• Title/Summary/Keyword: School Network

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A PROPOSAL OF ENHANSED NEURAL NETWORK CONTROLLERS FOR MULTIPLE CONTROL SYSTEMS

  • Nakagawa, Tomoyuki;Inaba, Masaaki;Sugawara, Ken;Yoshihara, Ikuo;Abe, Kenichi
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.201-204
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    • 1998
  • This paper presents a new construction method of candidate controllers using Multi-modal Neural Network(MNN). To improve a control performance of multiple controller, we construct, candidate controllers which consist of MNN. MNN can learn more complicated function than multilayer neural network. MNN consists of preprocessing module and neural network module. The preprocessing module transforms input signals into spectra which are used as input of the following neural network module. We apply the proposed method to multiple control system which controls the cart-pole balancing system and show the effectiveness of the proposed method.

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Multiple Network-on-Chip Model for High Performance Neural Network

  • Dong, Yiping;Li, Ce;Lin, Zhen;Watanabe, Takahiro
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.10 no.1
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    • pp.28-36
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    • 2010
  • Hardware implementation methods for Artificial Neural Network (ANN) have been researched for a long time to achieve high performance. We have proposed a Network on Chip (NoC) for ANN, and this architecture can reduce communication load and increase performance when an implemented ANN is small. In this paper, a multiple NoC models are proposed for ANN, which can implement both a small size ANN and a large size one. The simulation result shows that the proposed multiple NoC models can reduce communication load, increase system performance of connection-per-second (CPS), and reduce system running time compared with the existing hardware ANN. Furthermore, this architecture is reconfigurable and reparable. It can be used to implement different applications of ANN.

Design Methodology of Networked Control System using CAN(Controller Area Network) Protocol (CAN(Controller Area Network) 프로토콜을 이용한 네트워크 제어시스템 설계)

  • Jung, Joon-Hong;Choi, Soo-Young;Cho, Yong-Seok;Park, Ki-Heon
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2328-2330
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    • 2003
  • This paper presents a new design methodology of networked control system using CAN(Controller Area Network). Feedback control systems having control loops closed through a network are called networked control systems. We design CAN nodes which can transmit control and monitoring data through network bus and apply these to networked control system design. We analyze the variation of stability property according to network-induced delay and determine a proper sampling period of networked control system that preserves stability performance. The results of the experimental example validate effectiveness of our networked control system.

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Policy-based Network Security with Multiple Agents (ICCAS 2003)

  • Seo, Hee-Suk;Lee, Won-Young;Yi, Mi-Ra
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1051-1055
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    • 2003
  • Policies are collections of general principles specifying the desired behavior and state of a system. Network management is mainly carried out by following policies about the behavior of the resources in the network. Policy-based (PB) network management supports to manage distributed system in a flexible and dynamic way. This paper focuses on configuration management based on Internet Engineering Task Force (IETF) standards. Network security approaches include the usage of intrusion detection system to detect the intrusion, building firewall to protect the internal systems and network. This paper presents how the policy-based framework is collaborated among the network security systems (intrusion detection system, firewall) and intrusion detection systems are cooperated to detect the intrusions.

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Privacy Protection Method for Sensitive Weighted Edges in Social Networks

  • Gong, Weihua;Jin, Rong;Li, Yanjun;Yang, Lianghuai;Mei, Jianping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.540-557
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    • 2021
  • Privacy vulnerability of social networks is one of the major concerns for social science research and business analysis. Most existing studies which mainly focus on un-weighted network graph, have designed various privacy models similar to k-anonymity to prevent data disclosure of vertex attributes or relationships, but they may be suffered from serious problems of huge information loss and significant modification of key properties of the network structure. Furthermore, there still lacks further considerations of privacy protection for important sensitive edges in weighted social networks. To address this problem, this paper proposes a privacy preserving method to protect sensitive weighted edges. Firstly, the sensitive edges are differentiated from weighted edges according to the edge betweenness centrality, which evaluates the importance of entities in social network. Then, the perturbation operations are used to preserve the privacy of weighted social network by adding some pseudo-edges or modifying specific edge weights, so that the bottleneck problem of information flow can be well resolved in key area of the social network. Experimental results show that the proposed method can not only effectively preserve the sensitive edges with lower computation cost, but also maintain the stability of the network structures. Further, the capability of defending against malicious attacks to important sensitive edges has been greatly improved.

A Study on the Network of Civilian, Enterprise, School and Government Sectors for Disaster Management (재난관리를 위한 민관산학네트워크 구축에 관한 연구)

  • Sung, Ki-Whan
    • Journal of the Korean Society of Safety
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    • v.20 no.4 s.72
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    • pp.154-161
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    • 2005
  • As disasters in the modem era become a large scale and complexity, no single entity can manage them. Instead collective cooperation between civilian, enterprise, school and government sectors is significantly needed, along with a well prepared mechanism. Thus, I attempt to construct the applicable network of civilian, enterprise, school and government sectors for disaster management through exemplary case studies of established countries as well as Korea's current operations and its drawbacks, based upon a networking design of disaster management organizations as belows: Firstly, it is cooperation and coordination among relevant organizations that are required essentially in the new era, in view of formative condition of necessary environment for civil participation. The cooperation and coordination can be made only through the network of civilian, enterprise, school and government sectors. Secondly, in order to build up the network, major roles and tasks which should be done by civilian, enterprise, school and government sectors respectively are listed based upon a stage of disaster management. Thirdly, operation models of a safety monitoring unit, a disaster prevention unit, a emergency response unit, and a rehabilitation unit are proposed in line with the network of civilian, enterprise, school and government sectors in regional base.

Network Coding-based Maximum Lifetime Algorithm for Sliding Window in WSNs

  • Sun, Baolin;Gui, Chao;Song, Ying;Chen, Hua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1298-1310
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    • 2019
  • Network coding (NC) is a promising technology that can improve available bandwidth and packet throughput in wireless sensor networks (WSNs). Sliding window is an improved technology of NC, which is a supplement of TCP/IP technology and can improve data throughput and network lifetime on WSNs. This paper proposes a network coding-based maximum lifetime algorithm for sliding window in WSNs (NC-MLSW) which improves the throughput and network lifetime in WSN. The packets on the source node are sent on the WSNs. The intermediate node encodes the received original packet and forwards the newly encoded packet to the next node. Finally, the destination node decodes the received encoded data packet and recovers the original packet. The performance of the NC-MLSW algorithm is studied using NS2 simulation software and the network packet throughput, network lifetime and data packet loss rate were evaluated. The simulations experiment results show that the NC-MLSW algorithm can obviously improve the network packet throughput and network lifetime.

TOUSE: A Fair User Selection Mechanism Based on Dynamic Time Warping for MU-MIMO Networks

  • Tang, Zhaoshu;Qin, Zhenquan;Zhu, Ming;Fang, Jian;Wang, Lei;Ma, Honglian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4398-4417
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    • 2017
  • Multi-user Multiple-Input and Multiple-Output (MU-MIMO) has potential for prominently enhancing the capacity of wireless network by simultaneously transmitting to multiple users. User selection is an unavoidable problem which bottlenecks the gain of MU-MIMO to a great extent. Major state-of-the-art works are focusing on improving network throughput by using Channel State Information (CSI), however, the overhead of CSI feedback becomes unacceptable when the number of users is large. Some work does well in balancing tradeoff between complexity and achievable throughput but is lack of consideration of fairness. Current works universally ignore the rational utilizing of time resources, which may lead the improvements of network throughput to a standstill. In this paper, we propose TOUSE, a scalable and fair user selection scheme for MU-MIMO. The core design is dynamic-time-warping-based user selection mechanism for downlink MU-MIMO, which could make full use of concurrent transmitting time. TOUSE also presents a novel data-rate estimation method without any CSI feedback, providing supports for user selections. Simulation result shows that TOUSE significantly outperforms traditional contention-based user selection schemes in both throughput and fairness in an indoor condition.

Neural Network Based Image Genre Classification (Neural Network을 이용한 이미지 장르 분류 시스템)

  • Ahn, Jae-Hoon;Lee, Han-Ku;Ju, Hyun-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.10b
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    • pp.330-335
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    • 2006
  • 본 논문에서는 neural network을 이용한 이미지 장르(유형) 분류 시스템을 소개한다. 이 논문에서 제안된 시스템은 이미지를 예술(art), 사진(photo), 만화(cartoon) 이미지라는 세 가지 장르(유형) 중 하나로 분류한다. 이미지의 특성은 표준 MPEG-7 visual descriptor를 사용하여 추출된 후, neural networks를 이용하여 학습된다. 시뮬레이션 결과는 제안된 시스템이 80% 이상의 이미지들을 정확한 장르(유형)로 분류하는 것을 보여준다.

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