• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.90-95
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• 2000

In the Ordered Core Based Tree(OCBT) protocol, a core location is the most important feature to affect the performance. In this paper, the location placement of multiple level cores is studied. The proposed algorithm isthat each node in the network evaluates a sum of shortest path costs from all the other nodes and the entirenetwork is divided into a hierarchy region to have 3-logical level(Small, Medium, Large). The node to have thelowest cost in each S-Region is decided to be a core node. Then, the core nodes in the each S-Region evaluatea sum of shortest path costs from all the other core nodes in the same M-Region. The core node to have thelowest cost is decided to be the upper level core node. Similarly the highest level core node is decided in theL-Region. The proposed algoritthm is compared with conventional two methods to put the core nodes in thenetwork One is the random method to put the core nodes randomly. The other is the center method to locatethe core node at the nearest node from the center of each S-Region and then to locate the highest level corenode at the nearest core node from the center of the entire network. Extensive simulations are performed in theview of mean tree cost and join latency. Simulation results show that the proposed algorithm has betterperformance than random method or center method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.665-683
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• 2011

Wireless sensor networks (WSN) consist of a large amount of sensor nodes distributed in a certain region. Due to the limited battery power of a sensor node, lots of energy-efficient schemes have been studied. Clustering is primarily used for energy efficiency purpose. However, clustering in WSNs faces several unattained issues, such as ensuring connectivity and scheduling inter-cluster transmissions. In this paper, we propose a location-based spiral clustering (LBSC) algorithm for improving connectivity and avoiding inter-cluster collisions. It also provides reliable location aware routing paths from all cluster heads to a sink node during cluster formation. Proposed algorithm can simultaneously make clusters in four spiral directions from the center of sensor field by using the location information and residual energy level of neighbor sensor nodes. Three logical addresses are used for categorizing the clusters into four global groups and scheduling the intra- and inter-cluster transmission time for each cluster. We evaluated the performance with simulations and compared it with other algorithms.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.599-605
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• 2018

Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.424-433
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• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.566-577
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• 2012

In randomly deployed networks, such as sensor networks, an important problem for each node is to discover its neighbor nodes so that the connectivity amongst nodes can be established. In this paper, we consider this problem by incorporating the physical layer parameters in contrast to the most of the previous work which assumed a collision channel. Specifically, the pilot signals that nodes transmit are successfully decoded if the strength of the received signal relative to the interference is sufficiently high. Thus, each node must extract signal parameter information from the superposition of an unknown number of received signals. This problem falls naturally in the purview of random set theory (RST) which generalizes standard probability theory by assigning sets, rather than values, to random outcomes. The contributions in the paper are twofold: First, we introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms; such an introduction is necessary for the accurate assessment of how an algorithm performs. Secondly, given the double uncertainty of the environment (that is, the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters), we adopt the viewpoint of RST and demonstrate its advantage relative to classical matched filter detection method.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.7
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• pp.424-424
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• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1164-1172
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• 2007

To solve scalability problem in the ZigBee Network, this paper presents a new mesh routing protocol for ZigBee, called ZigBee Cluster Label (ZiCL). ZiCL divides the ZigBee network into one or more logical clusters and then assigns a unique Cluster Label to each cluster so that it discovers a route of a destination node based on Cluster Label. When a node collects new Cluster Label information of a destination node according to discovery based on Cluster Label, ZiCL encourages nodes with the same Cluster Label to share the information. Consequen tly, it contributes on reducing numerical potential route discoveries and improving network performances such as routing overhead, end-to-end delay, and packet delivery ratio. Simulation results using NS-2 show ZiCL performs well.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1433-1442
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• 1996

Data distribution of SPMD(Single Program Multiple Data) pattern is one of main features of HPF (High Performance Fortran). This paper describes design is sues for such data distribution and its efficient execution model on TICOM IV computer, named SPAX(Scalable Parallel Architecture computer based on X-bar network). SPAX has a hierarchical clustering structure that uses distributed shared memory(DSM). In such memory structure, it cannot make a full system utilization to apply unanimously either SMDD(shared Memory Data Distribution) or DMDD(Distributed Memory Data Distribution). Here we propose another data distribution model, called DSMDD(Distributed Shared Memory Data Distribution), a data distribution model based on hierarchical masters-slaves scheme. In this model, a remote master and slaves are designated in each node, shared address scheme is used within a node and message passing scheme between nodes. In our simulation, assuming a node size in which system performance degradation is minimized,DSMDD is more effective than SMDD and DMDD. Especially,the larger number of logical processors and the less data dependency between distributed data,the better performace is obtained.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.724-725
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• 2011

현재 전력설비는 디지털 변전소 국제 표준 통신 규격인 IEC61850을 채택하고 있는 추세에 있으며, 온라인 GIS (Gas Insulated Switchgear) 예방진단 시스템의 고객 요구 사양도 IEC61850을 이용하여 외부 인터페이스가 가능한 구조를 포함하고 있다. 본 연구에서는 온라인 GIS 예방진단 시스템에 대한 IEC61850 모델을 제시하고 Logical Node를 구성하였다. 부분방전 데이터를 비롯한 실시간 감시 데이터는 IEC61850의 fixed report 기능으로 구현하였고, 부분방전 이벤트 및 이력 정보는 파일로 저장하여 IEC61850의 file transfer 기능으로 구현하였다. 기능 검증을 위하여 온라인 GIS 예방진단 시스템 서버에 IEC61850 서버 기능을 탑재하였고 상용의 IEC61850 클라이언트 소프트웨어를 이용하여 데이터 통신 및 파일 전송 기능을 확인하였다

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.332-334
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• 2008

최근 IEC는 변전소 자동화 시스템의 국제표준인 IEC 61850을 기반으로 하는 풍력 발전단지의 원격 감시 제어를 위한 통신시스템 표준인 IEC 61400-25를 발표하였다. 본 논문에서는 가상의 풍력 발전 통신 시스템을 SISCO 사의 "MMS-EASE Lite" 개발 도구를 사용하여 풍력 발전의 원격 감시 제어를 위한 서버와 클라이언트 간의 MMS 통신 서비스를 구현한다. 또한 IEC 61400-25 기반의 웹 인터페이스 구현을 위하여 뛰어난 확장성을 가진 XML(Extensible Markup Language, 확장성 생성 언어) 언어를 사용하여 풍력 발전단지의 논리 노드(Logical Node)를 구성하고, 원격 감시를 위한 웹 인터페이스를 구현하는 방법을 제안하고 실제 인터넷 환경에서 검증한다.