• 대한수학회지
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• 제53권5호
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• pp.1037-1056
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• 2016

In this paper, we define the concepts of commute proximally, dominate proximally, weakly dominate proximally, proximal generalized ${\varphi}$-contraction and common best proximity point in probabilistic Menger space. We prove some common best proximity point and common fixed point theorems for dominate proximally and weakly dominate proximally mappings in probabilistic Menger space under certain conditions. Finally we show that proximal generalized ${\varphi}$-contractions have best proximity point in probabilistic Menger space. Our results generalize many known results in metric space.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제30권4호
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• pp.417-427
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• 2023

The purpose of this paper is establish the existence of proximity point for the cyclic B-contraction mapping on metric spaces and uniformly convex Banach spaces. Also, we prove the common proximity point for the S-weakly cyclic B-contraction mapping. In addition, a few examples are provided to demonstrate our findings.

• 대한수학회보
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• 제53권5호
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• pp.1363-1371
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• 2016

This paper is concerned with best proximity points for multimaps in normed spaces and in hyperconvex metric spaces. Using the generalized KKM theorem, we deduce new best proximity pair theorems for a family of multimaps with unionly open fibers in normed spaces. And we prove a new best proximity point theorem for quasi-lower semicontinuous multimaps in hyperconvex metric spaces.

• Nonlinear Functional Analysis and Applications
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• 제27권2호
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• pp.261-269
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• 2022

The purpose of this paper is to introduce a new generalization class of cyclic mappings, called cyclic generalized 𝜑-weak contraction and obtain a corresponding best proximity point theorem for this cyclic mapping under certain conditions.

• Journal of applied mathematics & informatics
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• 제29권1_2호
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• pp.119-133
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• 2011

This paper proposes an infeasible interior-point algorithm with full-Newton step for linear programming. We introduce a special self-regular proximity to induce the feasibility step and also to measure proximity to the central path. The result of polynomial complexity coincides with the best-known iteration bound for infeasible interior-point methods, namely, O(n log n/${\varepsilon}$).

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제29권4호
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• pp.335-352
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• 2022

In this paper, we give an extended version of fixed point results for 𝜃-contraction and 𝜃-𝜙-contraction and define a new type of contraction, namely, cyclic 𝜃-contraction and cyclic 𝜃-𝜙-contraction in a complete metric space. Moreover, we prove the existence of best proximity point for cyclic 𝜃-contraction and cyclic 𝜃-𝜙-contraction. Also, we establish best proximity result in the setting of uniformly convex Banach space.

• Korean Journal of Mathematics
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• 제12권1호
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• pp.41-47
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• 2004

We introduce the $K_0$-proximity space as a generalization of the Efremovi$\check{c}$-proximity space. We try to show every ultrafilter in $K_0$-proximity space generates a cluster and every Cauchy cluster is a point cluster.

• 충청수학회지
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• 제19권1호
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• pp.19-26
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• 2006

In this paper, using the fixed point theorem for acyclic factorizable multifunctions, we shall prove an existence theorem of general best proximity pairs and equilibrium pairs for free generalized games.

• 한국멀티미디어학회논문지
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• 제15권6호
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• pp.794-804
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• 2012

단백질 분자에 대해 공간 상의 한 점으로부터의 최소 거리를 계산하거나, 임의의 점에 대한 충돌을 감지하는 등의 proximity query는 분자에 대한 기하학적 연산을 수행하기 위해 매우 중요한 기본 연산이다. Proximity query의 계산 시간 효율성은 분자가 어떤 자료구조로 표현되는가에 따라 크게 달라질 수 있다. 본 논문에서는 GPU 가속을 이용하여 효율적으로 proximity 연산을 수행하기 위한 기법을 제안하고자 한다. 분자에 대응하는 구의 집합에 대해 복셀 맵 (voxel map)과 스피어 트리 (sphere tree) 를 사용한 자료구조를 제안하며 각 자료구조에 대응되는 알고리즘을 제시한다. 또한, 1,000개~15,000개의 원자를 포함하는 분자에 대한 실험을 통해 두 자료구조의 성능이 기존 자료구조에 비해 최소 3배에서 최대 633배 향상되었음을 보인다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제14권2호
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• pp.93-111
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• 2010

The purpose of this paper is to obtain new complexity results for a second-order cone optimization (SOCO) problem. We define a proximity function for the SOCO by a kernel function. Furthermore we formulate an algorithm for a large-update primal-dual interior-point method (IPM) for the SOCO by using the proximity function and give its complexity analysis, and then we show that the new worst-case iteration bound for the IPM is $O(q\sqrt{N}(logN)^{\frac{q+1}{q}}log{\frac{N}{\epsilon})$, where $q{\geqq}1$.