• Korean Journal of Mathematics
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• v.12 no.2
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• pp.107-115
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• 2004

In this paper, the new subclass denoted by $S_p({\alpha},{\beta},{\xi},{\gamma})$ of $p$-valent holomorphic functions has been introduced and investigate the several properties of the class $S_p({\alpha},{\beta},{\xi},{\gamma})$. In particular we have obtained integral representation for mappings in the class $S_p({\alpha},{\beta},{\xi},{\gamma})$) and determined closed convex hulls and their extreme points of the class $S_p({\alpha},{\beta},{\xi},{\gamma})$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.127-135
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• 2000

This paper provides a new method of initializing neurons used in self-organizing neural networks and sequencing input nodes for applying to Euclidean traveling salesman problem. We use a general property that in any optimal solution for Euclidean traveling salesman problem, vertices located on the convex hull are visited in the order in which they appear on the convex hull boundary. We composite input nodes as number of convex hulls and initialize neurons as shape of the external convex hull. And then adapt input nodes as the convex hull unit and all convex hulls are adapted as same pattern, clockwise or counterclockwise. As a result of our experiments, we obtain l∼3 % improved solutions and these solutions can be used for initial solutions of any global search algorithms.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.14-17
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• 2003

By Mazur's theorem, the convex hull of a relatively compact subset a Banach space is also relatively compact. But this is not true any more in the space of fuzzy numbers endowed with the Hausdorff-Skorohod metric. In this paper, we establish a necessary and sufficient condition for which the convex hull of K is also relatively compact when K is a relatively compact subset of the space F(R$\^$k/) of fuzzy numbers of R$\^$k/ endowed with the Hausdorff-Skorohod metric.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1073-1074
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• 2012

최근 인터넷의 발달과 사용량의 증가로 데이터의 양이 급증함에 따라 대용량 데이터를 효율적으로 검색하는 top k 질의 처리가 중요시 되고 있다. Layer 기반 방법은 가장 잘 알려진 top k 질의처리 방법이며, 객체의 모든 속성의 값들을 이용하여 객체들을 layer들의 리스트로 구성하는 방법이다. 본 논문에서는 그 중에서 convex hull을 사용하여 layer list를 생성하는 기존 연구를 조사하고 문제점을 파악한다.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.79-89
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• 2018

In this paper, we study the maximal property of the volume of the convex hull of d-dimensional independent random vectors. We show that the volume of the random convex hull from a multivariate location-scale family indexed by ${\Sigma}$ is stochastically maximized in simple stochastic order when ${\Sigma}$ is diagonal. The claim can be applied to a broad class of multivariate distributions that include skewed/unskewed multivariate t-distributions. We numerically investigate the proven stochastic relationship between the dependent and independent random convex hulls with the Gaussian random convex hull. The numerical results confirm our theoretical findings and the maximal property of the volume of the independent random convex hull.

• Korean Journal of Computational Design and Engineering
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• v.7 no.2
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• pp.131-139
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• 2002

Custom-tailored products always vary their sizes and shapes to satisfy the customers' tastes and requirements but they have to be fabricated as fast as possible when ordered. One way to solve this problem is to prepare several representative products in advance and each custom-tailored product is generated by machining the closest representative product. To realize this approach, it would be necessary to be able to group the products into several groups each of which has a representative product. Once the similar products are identified to be grouped, the representative shape can be generated such that all the products in the group can be made by machining the representative product. The custom-tailored products considered in this work have similar shapes but different sizes. Since these products have free surfaces, that are hard to be compared, their convex hulls are used for the grouping. Among all the products to be grouped, one product is chosen as a base shape. The shape and overall similarity values between the base shape and the remaining shapes are calculated as their convex hulls are rotated virtually. By calculating these similarity values at each rotation, the optimal alignment of the reference shape with respect to the base shape is determined. Overall similarity value at this optimal alignment is used as a measure for grouping. A prototype system based on the proposed methodology has been implemented and used to group the shoe-lasts for custom-tailored shoes.

• Journal of the Korea Concrete Institute
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• v.20 no.5
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• pp.627-634
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• 2008

This paper presents an optimum mixture design method for proportioning a concrete. In the proposed method, the search space is constrained as the domain defined by the minimal convex region of a database, instead of the available range of each component and the ratio composed of several components. The model for defining the search space which is expressed by the effective region is proposed. The effective region model evaluates whether a mix-proportion is effective on processing for optimization, yielding highly reliable results. Three concepts are adopted to realize the proposed methodology: A genetic algorithm for the optimization; an artificial neural network for predicting material properties; and a convex hull for evaluating the effective region. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix-proportion obtained from the proposed methodology using convex hulls is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.473-489
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• 2001

The notion of difference for two convex compact sets in Rⁿ, proposed by Rubinov et al, is generalized to R/sub mxn/. A formula of the difference for the two sets, which are convex hulls of a finite number of points, is developed. In the light of this difference, the relation between Clarke generalized Jacobian and quasidifferential, in the sense of Demyanov and Rubinov, for a nonsnooth function, is established. Based on the relation, the method of estimating Clarke generalized Jacobian via quasidifferential for a certain class of function, is presented.

• Journal of the Korea Computer Graphics Society
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• v.2 no.2
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• pp.61-68
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• 1996

In this paper we propose a new visualization technique to characterize qualitative information of a large DNA sequence. While a long DNA sequence has huge information, it is not easy to obtain genetic information from the DNA sequence. We transform DNA sequences into a polygon to compute their homology in image domain rather than text domain. Our program visualizes DNA sequences with colored random walk plots and simplify them k-convex hulls. A random walk plot represents DNA sequence as a curve in a plane. A k-convex hull simplifies a random work plot by removing some parts of its insignificant information. This technique gives a biologist an insight to detect and classify DNA sequences with easy. Experiments with real genome data proves our approach gives a good visual forms for long DNA sequences for homology analysis.