• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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• pp.223-224
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• 2021

Recently, k-farthest neighbor (kFN) queries have not as much attention as k-nearest neighbor (kNN) queries. Therefore, this study considers moving k-farthest neighbor (MkFN) queries for spatial network databases. Given a positive integer k, a moving query point q, and a set of data points P, MkFN queries can constantly retrieve k data points that are farthest from the query point q. The challenge with processing MkFN queries in spatial networks is to avoid unnecessary or superfluous distance calculations between the query and associated data points. This study proposes a batch processing algorithm, called MOFA, to enable efficient processing of MkFN queries in spatial networks. MOFA aims to avoid dispensable distance computations based on the clustering of both query and data points. Moreover, a time complexity analysis is presented to clarify the effect of the clustering method on the query processing time. Extensive experiments using real-world roadmaps demonstrated the efficiency and scalability of the MOFA when compared with a conventional solution.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (3)
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• pp.229-231
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• 2003

기존에 제시된 ad hoc 라우팅 프로토콜에는 안정성에 대한 부분이 고려되어 있지 않다. 본 논문에서는 기존의 DSR ad hoc 라우팅 프로토콜에 안정성을 접목한 SDSR 라우팅 프로토콜을 제시한다. SDSR은 DSR에 안정성 제공을 위해 abnormal node detector와 neighbor table이라는 것을 추가한다. abnormal node detector는 네트워크 내에 abnormal 노드를 탐지해 네트워크에서 고립시켜 네트워크에 안정성을 제공하고 neighbor table에 있는 priority를 값에 따라 이웃 노드에서 들어온 패킷을 처리함으로써 효율적인 처리 능력을 제공한다. 본 논문에서는 abnormal node detector와 neighbor table을 통해 어떤 방식으로 네트워크에 안정성을 제공하는지 살펴보도록 하겠다.

• 대한수학회논문집
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• 제34권3호
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• pp.1005-1014
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• 2019

A new simple method is proposed for reconstructing phylogenetic trees, which we call the spectral method. The most common distance based method is the neighbor-joining method which is based on the minimum evolution principle. The spectral method shows similar performance to the neighbor-joining method for simulated data generated by seq-gen. For real data, the spectral method shows much better performance than the neighbor-joining method. Hence it can be a complementary method for reconstructing phylogenetic trees.

• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.455-470
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• 2007

In phylogenetic tree construction the neighbor-joining algorithm is the most well known method which constructs a trivalent tree from a pairwise distance data measured by DNA sequences. The core part of the algorithm is its cherry picking criterion based on the tree structure of each quartet. We give a generalized version of the criterion based on the exact box model of quartets, known as the tight span of a metric. We also show by experiment why neighbor-joining and the quartet consistency count method give similar performance.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1996년도 학술대회
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• pp.175-180
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• 1996

In this paper, a new image segmentation method based on merging of two low contrast neighbor regions iteratively is proposed. It is suitable for very low bit rate coding. The proposed method reduces efficiently contour information and preserves subjective and objective image quality. It consists of image segmentation using 4-level hierarchical structure based on mathematical morphology and 1-level region merging structure using the contrast difference of two adjacent neighbor regions. For each segmented region of the third level, two adjacent neighbor regions having low contrast difference value in fourth level based on contrast difference value is merged iteratively. It preserves image quality and shows the noticeable reduction of the contour information, so that it can improve the bottleneck problem of segmentation-based coding at very low bit rate.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 1997년도 제9회 한글 및 한국어 정보처리 학술대회
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• pp.7-14
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• 1997

문서 범주화에서 문서의 내용에 따라 적합한 범주의 종류와 수를 찾는 문제를 해결하기 위해서는 문서 당 하나의 범주를 할당할 경우에 가장 좋은 성능을 보이는 모델이 효과적일 것이다. 그러므로, 본 논문에서는 문서 당 하나의 범주를 할당할 경우에 좋은 결과를 보이는 k-nearest neighbor 방법을 이용한다. 그리고 k-nearest neighbor 방법을 이용한 문서 범주화의 성능을 향상시키기 위해서, 문서 표현에 사용하는 단어들을 범주 자질의 성격을 갖는 단어들로 제한하는 방법을 제안한다. 제안한 방법은 Router 신문 일년치로 구성된 Router-21578 테스트 집합에서 breakeven point 82%라는 좋은 결과를 보였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (A)
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• pp.691-693
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• 2004

Mobile Ad hoc network은 stationary infrastructure의 도움 없이 이동 노드들이 필요 시 multi-hop wireless links network 형태를 구성하여 통신이 이루어지게 하는 network이다. 따라서 효율적인 라우팅 프로토콜의 개발이 중요한 issue인데 최근에는 routing overhead가 적은 on-demand 프로토콜이 주목을 받고 있다. On-demand 프로토콜은 새로운 route을 구성하기 위해서 query packet을 broadcasting하게 되는데, 특히 노드들의 mobility가 많은 mobile ad hoc network(MANET)의 경우에는 더욱더 자주 발생하게 되는데, blind broadcasting은 neighbor 노드들 간의 radio transmission region overlap에 의해 redundancy, contention, collision 같은 broadcast storm 문제를 발생시키게 된다. 본 논문은 on-demand 프로토콜의 broadcast storm 문제를 해결하기 위해 Neighbor Topology을 고려 한 Dynamic Adaptation Query flooding scheme을 제시한다. 또한 Dynamic Adaptive Query flooding scheme은 broadcast storm 문제 해결뿐만 아니라 network의 congestion을 감소시켜 data packet의 성능 향상에도 기여 할 것이다.

• 대한수학회논문집
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• 제25권1호
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• pp.149-160
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• 2010

Among the distance based algorithms in phylogenetic tree reconstruction, the neighbor-joining algorithm has been a widely used and effective method. We propose a new algorithm which counts the number of consistent quartets for cherry picking with tie breaking. We show that the success rate of the new algorithm is almost equal to that of neighbor-joining. This gives an explanation of the qualitative nature of neighbor-joining and that of dissimilarity maps from DNA sequence data. Moreover, the new algorithm always reconstructs correct trees from quartet consistent dissimilarity maps.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.3896-3915
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• 2014

The Reverse k Nearest Neighbor (RkNN) query is valuable for finding objects influenced by a specific object and is widely used in both scientific and commercial systems. However, the influence level of each object is unknown, information that is critical for some applications (e.g. target marketing). In this paper, we propose a new query type, Ordered Reverse k Nearest Neighbor (ORkNN), and make efforts to adapt it in an on-demand scenario. An Order-k Voronoi diagram based approach is used to answer ORkNN queries. In particular, for different values of k, we pre-construct only one Voronoi diagram. Algorithms on both the server and the clients are presented. We also present experimental results that suggest our proposed algorithms may have practical applications.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 추계학술발표논문집 (하)
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• pp.1429-1432
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• 2003

This paper addresses the problem of finding a constrained nearest neighbor for moving query point(we call it CNNMP) The Nearest neighbor problem is classified by existence of a constrained region, the number of query result and movement of query point and target. The problem assumes that the query point is not static, as 1-nearest neighbor problem, but varies its position over time to the constrained region. The parameters as NC, NCMBR, CQR and QL for the algorithm are also presented. We suggest the query optimization algorithm in consideration of topological relationship among them