• Title/Summary/Keyword: Electrical network

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Implementation to eye motion tracking system using OpenCV and convolutional neural network (OpenCV 와 Convolutional neural network를 이용한 눈동자 모션인식 시스템 구현)

  • Lee, Seung Jun;Heo, Seung Won;Lee, Hee Bin;Yu, Yun Seop
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.379-380
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    • 2018
  • Previoisly presented "Implementation to pupil motion recognition system using convolution neural network".is improved. Using OpenCV, face and eye areas are detected, and then configure the neural network using Numpy. This pupil motion recognition system is based on the Numpy for configuring and calculating the neural network. This system is implemented on DE1-SOC.

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Design of Space Search-Optimized Polynomial Neural Networks with the Aid of Ranking Selection and L2-norm Regularization

  • Wang, Dan;Oh, Sung-Kwun;Kim, Eun-Hu
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1724-1731
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    • 2018
  • The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

The Effect of Interpenetrating Polymer Network upon Tracking Resistance of Epoxy Composite Materials (에폭시 복합재료의 내트래킹성에 미치는 상호침입망목의 효과)

  • 김탁용;이덕진;손인환;김명호;김경환;김재환
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 1996.11a
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    • pp.225-229
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    • 1996
  • In this study, in order to develop outdoor insulating materials, SIN(simultaneous interpenetrating polymer network) was introduced to Epoxy resin and the environment resistance was investigated. The single network structure specimen(E series) formed of Epoxy resin alone and simultaneous interpenetrating polymer network specimen (EM series) in which epoxy resin was taken as the first network and methyl methacrylate resin as the second network were manufactured. Ten kinds of specimens were manufacture by filler (SiO$_2$) content. SEM were utilized in order to confirm their network structure changes, and AC voltage dielectric strength was measured. Also, UV-test and tracking test were carried out investigate the environment resistance characteristic. Therefore the variations of network structure were happened as a result of SEM test, and it was confirmed that simultaneous interpenetrating polymer network specimens were more excellent than single network structure specimens.

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Universal SSR Small Signal Stability Analysis Program of Power Systems and its Applications to IEEE Benchmark Systems

  • Kim, Dong-Joon;Nam, Hae-Kon;Moon, Young-Hwan
    • KIEE International Transactions on Power Engineering
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    • v.3A no.3
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    • pp.139-147
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    • 2003
  • The paper presents a novel approach of constructing the state matrix of the multi-machine power system for SSR (subsynchronous resonance) analysis using the linearized equations of individual devices including electrical transmission network dynamics. The machine models in the local d-q reference frame are integrated with the network models in the common R-I reference frame by simply transforming their output equations into the R-I frame where the transformed output is used as the input to the network dynamics or vice versa. The salient feature of the formulation is that it allows for modular construction of various component models without rearranging the overall state space formulation. This universal SSR small signal stability program provides a flexible tool for systematic analyses of SSR small-signal stability impacts of both conventional devices such as generation systems and novel devices such as power electronic apparatus and their controllers. The paper also presents its application results to IEEE benchmark models.

Power Disturbance Classifier Using Wavelet-Based Neural Network

  • Choi Jae-Ho;Kim Hong-Kyun;Lee Jin-Mok;Chung Gyo-Bum
    • Journal of Power Electronics
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    • v.6 no.4
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    • pp.307-314
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    • 2006
  • This paper presents a wavelet and neural network based technology for the monitoring and classification of various types of power quality (PQ) disturbances. Simultaneous and automatic detection and classification of PQ transients, is recommended, however these processes have not been thoroughly investigated so far. In this paper, the hardware and software of a power quality data acquisition system (PQDAS) is described. In this system, an auto-classifying system combines the properties of the wavelet transform with the advantages of a neural network. Additionally, to improve recognition rate, extraction technology is considered.

Mechanism for Reader Collision Avoidance using sensor nodes (센서 노드를 이용한 리더간의 충돌방지 방법)

  • Lee Hyun-Jung;Kim Sung-Jun;An Sun-Shin;Kim Dong-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06d
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    • pp.145-147
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    • 2006
  • 본 논문에서는 센서네트워크와 RFID 네트워크가 결합되어 있는 환경에서 센서 노드의 특성을 이용한 RFID 리더 충돌 방지 방법을 제안한다. 세부적으로 이웃 센서 노드 정보 확인 단계, 관리 노드로부터 리더 충돌 확인 단계, 태그 리드 단계를 포함한다. 리더와 센서가 결합되어 있는 환경에서, 센서 노드들간의 거리에 따라 리더들 간의 동기를 맞추어 충돌을 방지함으로써, 전체 시스템의 부하를 감소시키고, 시스템을 관리하는데 자원 낭비를 방지하며, 시스템의 처리율 및 효율을 향상시킬 수 있다.

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ART2 Neural Network Applications for Diagnosis of Sensor Fault in the Indoor Gas Monitoring System

  • Lee, In-Soo;Cho, Jung-Hwan;Shim, Chang-Hyun;Lee, Duk-Dong;Jeon, Gi-Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1727-1731
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    • 2004
  • We propose an ART2 neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, fault classifier by ART2 NN (adaptive resonance theory 2 neural network) with uneven vigilance parameters is used for fault isolation. The performances of the proposed fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

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A Switch Wrapper Design for an AMBA AXI On-Chip-Network (AMBA AHB와 AXI간 연동을 위한 Switch Wrapper의 설계)

  • Yi, Jong-Su;Chang, Ji-Ho;Lee, Ho-Young;Kim, Jun-Seong
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.869-872
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    • 2005
  • In this paper we present a switch wrapper for an AMBA AXI, which is an efficient on-chip-network interface compared to bus-based interfaces in a multiprocessor SoC. The AXI uses an idea of NoC to provide the increasing demands on communication bandwidth within a single chip. A switch wrapper for AXI is located between a interconnection network and two IPs connecting them together. It carries out a mode of routing to interconnection network and executes protocol conversions to provide compatibility in IP reuse. A switch wrapper consists of a direct router, AHB-AXI converters, interface modules and a controller modules. We propose the design of a all-in-one type switch wrapper.

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CAMR: Congestion-Aware Multi-Path Routing Protocol for Wireless Mesh Networks

  • Jang, Seowoo;Kang, Seok-Gu;Yoon, Sung-Guk
    • Journal of Electrical Engineering and Technology
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    • v.12 no.1
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    • pp.411-419
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    • 2017
  • The Wireless Mesh Network (WMN) is a multi-hop wireless network consisting of mesh routers and clients, where the mesh routers have minimal mobility and form the backbone. The WMN is primarily designed to access outer network to mesh clients through backhaul gateways. As traffic converges on the gateways, traffic hotspots are likely to form in the neighborhood of the gateways. In this paper, we propose Congestion Aware Multi-path Routing (CAMR) protocol to tackle this problem. Upon congestion, CAMR divides the clients under a mesh STA into two groups and returns a different path for each group. The CAMR protocol triggers multi-path routing in such a manner that the packet reordering problem is avoided. Through simulations, we show that CAMR improves the performance of the WMN in terms of throughput, delay and packet drop ratio.

Electro-optical Properties of Twisted Nematic Liquid Crystal Cell with Silver Nanowire Network Electrodes

  • Jang, Kyeong-Wook;Han, Jeong-Min;Shon, Jin-Geun
    • Journal of Electrical Engineering and Technology
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    • v.12 no.1
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    • pp.284-287
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    • 2017
  • This paper introduces liquid crystal (LC) alignment and its electro-optical properties in the LC cells with silver nanowire (AgNW) networks. The AgNW network was used as an electrode of LC cell as a substitute for an indium-tin-oxide (ITO) film. LC alignment characteristics in the LC cell using AgNW networks, which have two different sheet resistances of $60{\Omega}/m^2$ and $80{\Omega}/m^2$, were observed. The LC alignment characteristics including pretilt angle, LC alignment state, and thermal stability are similar irrespective of sheet resistance of AgNW network. However, twisted-nematic (TN)-LC cell normally operated when using AgNW network with sheet resistance of $80{\Omega}/m^2$. Electrooptical properties of TN-LC cell exhibited competitive performance compared to those of TN-LC cell based on conventional ITO electrode, which allow new approaches to replace conventional ITO electrode in display technology.