• Title/Summary/Keyword: Network loading

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Automatic Determination of Crack Opening Loading under Random Loading by the Use of Neural Network (신경회로망을 이용한 변동하중 하에서의 균열열림점 자동측정)

  • Gang, Jae-Yun;Song, Ji-Ho;Kim, Jeong-Yeop
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.9 s.180
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    • pp.2283-2291
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    • 2000
  • The neural network method is applied to automatically measure the crack opening load under random loading. The crack opening results obtained are compared with the visual measured results. Fatigue crack growth under random loading is predicted using the crack opening data measured by the neural network method, and the prediction results are compared with experimental ones. It is found that the neural network method can be successfully applied to consistently measure the crack opening load under random loading and also gives some results different from the results by visual measurement.

Dynamic Network Loading Method and Its Application (동적 네트워크 로딩 방법 및 적용에 관한 연구)

  • 한상진
    • Journal of Korean Society of Transportation
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    • v.20 no.1
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    • pp.101-110
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    • 2002
  • This study first explains general features of traffic assignment models and network loading methods, and investigates the relationship between them. Then it introduces a dynamic network loading method, which accounts far time variable additionally. First of all, this study suggests that it is important to consider some requirements for the dynamic network loading, such as causality, FIFO(First-In-First-Out) discipline, the flow propagation, and the flow conservation. The details of dynamic network loafing methods are explained in the form of algorithm, and numerical examples are shown in the test network by adopting deterministic queuing model for a link Performance function.

Development of Autonomous Loading and Unloading for Network-based Unmanned Forklift (네트워크 기반 무인지게차를 위한 팔레트 자율적재기술의 개발)

  • Park, Jee-Hun;Kim, Min-Hwan;Lee, Suk;Lee, Kyung-Chang
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.10
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    • pp.1051-1058
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    • 2011
  • Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. Especially, automation of pallet loading and unloading technique is useful for enhancing performance of logistics and reducing cost for automation system. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control, and so on. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. This paper presents a vision sensorbased autonomous loading and unloading for network-based unmanned forklift where system components are connected to a shared CAN network. Functions such as image processing and control algorithm are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. And the experimental results show that proposed architecture can be an appropriate choice for autonomous loading in the unmanned forklift.

Efficient Load Balancing Algorithms for a Resilient Packet Ring

  • Cho, Kwang-Soo;Joo, Un-Gi;Lee, Heyung-Sub;Kim, Bong-Tae;Lee, Won-Don
    • ETRI Journal
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    • v.27 no.1
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    • pp.110-113
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    • 2005
  • The resilient packet ring (RPR) is a data optimized ring network, where one of the key issues is on load balancing for competing streams of elastic traffic. This paper suggests three efficient traffic loading algorithms on the RPR. For the algorithms, we evaluate their efficiency via analysis or simulation.

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Congestion Detection and Avoidance for Reliable Data Transmission in Wireless Sensor Networks (무선 센서 네트워크에서 신뢰성 있는 데이터 전송을 위한 혼잡 탐지와 회피)

  • Park, Hong-Jin;Jang, Jae-Bok
    • Journal of Advanced Navigation Technology
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    • v.14 no.3
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    • pp.343-350
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    • 2010
  • Wireless Sensor Network is an event-driven system that a large number of micro sensor nodes are collected, giving and Wing information. Congestion can take place easily since a great number of sensor nodes are sensing data and transferring them to sink nodes when an event occurs, comparing to the existing wired network. Current internet transport protocol is TCP/UDP, however, this is not proper for wireless sensor network event-driven ESRT, STCP and CODA are being studied for reliable data transport in the wireless sensor network. Congestion are being detected local buffer and channel loading with these techniques. Broadcasting is mainly used and can avoid congestion when one happens. The way that combining local buffer and channel loading information and detecting congestion is being studied in this paper. When congestion occurs, buffering state is divided into three in order to lessen the broadcasting sending the message on congestion control to the node having frequent channel loading. Thus they have advantage of decreasing network's loading.

Study on Network Throughput of Power Line Communication System in In-Building Network (전력선 통신 시스템의 구내 네트워크 데이터 처리량 연구)

  • Jang, Ho-Deok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.1
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    • pp.43-47
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    • 2021
  • This paper investigates the network throughput of PLC (Power Line Communication) system in the in-building network. The OFDM (Orthogonal Frequency Division Multiplexing) modulation format and adaptive bit loading algorithm is used to minimize the effect of signal loss and noise on transmission performance in the power line channel characterized by frequency selective fading. The network throughput of the PLC system which consists of gateway and CPE(Customer Premise Equipment) PLC modem in the in-building network is measured by network performance measurement tool, iperf and analyzed according to the TCP (Transmission Control Protocol) window size.

A Study on the Buckling Characteristics of Single-Layer Latticed Domes under Equipment-Loading (설비하중을 고려하는 단층래티스돔의 좌굴특성에 관한 연구)

  • 박지영;정환목;권영환
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1994.04a
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    • pp.83-88
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    • 1994
  • Recently, the equipments of the structure are increasing remarkably. It is very important to evaluate the stability of the domes under concentrated loading such as a large-scale illuminating, visional, and sound equipment. The paper is aimed at investigating the buckling characteristics of single-layer latticed domes with triangular network under the uniformly distributed vertical-loading and the partially concentrated equipment-loading. The results show that the effects of the equipment-loading on the buckling strength is much more sensitive in domes of overall buckling than in domes of member buckling.

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Study on Buckling-Characteristics of Single-layer Latticed Domes -Effect of rise ratio- (단층래티스돔의 좌굴특성에 관한 연구 -라이즈 비의 영향-)

  • 권영환;정환목;이승재
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1992.10a
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    • pp.127-132
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    • 1992
  • The effect of 5 typical rise ratio(h/a=2/9, 5/18, l/3, l/2, 2/3) on the buckling characteristics of single-layer latticed domes with rectangular network under the external pressure are the theoretically studied on the basis of geometically nonlinear FEM and shell analogy method. The loading conditions are 4 types, that is, 1) the uniform pressure loading 2)the uniform snow loading 3) the half - sided asymmetric pressure loading 4) the half - sided asymmetric snow loading.

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A Systematic Approach for Designing a Self-Tuning Power System Stabilizer Based on Artificial Neural Network

  • Sedaghati, Alireza
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.281-286
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    • 2005
  • The main objective of the research work presented in this article is to present a systematic approach for designing a multilayer feed-forward artificial neural network based self-tuning power system stabilizer (ST-ANNPSS). In order to suggest an approach for selecting the number of neurons in the hidden layer, the dynamic performance of the system with ST-ANNPSS is studied and hence compared with that of conventional PSS. Finally the effect of variation of loading condition and equivalent reactance, Xe is investigated on dynamic performance of the system with ST-ANNPSS. Investigations reveal that ANN with one hidden layer comprising nine neurons is adequate and sufficient for ST-ANNPSS. Studies show that the dynamic performance of STANNPSS is quite superior to that of conventional PSS for the loading condition different from the nominal. Also it is revealed that the performance of ST-ANNPSS is quite robust to a wide variation in loading condition.

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Reducing the congestion in a class of job shops

  • 김성철
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1987.10a
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    • pp.35-35
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    • 1987
  • Consider a job shop that is modelled as an open queueing network of the Jackson(l957) type. All work stations in the shop have the same number of parallel servers. Two problems are studied : the loading of stations and the assignment of servers, which are represented by loading and assingment vectors, respectively. Ma jorization and arrangement orderings are established to order, respectively, the loading and the assignment vectors. It is shown that reducing the loading vector under ma jorizat ion or increasing the assignment vector under arrangement ordering will reduce the congestion in the shop in terms of reducing the total number of jobs(in the sense of likelihood ratio ordering), the maximum queue length(in the sense of stochastic ordering), and the queue-length vector( in the sense of stochastic majorization). The results can be used to supprot production planning in certain job shops, and to aid the desing of storage capacity. (OPEN QUEUEING NETWORK; WJORIZATION; ARRANGEMENT ORDERINC; LIKELIHOOD RATIO ORDERINC; STOCHASTIC ORDERING)

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