• Title/Summary/Keyword: Self-Organizing System

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A Recommender System Model Combining Collaborative filtering and SOM Neural Networks (협동적 필터링과 SOM 신경망을 결합한 추천시스템 모델)

  • Lee, Mi-Hee;Woo, Young-Tae
    • Journal of Korea Multimedia Society
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    • v.11 no.9
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    • pp.1213-1226
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    • 2008
  • A recommender system supports people in making recommendations finding a set of people who are likely to provide good recommendations for a given person, or deriving recommendations from implicit behavior such as browsing activity, buying patterns, and time on task. We proposed new recommender system which combined SOM(Self-Organizing Map) neural networks with the Collaborative filtering which most recommender systems hat applied First, we segmented user groups according to demographic characteristics and then we trained the SOM with people's preferences as ito inputs. Finally we applied the classic collaborative filtering to the clustering with similarity in which an recommendation seeker belonged to, and therefore we didn't have to apply the collaborative filtering to the whose data set. Experiments were run for EachMovies data set. The results indicated that the predictive accuracy was increased in terms of MAE(Mean-Absolute-Error).

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Self-Organizing Middleware Platform Based on Overlay Network for Real-Time Transmission of Mobile Patients Vital Signal Stream (이동 환자 생체신호의 실시간 전달을 위한 오버레이 네트워크 기반 자율군집형 미들웨어 플랫폼)

  • Kang, Ho-Young;Jeong, Seol-Young;Ahn, Cheol-Soo;Park, Yu-Jin;Kang, Soon-Ju
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.7
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    • pp.630-642
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    • 2013
  • To transmit vital signal stream of mobile patients remotely, it requires mobility of patient and watcher, sensing function of patient's abnormal symptom and self-organizing service binding of related computing resources. In the existing relative researches, the vital signal stream is transmitted as a centralized approach which exposure the single point of failure itself and incur data traffic to central server although it is localized service. Self-organizing middleware platform based on heterogenous overlay network is a middleware platform which can transmit real-time data from sensor device(including vital signal measure devices) to Smartphone, TV, PC and external system through overlay network applied self-organizing mechanism. It can transmit and save vital signal stream from sensor device autonomically without arbitration of management server and several receiving devices can simultaneously receive and display through interaction of nodes in real-time.

Self-organizing fuzzy controller using data base (데이타 베이스를 이용한 자기 구성 퍼지 제어기)

  • 윤형식;이평기;전기준
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.579-583
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    • 1991
  • A fuzzy logic controller with rule modification capability is proposed to overcome the difficulty of obtaining control rules from the human operators. This new SOC algorithm modifies control rules by a fuzzy inference machine utilizing data base. Computer simulation results show good performances on both a linear system and a nonlinear system.

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Self-Organization Fuzzy Control of Dual-Arm Robot (Dual-Arm로봇의 자기구성 퍼지제어)

  • 김홍래;김종수;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.10a
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    • pp.201-206
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    • 2003
  • In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed fir a hierarchical control structure consisting of basic level and high level that modify control rules. The proposed SOFC scheme is simple in structure, fast in computation and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for robot with eight joints.

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Robust Control of Dual Arm Robot with Eight Joint Based-on Self-Organization Fuzzy Control (자기구성 퍼지제어에 의한 8축 로봇의 강인제어)

  • 신행봉;김종수;김홍래;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2004.10a
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    • pp.187-192
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    • 2004
  • In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules. The proposed SOFC scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for robot with eight joints.

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A Self-Organizing Scheme for Swarm Systems

  • Kim, Dong-Hun;Kim, Hong-Pil
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2475-2480
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    • 2003
  • A control system design based on coupled nonlinear oscillators (CNOs) for a self-organized swarm system is presented. In this scheme, agents self-organize to flock and arrange group formations through attractive and repulsive forces among themselves using CNOs. Virtual agents are also used to create richer group formation patterns. The objective of the swarm control in this paper is to follow a moving target with a final group formation in the shortest possible time despite some obstacles. The simulation results have shown that the proposed scheme can effectively construct a self-organized multi-agent swarm system capable of group formation and group immigration despite the emergence of obstacles.

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Container Image Recognition using Fuzzy-based Noise Removal Method and ART2-based Self-Organizing Supervised Learning Algorithm (퍼지 기반 잡음 제거 방법과 ART2 기반 자가 생성 지도 학습 알고리즘을 이용한 컨테이너 인식 시스템)

  • Kim, Kwang-Baek;Heo, Gyeong-Yong;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.7
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    • pp.1380-1386
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    • 2007
  • This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is blacker white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm. Experiments using real images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

Dynamic Inter-Cell Interference Avoidance in Self-Organizing Femtocell Networks (자가구성 펨토셀의 동적 셀간간섭 회피 기법)

  • Park, Sang-Kyu;Bahk, Sae-Woong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.3A
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    • pp.259-266
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    • 2011
  • Femtocells are expected as the surest way to increase the system capacity with higher-quality links and more spatial reuse in future networks. In spite of their great potential, the system capacity is highly susceptible to network density because a large portion of users are exposed to inter-cell interference (ICI). In this work, we proposed a dynamic interference avoidance scheme in densely deployed cell environments. Our proposed DDIA (Distributed Dynamic ICI Avoidance) scheme not only works in a fully distributed manner, but also controls interference link connectivity of users with high agility so that it is suited for self-organizing networks (SONs). We introduced the concept of ICI-link and two-tier scheduling in designing the DDIA scheme. To avoid ICI without any central entity, our scheme tries to harmonize all base stations (BSs) with users adaptively. Through extensive simulations, it was shown that our proposed scheme improves the throughput of users by more than twice on average compared to the frequency reuse factor 1 scheme, who are exposed to ICI while maintaining or even improving overall network performance. Our scheme operates well regardless of network density and topology.