• Title/Summary/Keyword: Organizing

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A study on inspection area using neural network for vision systems (비젼 시스템에서 신경 회로망을 이용한 검사 영역에 관한 연구)

  • Oh, Je-Hui;Cha, Young-Youp
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.3
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    • pp.378-383
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    • 1998
  • A FOV, that stands for "Field Of View", refers to the maximum area where a camera could be wholly seen. If a FOV of CCD camera cannot the cover overall inspection area, the overall inspection area should be divided into sub-areas of size FOV. In this paper, we propose a new neural network-based FOV generation method by using a newly modified self-organizing map(SOM) which has multiple structure based on a self-organizing map, and uses new training rule that is composed of the movement, creation and deletion terms. Then, experiment results using real PCB indicate the superiority of the method developed in this study to the existing sequential method.al method.

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A generalized self organizing evolutionary algorithm and its efficient application to control problems (일반화된 자기 형성 진화 알고리즘의 개발과 제어 문제에 대한 효율적 응용에 대한 연구)

  • Jeong, Il-Gwon;Lee, Ju-Jang
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.3
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    • pp.259-264
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    • 1997
  • 널리 쓰이는 진화 알고리즘은 크게 두가지가 있다. 유전 알고리즘과 진화 기법이 그것이다. 이들 알고리즘은 실행 전에 사용자가 정해주어야 하는 변수들을 가지고 있다. 본 논문에서는 이 두 알고리즘을 일반화시키고 집단의 크기, 교차변이 연산자 적용 확률 그리고 돌연변이 연산자 적용 확률과 같은 변수들을 알고리즘이 수행되는 동안 스스로 정하는 일반화된 자기 형성 진화 알고리즘을 제안한다. 제안된 알고리즘의 타당성과 효용성은 시스템 동정화와 다개체 시스템 제어의 두가지 복잡한 제어 문제에 대한 적용을 통해 보여진다.

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Resource Allocation in Wireless Ad Hoc Networks Using Game Theory

  • Lee, Ki-Hwan;Halder, Nilimesh;Song, Ju-Bin
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.195-196
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    • 2007
  • The purpose of this paper is to analyze the resource allocation problem in a self organizing network from the viewpoint of game theory. The main focus is to suggest the model and analyze a power control algorithm in wireless ad-hoc networks using non cooperative games. Our approach is based on a model for the level of satisfaction and utility a wireless user in a self organizing network derives from using the system. Using this model, we show a distributed power control scheme that maximizes utility of each user in the network. Formulating this as a non-cooperative game we will show the feasibility of such power control as well as existence of the Nash Equilibrium achieved by the non-cooperative game.

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Detection of Characteristics by Pattern Classification of Water Quality and Runoff Data in a River (하천의 수질 및 유량자료의 패턴분류에 의한 특성 파악)

  • Park, Sung-Chun;Jin, Young-Hoon;Roh, Kyong-Bum;Kim, Yong-Gu;Lee, Yong-Hui
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.1380-1384
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    • 2010
  • 현재 환경부에서는 수질오염총량관리제를 위하여 각 단위유역의 말단지점에서 8일 간격으로 수질 및 유량을 측정하고 있으며, 이 자료들을 공개하고 있다. 이러한 양질의 자료의 활용성을 제고하기 위해서는 무엇보다도 자료의 분석을 위한 다양한 기법이 개발되고 제안되어야 한다. 따라서 본 연구에서는 수질 및 유량자료를 동시에 적용하여 두 자료 사이의 관계를 조사하고 특성을 파악하기 위하여 자기조직화 특성지도(Self-Organizing Feature Map: SOFM) 이론을 적용하였다. 시행착오법에 의해 적정한 SOFM 구조를 결정하였으며, 그 결과 $4{\times}4$ 구조의 육각형 배열을 갖는 구조를 이용하였다. SOFM에 의해 분류된 3개의 패턴 중 패턴-1은 유량자료의 크기에 의해 분류되었고, 패턴-2와 패턴-3은 BOD 농도의 크기에 따라 분류된 것으로 파악되었다. 따라서 SOFM의 적용에 의한 자료의 분류를 수행하고, 그 분류기준을 파악할 경우 SOFM의 자료 분석 도구로서의 활용성이 더욱 높아질 것으로 판단된다.

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Development and Characterization of Pattern Recognition Algorithm for Defects in Semiconductor Packages

  • Kim, Jae-Yeol;Yoon, Sung-Un;Kim, Chang-Hyun
    • International Journal of Precision Engineering and Manufacturing
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    • v.5 no.3
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    • pp.11-18
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    • 2004
  • In this paper, the classification of artificial defects in semiconductor packages is studied by using pattern recognition technology. For this purpose, the pattern recognition algorithm includes the user made MATLAB code. And preprocess is made of the image process and self-organizing map, which is the input of the back-propagation neural network and the dimensionality reduction method, The image process steps are data acquisition, equalization, binary and edge detection. Image process and self-organizing map are compared to the preprocess method. Also the pattern recognition technology is applied to classify two kinds of defects in semiconductor packages: cracks and delaminations.

Design of SOFLIC for reactor rod control system in nuclear power plant (원자력발전소 원자로 제어봉 제어계통에 대한 자기조정 퍼지제어기 설계)

  • 남해곤;문채주;최홍관
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1995.10b
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    • pp.145-152
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    • 1995
  • This paper presents a novel SOFLIC(self organizing fuzzy logic intelligent controller) for reactor rod control system in nuclear power plant. The output of fuzzy controller is gener ated by using two signal : the error between reference and average temperature, and the error between reference and neutron flux-converted temperatures. Flexibility of the controller is enhanced by using self-organizing feature and the controller respond to variation of system parameter with more precision. performances of the SOFLIC and PID are simulated with the model developed for a nuclear power plant. The SOFLIC is superior to PID : SOFLIC provides more rapid load following capability. more robustiness for variation in process dynamics and minimization of engineer's mistakes in controller design.

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Abnormal Vibration Diagnosis of rotating Machinery Using Self-Organizing Feature Map (자기조직화 특징지도를 이용한 회전기계의 이상진동진단)

  • Seo, Sang-Yoon;Lim, Dong-Soo;Yang, Bo-Suk
    • 유체기계공업학회:학술대회논문집
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    • 1999.12a
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    • pp.317-323
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    • 1999
  • The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal vibration diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised teaming algorithm is used to improve the quality of the classifier decision regions.

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Exploring Knowledge Processing in a Social Complex Adaptive Organization : Wikipedia through the Lens of the LIFE Model

  • Faucher, Jean-Baptiste P.L.;Everett, Andre M.;Lawson, Rob
    • Journal of Information Technology Applications and Management
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    • v.18 no.1
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    • pp.15-39
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    • 2011
  • A deeper understanding of how organizations behave as social complex adaptive systems is needed. In this paper we demonstrate how the Leadership Invigorating Flows of Energies model can help with this understanding. The model highlights the role of emergent leadership as a force encouraging the creation, diffusion, and utilization of knowledge through self-organizing mechanisms. We illustrate our approach by examining Wikipedia and show how it can be described as a social CAS. Our analysis of Wikipedia describes how emerging intrapreneurship behaviors result in dynamic flows of knowledge and self-organizing feedback mechanisms across the organization. We provide implications for organization studies and present evidence to support claims made by advocates of complexity theory. We conclude by proposing that Wikipedia can be seen as a new form of organization, and finish with a brief note highlighting a possible way forward.

Power Transformer Diagnosis Using a Modified Self Organizing Map

  • Lee J. P.;Ji P. S.;Lim J. Y.;Kim S. S.
    • KIEE International Transactions on Power Engineering
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    • v.5A no.1
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    • pp.40-45
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    • 2005
  • Substation facilities have become extremely large and complex parts of electric power systems. The development of condition monitoring and diagnosis techniques has been a very significant factor in the improvement of substation transformer security. This paper presents a method to analyze the cause, the degree, and the aging process power transformers by the Self Organizing Map (SOM) method. Dissolved gas data were non-linearly transformed by the sigmoid function in SOM that works much the same way as the human decision making process. The potential for failure and the degree of aging of normal transformers are identified by using the proposed quantitative criterion. Furthermore, transformer aging is monitored by the proposed criterion for a set of transformers. To demonstrate the validity of the proposed method, a case study is performed and its results are presented.

Perceptron-like SOM : Generalization of SOM (퍼셉트론 형태의 SOM : SOM의 일반화)

  • Song, Geun-Bae;Lee, Haing-Sei
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.10
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    • pp.3098-3104
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    • 2000
  • This paper defiens a perceptron-like self-organizing map(PSOM) and show that PSOM is equivalent to Kohonen's self-organizing map(SOM) if target values of output neurons of PSOM are selected properly. This fact imphes that PSOM is a generalized SOM algorithm. This paper also show that if clustering is restricted to vector sets distributed on hypersphere with unit radius, SOM and dot-product SOM(DOSM) are equivalent algorithms. Therefore we conclude that DSOM is a special case of SOM, which in turn a special, case of PSOM.

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