• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.323-327
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• 2006

During the past decades in South Korea, there have been several projects to reduce water demand and save water for paddy irrigation system by automation. This is called as intensive water management system by telemetering of paddy ponding depth and canal water level and telecontrol of water supply facilities. This study suggests a method of constructing topology-based irrigation network system using GIS tools. For the network modeling, a typical agricultural watershed included reservoirs, irrigation and drainage canals, pumping stations was selected. ArcHydro tools composed of edge, junction, waterbody and watershed were used to construct hydro-network. ArcHydro Model was then designed and the network was successfully built using the HydroID. Visualization using ArcHydro tools could display table property of each object. ArcHydro Model was linked to Agricultural Water Demamd and Supply Estimation System (AWDS) which developed by Korea Rural Community and Agriculture Corporation (KRC) to extract information of the study area. And menu of supply facilities information, demand analysis and supply analysis constructed for information acquisition and visualization of acquired informations.

• 정보처리학회논문지C
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• 제8C권5호
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• pp.543-550
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• 2001

본 논문에서는 네트워크 취약점 검색공격에 대한 기존의 탐지알고리즘들이 갖는 문제점을 분석하고 대규모 네트워크에서의 종합적인 탐지 및 대응을 지원하는 개선된 탐지시스템을 제안한다. 가상 공격에 의한 모의 실험을 통하여 제안된 시스템은 소수의 취약점 포트 위주의 공격과 협동공격, 느린 스캔 및 느린 협동공격을 정확히 탐지할 뿐 아니라 에이전트와 서버사이의 유기적인 연동을 통해 보다 종합적이고 계층적으로 공격에 대응함을 검증하였다

• 지능정보연구
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• 제15권3호
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• pp.151-165
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• 2009

퍼지신경망 모형은 인공신경망의 네트워크 구조 표현방법 및 학습알고리듬과 퍼지시스템의 추론방법을 통합한 모형으로 제어 및 예측분야에 성공적으로 적용되고 있다. 본 연구에서는 퍼지신경망 모형 중 우수한 예측정확도로 인해 최근 각광받고 있는ANFIS (Adaptive Network-based Fuzzy Inference System)모형을 기반으로 하는 분류모형을 설계하고 기존의 분류기법(C5.0 의사결정나무)과 비교하여 분류 정확성 관점에서 평가한다. ANFIS 추론의 경우, 최종 결과값이 계급값이 아닌 연속형 변수값을 취하게 되므로 산출된 결과값을 이용하여 적절한 계급값을 할당하는 과정이 필요하다. 본 연구에서는 의사결정나무기법을 이용하여 계급값을 할당하는 방식과 군집분석을 이용하여 계급값을 할당하는 두 가지 방식을 제안하고 두 가지 데이터 세트에 적용하여 ANFIS를 기반으로 한 분류모형의 정확도를 평가하였다.

• 한국철도학회논문집
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• 제9권3호
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• pp.319-324
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• 2006

Studied was a strategy of technology development for railway system in terms of railway network. First, The successful launch of the Korean HST system has not only decreased logistics burden but also significantly transformed the Korean trunk-line railway network, revolutionizing the logistics and technology sectors and reinvigorating the Korean railway industry in one century. Korean railway industry sector is now investing to develop many different types of railway system(G7, Post G7, tilting train...) so that these kinds of various railway system development should be integrated with the National Inter-modal Transportation Network Plan. To secure sufficient capacity that is required by the National Railroad Plan, the railway industry needs to establish mid- and long-term train purchase and operation strategies in compliance with railway construction and operation policies. During a railway construction planning, train operators, based on their train operation strategies, should come up with measures to closely cooperate with project operators from the planning stage through to the opening of a railway system. To be more precise, train operators should establish long-term train procurement plans reflecting both long-term national railroad network plans and plans for each railway line in order to suggest appropriate roles and schedules for each line. Also, based on the long-term railway plan, directions should be decided concerning the research and development of trains in advance.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1275-1280
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• 2014

In this study, the performance of a real-time micro telescopic monitoring system is evaluated, in which an artificial neural network is adopted for the diagnoses of vibratory bodies, such as solid piping system or machinery. The structural vibration was measured by a non-contact remote sensing method, in which images of a high-speed high-definition camera were used. The structural vibration data that can be obtained by the PIV (particle image velocimetry) technique were used for training the neural network. The structures of the neural network are dynamically changed and their performances are evaluated for the constructed diagnosis system. Optimized structures of the neural network are proposed for real-time diagnosis for the piping system. It was experimentally verified that the performances of the neural network used for real-time monitoring are influenced by the types of the vibration data, such as minimum, maximum and average values of the vibration data. It concludes that the time-mean values are most appropriate for monitoring the piping system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2267-2285
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• 2016

Information Centric Networking that uses content name instead of IP address as routing identifier can handle challenges such as traffic explosion and user mobility, but it also suffers from scalability and incompatibility problems. In this paper by combining the concept of software defined networking and Internet end to end arguments, we propose a wide area deployable software defined information centric networking service model named SD-ICN. SD-ICN employs a dual space structure that separates edge service network and core transmission network. The enhanced SDN techniques are used in edge service network in order to implement intelligent data routing and caching, while traditional IP technique is reserved in core transmission network so as to provide wide area high speed data transmission. Besides, a distributed name resolution system based on the cooperation of different controllers is also presented. The prototype experiments in our campus network show that SD-ICN can be deployed in a scalable and incremental way with no modification of the core network, and can support typical communication modes such as multicast, mobility, multihoming, load balancing, and multipath data transmission effectively.

• 한국산업정보학회논문지
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• 제12권4호
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• pp.25-31
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• 2007

본 연구에서는 문서에 나타나는 용어의 통계값을 이용하여 구술문서자료에 포함되어있는 용어들간의 의미 네트워크를 자동으로 구축하는 시스템을 제안하였다. 본 연구를 위하여 전북 새만금지역에서 채록한 186개의 구술생애사 문서자료를 사용하였으며, 구축된 용어네트워크에서 용어들 사이의 관계는 용어들을 백터화하여 결정하였다. 새만금 구술문서에서 중요단어로 선택된 단어의 수는 약 1700여 개이다. 단어들 사이의 용어네트워크는 구축 시스템을 통해서 실시간 내에 표현할 수 있었다. 이 용어네트워크는 앞으로 전개될 시멘틱 검색시스템 구축에 새로운 장을 열 것이며, 구술문서 분석에 크게 기여할 것으로 기대한다.

• 정보보호학회논문지
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• 제14권2호
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• pp.101-111
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• 2004

ISP 네트워크의 보안수준 진단과 대응방안을 수립하기 위해서는 네트워크상의 정보자산에 대한 취약점과 위협 요인을 식별하고, 피해 발생시 예상되는 손실의 정도를 산정하는 위험분석 절차가 필수적이다. 하지만, 기존의 위험분석 방법론 및 도구들은 대부분 방법론적 분석절차와 수단만을 제공하며, 개별 시스템의 취약점 및 위협요인의 변동정보를 실시간으로 반영할 수가 없다. 따라서. 본 논문에서는 네트워크 침입탐지 시스템과 취약점 분석 시스템의 탐지 정보들을 실시간으로 수집, 분석하여 네트워크 자산에 발생할 수 있는 위험의 가능성을 찾아내고, 정량적인 위험수준을 평가하는 시스템을 제안한다. 또한, 실험을 통해 시스템의 성능수준을 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2801-2815
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• 2022

With the advent and realization of Software Defined Network (SDN) architecture, many organizations are now shifting towards this paradigm. SDN brings more control, higher scalability, and serene elasticity. The SDN spontaneously changes the network configuration according to the dynamic network requirements inside the constrained environments. Therefore, a monitoring system that can monitor the physical and virtual entities is needed to operate this type of network technology with high efficiency and proficiency. In this manuscript, we propose a real-time monitoring system for data collection and visualization that includes the Prometheus, node exporter, and Grafana. A node exporter is configured on the physical devices to collect the physical and virtual entities resources utilization logs. A real-time Prometheus database is configured to collect and store the data from all the exporters. Furthermore, the Grafana is affixed with Prometheus to visualize the current network status and device provisioning. A monitoring system is deployed on the physical infrastructure of the KOREN topology. Data collected by the monitoring system is further pre-processed and restructured into a dataset. A monitoring system is further enhanced by including machine learning techniques applied on the formatted datasets to identify the elephant flows. Additionally, a Random Forest is trained on our generated labeled datasets, and the classification models' performance are verified using accuracy metrics.

• 전자공학회논문지A
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• 제30A권3호
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• pp.1-15
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• 1993

In this paper, we propose over-reporting avoidance scheme which avoids congestion of network traffics by adjusting managed system's over-reporting, on the OSI network management model which reports events from managed system to managing system. In case of reporting events from managed system to managing system, management traffic concentration occurs, and it causes over-loading on the managing system and congestion on the network. This scheme takes advantage of feedback from managing system to managed system. Managed system transmits event reports as much as maximum event pertime allocated to itself to managing system, and it sets it's management variables to LOCK state and stops event reports as Threshold time is reached. At the time, managing system directs event reports again by using M-set primitive with referring it's status. With this scheme, distributed processing, dynamic network adaptation, convergence of optimal operation point is possible. In addition to it, a fairness is assured. In order to detect characteristics of the Unary feedback over-reporting avoidance scheme. It is observed a control capability of the event reporting and fairness of each nodes through measuring. ThresholdTime value. It is measured a number of mean activating nodes and maintained time of LOCK state according to event reporting load, and also measured lost ratio of management packet, queuing delay in managing system, and goodput to observe effects of general packet load. Binary feedback scheme. Unary feedback overreporting avoidance scheme and raw scheme on the OSI network management system each are compared and analyzed, and finally proved that the scheme proposed in this study performs better.