• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.365-371
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• 2015

CB tree represents the binary trie by a compact binary sequence. However, retrieval time grows fast since the more keys stored in the trie, longer the binary sequences are. In addition it is inefficient for frequent key insertion/deletion. HCB tree is a hierarchical CB tree consisting of small binary tries. However it can not avoid shift operations and have to scan an additional table to refer child or parent trie. In order to improve retrieval performance and avoid shift operations when keys are inserted or deleted, we in this paper represent each separated trie by a full binary trie and then assign the unique identifier to it. Finally the theoretical evaluations show that both the proposed approach and HCB tree provides better than CB tree for key retrieval. The proposed approach shows the highest performance in case of key insertion/deletion and moreover requires only 71%~89% of storage as compared with CB tree.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.208-210
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• 2005

무선 통신, 유비쿼터스 컴퓨팅의 발달과 인터넷 환경이 널리 보급되면서 이동체의 색인을 위한 연구가 활발히 진행되었다. MV3R-tree 알고리즘은 과거 정보의 검색을 위한 Timestamp 질의와 Interval 질의 모두에 좋은 성능을 보여 주는 색인 기법이다. 그러나 기존의 인덱싱 기법인 3D R-tree에 비해 인덱스의 크기가 1.5배 크고, 삽입 시 재배치 비용이 2배정도 크다. 빈번하게 이동하는 이동체의 정보를 저장한다면 삽입 비용의 증가로 인하여 효율성은 현저하게 떨어진다. 본 논문에서는 노드 삽입 과정에서 아주 작은 변화나 반복적인 움직임 같은 불필요한 이동체의 거리 변화의 정보를 제한하는 방법을 제안한다. 정보를 제한할 임계치 값은 이동체들의 과거 정보를 통해 결정한다. 불필요한 정보를 제거하여 노드 공간의 낭비와 재배치를 횟수를 줄인다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.292-293
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• 2011

보로노이 다면체 기법은 금속비정질재료에서의 20면체 Short-Range order와 같은 원자 구조를 분석하는 가장 유용한 도구 중에 하나이다. 기존의 보로노이 다면체 기법에서는 다면체의 평면은 다른 크기를 가진 원자간 거리의 중간에 위차하였다. 하지만, 이러한 방법은 필연적으로 분석 오차를 발생시킨다. 대안적인 방법으로서 근평면법이라고 불리우는 가중 보로노이법을 사용하면, 원자의 크기의 차이를 고려하여 해석할 수 있다. 본논문에서는 이러한 근평면법을 여러 가지의 성분비를 가진 비정질 재료에 적용하여 기존의 보로노이법과 비교 분석하였다. 결과적으로 보로노이 인덱스, 원자체적 분포, 보로노이 다면체 분포, 20면체의 공간 분포등등에서 기존의 보로노이법은 완전히 잘못된 결과를 보여줄 수도 있다는 것이 발견되었다.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.373-383
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• 2001

The distance join is a spatial join which finds data pairs in the order of distance when associating two spatial data sets. This paper proposes several methods to optimize the adaptive multi-stage distance join, presented in [1]. First, we optimize the sweeping index formula which is used for selecting sweeping axis during plane sweeping. Second, to improve the performance of a priority queue used for maintaining node pairs, we propose to use the maximum distance of a node pair as the second priority of the queue. Moreover, we compare trade-offs in estimating the cut-off distance between under uniformity assumption of data distribution and non-uniformity assumption. The experiments show that the proposed methods greatly improve the performance of the algorithm in CPU cost as well as in I/O cost.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.35-40
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• 2005

Recently, the location based service for moving customers is becoming one of the most important service in mobile communication area and for moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries and to improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structure, which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

• Journal of KIISE
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• v.45 no.3
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• pp.294-302
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• 2018

With the emergence of the new service industry due to the development of information and communication technology, cyber space risks such as personal information infringement and industrial confidentiality leakage have diversified, and the security problem has emerged as a critical issue. In this paper, we propose a behavior-based anomaly detection method that is suitable for real-time and large-volume data analysis technology. We show that the proposed detection method is superior to existing signature security countermeasures that are based on large-capacity user log data according to in-company personal information abuse and internal information leakage. As the proposed behavior-based anomaly detection method requires a technique for processing large amounts of data, a real-time search engine is used, called Elasticsearch, which is based on an inverted index. In addition, statistical based frequency analysis and preprocessing were performed for data analysis, and the DBSCAN algorithm, which is a density based clustering method, was applied to classify abnormal data with an example for easy analysis through visualization. Unlike the existing anomaly detection system, the proposed behavior-based anomaly detection technique is promising as it enables anomaly detection analysis without the need to set the threshold value separately, and was proposed from a statistical perspective.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1696-1704
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• 2008

The conventional hard disk has been the dominant database storage system for over 25 years. Recently, hybrid systems which incorporate the advantages of flash memory into the conventional hard disks are considered to be the next dominant storage systems. Their features are satisfying the requirements like enhanced data I/O, energy consumption and reduced boot time, and they are sufficient to hybrid storage systems as major database storages. However, we need to improve traditional index management schemes based on B-Tree due to the relatively slow characteristics of hard disk operations, as compared to flashmemory. In order to achieve this goal, we propose a new index management scheme called FNC-Tree. FNC-Tree-based index management enhanced search and update performance by caching data objects in unused free area of flash leaf nodes to reduce slow hard disk I/Os in index access processes. Based on the results of the performance evaluation, we conclude that our scheme outperforms the traditional index management schemes.

• Spatial Information Research
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• v.21 no.3
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• pp.45-53
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• 2013

Web GIS, based on the latest web-technology, has evolved to provide efficient and accurate spatial information to users. Furthermore, Web GIS Server has improved the performance constantly to respond user web requests and to offer spatial information service. This research aims to create a designed and implemented Web GIS Server that is named as Nodemap which uses the emergent technology, Node.js, which has been issued for an event-oriented, non-blocking I/O model framework for coding JavaScript on the server development. Basically, NodeMap is Web GIS Server that supports OGC implementation specification. It is designed to process GIS data by using DBMS, which supports spatial index and standard spatial query function. And NodeMap uses Node-Canvas module supported HTML5 canvas to render spatial information on tile map. Lastly, NodeMap uses Express module based connect module framework. NodaMap performance demonstration confirmed a possibility of applying Node.js as a (next/future) Web GIS Server development technology through the benchmarking. Having completed its quality test of NodeMap, this study has shown the compatibility and potential for Node.js as a Web GIS server development technology, and has shown the bright future of internet GIS service.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.12-36
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• 2023

Graph databases, which store different types of data and their relationships modeled as a graph, can be effective in managing and analyzing real estate spatial data linked by complex relationships. However, they are not widely used due to the limited spatial functionalities of graph databases. In this study, we propose a uniform grid-based real estate spatial data management approach using a graph database to respond to various real estate-related spatial questions. By analyzing the real estate community to identify relevant data and utilizing national point numbers as unit grids, we construct a graph schema that linking diverse real estate data, and create a test database. After building a test database, we tested basic topological relationships and spatial functions using the Jackpine benchmark, and further conducted query tests based on various scenarios to verify the appropriateness of the proposed method. The results show that the proposed method successfully executed 25 out of 29 spatial topological relationships and spatial functions, and achieved about 97% accuracy for the 25 functions and 15 scenarios. The significance of this study lies in proposing an efficient data integration method that can respond to real estate-related spatial questions, considering the limited spatial operation capabilities of graph databases. However, there are limitations such as the creation of incorrect spatial topological relationships due to the use of grid-based indexes and inefficiency of queries due to list comparisons, which need to be improved in follow-up studies.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.51-62
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• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries. To improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structures of GALIS architecture,which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.