toughened SiC(IST-SiC). Both materials exhibited an increasing T-curve behavior, although the T-curve of IST-SiC was steeper than that of fine grained SiC. The fracture toughness of IST-SiC was larger than that of fine grained SiC at long crack regime, whereas an opposite tendency occurred at short crack regime. The rate of material removal during wear and erosion tests was higher in IST-SiC compared to fine grained SiC. The difference between the material removal rates of two materials was discussed in the light of their R-curve behaviors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.188-196
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• 2007

In this paper we propose an efficient offset curve generation algorithm for open and closed 2D point sequence curve(PS curve) with line segments in the plane. One of the most difficult problems of offset generation is the loop intersection problem caused by the interference of offset curve segments. We propose an algorithm which removes global as well as local intersection loop without making an intermediate offset curve by forward tracing of tangential circle. Experiment in computer sewing machine shows that proposed method is very useful and simple.

• Kyungpook Mathematical Journal
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• v.58 no.1
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• pp.117-135
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• 2018

The orthogonal trajectories of the first tangents of the curve are called the involutes of x. The hyperspheres which have higher order contact with a curve x are known osculating hyperspheres of x. The centers of osculating hyperspheres form a curve which is called generalized evolute of the given curve x in n-dimensional Euclidean space ${\mathbb{E}}^n$. In the present study, we give a characterization of involute curves of order k (resp. evolute curves) of the given curve x in n-dimensional Euclidean space ${\mathbb{E}}^n$. Further, we obtain some results on these type of curves in ${\mathbb{E}}^3$ and ${\mathbb{E}}^4$, respectively.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.139-145
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• 1998

This paper addresses the R-curve properties, wear resistance, and erosion resistance of the two silicon carbide ceramics with different microstructures, i.e. , fine grained SiC and in situ-toughened SiC(IST SIC). Fine grained SiC exhibits a relatively flat R-curve behavior whereas the IST SiC exhibits a increasing R-curve behavior. The increasing R-curve behavior in IST SiC is attributed to relatively weak grain boundaries. The rate of material removal during wear tests and erosion tests was higher for IST SiC than that for fine grained SiC. This is attributed to the weaker grain boundaries in IST SiC than that in fine grained SiC. It is implied that fracture toughness in short crack regime should be taken into consideration in the interpretation of the microscopical material removal process. We show that the higher the strength of grain boundaries is, the higher wear and erosion resistances are.