• International Journal of Contents
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• v.1 no.1
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• pp.50-58
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• 2005

Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.32-41
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• 1999

In spatial database system, the nearest neighbor query occurs frequently and requires the processing cost higher than other spatial queries do. The number of nodes to be searched in the index can be minimized for optimizing the cost of processing the nearest neighbor query. The optimal search distance is pr9posed for the measurement of a search distance to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we prove properties of the optimal search distance in N-dimensional. We show through experiments that the performance of query processing of our method is superior to other method using maximum search distance.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1025-1030
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• 2004

In multimedia database systems, the k nearest neighbor query occurs frerluently and requires the processing cost higher than other spatial queries do. The numberof searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the k nearest neighbor query. In this paper, we propose the search distance which can reduce the computation time of the optimal search distance.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.1-8
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• 2023

Smart IoT over high speed network and high performance smart devices explodes the ubiquitous services and applications. Nearest Neighbor(NN) query is one of the important type of queries that have to be supported for ubiquitous information services. In order to process efficiently NN queries in the wireless broadcast environment, it is important that the clients determine quickly the search space and filter out NN from the candidates containing the search space. In this paper, we propose a hybrid index of Voronoi and grid partition to provide quick search space decision and rapid filtering out NN from the candidates. Grid partition plays the role of helping quick search space decision and Voronoi partition providing the rapid filtering. We show the effectiveness of the proposed index by comparing the existing indexing schemes in the access time and tuning time. The evaluation shows the proposed index scheme makes the two performance parameters improved than the existing schemes.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.203-209
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• 2012

Recently, k-nearest neighbors query methods based on wireless broadcasting environment are actively studied. The advantage of wireless broadcasting environment is the scalability that enables collective query processing for unspecified users connected to the server. However, in case existing k-NN query is applied in wireless broadcasting environment, there can be a disadvantage that backtracking may occur and consequently the query processing time is increasing. In this paper proposes a hierarchical bitmap-based spatial index in order to efficiently process the k-NN queries in wireless broadcasting environment. HBI reduces the bitmap size using such bitmap information and tree structure. As a result, reducing the broadcast cycle can reduce the client's tuning time and query processing time. In addition, since the locations of all the objects can be detected using bitmap information, it is possible to tune to necessary data selectively. For this paper, a test was conducted implementing HBI to k-NN query and the proposed technique was proved to be excellent by a performance evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2919-2925
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• 2014

Because of the rapid growth of mobile communication and wireless communication, Location-based services are handled in many applications. So, the management and analysis of spatio-temporal data are a hot issue in database research. Index structure and query processing of such contents are very important for these applications. This paper addressees algorithms that make index structure by using Douglas-Peucker Algorithm and process nearest neighbor search query efficiently on moving objects trajectories. We compare and analyze our algorithms by experiments. Our algorithms make small size of index structure and process the query more efficiently.

• Journal of Wetlands Research
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• v.16 no.1
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• pp.103-112
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• 2014

Area average rainfall estimation is important to determine the exact amount of the available water resources and the essential input data for rainfall-runoff analysis. Like that, the necessary criterion for accurate area average rainfall estimate is the uniform spatial distribution of raingauge network. In this study, we suggest the spatial distribution evaluation methodology of raingauge network to estimate better area average rainfall and after the suggested method is applied to Han River and Geum River basin. The spatial distribution of rainfall network can be quantified by the nearest neighbor index. In order to evaluate the effects of the spatial distribution of rainfall network by each basin, area average rainfall was estimated by arithmetic mean method, the Thiessen's weighting method and estimation theory for 2013's rainfall event, and evaluated the involved errors by each cases. As a result, it can be found that the estimation error at the best basin of spatial distribution was lower than the worst basin of spatial distribution.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.269-280
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• 2004

The Pyramid-Technique is based on mapping n-dimensional space data into one-dimensional data and expresses it as a B+-tree. By solving the problem of search time complexity the pyramid technique also prevents the effect of "phenomenon of dimensional curse" which is caused by treatment of hypercube range query in n-dimensional data space. The SPY-TEC applies the space division strategy in pyramid method and uses spherical range query suitable for similarity search so that Improves the search performance. However, nearest neighbor query is more efficient than range query because it is difficult to specify range in similarity search. Previously proposed index methods perform well only in the specific distribution of data. In this paper, we propose an efficient searching technique for nearest neighbor object using PdR-Tree suggested to improve the search performance for high dimensional data such as multimedia data. Test results, which uses simulation data with various distribution as well as real data, demonstrate that PdR-Tree surpasses both the Pyramid-Technique and SPY-TEC in views of search performance.rformance.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.632-642
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• 2001

The nearest neighbor query is an important operation widely used in multimedia databases for finding the object that is most similar to a given object Most of techniques for processing nearest neighbor queries employ multidimensional indexes for effective indexing of objects. However, the performance of previous multidimensional indexes, which use N-dimensional rectangles or spheres for representing the capsule of the object cluster, deteriorates seriously as th number of dimensions gets higher, In this paper we first point out the fact that the simple representation of capsuler incurs performance degradation in processing nearest neighbor queries. For alleviating this problem,. we propose(1) adopting new axis systems appropriate to a given cluster (2) representing various shapes of capsules by combining rectangles and spheres, and (3) maintaining outliers separately, We also verify the superiority of our approach through performance evaluation by performing extensive experiments.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.68.3-68.3
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• 2016

We analyze the dependence of environment of warped galaxies by using the local background density, Tidal Index and projected distance as measures of the environment. we use galaxies with redshift less than z=0.025 from the Sloan Digital Sky Survey (SDSS) DR7. We selected 345 edge-on galaxies using color images provided by the SDSS DR7 and checked it using isophotal maps. This sample contains 136 warped galaxies, 209 non-warped galaxies. Among warped galaxies, there are 18 strongly warped galaxies which have warp angles larger than 7.5o. We calculated the fractional distributions of galaxies as a function of environmental parameters. All of these parameters show little difference between warped galaxies and non-warped galaxies if we include weakly warped galaxies. However, there is a clear difference in the fractional distributions between the strongly warped galaxies and non-warped galaxies. The fraction of warped galaxies increases with decreasing distance to the nearest neighbor galaxy but It increases with increasing background density and Tidal Index. However, the relationships between warp angles and the three environmental parameters are not strong. The effect of Tidal Index is well distinguished in small, bright galaxies whereas the effects of the background density and the distance to the nearest neighbor galaxy are more pronounced in large, bright galaxies.