• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1248-1257
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• 2014

Overhead transmission lines are crucial components in power transmission systems. Well-designed maintenance strategy for overhead lines is required for power utilities to minimize operating costs, while improving the reliability of the power system. This paper presents a maintenance priority index (MPI) of overhead lines for a reliability centered approach. Proposed maintenance strategy is composed of a state index and importance indices, taking into account a transmission condition and importance in system reliability, respectively. The state index is used to determine the condition of overhead lines. On the other hand, the proposed importance indices indicate their criticality analysis in transmission system, by using a load effect index (LEI) and failure effect index (FEI). The proposed maintenance method using the MPI has been tested on an IEEE 9-bus system, and a numerical result demonstrates that our strategy is more cost effective than traditional maintenance strategies.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.55-62
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• 2009

Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.4
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• pp.343-355
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• 2001

The choice of map projection method is depend on the desired map purpose because there is no best projection for maps. Previous projection decisions for published paper maps are not necessarily the right decisions for corresponding digital maps. The map grid and index system is simpler than projection system but it can be easily understanded by general users. In this study, through the study for the grid and index systems of the digital and paper map in our and other countries, I suggested the improvement plan on the problems of our digital map. New grid and index system of this paper are presented on behalf of digital geospatial data which as digital topographic map, digital elevation model and other digital maps.

• Journal of KIISE
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• v.43 no.5
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• pp.590-595
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• 2016

In this study, we propose an efficient method for monitoring continuous top-k queries. In contrast to the conventional top-k queries, the presented top-k query considers both spatial and non-spatial attributes. We proposed a novel main-memory based grid access method, called Bit-Vector Grid Index (BVGI). The proposed method quickly identifies whether the moving objects are included in some of the grid cell by encoding a non-spatial attribute value of the moving object to bit-vector. Experimental simulations demonstrate that the proposed method is several times faster than the previous method and uses considerably less memory.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.107-117
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• 2020

With the recent development of autonomous vehicles, various sensors installed in vehicles have become common, and big data generated from those sensors is increasingly being used in the transportation field. In this study, we proposed a grid index method to efficiently process real-time vehicle sensing big data and public data such as road weather. The applicability and effect of the proposed grid space division method and grid ID generation method were analyzed. We created virtual data based on DTG data and mapped to the road link based on coordinates. As a result of analyzing the data processing speed in grid index method, the data processing performance improved by more than 2,400 times compared to the existing link unit processing method. In addition, in order to analyze the efficiency of the proposed technology, the virtually generated data was mapped and visualized.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.76-81
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• 2015

Research on top-k query processing algorithms for analyzing big data have been spotlighted recently. However, because existing top-k query processing algorithms do not provide an efficient index structure, they incur high query processing costs and cannot support various types of queries. To solve these problems, we propose a top-k query processing algorithm using a view selection method based on a grid index. The proposed algorithm reduces the query processing time by retrieving the minimum number of grid cells for the query range, by using a grid index-based view selection method. Finally, we show from our performance analysis that the proposed scheme outperforms an existing scheme, in terms of both query processing time and query result accuracy.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.304-314
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• 2005

In this paper, we propose a new phantom protection method for multi-dimensional index structures that uses multi-level grid technique. The proposed mechanism is independent of the types of multi-dimensional index structures, i.e., it can be applied to all types of index structures such as tree-based, file-based and hash-based index structures. Also, it achieves low development cost and high concurrency with low lock overhead. It is shown through various experiments that the proposed method outperforms existing phantom protection methods for multi-dimensional index structures.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.4
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• pp.293-304
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• 2005

In this paper, we research on job migration in a grid computing environment with cactus and MPICH-C2 based on Globus. Our concepts are to perform job migration by finding the site with plenty of computational resources that would decrease execution time in a grid computing environment. The Migration Manager recovers the job from the checkpointing files and restarts the job on the migrated site. To select a migrating site, the proposed method considers system's performance index, cpu's load, network traffic to send migration job tiles and the execution time predicted on a migration site. Then it selects a site with maximal performance gains. By selecting a site with minimum migration time and minimum execution time. this approach implements a more efficient grid computing environment. The proposed method Is proved by effectively decreasing total execution time at the $K\ast{Grid}$.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.4
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• pp.53-62
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• 2006

Two-dimensional steady flowfields generated by transverse injection jets into a supersonic mainstream are numerically simulated. Fine-scale turbulence effects are represented by a k-${\omega}$ SST two-equation closure model which includes $y^+$ effects on the turbulence model. Solution convergence is evaluated by using Grid Convergence Index(GCI), a measure of uncertainty of the grid convergence. Comparison is made with experimental data and other turbulence models in term of surface static pressure distributions, the length of the upstream separation region, and the penetration height. Results indicate that the k-${\omega}$ SST model correctly predicts the mean surface pressure distribution and the upstream separation length for low static pressure ratios. However, the numerical predictions become less consistent with experimental results as the static pressure ratio increases. All these results are taken within 1% error band of grid convergence.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.287-292
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• 2005

The flowfields generated by gaseous slot injection into a supersonic flow at a Mach number of 3.75 and a Reynolds number of $2.07{\times}10^7$ are simulated numerically. Fine-scale turbulence effects are represented by a two-equation(k-w SST model) closure model which includes $y^+$ effects on the turbulence model. Grid convergence index(GCI) is also considered to provide a measure of uncertainty of the grid convergence. Comparison is made with experimental data and other turbulence model in term of surface static pressure distributions, the length of the upstream separation region, and the penetration height. Results indicate that the k-w SST model correctly predicts mean surface pressure distribution and upstream separation length. However, it is also observed that the numerical simulation over predicts the pressure spike and penetration height compared with experimental data. All these results are taken within $1\%$ error band of grid convergence.