• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 추계학술대회
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• pp.197-200
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• 1995

In this paper, we proposed the multi-step multi-layer artificial neural network(MMANN) to classify the chromosome, Which is used as a chromosome pattern classifier after learning. We extracted three chromosome morphological feature parameters such as centromeric index, relative length ratio, and relative area ratio by means of preprocessing method from ten chromosome images. The feature parameters of five chromosome images were used to learn neural network and the rest of them were used to classify the chromosome images. The experiment results show that the chromosome classification error is reduced much more, comparing with less feature parameters than that of the other researchers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3468-3495
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• 2015

In this paper, we present a multi-chain based hierarchical topology control algorithm (MCHTC) for wireless sensor networks. In this algorithm, the topology control process using static clustering is divided into sensing layer that is composed by sensor nodes and multi-hop data forwarding layer that is composed by leader nodes. The communication cost and residual energy of nodes are considered to organize nodes into a chain in each cluster, and leader nodes form a tree topology. Leader nodes are elected based on the residual energy and distance between themselves and the base station. Analysis and simulation results show that MCHTC outperforms LEACH, PEGASIS and IEEPB in terms of network lifetime, energy consumption and network energy balance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.503-504
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• 2007

The most Important thing in Sensor Network Design is a Energy Efficiency. Limited sources of Sensor Mote tan occur merging of Protocol. In this paper, we proposed Cross Layer Protocol for Energy Efficienty. The proposed protocol can increase the network life time using multi hop transmission. sensor network should use multi hop communication and small radius because radio in wireless communication is the most spendable thing in sensor network.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.909-922
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• 2000

High sped messaging layer for application's feeling of low level network performance is needed by Clustering System based on high speed network fabrics. It should have the mechanism to directly pass messages between network card and application space, and provide flexible affodabilities for many diverse applications. In this paper, CROWN (Clustering Resources On Workstations' Network) which is designed and implemented for multi-purpose clustering system will be introduced briefly, and CLCP(CROWN Lean Communication Primitives)which is the high speed messaging layer for CROWN will be followed. CLCP consists of a firmware for controlling Myrinet card, device drier, and user libraries. CLCP supports various application domains as a result of pooling and interrupt receive mechanism. In case of polling based receive, 8 bytes short message, and no other process, CLCP has 262 micro-second response time between two nodes, and IM bytes large message, it shows 442Mbps bandwidth.

• 전기학회논문지
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• 제67권11호
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• pp.1506-1511
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• 2018

This study presents a human sensibility evaluation method using neural network and multiple-template method on electroencephalogram(EEG). We used a multi-layer perceptron type neural network as the sensibility classifier using EEG signal. For our research objective, 10-channel EEG signals are collected from the healthy subjects. After the necessary preprocessing is performed on the acquired signals, the various EEG parameters are estimated and their discriminating performance is evaluated in terms of pattern classification capability. In our study, Linear Prediction(LP) coefficients are utilized as the feature parameters extracting the characteristics of EEG signal, and a multi-layer neural network is used for indicating the degree of human sensibility. Also, the estimation for human comfortableness is performed by varying temperature and humidity environment factors and our results showed that the proposed scheme achieved good performances for evaluation of human sensibility.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제6권4호
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• pp.203-210
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• 2017

본 논문에서는 이미지 캡션 생성과 모델 전이에 효과적인 심층 신경망 모델을 제시한다. 본 모델은 멀티 모달 순환 신경망 모델의 하나로서, 이미지로부터 시각 정보를 추출하는 컨볼루션 신경망 층, 각 단어를 저차원의 특징으로 변환하는 임베딩 층, 캡션 문장 구조를 학습하는 순환 신경망 층, 시각 정보와 언어 정보를 결합하는 멀티 모달 층 등 총 5 개의 계층들로 구성된다. 특히 본 모델에서는 시퀀스 패턴 학습과 모델 전이에 우수한 LSTM 유닛을 이용하여 순환 신경망 층을 구성하며, 캡션 문장 생성을 위한 매 순환 단계마다 이미지의 시각 정보를 이용할 수 있도록 컨볼루션 신경망 층의 출력을 순환 신경망 층의 초기 상태뿐만 아니라 멀티 모달 층의 입력에도 연결하는 구조를 가진다. Flickr8k, Flickr30k, MSCOCO 등의 공개 데이터 집합들을 이용한 다양한 비교 실험들을 통해, 캡션의 정확도와 모델 전이의 효과 면에서 본 논문에서 제시한 멀티 모달 순환 신경망 모델의 높은 성능을 확인할 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.1-8
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• 2016

Convolutional neural network (CNN) consists of a few pairs of both convolution layer and subsampling layer. Thus it has more hidden layers than multi-layer perceptron. With the increased layers, the size of convolution mask ultimately determines the total number of weights in CNN because the mask is shared among input images. It also is an important learning factor which makes or breaks CNN's learning. Therefore, this paper proposes the best method to choose the convolution size and the number of layers for learning CNN successfully. Through our face recognition with vast learning examples, we found that the best size of convolution mask is 5 by 5 and 7 by 7, regardless of the number of layers. In addition, the CNN with two pairs of both convolution and subsampling layer is found to make the best performance as if the multi-layer perceptron having two hidden layers does.

• 융합보안논문지
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• 제13권3호
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• pp.25-31
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• 2013

최근 네트워크 사용자들이 네트워크를 사용하는 방식이나 가치의 변화를 살펴보면 간단한 웹 정보와 같은 단방향 정보만을 제공받는 형태에서 자유로운 이동성을 기반으로 보안과 개인화가 보장된 대용량 정보 전송 형태로 바뀌고 있다. 이처럼 다양한 요구사항들의 변화에 따라 개별적으로 서비스를 제공하던 형태에서 하나의 형태로 통합되는 추세에 있다. 아울러 네트워크 또한 개별적인 네트워크를 통합하는 형태로 발전하고 있으며 이러한 여러 네트워크를 통합적으로 제어할 수 있는 네트워크 제어 기술이 핵심 요소로 등장하였다. 이러한 사용자들의 요구사항을 반영하여 차세대 네트워크는 WDM/IP 전송기술을 기반으로 동적 재구성을 지원하는 다계층 네트워크가 대세를 이루고 있다. 이처럼 패킷-광전달 시스템(P-OTS)은 SONET/SDH와 Ethernet, DWDM, OTN, 그리고 ROADM과 같은 기술들을 통합한 플랫폼이라고 할 수 있다. 본 논문에서는 다계층 광 네트워크 제어 시스템에서 PCE 기반 광 및 패킷전달계층 경로계산엔진 알고리즘을 제안하였다.

• 한국통신학회논문지
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• 제35권5A호
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• pp.474-481
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• 2010

본 논문에서는 다중 홉 이동 애드 혹 네트워크에서 크로스 레이어 (Cross layer) 기반의 효과적인 멀티미디어 전송 알고리즘을 제안한다. 제안 알고리즘은 멀티레이트를 지원하는 IEEE 802.11 MAC을 기반으로 하며, 수신 노드에서 패킷 손실률 (Packet Loss Rate, PLR)이 제약 조건 이내를 유지하고 종단간 지연시간이 최소가 되도록 하기 위해 경로상의 각 노드들은 MAC 계층에서 응용계층의 데이터 특성과 물리 계층의 채널정보를 이용하여 효과적인 전송 모드를 선택 한다. 마지막으로 실험을 통하여 제안 알고리즘의 우수성을 확인 한다.

• 항공우주시스템공학회지
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• 제14권6호
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• pp.26-35
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• 2020

The national satellite operation network, which supports multiple satellites, was designated as a Critical Information Infrastructure (CII) in 2017. The network was designed independently from the control network and the information network to enhance physical security. Planning is underway to establish a bidirectional data interface between networks. The data transmission system allows data flow only to the physical layer and the data link layer; hence, only one file can be transferred at any one time. This means that when large amounts of data are being transmitted, no other data can be sent simultaneously in urgent situations. Thus, this paper discusses the design of flexible packets for the transmission of data between networks in an environment where physical security has been enhanced through network separation and based on this, presents a method for transmitting data effectively.