• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2329-2336
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• 2010

Hierarchical tree routing is a inefficient routing method of transmitting data in a wireless sensor network. Zigbee routing which is made to improve inefficiency of the hierarchical tree routing only fulfills the tree routing when a destination node don't exists in neighbor nodes of a router. We suggest a TFSR algorithm that is improved more than the zigbee routing. The TFSR algorithm generates a family set included a parent node and child nodes and over of a destination node, and uses this information. According to simulation results, the TFSR algorithm reduce routing costs over 30 percent in comparison with the hierarchical tree routing and the zigbee routing.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.637-647
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• 2018

In this paper, we propose a method to search candidates of network reconfiguration to restore distribution system with distributed energy resources using a level-based tree search algorithm. First, we introduce a method of expressing distribution network with distributed energy resources for fault restoration, and to represent the distribution network into a simplified graph. Second, we explain the tree search algorithm, and introduce a method of performing the tree search on the basis of search levels, which we call a level-based tree search in this paper. Then, we propose a candidate search method for fault restoration, and explain it using an example. Finally, we verify the proposed method using computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.363-371
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• 1994

This thesis investigates an expert system(ES) to propose fault restoration plan by utilizing tree search strategies. In order to cope with an extensive amount of data and frequent breaker switching operations in distribution systems, the database of system configuration is constructed by using binary trees. This remarkably enhances the efficiency of search algorithm and makes the proposed ES easily adaptable to system changes due to switching operations. The rule-base is established to fully utilize the meris of tree-structured database. The inferring strategy is developed mainly based on the best-first search algorithm to increase computation efficiency. The proposed ES has been implemented to efficiently deal with large distribution systems by reducing computational burden remarkably compared with the conventional ES's.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.12
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• pp.1242-1251
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• 1991

This paper is to investigate the tree growth phenomena and the characteristics of $\varepsilon$' and tan$\delta$ for the effect of ultrasonic wave on polymer insulation material. The conclusions are as follows. 1) As the pressure amplitude of ultrasonic wave is larger and its irradiated time is longer, tree inception voltage and its breakdown voltage in specimen are smaller, and tree growing is faster. 2) As the irradiated quantity of ultrasonic wave is more increased, the value of tan$\delta$ is larger, but the value of $\varepsilon$' is almost constant. 3) The effect by the pressure amplitude of ultrasonic wave is greater than that by its irradiated time on the insulation characteristics of polymer material.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2292-2298
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• 2009

In this paper, the lossy image compression algorithm using the quad tree and the bandlets is proposed. The proposed algorithm transforms input images by the discrete wavelet transform (DWT) and represents the geometrical structures of high frequency bands using the bandlets with a 8 block- size. In addition, the proposed algorithm searches the position information of the significant coefficients by using the quad tree algorithm and computes the magnitude and the sign information of the significant coefficients by using the Embedded Image Coding using Zerotrees of Wavelet Coefficients (EZW) algorithm. The compression result by using the quad tree algorithm improves the PSNR performance of high frequency images up to 1 dB, compared to that of JPEG-2000 algorithm and that of S+P algorithm. The PSNR performance by using DWT and bandlets improves up to 7.5dB, compared to that by using only DWT.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.5
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• pp.213-221
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• 2002

In order to improve the reliability of XLPE cables, it is necessary to find the useful diagnostic parameter according to long term aging. This paper described the change of partial discharge(PD) phase Properties of XLPE cable insulation with branch type electrical tree degradation. for long term aging. To understand the PD Properties with $\phi$ -q-n distributed shape of XLPE insulation, specimens were prepared by 22.9㎸ distribution cable and made in a type of block(16${\times}$16${\times}$3[mm]). Ogura needles having tip radius of l0${\mu}{\textrm}{m}$ were inserted into each block pieces. The measuring system was consisted of PD detector, digitizer for digital conversion, VXI system for signal processing. The PD properties of the specimens were measured from initiation of tree to breakdown and their characteristics were analyzed. We analyzed the relationship between electrical properties(PD Quantity, PD initiation angle, PD extinction angle, PD occurrence angle : (PD extinction angle - PD initiation angle)) and the normalized aging rate. We found PD parameter, PD initiation angle and occurrence angle, which are a useful diagnostic parameter in estimating the branch type electrical tree for XLPE insulation condition.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.128-128
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• 2004

• Journal of Communications and Networks
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• v.18 no.5
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• pp.699-712
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• 2016

Recently, greedy algorithm has received much attention as a cost-effective means to reconstruct the sparse signals from compressed measurements. Much of previous work has focused on the investigation of a single candidate to identify the support (index set of nonzero elements) of the sparse signals. Well-known drawback of the greedy approach is that the chosen candidate is often not the optimal solution due to the myopic decision in each iteration. In this paper, we propose a tree search based sparse signal recovery algorithm referred to as the tree search matching pursuit (TSMP). Two key ingredients of the proposed TSMP algorithm to control the computational complexity are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In numerical simulations of Internet of Things (IoT) environments, it is shown that TSMP outperforms conventional schemes by a large margin.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.183-186
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• 2007

Faster, safer and cheaper mailing of the postal matter is essential for surviving in the competitive market of home-delivery service. The Steiner tree connects points minimally in geometrical way and has been used in the distribution system optimization and optimal routing of the transmission lines of the electric power system. This paper proposes a method to select the optimal location of mail distribution center that minimally connect the local mail center of some major cities using the Steiner tree theorem.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.98-103
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• 2000

This paper suggests a method to recognize the various defect patterns of a cold mill strip using a binary decision tree automatically constructed by a genetic algorithm(GA). In classifying complex patterns with high similarity like the defect patterns of a cold mill stirp, the selection of an optimal feature set and an appropriate recognizer is important to achieve high recognition rate. In this paper a GA is used to select a subset of the suitable features at each node in the binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes using a linear decision function. This process is repeated at each node until all the patterns are classified into individual classes. In this way, the classifier using the binary decision tree is constructed automatically. After constructing the binary decision tree, the final recognizer is accomplished by having neural network learning sits of standard patterns at each node. In this paper, the classifier using the binary decision tree is applied to the recognition of defect patterns of a cold mill strip, and the experimental results are given to demonstrate the usefulness of the proposed scheme.