• Magazine of the Korean Society of Hazard Mitigation
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• v.11 no.1
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• pp.54-64
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• 2011

본 연구에서는 기상청 기상관측소 325개소(기상관서:61개소, 자동기상시스템(AWS):264개소)의 관측자료를 이용하여 우리나라 최근 10년간의 강수 현황, 평년대비 변화 추세, 그리고 전국적 가뭄년도의 강수 특성에 대한 분석을 수행하였다. 최근 10년간의 연강수량은 평년 대비 7.3% 증가하는 추세로서 7월의 경우 평년 대비 25% 증가하나 11월의 경우 34% 감소하여 가뭄과 홍수의 자연재해 발생 위험도가 높아지고 있음을 보여주고 있다. 최근 10년간의 언론보도 조사결과, 가뭄이 발생하지 않은 2003년을 제외하고 매년 지역적 강수부족으로 제한급수가 실시되어져 지역적 강수부족은 매년 존재하고 있음이 확인되었다. 가뭄년도와 비가뭄년도의 월별 강수 변화 분석결과, 최근 20년 전국적 가뭄이 발생한 연도에는 2-5월사이 10년 평균강수량에 못미치는 강수가 발생하고 있음이 나타났고 이 특성을 이용한 누적강수량의 지속적 감시는 가뭄 조기경보 가능성을 보여주고 있다고 사료된다. 이에 관하여 최근 90일 누적 강수량과 댐 수위 상황도를 산출하고 이를 사례분석하여 보았다. 이 방법을 사용할 때 현재(2011년 3월말) 강수부족이 지속된다면 낙동강 중 상류지역에 물부족이 발생 가능성이 높을 것으로 예상된다.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.196-200
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• 2008

Recently, the query processing algorithm in spatial network database (SNDB) has attracted many interests. However, there is little research on route-based query processing algorithm in SNDB. Since the moving objects moves only in spatial networks, the route-based algorithm is very useful for LBS and Telematics applications. In this paper, we analyze In-Route Nearest Neighbor (IRNN) query, which is an typical one of route-based queries, and propose a new IRNN query processing algorithm with time constraint. In addition, we show from our performance analysis that our IRNN query processing algorithm with time constraint is better on retrieval performance than the existing IRNN query processing one.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.199-208
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• 2000

The k-nearest neighbor search query based on similarity is very important for content-based multimedia information retrieval(MIR). The conventional exact k-nearest neighbor search algorithm is not efficient for the MIR application because multimedia data should be represented as high dimensional feature vectors. Thus, an approximate k-nearest neighbor search algorithm is required for the MIR applications because the performance increase may outweigh the drawback of receiving approximate results. For this, we propose a new approximate k-nearest neighbor search algorithm for high dimensional data. In addition, the comparison of the conventional algorithm with our approximate k-nearest neighbor search algorithm is performed in terms of retrieval performance. Results show that our algorithm is more efficient than the conventional ones.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1595-1598
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• 2003

이 논문은 질의와 검색 대상 객체가 모두 이동 객체인 경우, 즉 3 차원 폴리라인(polyline) 형태의 경로를 가지는 객체들 간의 연속(continuous) 최근접 질의 처리에 유용한 기법을 제안한다. 질의경로를 따라 객체를 탐색해가면서 질의에 대한 최근접 정보가 변하는 시점을 찾는 것이 목적인 연속 최근접 질의 처리는 전체 질의 경로에 올바른 최근접 정보 리스트를 제공하지만, 기존의 방법들은 검색 대상 객체가 동적인 경우에 적용되기에는 시간에 따라 움직이는 객체의 위치변화를 처리하지 못하고, 질의 시점과 대상 객체간의 시점을 연관시키기 어렵다는 문제점들을 가지고 있다. 따라서 이 논문에서는 데이터 객체들의 궤적 정보는 STR 트리로 유지하고, 질의 경로 세그먼트와 질의의 시간 인터벌에 포함되는 데이터 객체 세그먼트 모두에 대해 추출시간(sampling time) 선택, 스윕라인(sweep line) 적용, 위치 추정 함수 이용 등의 단계를 처리함으로써, 이 문제를 해결하고 질의 경로 전체에 정확한 최근접 객체 정보 리스트를 제공한다. 제안된 기법은 물류정보시스템, 국방정보시스템, 기상, 교통 등 시공간 이동 객체의 질의를 다루는 시스템에 적용할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.927-930
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• 2010

Recently, continuous k-nearest neighbor query(CkNN) which is defined as a query to find the nearest points of interest to all the points on a given path is widely used in the LBS(Location Based Service) and ITS(Intelligent Transportation System) applications. It is necessary to acquire results quickly in the above applications and be applicable to spatial network databases. This paper proposes a new method to search nearest POIs(Point Of Interest) for moving query objects on the spatial networks. The method produces a set of split points and their corresponding k-POIs as results. There is no order between the POIs. The analysis show that the proposed method outperforms the existing methods.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.19-30
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• 2008

Recently, the query processing algorithm in the field of spatial network database(SNDB) has been attracted by many Interests. But, there is little research on route-based queries. Since the moving objects move only in spatial networks, the efficient route-based query processing algorithms, like in-route nearest neighbor(IRNN), are essential for Location-based Service(LBS) and Telematics application. However, the existing IRNN query processing algorithm has a problem that it does not consider traffic jams in the road network. In this thesis, we propose an IRNN query processing algorithm which considers space restriction. Finally, we show that space-constrained IRNN query processing algorithm is efficient compared with the existing IRNN algorithm.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.492-504
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• 2004

Recently, as growing of interest for LBS(location-based services) techniques, lots of works on moving objects that continuously change their information over time, have been performed briskly. Also, researches for NN(nearest neighbor) query which has often been used in LBS, are progressed variously However, the results of conventional NN Query processing techniques may be invalidated as the query and data objects move. Therefore, they are usually meaningless in moving object management system such as LBS. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet accurate and continuous query processing for moving objects. Our techniques include an Approximate CTNN(ACTNN) technique, which has quick response time, and an Exact CTNN(ECTNN) technique, which makes it possible to search nearest neighbor objects accurately. In order to evaluate the proposed techniques, we experimented with various datasets. Experimental results showed that the ECTNN technique has high accuracy, but has a little low performance for response time. Also the ACTNN technique has low accuracy comparing with the ECTNN, but has quick response time The proposed techniques can be applied to navigation system, traffic control system, distribution information system, etc., and specially are most suitable when both data and query are moving objects and when we already know their trajectory.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.105-114
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• 2009

Recently, location-based services which provides k nearest POIs, e.g., gas stations, restaurants and banks, are essential such applications as telematics, ITS(Intelligent Transport Systems) and kiosk. For this, the Voronoi Diagram k-NN(Nearest Neighbor) search algorithm has been proposed. It retrieves k-NNs by using a file storing pre-computed network distances of POIs in Voronoi diagram. However, this algorithm causes the cost problem when expanding a Voronoi diagram. Therefore, in this paper, we propose an algorithm which generates a matrix of the shortest distance between border points of a Voronoi diagram. The shortest distance is measured each border point to all of the rest border points of a Voronoi Diagram. To retrieve desired k nearest POIs, we also propose a k-NN search algorithm using the matrix of the shortest distance. The proposed algorithms can m inim ize the cost of expanding the Voronoi diagram by accessing the pre-computed matrix of the shortest distances between border points. In addition, we show that the proposed algorithm has better performance in terms of retrieval time, compared with existing works.

• Spatial Information Research
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• v.17 no.2
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• pp.213-222
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• 2009

Finding exclusive closest pairs in road network is very useful to real applications such as, for example, finding a closest pair between a passenger and a nearby taxi in a road network. Few studies, however, have been interested in this problem. To match two close moving objects exclusively, one object must belong to only one result pair. Because moving objects in a road network change their position continuously, it is necessary to monitor closest pair results. In this paper, we propose a methodology to monitor k exclusive closest pairs via a road network. Proposed method only updates the results which are influenced by objects' movement. We evaluated the performance of the proposed method with various real road network data. The results show that our method produces better accuracy than normal batch processing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.126-132
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• 2011

In the application areas of LBS(Location Based Service) and ITS(Intelligent Transportation System), continuous k-nearest neighbor query(CkNN) which is defined as a query to find the nearest points of interest to all the points on a given path is widely used. It is necessary to acquire results quickly in the above applications and be applicable to spatial network databases. It is also able to cope successfully with frequent updates of POI objects. This paper proposes a new method to search nearest POIs for moving query objects on the spatial networks. The method produces a set of split points and their corresponding k-POIs as results with partial order among k-POIs. The results obtained from experiments with real dataset show that the proposed method outperforms the existing methods. The proposed method achieves very short processing time(15%) compared with the existing method.