• Journal of KIISE:Computer Systems and Theory
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• v.26 no.12
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• pp.1447-1457
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• 1999

본 논문에서는 일반적인 네트워크에서 적응력 있는(adaptive) 분산형 시스템 레벨 결함 진단을 위한 분할 기법을 제안한다. 적응력 있는 분산형 시스템 레벨 결함 진단 기법에서는 시스템의 형상이 변경될 때마다 시험 할당 알고리즘이 수행되므로 적응력 없는 결함 진단 기법에 비하여 결함 감지를 위한 시험의 갯수를 줄일 수 있다. 기존의 시험 할당 알고리즘들은 전체 시스템을 대상으로 하는 비분할(non-partitioning) 방식을 이용하였는데, 이 기법은 불필요한 과다한 메시지를 생성한다. 본 논문에서는 전체 시스템을 이중 연결 요소(biconnected component) 단위로 분할한 후, 시험 할당은 각 이중 연결 요소 내에서 수행한다. 이중 연결 요소의 관절점(articulation point)의 특성을 이용하여 각 시험 할당에 필요한 노드의 수를 줄임으로서, 비분할 기법들에 비해 초기 시험 할당에 필요한 메시지의 수를 감소시켰다. 또한 결함이 발생한 경우나 복구가 완료된 경우의 시험 재 할당은 직접 영향을 받는 이중 연결 요소내로 국지화(localize) 시켰다. 본 논문의 시스템 레벨 결함 진단 기법의 정확성을 증명하였으며, 기존 비분할 방식의 시스템 레벨 결함 진단 기법과의 성능 분석을 수행하였다.Abstract We propose an adaptive distributed system-level diagnosis using partitioning method in arbitrary network topologies. In an adaptive distributed system-level diagnosis, testing assignment algorithm is performed whenever the system configuration is changed to reduce the number of tests in the system. Existing testing assignment algorithms adopt a non-partitioning approach covering the whole system, so they incur unnecessary extra message traffic and time. In our method, the whole system is partitioned into biconnected components, and testing assignment is performed within each biconnected component. By exploiting the property of an articulation point of a biconnected component, initial testing assignment of our method performs better than non-partitioning approach by reducing the number of nodes involved in testing assignment. It also localizes the testing reassignment caused by system reconfiguration within the related biconnected components. We show that our system-level diagnosis method is correct and analyze the performance of our method compared with the previous non-partitioning ones.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.53-60
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• 2020

The bogies of railway vehicles are one of the most critical components for service. Fatigue defects in the bogie can be initiated for various reasons, such as material imperfection, welding defects, and unpredictable and excessive overloads during operation. To prevent the derailment of a railway vehicle, it is necessary to evaluate and detect the defect of a connection weldment between the car body and bogie accurately. The safety of the bogie weldment was checked using an ultrasonic test, and it is necessary to determine the occurrence of defects using a learning method. Recently, studies on deep learning have been performed to identify defects with a high recognition rate with respect to a fine and similar defect. In this paper, the databases of weldment specimens with artificial defects were constructed to detect the defect of a bogie weldment. The ultrasonic inspection using the wedge angle was performed to understand the detection ability of fatigue cracks. In addition, the convolutional neural network was applied to minimize human error during the inspection. The results showed that the defects of connection weldment between the car body and bogie could be classified with more than 99.98% accuracy using CNN, and the effectiveness can be verified in the case of an inspection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12A
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• pp.975-982
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• 2003

A connection admission control scheme is proposed that can seamlessly support QoS in face of handoff in mobile packet networks. The proposed scheme is based on the adaptive time-selective bandwidth reservation with the reduced signaling and computational overhead. The reservation parameters are adjusted dynamically to cope with user mobility. Throughout the computer simulations, the performance of the proposed scheme is evaluated. As a result, it is shown that the proposed scheme reduces handoff call blocking probability remarkably, while other parameters (new call blocking probability and bandwidth utilization efficiency) are slightly deteriorated.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.65-66
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• 2007

본 논문에서는 주어진 블로그 연결망의 정보 중시 성향과 친분 중시 성향의 정도를 판정하는 방안에 관하여 논의한다. 먼저, 데이터 마이닝 기법의 하나인 분류(classification)를 이용하여 블로그 연결망의 기본 단위인 관계 성향의 정도를 판정하고, 그 결과를 이용하여 주어진 연결망의 전체 성향의 정도를 판정한다. 또한, 블로그 연결망의 규모에 따라 성향의 정도가 좌우되는 문제를 해결하기 위한 기법을 제안한다. 실제 블로그 데이터를 이용한 실험을 통하여 제안하는 방안의 우수성을 검증한다.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.540-544
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• 2006

사용자가 자료를 직접 송수신하기 위한 P2P 네트워크 환경에는 하이브리드 P2P 네트워크 환경과 순수 P2P 네트워크 환경이 있다. 하이브리드 P2P 네트워크 환경에서 모든 피어들은 서버에 연결되어 있기 때문에, 피어들 간 메시지를 전달할 수 없는 네트워크 고립 상태가 발생되지 않는다. 그러나 순수 P2P 네트워크 환경에서 각 피어들은 서버 없이 서로 직접 연결하여 다른 피어로부터 서비스를 제공받기 때문에, 각 피어들 간의 통신을 중재하는 특정 피어가 종료할 경우 대상 피어들과의 통신이 단절되는 네트워크 고립 현상이 발생될 수 있다. 본 논문에서는 이러한 문제점을 해결하기 위해 각 피어들로 하여금 인접한 피어로부터 IP 주소를 얻어 목록으로 관리하게 함으로써, 연결된 피어가 종료할 경우 목록으로 유지된 IP 주소로 연결하여 네트워크 그룹에 지속적으로 참여할 수 있게 하는 기법을 연구하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.65-66
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• 2016

최근 과학의 발달로 사물에 대한 다양한 센서와 통신 기능을 부여하여 사람 대 사람 또는 사물 대 사물 서로 교류하는 개념인 IoT(Internet of Things)가 화제이다. IoT를 구성하는 요소 중에 하나인 Wireless Sensor Networks(WSN)에 대한 연구를 한다. WSN은 전쟁터의 정찰과 같은 가혹한 환경에 적용되며 이를 구성하는 센서는 제한된 자원을 가지고 있기 때문에 고장에 취약한 특성이 있다. 따라서 상호 통신이 외부 요인에 의해 단절된 네트워크의 연결 복구에 대한 연구가 지속적으로 이루어지고 있다. 본 논문에서는 이러한 WSN 네트워크의 연결 복구 방식, 연결 복구기법 및 알고리즘의 연구 동향에 대해서 서술한다.

• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.113-120
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• 2010

Even networks were introduced as a class of fault-tolerant multiprocessor networks and analyzed so many useful properties and algorithms such as simple routing algorithms, maximal fault tolerance, node disjoint path. Introduced routing algorithms and node disjoint path algorithms are proven to be optimal. However, it has not been introduced to constructing scheme for edge-disjoint spanning trees in even networks. The design of edge-disjoint spanning trees is a useful scheme to analyze for measuring the efficiency of fault tolerant of interconnection network and effective broadcasting. Introduced routing algorithm or node disjoint path algorithm are for the purpose of routing or node disjoint path hence they are not applicable to constitute edge disjoint spanning tree. In this paper, we show a construction algorithm of edge-disjoint spanning trees in even network $E_d$.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.3
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• pp.259-265
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• 2009

This paper studies the Element Connectivity Parameterization Method(ECP method) for topology optimization considering dynamic compliance. The previous element density based topology optimization method interpolates Young's modulus with respect to design variables defined in each element for topology optimization. Despite its various applications, these element density based methods suffer from numerical instabilities for nonlinear structure and multiphysics systems. To resolve these instabilities, recently a new numerical method called the Element Connectivity Parameterization(ECP) Method was proposed. Unlike the existing design methods, the ECP method optimizes the connectivities among plane or solid elements and it shows some advantages in topology optimization for both nonlinear structure and multiphysics systems. In this study, the method was expanded for topology optimization for the dynamic compliance by developing a way to model the mass matrix in the framework of the ECP method.

• Korean Journal of Construction Engineering and Management
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• v.15 no.6
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• pp.44-52
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• 2014

Generally, the most difficult works at scheduling are to estimate the duration of activities and linkages between them because the possibility that the duration and linkages could be exposed to the uncertainties is so high. When estimating a project duration, therefore, the probabilistic estimation of the duration as well as the probabilistic estimation of the linkages between activities should be considered concurrently. The PERT that is one of the most popular techniques applied for the probabilistic estimation of a project duration can not consider the uncertainties of the linkages because it only estimates the probabilistic duration limited to 'FS0' relationship. The purpose of this study is to propose the new method "PLET" for stochastically estimating the project duration based on the probabilistic estimation of the BDM's relationships, and also provide more wide and various probabilsitic information about the project duration by it.

• Journal of Advanced Navigation Technology
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• v.17 no.4
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• pp.435-441
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• 2013

This paper proposes a neural net based-predictive connection admission control (CAC) scheme for multiclass users in wireless cognitive radio networks. We classifies cognitive users(cu) into real and non real time services, and then permit only real time services to reserve the demanded resource for spectrum handoff in guard channel for provisioning the desired QoS. Neural net is employed to predict primary user's arrival on time and demanded channels. Resource scheduling scheme is based on $C_IA$(cognitive user I complete access) shown in this paper. For keeping primary users from interference, the CAC is performed on only cognitive user not primary user. Simulation results show that our schemes can guarantee the desired QoS by cognitive real time services.