• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.202-210
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• 2019

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.545-551
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• 2017

It is very important to effectively obtain the information related to the human body shape for user-centered design. The human body shape is a huge combination of various irregular curves and is typically obtained by a 3-D Scanner. 3-D scanners show high reliability; however, they are expnsive equipment with limited mobility. 3-D models of irregular-shaped curves were created by a photogrammetric approach and the errors between the original curve and the models were evaluated. 3-D models were created based on 160, 80, 40, 20, 10, and 5 marking points evenly located on the original curve. In the case of convex curve, low levels of residuals were observed in the models from 160, 80, 40, and 20 marking points (0.13% max). In the combination of convex and concave curves, relatively low levels of residuals were observed in the models from 160, 80, and 40 marking points (0.29%). It is possible to conclude that marking points should be placed at every 5% of overall length of a convex curve and at every 2.5% of overall length of a curve with convex and concave curve in order to maintain low levels of errors. A photogrammetric approach can be used as an alternative for the 3-D scanners with advantages of low cost and mobility.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.130-136
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• 1998

This paper develops an efficient algorithm for the minimum distance calculation between two general polyhedra(convex and/or concave) in three-dimensional space. The polyhedra approximate objects using flat polygons which composed of more than three vertices. The algorithm developed in this paper basically computes minimum distance between two polygons(one polygon per object) and finds a set of two polygons which makes a global minimum distance. The advantage of the algorithm is that the global minimum distance can be computed in any cases. But the big disadvantage is that the minimum distance computing time is rapidly increased with the number of polygons which used to approximate an object. This paper develops a method to eliminate sets of two polygons which have no possibility of minimum distance occurrence, and an efficient algorithm to compute a minimum distance between two polygons in order to compensate the inherent disadvantage of the algorithm. The correctness of the algorithm is verified not only comparing analytically calculated exact minimum distance with one calculated using the developed algorithm but also watching a line which connects two points making a global minimum distance of a convex object and/or a concave object. The algorithm efficiently finds minimum distance between two convex objects made of 224 polygons respectively with a computation time of about 0.1 second.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.375-379
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• 2010

The support vector machine (SVM) has been widely used in variety pattern recognition problems applicable to recommendation systems due to its strong theoretical foundation and excellent empirical successes. However, SVM is sensitive to the presence of outliers since outlier points can have the largest margin loss and play a critical role in determining the decision hyperplane. For robust SVM, we limit the maximum value of margin loss which includes the non-convex optimization problem. Therefore, we proposed the design method of robust SVM using genetic algorithm (GA) which can solve the non-convex optimization problem. To demonstrate the performance of the proposed method, we perform experiments on various databases selected in UCI repository.

• Honam Mathematical Journal
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• v.38 no.3
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• pp.495-506
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• 2016

In this paper, we introduce and investigate a new subclass of meromorphic functions associated with a certain integral operator on Hilbert space. For this class, we obtain several properties like the coefficient inequality, extreme points, radii of close-to-convexity, starlikeness and meromorphically convexity and integral transformation. Further, it is shown that this class is closed under convex linear combination.

• Kyungpook Mathematical Journal
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• v.59 no.4
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• pp.651-663
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• 2019

In this paper, we introduce and study a new subclass of p-valent harmonic functions defined by modified operator and obtain the basic properties such as coefficient characterization, distortion properties, extreme points, convolution properties, convex combination and also we apply integral operator for this class.

• Kyungpook Mathematical Journal
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• v.54 no.1
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• pp.103-111
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• 2014

Let X be a uniformly convex Banach space, and S, T be pair of mean nonexpansive mappings. Some necessary and sufficient conditions are given for Ishikawa iterative sequence converge to common fixed points, and we prove that the sequence of Ishikawa iterations associated with S and T converges to the common fixed point of S and T. This generalizes former results proved by Z. Gu and Y. Li [4].

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1991.04a
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• pp.309-315
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• 1991

This paper presents a method for automatic part feature recognition from the database of AutoCAD system for automatic process planning input. The parts considered in this study are primastic parts composed of faces perpendicular to the X, Y, Z axes and the types of features considered are through steps, blind steps, through slots, blind slots, and pockets. Features are recognized by using the concept of convex points and concave points. The software program is coded by using Turbo Pascal on the IBM PC/AT.

• Bulletin of the Korean Mathematical Society
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• v.60 no.2
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• pp.389-404
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• 2023

We prove sharp bounds for Hankel determinants for starlike functions f with respect to symmetrical points, i.e., f given by $f(z)=z+{\sum{_{n=2}^{\infty}}}\,{\alpha}_nz^n$ for z ∈ 𝔻 satisfying $$Re{\frac{zf^{\prime}(z)}{f(z)-f(-z)}}>0,\;z{\in}{\mathbb{D}}$$. We also give sharp upper and lower bounds when the coefficients of f are real.

• Kyungpook Mathematical Journal
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• v.43 no.4
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• pp.579-585
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• 2003

A new class of univalent functions is defined by making use of the Ruscheweyh derivatives. We provide necessary and sufficient coefficient conditions, extreme points, integral representations, distortion bounds, and radius of starlikeness and convexity for this class.