• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제1권3호
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• pp.119-124
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• 2012

스마트 유틸리티 네트워크는 기존의 AMR, 스마트 그리드, 스마트 워터 그리드 등의 다양한 에너지 관련 서비스를 통합할 수 있는 에너지망 인프라로서 기존 사용자 중심의 통신망으로부터 기기 중심의 통신망으로의 새로운 패러다임 전환을 가능케 하고 있다. 이러한 스마트 유틸리티 네트워크는 관련 응용분야의 제약 조건과 요구사항에 있어 센서 네트워크와 많은 유사성을 가진다. 그리하여, 스마트 유틸리티 네트워크를 위한 새로운 네트워크 프로토콜을 개발하기 위해서는 기존의 관련 연구에 대한 철저한 분석이 선행되어야 한다. 따라서 본 논문에서는 스마트 유틸리티 네트워크의 서비스 요구사항과 설계 고려사항을 분석하고 기존의 저 전력 프로토콜과 데이터 수집기법 그리고 In-network 저장기법에 대한 분석을 통해 스마트 유틸리티 네트워크를 위한 새로운 네트워크 프로토콜의 설계 가이드라인을 제시한다.

• 한국컴퓨터정보학회논문지
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• 제24권5호
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• pp.149-156
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• 2019

The existing subtract image based intrusion detection system for CCTV digital images has a problem that it can not distinguish intruders from moving backgrounds that exist in the natural environment. In this paper, we tried to solve the problems of existing system by designing real - time intrusion detection system for CCTV digital image by combining subtract image based intrusion detection method and background learning artificial neural network technology. Our proposed system consists of three steps: subtract image based intrusion detection, background artificial neural network learning stage, and background artificial neural network evaluation stage. The final intrusion detection result is a combination of result of the subtract image based intrusion detection and the final intrusion detection result of the background artificial neural network. The step of subtract image based intrusion detection is a step of determining the occurrence of intrusion by obtaining a difference image between the background cumulative average image and the current frame image. In the background artificial neural network learning, the background is learned in a situation in which no intrusion occurs, and it is learned by dividing into a detection window unit set by the user. In the background artificial neural network evaluation, the learned background artificial neural network is used to produce background recognition or intrusion detection in the detection window unit. The proposed background learning intrusion detection system is able to detect intrusion more precisely than existing subtract image based intrusion detection system and adaptively execute machine learning on the background so that it can be operated as highly practical intrusion detection system.

• 한국컴퓨터정보학회논문지
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• 제24권2호
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• pp.185-192
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• 2019

In the case of a hearing impaired person using sign language, there are many difficulties in communicating with a normal person who does not understand sign language. The sign language translation system is a system that enables communication between the hearing impaired person using sign language and the normal person who does not understand sign language in this situation. Previous studies on sign language translation systems for communication between normal people and hearing impaired people using sign language are classified into two types using video image system and shape input device. However, the existing sign language translation system does not solve such difficulties due to some problems. Existing sign language translation systems have some problems that they do not recognize various sign language expressions of sign language users and require special devices. Therefore, in this paper, a sign language translation system using an artificial neural network is devised to overcome the problems of the existing system.

• 한국정보처리학회논문지
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• 제7권7호
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• pp.2161-2168
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• 2000

Since most of the existing web cache structures are static, they cannot support the dynamic request change of he current WWW users well. Users re generally using multiple programs in several different windows with rapid preference change within a relatively short period of time. We develop a network-path based algorithm. It organizes a cache according to the network path of the requested URLs and build a network cache farm where caches are logically connected with each other and each cache has its own preference over certain network paths. The algorithm has been implemented and tested in a real site. The performance results show that the new algorithm outperforms the existing static algorithms in the hit ratio and response time dramatically.

• 한국콘텐츠학회논문지
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• 제9권7호
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• pp.86-94
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• 2009

본 논문은 IP 기반 네트워크 환경에서 액세스 네트워크간의 글로벌 이동성을 제공하기 위한 방안을 제안한다. 제안 기술은 코어네트워크 영역에서는 빠른 위치 등록을 위해 전송 영역과 제어영역을 분리하였다. 로컬영역에서는 PMIPv6기술을 적용함으로써 네트워크 기반 로컬 및 글로벌 이동성이 가능하도록 하였다. 또한 성능분석을 통해서 기존의 기술과 제안기술의 성능분석 비교를 통해서, 제안기술이 핸드오버 지연시간을 단축함을 확인하였다.

• 기술혁신학회지
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• 제4권2호
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• pp.157-171
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• 2001

This paper discusses the economics of local loop architecture focusing on existing technologies, ADSL, HFC, and new one, PLC, and suggests a new modeling approach of access network system and the numerical equations. To modelize access network system and drive the numerical equations, we consider the double star and the tree & branch architecture and made block diagram of each access system. In addition, we introduce the density of subscriber as a variable and the equation of seeking the optimal number of cell in a service area. The economics of local loop architecture is analyzed in two ways, i.e. with and without consideration of the cost of cable and infrastructure. From the numerical analysis, we find that in case of not including the cost of cable and infrastructure, there is no much difference in the cost per one subscriber, while, in case of including it, there is remarkable difference among technologies. Therefore we conclude that the economics of local loop architecture is depend on the density of subscriber and existing network infrastructures.

• Asian Journal for Public Opinion Research
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• 제1권2호
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• pp.103-127
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• 2014

This study reviews existing research on the measurement of and the relationship between political diversity and political participation. It addresses the inconsistency in the arguments of existing studies researching the influence of political diversity on political participation. It attempts to find the cause in the variety of approaches to conceptualize and operationalize the two variables. As the measure of political diversity, political network heterogeneity and network attributes are discussed in detail in specific relation to political participation. As for political participation, an in-depth analysis of various ways to understand different forms of political involvement is presented. Implications for public opinion research are discussed.

• 시스템엔지니어링학술지
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• 제19권1호
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• pp.1-13
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• 2023

Transportation of goods by rail in border areas requires considerable time, money, and human resources. Therefore, in this study, a blockchain-based non-stop passing system is proposed to solve this problem. In this study, each transit station and train are designated as one network node, and the corresponding node participates in the blockchain network to record and verify data. In the process, we will design a blockchain network using Docker and design a network interface. Without changing the data and information generated in the existing legacy clearance system, it is possible to configure a blockchain network to ensure the integrity and reliability of the data and to minimize the consumption of time and human resources. The railroad non-stop passing system aims to change the existing legacy system to a blockchain-based non-stop passing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.420-437
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• 2024

There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.188-198
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• 2018

With recent development of high-speed wide-area wireless networks and wide spread of highperformance wireless devices, the demand on seamless video streaming services in Long Term Evolution (LTE) network environments is ever increasing. To meet the demand and provide enhanced Quality of Experience (QoE) with mobile users, the Dynamic Adaptive Streaming over HTTP (DASH) has been actively studied to achieve QoE enhanced video streaming service in dynamic network environments. However, the existing DASH algorithm to select the quality of requesting video segments is based on a procedural algorithm so that it reveals a limitation to adapt its performance to dynamic network situations. To overcome this limitation this paper proposes a novel quality selection mechanism based on a Deep Q-Network (DQN) model, the DQN-based DASH ABR($DQN_{ABR}$) mechanism. The $DQN_{ABR}$ mechanism replaces the existing DASH ABR algorithm with an intelligent deep learning model which optimizes service quality to mobile users through reinforcement learning. Compared to the existing approaches, the experimental analysis shows that the proposed solution outperforms in terms of adapting to dynamic wireless network situations and improving QoE experience of end users.