• Title/Summary/Keyword: set grouping

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A study on machine-cell formation in cellular manufacturing based on fuzzy set (퍼지집합에 기초한 셀 생산방식에서의 머신-셀 구성에 관한 연구)

  • Leam, Choon-Woo;Lee, Noh-Sung
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.3
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    • pp.305-310
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    • 1997
  • In this paper, a fuzzy set based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy logic is emoloyed to express the degree of appropriateness when alternative machines are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

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A Study of Library Grouping using Cluster Analysis Methods (군집분석 기법을 이용한 공공도서관 그룹화에 대한 연구)

  • Kwak, Chul Wan
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.31 no.3
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    • pp.79-99
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    • 2020
  • The purpose of this study is to investigate the model of cluster analysis techniques for grouping public libraries and analyze their characteristics. Statistical data of public libraries of the National Library Statistics System were used, and three models of cluster analysis were applied. As a result of the study, cluster analysis was conducted based on the size of public libraries, and it was largely divided into two clusters. The size of the cluster was largely skewed to one side. For grouping based on size, the ward method of hierarchical cluster analysis and the k-means cluster analysis model were suitable. Three suggestions were presented as implications of the grouping method of public libraries. First, it is necessary to collect library service-related data in addition to statistical data. Second, an analysis model suitable for the data set to be analyzed must be applied. Third, it is necessary to study the possibility of using cluster analysis techniques in various fields other than library grouping.

Hierarchical Grouping of Line Segments for Building Model Generation (건물 형태 발생을 위한 3차원 선소의 계층적 군집화)

  • Han, Ji-Ho;Park, Dong-Chul;Woo, Dong-Min;Jeong, Tai-Kyeong;Lee, Yun-Sik;Min, Soo-Young
    • Journal of IKEEE
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    • v.16 no.2
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    • pp.95-101
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    • 2012
  • A novel approach for the reconstruction of 3D building model from aerial image data is proposed in this paper. In this approach, a Centroid Neural Network (CNN) with a metric of line segments is proposed for connecting low-level linear structures. After the straight lines are extracted from an edge image using the CNN, rectangular boundaries are then found by using an edge-based grouping approach. In order to avoid producing unrealistic building models from grouping lined segments, a hierarchical grouping method is proposed in this paper. The proposed hierarchical grouping method is evaluated with a set of aerial image data in the experiment. The results show that the proposed method can be successfully applied for the reconstruction of 3D building model from satellite images.

A machine-cell formation method based on fuzzy set (퍼지 이론에 기초한 머신-셀 구성방법)

  • 이노성;임춘우
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1565-1568
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    • 1997
  • In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

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A Rule-driven Automatic Learner Grouping System Supporting Various Class Types (다양한 수업 유형을 지원하는 규칙 기반 학습자 자동 그룹핑 시스템)

  • Kim, Eun-Hee;Park, Jong-Hyun;Kang, Ji-Hoon
    • Journal of The Korean Association of Information Education
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    • v.14 no.3
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    • pp.291-300
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    • 2010
  • Group-based learning is known to be an effective means to improve scholastic achievement in online learning. Therefore, there are some previous researches for the group-based learning. A lot of previous researches define factors for grouping from the characteristics of classes, teacher's decision and students' preferences and then generate a group based on the defined factors. However, many algorithms proposed by previous researches depend on a specific class and is not a general approach since there exist several differences in terms of the need of courses, learners, and teachers. Moreover it is hard to find a automatic system for group generation. This paper proposes a grouping system which automatically generate a learner group according to characteristics of various classes. the proposed system automatically generates a learner group by using basic information for a class or additional factors inputted from a user. The proposed system defines a set of rules for learner grouping which enables automatic selection of a learner grouping algorithm tailored to the characteristics of a given class. This rule based approach allows the proposed system to accommodate various learner grouping algorithms for a later use. Also we show the usability of our system by serviceability evaluation.

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Re-establishment of a Conservation Area in Odaesan(Mt.) National Park based on Ecological Values (생태적가치 기반의 오대산국립공원 보전지구 재설정 방안 연구)

  • Yeum, Jung-Hun
    • Journal of Environmental Science International
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    • v.29 no.10
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    • pp.951-959
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    • 2020
  • This study aimed to re-establish the conservation area reflecting landscape ecological value through scenario program, targeting Odaesan National Park. The basic data were mapped in watershed planning units, which were set considering topographical and ecological values. The framework of Marxan with Zones, using an indexation process, was using the mapped indicators. Each best solution according to the scenarios was assessed through sensitivity analysis, and a final solution was selected among the best solutions, considering criteria including area ratio of conservation area and grouping. Lastly, the final solution was verified in the overlap analysis with recent zonation. As a result, through the framework of Marxan with Zones, the best solution of scenario 1, which was set by the highest conservation criteria was selected as the final solution, and the area ratio of conservation area and grouping was excellent. As for the overlap analysis, the suggested conservation area was improved compared to recent zonation in terms of the area ratio (39.4%), biotope grade I (35.6%) and the distribution points (7 places) of legally protected species.

A Region Based Approach to Surface Segmentation using LIDAR Data and Images

  • Moon, Ji-Young;Lee, Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.6_1
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    • pp.575-583
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    • 2007
  • Surface segmentation aims to represent the terrain as a set of bounded and analytically defined surface patches. Many previous segmentation methods have been developed to extract planar patches from LIDAR data for building extraction. However, most of them were not fully satisfactory for more general applications in terms of the degree of automation and the quality of the segmentation results. This is mainly caused from the limited information derived from LIDAR data. The purpose of this study is thus to develop an automatic method to perform surface segmentation by combining not only LIDAR data but also images. A region-based method is proposed to generate a set of planar patches by grouping LIDAR points. The grouping criteria are based on both the coordinates of the points and the corresponding intensity values computed from the images. This method has been applied to urban data and the segmentation results are compared with the reference data acquired by manual segmentation. 76% of the test area is correctly segmented. Under-segmentation is rarely founded but over-segmentation still exists. If the over-segmentation is mitigated by merging adjacent patches with similar properties as a post-process, the proposed segmentation method can be effectively utilized for a reliable intermediate process toward automatic extraction of 3D model of the real world.

Fuzzy PID Control by Grouping of Membership Functions of Fuzzy Antecedent Variables with Neutrosophic Set Approach and 3-D Position Tracking Control of a Robot Manipulator

  • Can, Mehmet Serhat;Ozguven, Omerul Faruk
    • Journal of Electrical Engineering and Technology
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    • v.13 no.2
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    • pp.969-980
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    • 2018
  • This paper aims to design of the neutrosophic fuzzy-PID controller and it has been compared with the conventional fuzzy-PID controller for position tracking control in terms of robustness. In the neutrosophic fuzzy-PID controller, error (e) and change of error (ce) were assessed separately on two fuzzy inference systems (FISs). In this study, the designed method is different from the conventional fuzzy logic controller design, membership degrees of antecedent variables were determined by using the T(true), I(indeterminacy), and F(false) membership functions. These membership functions are grouped on the universe of discourse with the neutrosophic set approach. These methods were tested on three-dimensional (3-D) position-tracking control application of a spherical robot manipulator in the MATLAB Simulink. In all tests, reference trajectory was defined for movements of all axes of the robot manipulator. According to the results of the study, when the moment of inertia of the rotor is changed, less overshoot ratio and less oscillation are obtained in the neutrosophic fuzzy-PID controller. Thus, our suggested method is seen to be more robust than the fuzzy-PID controllers.

A Feature Analysis of Industrial Accidents Using C4.5 Algorithm (C4.5 알고리즘을 이용한 산업 재해의 특성 분석)

  • Leem, Young-Moon;Kwag, Jun-Koo;Hwang, Young-Seob
    • Journal of the Korean Society of Safety
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    • v.20 no.4 s.72
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    • pp.130-137
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    • 2005
  • Decision tree algorithm is one of the data mining techniques, which conducts grouping or prediction into several sub-groups from interested groups. This technique can analyze a feature of type on groups and can be used to detect differences in the type of industrial accidents. This paper uses C4.5 algorithm for the feature analysis. The data set consists of 24,887 features through data selection from total data of 25,159 taken from 2 year observation of industrial accidents in Korea For the purpose of this paper, one target value and eight independent variables are detailed by type of industrial accidents. There are 222 total tree nodes and 151 leaf nodes after grouping. This paper Provides an acceptable level of accuracy(%) and error rate(%) in order to measure tree accuracy about created trees. The objective of this paper is to analyze the efficiency of the C4.5 algorithm to classify types of industrial accidents data and thereby identify potential weak points in disaster risk grouping.

An Efficient Multibody Dynamic Algorithm Using Independent Coordinates Set and Modified Velocity Transformation Method (수정된 속도변환기법과 독립좌표를 사용한 효율적인 다물체 동역학 알고리즘)

  • Kang, Sheen-Gil;Yoon, Yong-San
    • Proceedings of the KSME Conference
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    • 2001.06b
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    • pp.488-494
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    • 2001
  • Many literatures, so far, have concentrated on approaches employing dependent coordinates set resulting in computational burden of constraint forces, which is needless in many cases. Some researchers developed methods to remove or calculate it efficiently. But systematic generation of the motion equation using independent coordinates set by Kane's equation is possible for any closed loop system. Independent velocity transformation method builds the smallest size of motion equation, but needs practically more complicated code implementation. In this study, dependent velocity matrix is systematically transformed into independent one using dependent-independent transformation matrix of each body group, and then motion equation free of constraint force is constructed. This method is compared with the other approach by counting the number of multiplications for car model with 15 d.o.f..

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