• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.551-562
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• 2000

Content-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. GContent-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. Generally, the query image produced by a user is different from the intended target image. To overcome this problem, many image retrieval systems use the spatial relationships of the objects, instead of pixel coordinates of the objects. In this paper, a query-converting algorithm for an image retrieval system, which uses the spatial relationship of every two objects as an image feature, is proposed. The proposed algorithm converts the query image into a graph that has the minimum number of edges, by eliminating every transitive edge. Since each edge in the graph represents the spatial relationship of two objects, the elimination of unnecessary edges makes the retrieval process more efficient. Experimental results show that the proposed algorithm leads the smaller number of comparison in searching process as compared with other algorithms that do not guarantee the minimum number of edges.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2383-2389
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• 2011

Ubiquitous applications require hybrid continuous query processing which processes both on-line data stream and spatial data in the disk. In the hybrid continuous spatial query processing, disk access costs for the high-volume spatial data should be minimized. However, previous indexing methods cannot reduce the disk seek time, because it is difficult that the data are stored in contiguity with others. Also, existing methods for the space-filling curve considering data cluster have the problem which does not cluster available data for queries. Therefore, we propose the region storage structure for efficient data access in hybrid continues spatial query processing. This paper shows that there is an obvious improvement of query processing costs through the contiguous data storing method and the group processing for user queries based on the region storage structure.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.229-236
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• 2009

Sensors are deployed to gather physical, environmental data in sensor networks. Depending on scenarios, it is often assumed that it is difficult for batteries to be recharged or exchanged in sensors. Thus, sensors should be able to process users' queries in an energy-efficient manner. This paper proposes a spatial query processing scheme- Minimum Bounding Area Based Scheme. This scheme has a purpose to decrease the number of outgoing messages during query processing. To do that, each sensor has to maintain some partial information locally about the locations of descendent nodes. In the initial setup phase, the routing path is established. Each child node delivers to its parent node the location information including itself and all of its descendent nodes. A parent node has to maintain several minimum bounding boxes per child node. This scheme can reduce unnecessary message propagations for query processing. Finally, the experimental results show the effectiveness of the proposed scheme.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.362-372
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• 2004

One of the most difficult problems in building a distributed GIS lies in the heterogeneity of spatial databases. In particular, positional mismatches between spatial databases, which arise due to several reasons, may incur incorrect query results. They result in unreliable outputs of query processing. One simple solution is to correct positional data in spatial databases at each site, according to the most accurate one. This solution is however not practical in cases where the autonomy of each database should be respected. In this paper, we propose a spatial query processing method without correcting positional data in each spatial database. Instead of correcting positional data, we dynamically transform a given query region or position onto each space where spatial objects of each site are located. Our proposed method is based on an elastic transformation method by using delaunay triangulation. Accuracy of this method is proved mathematically, and is confirmed by an experiment. Moreover, we implemented using common use database system for usefulness verification of this method.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.588-591
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• 2008

본 논문은 Data mining에서 선호도 분석 등에 사용되는 Skyline Query[2] 중 자료의 속성에 spatial한 성질이 있을 때 사용할 수 있는 Spatial Skyline Query[3] 문제에 대해 연구한다. 우선 Spatial Skyline 집합을 추출하기 위한 기존의 알고리즘의 문제점을 짚어보고 보다 개선된 알고리즘을 제시한다. 또한 전체 Spatial Skyline 집합이 아닌 그 중 더 의미 있을 수 있는 부분 집합을 좀 더 빠른 시간 복잡도에 구하는 방법 또한 제시한다.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.521-531
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• 2003

Multi-level geographic data can be mainpulated by a window query such as a zoom operation. In order to handle multi-level geographic data efficiently, a spatial indexing method supporting a window query is needed. However, the conventional spatial indexing methods are not efficient to access multi-level geographic data quickly. To solve it, other a few spatial indexing methods for multi-level geographic data are known. However these methods do not support all types of multi-level geographic data. This paper presents a new efficient spatial indexing method, the MLR-tree for window query of multi-level geographic data. The MLR-tree offers both high search performance and no data redundancy. Experiments show them. Moreover, the MLR-tree supports all types of multi-level geographic data.

• Spatial Information Research
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• v.18 no.5
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• pp.93-105
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• 2010

Spatial neighborhoods are spaces which are relate to target space. A 3D spatial query which is a function for searching spatial neighborhoods is a significant function in spatial analysis. Various methodologies have been proposed in related these studies, this study suggests an adjacent based methodology. The methodology of this paper implements topological data for represent a adjacency via using network based topological data model, then apply modifiable Dijkstra's algorithm to each topological data. Results of ordering analysis about an adjacent space from a target space were visualized and considered ways to take advantage of. Object of this paper is to implement a 3D spatial query for searching a target space with a adjacent relationship in 3D space. And purposes of this study are to 1)generate adjacency based 3D network data via network based topological data model and to 2)implement a 3D spatial query for searching spatial neighborhoods by applying Dijkstra's algorithms to these data.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.93-107
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• 2007

In this paper, an adaptive range aggregation spatial index method is proposed for spatial range query in ubiquitous sensor networks. As the ubiquitous sensor networks are the new information-oriented paradigm, many energy efficient spatial range query methods in ubiquitous sensor networks environment are studied vigorously. In sensor networks, users can monitor environment scalar data such as temperature and humidity during user defined time and spatial ranges. In order to execute spatial range query efficiently, rectangle based index methods are proposed, such as SPIX. But they define the return path as the opposite of its query transmit path. However, the sensor nodes in queried ranges are closed to each other, they can't aggregate the sensed value in a queried range because their query transmission paths are different. As a result, the previous methods waste energy unnecessarily to aggregate sensing data out of the queried range. In this paper, an adaptive aggregation index method is proposed that can aggregate values in a user defined range adaptively by using its neighbor information. It is shown that sensor power is saved efficiently by using the proposed method over the performance evaluation.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.138-143
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• 2002

This paper describes a framework for extending GIS databases to support moving object data type and query language. The rapid progress of wireless communications, positioning systems, and mobile computing devices have led location-aware applications to be essential components for commercial and industrial systems. Location-aware applications require GIS databases system to represent moving objects and to support querying on the motion properties of objects. For example, fleet management applications may require storage of information about moving vehicles. Also, advanced CRM(Customer Relationship Management) applications may require to store and query the trajectories of mobile phone users. In this trend, maintaining consistent information about the location of continuously moving objects and processing motion-specific queries is challenging problem. We formally define a data model and query language for mobile objects that includes complex evolving spatial structure, and propose core algebra to process the moving object query language. Main profit of proposed moving objects query language and algebra is that proposed model can be constructed on the top of GIS databases.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.45-56
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• 2010

This paper suggests constraint data modeling based on constraint data presentation techniques to perform complex spatial database operation naturally. We were able to identify the limitation of extendibility of dimension and non-equal framework via relevant research for former schema of spatial database and query processing. Therefore we described generalized tuple of spatial data and the definition of suggested constraint data modeling. Also we selected MLPQ/PReSTO tool among constraint database prototype and compare standard functionality of ARC/VIEW. Then we design scenario for spatial operation using MLPQ/PReSTO and we suggested application effect after query processing. Based on above explanation, we were able to identify that we can process spatial data naturally and effectively using simple constraint routine on same framework via constraint data modeling.