• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.23-37
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• 2004

Location Based Services(LBSs) in mobile environments become very popular recently. For efficient LBSs, spatial database management systems must need a spatial indexing scheme such as R-trees in order to manage the huge spatial database. However, it may need unnecessary disk accesses since it needs to access objects which are not actually concerned to user's location-based queries. In this paper, to support the location-based queries efficiently, we propose a CLR-tree(Cell Leveling R-tree) in which a dynamic cell is built up within the minimum bounding rectangle of R-trees' node. The cell level of nodes is compared with the query's cell level in location-based query processing and determines the minimum search space. Also, we propose the insertion, split, deletion, and search algorithms for CRL-trees. From the experimental results, we see that a CLR-tree is able to decrease $5{\sim}20%$ of disk accesses from those of R-trees. So, a CLR-tree can be used for fast accessing spatial objects to user's location-based queries in LBSs.

• MALSORI
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• no.45
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• pp.117-126
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• 2003

Decision tree-based state tying has been proposed in recent years as the most popular approach for clustering the states of context-dependent hidden Markov model-based speech recognition. The aims of state tying is to reduce the number of free parameters and predict state probability distributions of unseen models. But, when doing state tying, the size of a decision tree is very important for word independent recognition. In this paper, we try to construct optimized decision tree based on the average of feature vectors in state pool and the number of seen modes. We observed that the proposed optimal decision tree is effective in predicting the state probability distribution of unseen models.

• ETRI Journal
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• v.22 no.1
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• pp.30-37
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• 2000

Existing tree construction mechanisms are classified into source-based trees and center-based trees. The source-based trees produce a source-rooted tree with a low delay. However, for the applications with multiple senders, the management overheads for routing tables and resource reservations are too high. The center-based trees are easy to implement and manage, but a priori configuration of candidate center nodes is required, and the optimization mature such as tree cost and delay is not considered. In this paper, we propose a new multicast tree building algorithm. The proposal algorithm basically builds a non-center based shared tree. In particular, any center node is not pre-configured. In the purposed algorithm, a multicast node among current tree nodes is suitably assigned to each incoming user: Such a node is selected in a fashion that tree cost and the maximum end-to-end delay on the tree are jointly minimized. The existing and proposed algorithms are compared by experiments. In the simulation results, it is shown that the proposed algorithm approximately provides the cost saving of 30% and the delay saving of 10%, compared to the existing approaches. In conclusion, we see that the cost and delay aspects for multicast trees can be improved at the cost of additional computations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3138-3150
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• 2021

Multimedia services on the Internet are continuously increasing. Accordingly, the demand for a technology for efficiently delivering multimedia traffic is also constantly increasing. The multicast technique, that delivers the same content to several destinations, is constantly being developed. This technique delivers a content from a source to all destinations through the multicast tree. The multicast tree with low cost increases the utilization of network resources. However, the finding of the optimal multicast tree that has the minimum link costs is very difficult and its calculation complexity is the same as the complexity of the Steiner tree calculation which is NP-complete. Therefore, we need an effective way to obtain a multicast tree with low cost and less calculation time on SDN-based smart network platforms. In this paper, we propose a new multicast tree generation algorithm which produces a multicast tree using an agent trained by model-based meta reinforcement learning. Experiments verified that the proposed algorithm generated multicast trees in less time compared with existing approximation algorithms. It produced multicast trees with low cost in a dynamic network environment compared with the previous DQN-based algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.214-216
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• 2002

본 논문에서는 many-to-many IP 멀티캐스팅을 위한 효율적인 Backbone Core Tree(BCT)생성 알고리즘에 대하여 제안한다. 본 논문의 제안기법은 Core Based Tree(CBT)에 기반을 두고 있다. CBT는 공유 트리를 이용하여 멀티캐스트 자료를 전달하기 때문에 Source Based Tree에 비하여 각 라우터가 유지해야 하는 상태 정보의 양에 적고 적용하기 간단하지만, Core 라우터 선택의 어려움과 트래픽이 Core로 집중되는 문제점을 가지고 있다. 이에 대한 보완책으로 Backbone Core Tree기법이 제안되었는데, 본 논문에서는 주어진 네트워크 위상 그래프에서 최소신장 트리를 만들고, 센트로이드를 이용하여 효율적인 BCT를 생성하는 알고리즘을 제안한다.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.543-552
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• 2005

As random access memory chip gets cheaper, it becomes affordable to realize main memory-based database systems. The disk-based spatial indexing techniques, however, cannot direct apply to main memory databases, because the main purpose of disk-based techniques is to reduce the number of disk accesses. In main memory-based indexing techniques, the node access time is much faster than that in disk-based indexing techniques, because all index nodes reside in a main memory. Unlike disk-based index techniques, main memory-based spatial indexing techniques must reduce key comparing time as well as node access time. In this paper, we propose an efficient spatial index structure for main memory-based databases, called Tmr-tree. Tmr-tree integrates the characteristics of R-tree and T-tree. Therefore, Nodes of Tmr-tree consist of several entries for data objects, main memory pointers to left and right child, and three additional fields. First is a MBR of a self node, which tightly encloses all data MBRs (Minimum Bounding Rectangles) in a current node, and second and third are MBRs of left and right sub-tree, respectively. Because Tmr-tree needs not to visit all leaf nodes, in terms of search time, proposed Tmr-tree outperforms R-tree in our experiments. As node size is increased, search time is drastically decreased followed by a gradual increase. However, in terms of insertion time, the performance of Tmr-tree was slightly lower than R-tree.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.316-327
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• 2007

RFID (Radio Frequency Identification) is one of the most promising air interface technologies in the future for object identification using radio wave. If there are multiple tags within the range of the RFID tag reader, all tags send their tag identifications to the reader at the same time in response to the reader's query. This causes collisions on the reader and no tag is identified. A multi-tag identification problem is a core issue in the RFID. It can be solved by anti-collision algorithm such as slot based ALHOA algorithms and tree based algorithms. This paper, proposes a collision tree based anti-collision algorithm using collision tree in RFID system. It is a memory-less algorithm and is an efficient RFID anti-collision mechanism. The collision tree is a mechanism that can solve multi-tag identification problem. It is created in the process of querying and responding between the reader and tags. If the reader broadcasts K bits of prefix to multiple tags, all tags with the identifications matching the prefix transmit the reader the identifications consisted of k+1 bit to last. According to the simulation result, a proposed collision tree based anti-collision algorithm shows a better performance compared to tree working algorithm and query tree algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.43-53
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• 2011

The many cities are changing in the city form where the person and nature are mixed. Namely, the government invests many expense in tree field of distance space for the change in the green city. In this paper, we design and implement a tree growth management system using PDA built in 13.56MHz RFID reader and CBD(Component Based Development) for ubiquitous computing environments. Our system provides history management to increase business efficiency for location coordinate of tree and history information of tree which using RFID, the RFlD tag is attaching the new tree and that is inputting GPS location information in PDA and provides tree information of tree by location coordinate to history management. Finally, we show from a performance analysis that our system achieves about 85% average tree read rate of RFID under test scenario environments.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.82-89
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• 2008

최근, GIS 분야에서 RFID와 GPS 센서 같은 위치 및 공간 데이타를 포함하는 다양한 GeoSensor의 활용으로 수집되는 공간 데이타가 크게 증가하면서, 대용량 공간 데이타의 빠른 처리를 위한 공간 인덱스의 중요성이 높아지고 있다. 특히, 대표적인 공간 인덱스인 R-Tree를 기반으로 검색 성능을 높이기 위한 연구가 활발히 진행되고 있다. 그러나, 기존 연구는 R-Tree에서 노드의 MBR 간의 겹침이나 트리 높이를 어느 정도 줄임으로써 다소 검색 성능을 향상시켰지만, 트리 검색에서 발생하는 불필요한 노드 접근 비용 문제를 효율적으로 해결하지 못하고 있다. 본 논문에서는 이러한 문제를 해결하고 R-Tree에서 대용량 공간 데이타의 빠른 검색을 제공하는 인덱스인 HR-Tree(Hash based R-Tree)를 제시한다. HR-Tree는 트리 검색 없이 R-Tree 리프 노드를 직접 접근할 수 있는 해시 테이블을 이용함으로써 R-Tree의 검색 성능을 높인다. 해시 테이블은 데이타 영역을 차원에 따라 반복적으로 분할한 Partition과 대응되는 R-Tree 리프 노드의 MBR과 포인터들로 구성된다. 각 Partition은 생성 과정에서 고유의 식별 코드를 갖기 때문에 Partition 코드가 주어지면 해시 테이블에서 해당 레코드를 쉽게 접근할 수 있다. 또한, HR-Tree는 R-Tree구조의 변경없이 다양한 R-Tree 변형 구조에 쉽게 적용할 수 있는 장점이 있다. 마지막으로 실험을 통하여 HR-Tree의 우수성을 입증하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1096-1100
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• 2012

Most of previous genetic algorithms for solving graph problems have used a vertex-based encoding. We proposed an edge encoding based new genetic algorithm using a spanning tree. Contrary to general edge-based encoding, a spanning tree-based encoding represents only feasible partitions. As a target problem, we adopted the MAX CUT problem, which is well known as a representative NP-hard problem, and examined the performance of the proposed genetic algorithm. The experiments on benchmark graphs are executed and compared with vertex-based encoding. Performance improvements of the spanning tree-based encoding on sparse graphs was observed.