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Sensitivity Analysis on the Non-tree Solution of the Minimum Cost Flow Problem (최소비용문제의 비정점 최적해에 대한 감도분석)

  • 정호연;박순달
    • Journal of the Korean Operations Research and Management Science Society
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    • v.20 no.1
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    • pp.1-10
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    • 1995
  • The purpose of this paper is to develop a method of the sensitivity analysis that can be applied to a non-tree solution of the minimum cost flow problem. First, we introduce two types of sensitivity analysis. A sensitivity analysis of Type 1a is the well known method applicable to a tree solution. However this method can not be applied to a non-tree solution. So we propose a sensitivity analysis of Type 2 that keeps solutions of upper bounds at upper bounds, those of lower bounds at lower bounds, and those of intermediate values at intermediate values. For the cost coefficient we present a method that the sensitivity analysis of Type 2 is solved by finding the shortest path. Besides we also show that the results of Type 2 and Type 1 are the same in a spanning tree solution. For the right-hand side constant or the capacity, the sensitivity analysis of Type 2 is solved by a simple calculation using arcs with intermediate values.

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Economic Design of Tree Network Using Tabu List Coupled Genetic Algorithms (타부 리스트가 결합된 유전자 알고리즘을 이용한 트리형 네트워크의 경제적 설계)

  • Lee, Seong-Hwan;Lee, Han-Jin;Yum, Chang-Sun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.35 no.1
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    • pp.10-15
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    • 2012
  • This paper considers an economic design problem of a tree-based network which is a kind of computer network. This problem can be modeling to be an objective function to minimize installation costs, on the constraints of spanning tree and maximum traffic capacity of sub tree. This problem is known to be NP-hard. To efficiently solve the problem, a tabu list coupled genetic algorithm approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

The Effect of Chitosan Treatment of Fabrics on the Natural Dyeing using Japanese Pagoda Tree (I) (키토산 처리포의 괴화 천연염색에 관한 연구(I))

  • 전동원;김종준;신혜선
    • The Research Journal of the Costume Culture
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    • v.11 no.3
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    • pp.423-430
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    • 2003
  • Cotton fabric md nylon fabric were chosen as base fabric specimens for dyeing using Japanese pagoda tree colorants through chitosan, treatment. With the chitosan treatment, the dye-uptake of the treated fabric increased. This treatment is also expected to be effective in terms of environment-friendliness. The effect of the dyeing methods, mordanting or non-mordanting, and chitosan treatment on the dye-uptake and air permeability of the treated fabrics was investigated. In case of cotton fabric, Al mordanted dyeing resulted in higher dye-uptake through the chitosan treatment. Therefore, the chitosan treatment is effective in this case. Japanese pagoda tree seems to have direct affinity for nylon fabric without the mordanting treatment. In case of cotton fabric, it seems that the cellulose molecules, colorants, and the chitosan make a complex, thereby reducing the air permeability. In case of nylon fabric, due to the fact the Japanese pagoda tree colorant molecules form direct physical bonding with the nylon molecules, it seems that there is not much of air permeability reduction.

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A Method for Tree Image Segmentation Combined Adaptive Mean Shifting with Image Abstraction

  • Yang, Ting-ting;Zhou, Su-yin;Xu, Ai-jun;Yin, Jian-xin
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1424-1436
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    • 2020
  • Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.

Comparison among Algorithms for Decision Tree based on Sasang Constitutional Clinical Data (사상체질 임상자료 기반 의사결정나무 생성 알고리즘 비교)

  • Jin, Hee-Jeong;Lee, Su-Kyung;Lee, Si-Woo
    • Korean Journal of Oriental Medicine
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    • v.17 no.2
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    • pp.121-127
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    • 2011
  • Objectives : In the clinical field, it is important to understand the factors that have effects on a certain disease or symptom. For this, many researchers apply Data Mining method to the clinical data that they have collected. One of the efficient methods for Data Mining is decision tree induction. Many researchers have studied to find the best split criteria of decision tree; however, various split criteria coexist. Methods : In this paper, we applied several split criteria(Information Gain, Gini Index, Chi-Square) to Sasang constitutional clinical information and compared each decision tree in order to find optimal split criteria. Results & Conclusion : We found BMI and body measurement factors are important factors to Sasang constitution by analyzing produced decision trees with different split measures. And the decision tree using information gain had the highest accuracy. However, the decision tree that produced highest accuracy is changed depending on given data. So, researcher have to try to find proper split criteria for given data by understanding attribute of the given data.

Multi-level Building Layout With Dimension Constraints On Departments (형태제약을 가지는 부서의 다층빌딩 설비배치)

  • Chae-Bogk Kim
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.26 no.4
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    • pp.42-49
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    • 2003
  • The branch and bound techniques based on cut tree and eigenvector have been Introduced in the literature [1, 2, 3, 6, 9, 12]. These techniques are used as a basis to allocate departments to floors and then to fit departments with unchangeable dimensions into floors. Grouping algorithms to allocate departments to each floor are developed and branch and bound forms the basis of optimizing using the criteria of rectilinear distance. The proposed branch and bound technique, in theory, will provide the optimal solution on two dimensional layout. If the runs are time and/or node limited, the proposed method is a strong heuristic The technique is made further practical by the fact that the solution is constrained such that the rectangular shape dimensions length and width are fixed and a perfect fit is generated if a fit is possible. Computational results obtained by cut tree-based algorithm and eigenvector-based algorithm are shown when the number of floors are two or three and there is an elevator.

Antibacterial Characteristics of the Extracts of Yellow Natural Dyes (황색계 천연색소 추출물의 항균 특성)

  • 한신영;최석철
    • Textile Coloration and Finishing
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    • v.12 no.5
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    • pp.315-322
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    • 2000
  • The purpose of this study was to investigate the antibacterial effects of natural colors extracted from yellow natural dyes(Tumeric, Amur Cork Tree and Onion Shell). The water and the methanol extracts of Tumeric and Amur Cork Tree significally decreased the growth of E. coli in vitro and the methanol extract of Tumeric exhibited the strongest inhibitory effect among the samples. Silk and nylon fabrics dyed with water and methanol extracts of the yellow natural dyes showed antimicrobial activities against E. coli and Staph aureus in the Bioassay Test. Nylon fabric dyed with methanol extracts of them showed strong antibacterial effect on E. coli compared with that of water extracts. However, slik fabrics dyed with the extracts could not reduce the growth of E. coli. Silk or nylon fabrics dyed with methanol or water extracts of yellow natural dyes showed antimicrobial activities against Staph aureus. The antimicrobial activity of the fabrics dyed with methanol extracts from Tumeric, Amur Cork Tree and Onion Shell was stronger than that of water extracts, especially, the fabrics dyed with Tumeric extract showed the highest antibacterial property among the dyed fabrics.

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A Hybrid Index based on Aggregation R-tree for Spatio-Temporal Aggregation (시공간 집계정보를 위한 Aggregation R-tree 기반의 하이브리드 인덱스)

  • You, Byeong-Seob;Bae, Hae-Young
    • Journal of KIISE:Databases
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    • v.33 no.5
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    • pp.463-475
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    • 2006
  • In applications such as a traffic management system, analysis using a spatial hierarchy of a spatial data warehouse and a simple aggregation is required. Over the past few years, several studies have been made on solution using a spatial index. Many studies have focused on using extended R-tree. But, because it just provides either the current aggregation or the total aggregation, decision support of traffic policy required historical analysis can not be provided. This paper proposes hybrid index based on extended aR-tree for the spatio-temporal aggregation. The proposed method supports a spatial hierarchy and the current aggregation by the R-tree. The sorted hash table using the time structure of the extended aR-tree provides a temporal hierarchy and a historical aggregation. Therefore, the proposed method supports an efficient decision support with spatio-temporal analysis and is Possible currently traffic analysis and determination of a traffic policy with historical analysis.

Tier-based Proactive Path Selection Mode for Wireless Mesh Networks

  • Fu-Quan, Zhang;Joe, In-Whee;Park, Yong-Jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.5
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    • pp.1303-1315
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    • 2012
  • In the draft of the IEEE 802.11s standard, a tree topology is established by the proactive tree-building mode of the Hybrid Wireless Mesh Protocol (HWMP). It is used for cases in which the root station (e.g., gateway) is an end point of the majority of the data connections. In the tree topology, the root or central stations (e.g., parent stations) are connected to the other stations (e.g., leaves) that are one level lower than the central station. Such mesh stations are likely to suffer heavily from contention in bottleneck links when the network has a high traffic load. Moreover, the dependence of the network on such stations is a point of vulnerability. A failure of the central station (e.g., a crash or simply going into sleep mode to save energy) can cripple the whole network in the tree topology. This causes performance degradation for end-to-end transmissions. In a connected mesh topology where the stations having two or more radio links between them are connected in such a way that if a failure subsists in any of the links, the other link could provide the redundancy to the network. We propose a scheme to utilize this characteristic by organizing the network into concentric tiers around the root mesh station. The tier structure facilitates path recovery and congestion control. The resulting mode is referred to as Tier-based Proactive Path Selection Mode (TPPSM). The performance of TPPSM is compared with the proactive tree mode of HWMP. Simulation results show that TPPSM has better performance.

Integrity Assessment for Reinforced Concrete Structures Using Fuzzy Decision Making (퍼지의사결정을 이용한 RC구조물의 건전성평가)

  • 박철수;손용우;이증빈
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2002.04a
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    • pp.274-283
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    • 2002
  • This paper presents an efficient models for reinforeced concrete structures using CART-ANFIS(classification and regression tree-adaptive neuro fuzzy inference system). a fuzzy decision tree parttitions the input space of a data set into mutually exclusive regions, each of which is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the Predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it everywhere continuous and smooth. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

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