• 제목/요약/키워드: Network degradation

검색결과 688건 처리시간 0.035초

Development of a New Moving Obstacle Avoidance Algorithm using a Delay-Time Compensation for a Network-based Autonomous Mobile Robot (네트워크 기반 자율 이동 로봇을 위한 시간지연 보상을 통한 새로운 동적 장애물 회피 알고리즘 개발)

  • Kim, Dong-Sun;Oh, Se-Kwon;Kim, Dae-Won
    • Proceedings of the KIEE Conference
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.1916-1917
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    • 2011
  • A development of a new moving obstacle avoidance algorithm using a delay-time Compensation for a network-based autonomous mobile robot is proposed in this paper. The moving obstacle avoidance algorithm is based on a Kalman filter through moving obstacle estimation and a Bezier curve for path generation. And, the network-based mobile robot, that is a unified system composed of distributed environmental sensors, mobile actuators, and controller, is compensated by a network delay compensation algorithm for degradation performance by network delay. The network delay compensation method by a sensor fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of readings of an odometry and the delay of reading of environmental sensors. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal point is shown here.

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Optimum QoS Classes in Interworking of Next Generation Networks

  • Khoshnevis, Behrouz;Khalaj, Babak H.
    • Journal of Communications and Networks
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    • 제9권4호
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    • pp.438-445
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    • 2007
  • In this paper, we consider the problem of optimum selection of quality-of-service(QoS) classes in interworking between the networks in a next-generation-network(NGN) environment. After introducing the delay-cost and loss-cost characteristics, we discuss the time-invariant(TI) and time-variant(TV) scenarios. For the TI case, we show that under nearly lossless transmission condition, each network can make its own optimization regardless of other networks. For the TV case, we present sufficient conditions under which the optimum QoS class of each network can be considered fixed with respect to time without considerable degradation in the optimization target. Therefore, under the conditions presented in this paper, the QoS of a flow in each network can be determined solely by considering the characteristics of that network and this QoS class can be held fixed during the flow period.

Classification of Degradation Types Based on Distribution of Blocky Blocks for IP-Based Video Services

  • Min, Kyung-Yeon;Lee, Seon-Oh;Sim, Dong-Gyu;Lee, Hyun-Woo;Ryu, Won;Lee, Kyoung-Hee
    • ETRI Journal
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    • 제33권3호
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    • pp.454-457
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    • 2011
  • In this letter, we propose a new quality measurement method to identify the causes of video quality degradation for IP-based video services. This degradation mainly results from network performance issues and video compression. The proposed algorithm identifies the causes based on statistical feature values from blocky block distribution in degraded IP-based videos. We found that the sensitivity and specificity of the proposed algorithm are 93.63% and 91.99%, respectively, in comparison with real error types and subjective test data.

Convolutional Neural Network Based on Accelerator-Aware Pruning for Object Detection in Single-Shot Multibox Detector (싱글숏 멀티박스 검출기에서 객체 검출을 위한 가속 회로 인지형 가지치기 기반 합성곱 신경망 기법)

  • Kang, Hyeong-Ju
    • Journal of the Korea Institute of Information and Communication Engineering
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    • 제24권1호
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    • pp.141-144
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    • 2020
  • Convolutional neural networks (CNNs) show high performance in computer vision tasks including object detection, but a lot of weight storage and computation is required. In this paper, a pruning scheme is applied to CNNs for object detection, which can remove much amount of weights with a negligible performance degradation. Contrary to the previous ones, the pruning scheme applied in this paper considers the base accelerator architecture. With the consideration, the pruned CNNs can be efficiently performed on an ASIC or FPGA accelerator. Even with the constrained pruning, the resulting CNN shows a negligible degradation of detection performance, less-than-1% point degradation of mAP on VOD0712 test set. With the proposed scheme, CNNs can be applied to objection dtection efficiently.

A Investment on Wire-wireless Communication Method for Electrical Device Infrastructure Maintenance (전력설비 관리를 위한 무선 및 유선 통신 방법에 관한 고찰)

  • Kim, Young-Eok;Lee, Jin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • 제65권2호
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    • pp.354-359
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    • 2016
  • Power plants maintenance data is to be sent to management server system via a communication network. In this case, reliable communication network is required. Transmission of the power plants maintenance data is used in the wired communication network or wireless communication network. PLC communication network is a kind of wired communication network. However PLC communication network is easily affected by noise. On the vulnerable areas in power line system, such as a mountain or rural areas, it is difficult to form a power line communication network. For a wireless communication, environment are also influenced factors in wireless communication. Harsh environmental factors are bring the communication characteristic degradation. In such areas it can be used a combination of two networks and in this way the complementary function can be achieved. Power plants are distributed in various regions across the country. The appropriate communication network is needed to maintain the power plant.This study investigated the effect of environment on the wired communication and wireless communication. It would examine a variable factor which is affect to the communication characteristic. We used PLC communication for wired communication network and ZigBee communication for wireless communication network. We investigated the characteristics of a single communication network and it raised the need for a complex communication technology to complement a single communication network.

AMD Identification from OCT Volume Data Acquired from Heterogeneous OCT Machines using Deep Convolutional Neural Network (이종의 OCT 기기로부터 생성된 볼륨 데이터로부터 심층 컨볼루션 신경망을 이용한 AMD 진단)

  • Kwon, Oh-Heum;Jung, Yoo Jin;Kwon, Ki-Ryong;Song, Ha-Joo
    • Database Research
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    • 제34권3호
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    • pp.124-136
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    • 2018
  • There have been active research activities to use neural networks to analyze OCT images and make medical decisions. One requirement for these approaches to be promising solutions is that the trained network must be generalized to new devices without a substantial loss of performance. In this paper, we use a deep convolutional neural network to distinguish AMD from normal patients. The network was trained using a data set generated from an OCT device. We observed a significant performance degradation when it was applied to a new data set obtained from a different OCT device. To overcome this performance degradation, we propose an image normalization method which performs segmentation of OCT images to identify the retina area and aligns images so that the retina region lies horizontally in the image. We experimentally evaluated the performance of the proposed method. The experiment confirmed a significant performance improvement of our approach.

Modeling for Efficient QoS support in wireless Networks (무선 네트웍에서의 효율적인 QoS제공을 위한 모델링)

  • 이성협;염익준
    • Proceedings of the IEEK Conference
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(1)
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    • pp.249-252
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    • 2001
  • This paper focuses on the consideration of not only QoS parameters in wired network, but also QoS parameters in wireless network that supported for the Efficient QoS in the Al1 Service Levels. So, We supposed the "Efficient QoS Model" that guaranteed the QoS parameters "Loss Profile" , "Service Degradation" , "Latency and Jittering" , "Mobility of Mobile User" , "Probability of seamless communication" in wired-wireless networks. And the Method of Efficient QoS support that we supposed consists of "Multicast Routing-RSVP Protocol architecture based on Mobile IP" and "Protocols internetworking model ".

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Study on a Neural Network UPC Algorithm Using Traffic Loss Rate Prediction (트래픽 손실율 예측을 통한 신경망 UPC 알고리즘에 관한 연구)

  • 변재영;이영주정석진김영철
    • Proceedings of the IEEK Conference
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.126-129
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    • 1998
  • In order to control the flow of traffics in ATM networks and optimize the usage of network resources, an efficient control mechanism is necessary to cope with congestion and prevent the degradation of network performance caused by congestion. This paper proposes a new UPC(Usage Parameter Control) mechanism that varies the token generation rate and the buffer threshold of leaky bucket by using a Neural Network controller observing input buffers and token pools, thus achieving the improvement of performance. Simulation results show that the proposed adaptive algorithm uses of network resources efficiently and satisfies QoS for the various kinds of traffics.

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Inter-Cell Cooperative Transmission Scheme for Improving Reliability at the Heterogeneous Network (이종 네트워크 환경에서 신뢰성 향상을 위한 인접 셀 간 협력 전송 기법)

  • Kang, Sung-jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제40권10호
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    • pp.1931-1933
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    • 2015
  • This paper proposes inter-cell cooperative transmission scheme in order to improve the reliability of the wireless communication system at the heterogeneous network environments. The heterogeneous network can increase data rate by using existing network technologies. However, degradation of communication performance in the cell edge has been a serious problem. Therefore, this letter proposes an adaptive transmission scheme according to the diverse situations in order to solve this problem.

Discrimination of insulation defects using a neural network (신경회로망을 이용한 절연 결함의 판별)

  • 최재관;김재환;김성홍;윤헌주;박재준
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 한국전기전자재료학회 1997년도 추계학술대회 논문집
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    • pp.381-384
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    • 1997
  • This paper describes the method of diagnosing the degradation by void defects of insulator inside in operation. Needle-shape void specimens, made from LDPE, were used to generate an electrical tree under ac voltage. The method uses a neural network system with input signal of AE patterns. AE pattern consists of the pulse count and average amplitude according to the phase angle. After the learning process was over, unknown emission patterns were put into the network. It was shown that the network discriminates the void deflects well. The effectiveness of the neural network system for partial discharge recognition was shown.

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