• Title/Summary/Keyword: Network mapping

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STEPANOV ALMOST PERIODIC SOLUTIONS OF CLIFFORD-VALUED NEURAL NETWORKS

  • Lee, Hyun Mork
    • Journal of the Chungcheong Mathematical Society
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    • v.35 no.1
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    • pp.39-52
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    • 2022
  • We introduce Clifford-valued neural networks with leakage delays. Furthermore, we study the uniqueness and existence of Clifford-valued Hopfield artificial neural networks having the Stepanov weighted pseudo almost periodic forcing terms on leakage delay terms. However the noncommutativity of the Clifford numbers' multiplication made our investigation diffcult, so our results are obtained by decomposing Clifford-valued neural networks into real-valued neural networks. Our analysis is based on the differential inequality techniques and the Banach contraction mapping principle.

Image Demorieing Based on a Multi-scale Neural Network (다중 스케일 네트워크 기반 영상 내 모아레 무늬 제거 기법)

  • Park, Hyunkook;Vien, An Gia;Lee, Chul
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.07a
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    • pp.263-265
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    • 2020
  • 본 논문에서는 다중 스케일로 구성된 뉴럴 네트워크를 이용하여 영상 내 모아레 무늬을 제거하는 기법을 제안한다. 제안하는 기법은 영상 피라미드를 생성하여 모아레 무늬를 구성하는 다양한 주파수 범위의 정보를 제거한다. 각 branch는 Multi-scale Feature Block (MFB)과 Tone-Mapping Block (TMB)으로 구성하여 효과적으로 모아레 현상을 제거하고 저하된 색상 저하를 복원한다. 컴퓨터 모의실험을 통해 제안하는 기법이 기존 기법에 비해서 높은 모아레 제거 성능을 보이는 것을 확인한다.

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Study of Active Galactic Nuclei and Gravitational Wave Sources with Time-series Observation

  • Kim, Joonho;Im, Myungshin
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.2
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    • pp.39.1-39.1
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    • 2021
  • In this presentation, study of the energetic astronomical phenomena, active galactic nucleus (AGN) and gravitational wave (GW) source, with time-series observation will be reported. They emit large amounts of energy and play an important role in the history of the Universe. First, intra-night variability of AGNs is studied using Korea Microlensing Telescope Network (KMTNet). Second topic is photometric reverberation mapping which is applied for 11 AGNs with medium-bands and Lee Sang Gak Telescope. Last, three gravitational wave events were followed-up by various optical telescopes. Each topic will be specifically addressed in the presentation.

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Mesh topological form design and geometrical configuration generation for cable-network antenna reflector structures

  • Liu, Wang;Li, Dong-Xu;Jiang, Jian-Ping
    • Structural Engineering and Mechanics
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    • v.45 no.3
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    • pp.411-422
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    • 2013
  • A well-designed mesh shape of the cable net is of essential significance to achieve high performance of cable-network antenna reflectors. This paper is concerned with the mesh design problem for such antenna reflector structure. Two new methods for creating the topological forms of the cable net are first presented. Among those, the cyclosymmetry method is useful to generate different polygon-faceted meshes, while the topological mapping method is suitable for acquiring triangle-faceted meshes with different mesh grid densities. Then, the desired spatial paraboloidal mesh geometrical configuration in the state of static equilibrium is formed by applying a simple mesh generation approach based on the force density method. The main contribution of this study is that a general technical guide for how to create the connectivities between the nodes and members in the cable net is provided from the topological point of view. With the new idea presented in this paper, multitudes of mesh configurations with different net patterns can be sought by a certain rule rather than by empiricism, which consequently gives a valuable technical reference for the mesh design of this type of cable-network structures in the engineering.

Expansible & Reconfigurable Neuro Informatics Engine : ERNIE (대규모 확장이 가능한 범용 신경망 연산기 : ERNIE)

  • 김영주;동성수;이종호
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.6
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    • pp.56-68
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    • 2003
  • Difficult problems In implementing digital neural network hardware are the extension of synapses and the programmability for relocating neurons. In this paper, the structure of a new hardware is proposed for solving these problems. Our structure based on traditional SIMD can be dynamically and easily reconfigured connections of network without synthesizing and mapping original design for each use. Using additional modular processing unit the numbers of neurons find synapses increase. To show the extensibility of our structure, various models of neural networks : multi-layer perceptrons and Kohonen network are formed and tested. The performance comparison with software simulation shows its superiority in the aspects of performance and flexibility.

ARP Modification for Prevention of IP Spoofing

  • Kang, Jung-Ha;Lee, Yang Sun;Kim, Jae Young;Kim, Eun-Gi
    • Journal of information and communication convergence engineering
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    • v.12 no.3
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    • pp.154-160
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    • 2014
  • The address resolution protocol (ARP) provides dynamic mapping between two different forms of addresses: the 32-bit Internet protocol (IP) address of the network layer and the 48-bit medium access control (MAC) address of the data link layer. A host computer finds the MAC address of the default gateway or the other hosts on the same subnet by using ARP and can then send IP packets. However, ARP can be used for network attacks, which are one of the most prevalent types of network attacks today. In this study, a new ARP algorithm that can prevent IP spoofing attacks is proposed. The proposed ARP algorithm is a broadcast ARP reply and an ARP notification. The broadcast ARP reply was used for checking whether the ARP information was forged. The broadcast ARP notification was used for preventing a normal host's ARP table from being poisoned. The proposed algorithm is backward compatible with the current ARP protocol and dynamically prevents any ARP spoofing attacks. In this study, the proposed ARP algorithm was implemented on the Linux operating system; here, we present the test results with respect to the prevention of ARP spoofing attacks.

A Study on the Prediction of the Nonlinear Chaotic Time Series Using a Self-Recurrent Wavelet Neural Network (자기 회귀 웨이블릿 신경 회로망을 이용한 비선형 혼돈 시계열의 예측에 관한 연구)

  • Lee, Hye-Jin;Park, Jin-Bae;Choi, Yoon-Ho
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2209-2211
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    • 2004
  • Unlike the wavelet neural network, since a mother wavelet layer of the self-recurrent wavelet neural network (SRWNN) is composed of self-feedback neurons, it has the ability to store past information of the wavelet. Therefore we propose the prediction method for the nonlinear chaotic time series model using a SRWNN. The SRWNN model is learned for the modeling of a function such that the inputs arc known values of the time series and the output is the value in the future. The parameters of the network are tuned to minimize the difference between the nonlinear mapping of the chaotic time series and the output of SRWNN using the gradient-descent method for the adaptive backpropagation algorithm. Through the computer simulations, we demonstrate the feasibility and the effectiveness of our method for the prediction of the logistic map and the Mackey-Glass delay-differential equation as a nonlinear chaotic time series.

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A Study of Protocol comparison Analysis for MPLS Traffic Engineering (MPLS 트래픽 엔지니어링을 위한 프로토콜 비교 분석에 관한 연구)

  • Ha Yun-sik;Kim Dong-il;Choi Sam-gil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.4
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    • pp.772-776
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    • 2005
  • To support abruptly increasing data traffic in these days, network management is needed. And also to maintain the steady infra, there is MPLS need which can support traffic engineering. It's necessary that MPLS doesn't only manage network to support recently booming data traffic, but has capacity to support traffic engineering to keep static infrastructure. Traffic engineering, method that a large-scale user shifts traffic to the beforehand designated routes that pass through specific nodes on network, is operation that is mapping traffic flow to the physical network topology. In this paper, we supplement the defect of the traditional RSVP traffic engineering and to construct far more steady infra, we suggest the way of its development of ERSVP signaling protocol.

A Study of Protocol comparison Analysis for MPLS Traffic Engineering (MPLS 트래픽 엔지니어링을 위한 프로토콜 비교 분석에 관한 연구)

  • Ha, Yun-Sik;Kim, Dong-Il;Choi, Sam-Gil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.105-108
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    • 2005
  • To support abruptly increasing data traffic in these days. network management is needed. And also to maintain the steady infra, there is MPLS need which can support traffic engineering. It's necessary that MPLS doesn't only manage network to support recently booming data traffic, but has capacity to support traffic engineering to keep static infrastructure. Traffic engineering, method that a large-scale user shifts traffic to the beforehand designated routes that pass through specific nodes on network, is operation that is mapping traffic flow to the physical network topology. In this paper, we supplement the defect of the traditional RSVP traffic engineering and to construct far more steady infra, we suggest the way of its development of ERSVP signaling protocol.

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Topological Properties and Broadcasting Algorithm of Hyper-Star Interconnection Network (하이퍼-스타 연결망의 위상적 성질과 방송 알고리즘)

  • Kim Jong-Seok;Oh Eun-seuk;Lee Hyeong-Ok
    • The KIPS Transactions:PartA
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    • v.11A no.5
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    • pp.341-346
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    • 2004
  • Recently A Hyper-Star Graph HS(m, k) has been introduced as a new interconnection network of new topology for parallel processing. Hyper-Star Graph has properties of hypercube and star graph, further improve the network cost of a hypercube with the same number of nodes. In this paper, we show that Hyper-Star Graph HS(m, k) is subgraph of hypercube. And we also show that regular graph, Hyper-Star Graph HS(2n, n) is node-symmetric by introduced mapping algorithm. In addition, we introduce an efficient one-to-all broadcasting scheme - takes 2n-1 times - in Hyper-Star Graph HS(2n, n) based on a spanning tree with minimum height.