• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.153-162
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• 2011

The minimum cut problem is to minimize c(S,T), that is, to determine source S and sink T such that the capacity of the S-T cut is minimal. The flow-based algorithm is mostly used to find the bottleneck arcs by calculating flow network, and does not presents the minimum cut. This paper suggests an algorithm that simply includes the maximum capacity vertex to adjacent set S or T and finds the minimum cut without obtaining flow network in advance. On applying the suggested algorithm to 13 limited graphs, it can be finds the minimum cut value $_{\min}c$(S, T) with simply and correctly.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.7-16
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• 1994

In the existing deterministic network, the capacity of each arc has determined property. But actually, it may be a property which cannot be determined. Even though it should be determining, it contains many errors. In treating these kinds of problems, fuzzy theory is suitable. Recently, due to development the study on complicated and indefinited systems which contain fuzziness could be possible. This paper includes that the capacity of each arc and the goal quantity with nonnegative integer have the fuzziness. The object is to search the new mathod of fuzzy maximal flow quantity. If the degree of arc membership function of the minimal cut part is not larger than that of arc membership function of the part except the minimal cut, first calcurate nonfuzzy maximal flow quantity, and then can compute the optimal quantity the 3rd step at one time with Max-Min fuzzy operating in the arc capacity of minimal cut and the goal quantity without a great number of recalculation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.147-152
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• 2020

The baseball elimination problem(BEP) is eliminates teams that finishes the season in the early stage without play the remaining games because of the team never most wins even though all wins of remaining games. This problem solved by max-flow/min-cut theorem. But the max-flow/min-cut method has a shortcoming of iterative constructs the network for all of team and decides the min-cut for each network. This paper suggests ascending sort in wins game plus remaining games for each team, then the candidate eliminating team set K with lower 1/2 rank and most easy, simple, and fast computes the existence or not of subset R that a team elimination decision. As a result of various experimental data, this algorithm can be find all of elimination teams for whole data with fast and correct.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.103-113
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• 2019

Motivation: Polymerized actin-based cytoskeletal structures are crucial in shape, dynamics, and resilience of a cell. For example, dynamical actin-containing ruffles are located at leading edges of cells and have a significant impact on cell motility. Other filamentous actin (F-actin) bundles, called stress fibers, are essential in cell attachment and detachment. For this reason, their mechanistic understanding provides crucial information to solve practical problems related to cell interactions with materials in tissue engineering. Detecting and counting actin-based structures in a cellular ensemble is a fundamental first step. In this research, we suggest a new method to characterize F-actin wrapping fibers from confocal fluorescence image stacks. As fluorescently labeled F-actin often envelope the fibers, we first propose to segment these fibers by diminishing an energy based on maximum flow and minimum cut algorithm. The actual actin is detected through the use of bilateral filtering followed by a thresholding step. Later, concave actin bundles are detected through a graph-based procedure that actually determines if the considered actin filament is enclosing the fiber.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.129-139
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• 2012

Given digraph network $D=(N,A),n{\in}N,a=c(u,v){\in}A$ with source s and sink t, the maximum flow from s to t is determined by cut (S, T) that splits N to $s{\in}S$ and $t{\in}T$ disjoint sets with minimum cut value. The Ford-Fulkerson (F-F) algorithm with time complexity $O(NA^2)$ has been well known to this problem. The F-F algorithm finds all possible augmenting paths from s to t with residual capacity arcs and determines bottleneck arc that has a minimum residual capacity among the paths. After completion of algorithm, you should be determine the minimum cut by combination of bottleneck arcs. This paper suggests maximum adjacency merging and compute cut value method is called by MA-merging algorithm. We start the initial value to S={s}, T={t}, Then we select the maximum capacity $_{max}c(u,v)$ in the graph and merge to adjacent set S or T. Finally, we compute cut value of S or T. This algorithm runs n-1 times. We experiment Ford-Fulkerson and MA-merging algorithm for various 8 digraph. As a results, MA-merging algorithm can be finds minimum cut during the n-1 running times with time complexity O(N).

• ICROS
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• v.6 no.4
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• pp.38-48
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• 2000

Abstract :본 논문에서는 관리제어시스템의 동적특성을 허용언어(admissible language) 범위 이내에서 최적화시키는 최적 관리제어기법들을 소개한다. 본 논문에서 주로 다루고자 하는 최적 관리제어기법은 Kumar와 Garg에 의해 제안된 기법과 Cho와 Lim에 의해 제안된 계층적 최적 관리제어기법, 그리고, Sengupta와 Lafortune이 제안한 최적 관리제어기법 등이다. 첫 번째 기법에서는 우선 시스템의 최적화를 위해 고려되고 있는 비용함수(cost function)를 소개한 후, 최대흐름 최소분할생성 정리(max-flow min-cut theorem)를 이용한 최적 관리제어기 설계기법을 제시하고, 이를 부분관측 하에서도 최적 관리제어기를 설계할 수 있도록 확장한다. 그런 후 제시된 설계기법에 의해 설계된 관리제어시스템에서 발생 할 수 있는 문제점들을 지적하고, Cho와 Lim에 의해 제안된 완전 최소분할생성(complete min-cut)이라는 개념을 도입하여 지적된 문제점들을 해결할 수 있는 방법을 제시한다. 또한 시스템의 고장을 고려한 계층적 최적 관리 제어(layered optimal supervisory control)기 법을 소개한다 그리 고 마지막으로 Sengupta와 Lafortune이 제안한 최적 관리제어기법에 대해서 살펴본다.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.61-70
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• 2023

Image segmentation is a very crucial step in effective digital image processing. In the past decade, several research contributions were given related to this field. However, a general segmentation algorithm suitable for various applications is still challenging. Among several image segmentation approaches, graph-based approach has gained popularity due to its basic ability which reflects global image properties. This paper proposes a methodology to partition the image with its pixel, region and texture along with its intensity. To make segmentation faster in large images, it is processed in parallel among several CPUs. A way to achieve this is to split images into tiles that are independently processed. However, regions overlapping the tile border are split or lost when the minimum size requirements of the segmentation algorithm are not met. Here the contributions are made to segment the image on the basis of its pixel using min-cut/max-flow algorithm along with edge-based segmentation of the image. To segment on the basis of the region using a homogenous optimum cut algorithm with boundary segmentation. On the basis of texture, the object type using spectral partitioning technique is identified which also minimizes the graph cut value.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.89-102
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• 2019

Collagen can be used in building artificial skin replacements for treatment of burns and towards the reconstruction of bone as well as researching cell behavior and cellular interaction. The strength of collagen in connective tissue rests on the characteristics of collagen fibers. 3D confocal imaging of collagen fibers enables the characterization of their spatial distribution as related to their function. However, the image stacks acquired with confocal laser-scanning microscope does not clearly show the collagen architecture in 3D. Therefore, we developed a new method to reconstruct, visualize and characterize collagen fibers from fluorescence confocal images. First, we exploit the tensor voting framework to extract sparse reliable information about collagen structure in a 3D image and therefore denoise and filter the acquired image stack. We then propose to segment the collagen fibers by defining an energy term based on the Hessian matrix. This energy term is minimized by a min cut-max flow algorithm that allows adaptive regularization. We demonstrate the efficacy of our methods by visualizing reconstructed collagen from specific 3D image stack.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.143-152
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• 2013

Given weighted graph G=(V,E), n=|V|, m=|E|, the minimum cut problem is classified with source s and sink t or without s and t. Given undirected weighted graph without s and t, Stoer-Wagner algorithm is most popular. This algorithm fixes arbitrary vertex, and arranges maximum adjacency (MA)-ordering. In the last, the sum of weights of the incident edges for last ordered vertex is computed by cut value, and the last 2 vertices are merged. Therefore, this algorithm runs $\frac{n(n-1)}{2}$ times. Given graph with s and t, Ford-Fulkerson algorithm determines the bottleneck edges in the arbitrary augmenting path from s to t. If the augmenting path is no more exist, we determine the minimum cut value by combine the all of the bottleneck edges. This paper suggests minimum cut algorithm for undirected weighted graph with s and t. This algorithm suggests MA-merging and computes cut value simultaneously. This algorithm runs n-1 times and successfully divides V into disjoint S and V sets on the basis of minimum cut, but the Stoer-Wagner is fails sometimes. The proposed algorithm runs more than Ford-Fulkerson algorithm, but finds the minimum cut value within n-1 processing times.