• 제목/요약/키워드: grouping.

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Grouping DNA sequences with similarity measure and application

  • Lee, Sanghyuk
    • 한국융합학회논문지
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    • 제4권3호
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    • pp.35-41
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    • 2013
  • Grouping problem with similarities between DNA sequences are studied. The similaritymeasure and the distance measure showed the complementary characteristics. Distance measure can be obtained by complementing similarity measure, and vice versa. Similarity measure is derived and proved. Usefulness of the proposed similarity measure is applied to grouping problem of 25 cockroach DNA sequences. By calculation of DNA similarity, 25 cockroaches are clustered by four groups, and the results are compared with the previous neighbor-joining method.

애로기계가 존재하는 기계-부품 그룹형성 문제에 대한 해법 (Machine-Part Grouping Algorithm for the Bottleneck Machine Problem)

  • 박수관;이근희
    • 산업경영시스템학회지
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    • 제19권37호
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    • pp.1-7
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    • 1996
  • The grouping of parts into families and machines into cells poses an important problem for the improvement of productivity and quality in the design and planning of the flexible manufacturing system(FMS). This paper proposes a new algorithm of forming machine-part groups in case of the bottleneck machine problem and shows the numerical example. This algorithm could be applied to the large scale machine-part grouping problem.

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분지한계법을 이용한 기계-부품 그룹형성 최적해법 (Machine-part Grouping Algorithm Using a Branch and Bound Method)

  • 박수관;이근희
    • 산업경영시스템학회지
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    • 제18권34호
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    • pp.123-128
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    • 1995
  • The grouping of parts into families and machines into cells poses an important problem in the design and planning of the flexible manufacturing system(FMS). This paper proposes a new optimal algorithm of forming machine-part groups to maximize the similarity, based on branching from seed machine and bounding on a completed part. This algorithm is illustrated with numerical example. This algorithm could be applied to the generalized machine-part grouping problem.

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Electrical Resistance Tomography: Mesh Grouping and Boundary Estimation Algorithms

  • Kim Sin;Cho Hyo-Sung;Lee Bong-Soo
    • International Journal of Contents
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    • 제1권1호
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    • pp.1-5
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    • 2005
  • This paper presents the development and application of electrical resistance imaging techniques for the visualization of two-phase flow fields. Two algorithms, the so-called the mesh grouping and the boundary estimation, are described for potential applications of electrical resistance tomography (ERT) and results from extensive numerical simulations are also presented. In the electrical resistance imaging for two-phase flows, numerical meshes fairly belonging to each phase can be grouped to improve the reconstruction performance. In many cases, the detection of phase boundary is a key subject and a mathematical model to estimate phase boundary can be formulated in a different manner. Our results indicated that the mesh grouping algorithm is effective to enhance computational performance and image quality, and boundary estimation algorithm to determine the phase boundary directly.

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Gene Algorithm of Crowd System of Data Mining

  • Park, Jong-Min
    • Journal of information and communication convergence engineering
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    • 제10권1호
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    • pp.40-44
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    • 2012
  • Data mining, which is attracting public attention, is a process of drawing out knowledge from a large mass of data. The key technique in data mining is the ability to maximize the similarity in a group and minimize the similarity between groups. Since grouping in data mining deals with a large mass of data, it lessens the amount of time spent with the source data, and grouping techniques that shrink the quantity of the data form to which the algorithm is subjected are actively used. The current grouping algorithm is highly sensitive to static and reacts to local minima. The number of groups has to be stated depending on the initialization value. In this paper we propose a gene algorithm that automatically decides on the number of grouping algorithms. We will try to find the optimal group of the fittest function, and finally apply it to a data mining problem that deals with a large mass of data.

Watershed Algorithm 과 Object Grouping 을 이용한 얼굴영역분할 (Face Region Segmentation using Watershed Algorithm And Object Grouping)

  • 황훈;최영관;최철;이정아;박장춘
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2003년도 추계학술발표논문집 (상)
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    • pp.587-590
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    • 2003
  • 얼굴영역을 분할하기 위해서 Watershed Algorithm 와 Object Grouping 을 이용한 얼굴영역 분할기법을 제안한다. 영상분할에 단점은 단일 알고리즘으로 영역분할이 어렵고, 또한 복잡한 영상에서 정확한 영역을 분할하기가 어렵다는 것이다. 그래서 본 논문에서는 Watershed Segmentation 기법과 Grouping 작업을 통한 병합, 그리고 색상의 선형회귀분석을 이용한 분석법을 적용하여 분할하고자 한다. 얼굴영역 분할방법을 전처리 과정과 영역 병합 그리고 얼굴 부분을 추출하는 3 단계의 과정으로 나누고, 전처리 과정에서는 수리형태학적(Mophological) 연산자를 이용한 영상 분할기법을 이용하여 분할한 후 얼굴 후보 영역을 검출, 영역병합과정에서 기존의 학습데이터와의 유사도를 측정, 얼굴객체추출 조건에 맞지 않는 객체들을 모두 제거함으로써, 정확한 얼굴부분을 분할해 낸다. 실험결과 제안한 방법을 통해 비교적 정확한 얼굴영역을 분할 할 수 있었다.

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INPUT GROUPING OF LIGICAL CIRCUIT BY USE OF M-SEQUENCE CORRELATION

  • Miyata, Chikara;Kashiwagi, Hiroshi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.146-149
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    • 1995
  • A new method for grouping of relevant and equivalent inputs of a logical circuit was proposed by the authors by making use of pseudorandom M-sequence correlation. The authors show in this paper that it is possible to estimate the input grouping from a part of correlation functions when we admit small percentage of error, whereas it is impossible to reduce the data necessary to estimate the grouping by use of the truth table method. For example in case of 30-input logic circuit, the number of correlation functions necessary to calculate can be reducible from 1.07 * 10$^{9}$ to 465.

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셀 생산방식에서 자기조직화 신경망과 K-Means 알고리즘을 이용한 기계-부품 그룹형성 (Machine-Part Grouping in Cellular Manufacturing Systems Using a Self-Organizing Neural Networks and K-Means Algorithm)

  • 이상섭;이종섭;강맹규
    • 산업경영시스템학회지
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    • 제23권61호
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    • pp.137-146
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    • 2000
  • One of the problems faced in implementing cellular manufacturing systems is machine-part group formation. This paper proposes machine-part grouping algorithms based on Self-Organizing Map(SOM) neural networks and K-Means algorithm in cellular manufacturing systems. Although the SOM spreads out input vectors to output vectors in the order of similarity, it does not always find the optimal solution. We rearrange the input vectors using SOM and determine the number of groups. In order to find the number of groups and grouping efficacy, we iterate K-Means algorithm changing k until we cannot obtain better solution. The results of using the proposed approach are compared to the best solutions reported in literature. The computational results show that the proposed approach provides a powerful means of solving the machine-part grouping problem. The proposed algorithm Is applied by simple calculation, so it can be for designer to change production constraints.

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Flickering Effect Reduction Based on the Modified Transformation Function for Video Contrast Enhancement

  • Yang, Hyeonseok;Park, Jinwook;Moon, Youngshik
    • IEIE Transactions on Smart Processing and Computing
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    • 제3권6호
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    • pp.358-365
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    • 2014
  • This paper proposes a method that reduces the flickering effect caused by A-GLG (Adaptive Gray-Level Grouping) during video contrast enhancement. Of the GLG series, A-GLG shows the best contrast enhancement performance. The GLG series is based on histogram grouping. Histogram grouping is calculated differently between the continuous frames with a similar histogram and causes a subtle change in the transformation function. This is the reason for flickering effect when the video contrast is enhanced by A-GLG. To reduce the flickering effect caused by A-GLG, the proposed method calculates a modified transformation function. The modified transformation function is calculated using a previous and current transformation function applied with a weight separately. The proposed method was compared with A-GLG for flickering effect reduction and video contrast enhancement. Through the experimental results, the proposed method showed not only a reduced flickering effect, but also video contrast enhancement.

분산 멀티미디어 스트리밍을 위한 시/공간적 객체 그룹화 (Temporal and Spatial Object Grouping for Distributed Multimedia Streaming)

  • 이종득
    • 한국컴퓨터산업학회논문지
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    • 제8권2호
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    • pp.113-122
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    • 2007
  • 최근에 효율적이고 시/공간적인 분산 멀티미디어 스트리밍 서비스를 제공하기 위한 많은 연구가 시도되고 있다. 본 논문에서는 이러한 분산 멀티미디어 스트리밍 서비스를 위한 시/공간적 객체 그룹화 방법을 제안하였다. 제안된 기법은 응용도메인에서 수집된 프레임 객체를 필터링과 사상을 통하여 그룹화를 수행하며, 사상된 프레임객체들에 대해서 JM관계성을 수행한다. 그 결과 제안된 기법의 성능이 효율적임을 보였다.

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