• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.89-95
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• 2009

This paper proposes a tag indexing scheme for RFID tag using spatial index. The tag being used for the inventory management and the tag's location is determined by the position of readers. Therefore, the reader recognizes the tag, which is attached products and thereby their positions can be traced down. In this paper, we propose hTag-tree( Hybrid Tag index) which manages RFID tag attached products. hTag-tree is a new index, which is based on tag's attributes with fast searching, and this tag index manages RFID tags using reader's location. This tag index accesses rapidly to tags for insertion, deletion and updating in dynamic environment. This can minimize the number of node accesses in tag searching comparing to previous techniques. Also, by the extension of MER in present tag index, it is helpful to stop the lowering of capacity which can be caused by parent node approach. The proposed index experiment deals with the comparison of tag index. Fixed Interval R-tree, and present spatial index, R-tree comparison. As a result, the amount of searching time is significantly shortened through hTag-tree node access in data search. This shows that the use of proposed index improves the capacity of effective management of a large amount of RFID tag.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.63-74
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• 2005

The telematics device, which is a typical embedded system on the transportation or vehicle, requires the embedded spatial DBMS based on RTOS (Real Time Operating System) for processing the huge spatial data in real time. This spatial DBMS can be developed very easily by SQL3 functions of the ORDBMS such as UDT (user-defined type) and UDF (user-defined function). However, developing index suitable for the embedded spatial DBMS is very difficult. This is due to the fact that there is no built-in SQL3 functions to construct spatial indexes. In this study, we compare and analyze both Generalized Search Tree and Relational Indexing methods which are suggested as common ways of developing User-Defined Indexes nowadays. Two implementations of R-Tree based on each method were done and region query performance test results were evaluated for suggesting a suitable indexing method of an embedded spatial DBMS, especially for telematics devices.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.101-113
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• 2006

A path query is used in XML. Several index structures have been studied for processing the path query efficiently. In recent. the index schemes using suffix tree with structure join method were proposed. ViST is the most representative method among such methods. ViST processes the query using suffix tree and uses B+-tree to reduce the search time of the documents. However, it significantly degrades the search performance when processing the path query. The reason is that it regards the element that is not ancestor-descendant relation in the document as a descendent. In this paper, we propose an efficient index structure to solve the problem of ViST. The query processing method suitable to the index structure is also proposed. It is shown through various experiments that the proposed index structure outperforms the existing index structure in terms of the query processing time.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.119-132
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• 2007

In molecular biology, approximate subsequence search is one of the most important operations. In this paper, we propose an accurate and efficient method for approximate subsequence search in large DNA databases. The proposed method basically adopts a binary trie as its primary structure and stores all the window subsequences extracted from a DNA sequence. For approximate subsequence search, it traverses the binary trie in a breadth-first fashion and retrieves all the matched subsequences from the traversed path within the trie by a dynamic programming technique. However, the proposed method stores only window subsequences of the pre-determined length, and thus suffers from large post-processing time in case of long query sequences. To overcome this problem, we divide a query sequence into shorter pieces, perform searching for those subsequences, and then merge their results. To verify the superiority of the proposed method, we conducted performance evaluation via a series of experiments. The results reveal that the proposed method, which requires smaller storage space, achieves 4 to 17 times improvement in performance over the suffix tree based method. Even when the length of a query sequence is large, our method is more than an order of magnitude faster than the suffix tree based method and the Smith-Waterman algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.9
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• pp.1059-1064
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• 2015

To write a medical record using SNOMED CT standard clinical terminologies, it is necessary to find and select an appropriate terminology from the huge volume of terminologies within short time. Using previous SNOMED CT search browsers, it is very difficult to select appropriate one from search results since they provide a simple list-up of similar candidate terminologies. This paper proposes a novel search browser which supports effect searching of clinical terminology by utilizing characteristics of SNOMED CT. The proposed system provides a simplified tree-view representing hierarchical structures of search results which enables fast selection of appropriate terminology from the search results. Design and Implementation of the system proves effectiveness of the proposed approach.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.393-401
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• 2013

Most traditional databases exploit record-oriented storage model where the attributes of a record are placed contiguously in hard disk to achieve high performance writes. However, for search-mostly datawarehouse systems, column-oriented storage has become a proper model because of its superior read performance. Today, flash memory is largely recognized as the preferred storage media for high-speed database systems. In this paper, we introduce fast column-oriented database model and then propose a new column-aware index management scheme for the high-speed column-oriented datawarehouse system. Our index management scheme which is based on enhanced $B^+$-Tree achieves high search performance by embedded flash index and unused space compression in internal and leaf nodes. Based on the results of the performance evaluation, we conclude that our index management scheme outperforms the traditional scheme in the respect of the search throughput and response time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.402-410
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• 2013

In this paper, we propose a new fast block matching algorithm for block matching using the temporal and spatially correlation of the video sequence and local statistics of neighboring motion vectors. Since the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vectors of neighboring blocks around the same block of the previous frame and the current frame and the predictor candidate point on each division region by binary-tree structure. Experimental results show that the proposed algorithm has the capability to dramatically reduce the search points and computing cost for motion estimation, comparing to fast FS(full search) motion estimation and other fast motion estimation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1266-1272
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• 2004

Location-Based Services(LBS) give rise to location-dependent queries of which results depend on the positions of moving objects. Because positions of moving objects change continuously, indexes of moving object must perform update operations frequently for keeping the changed position information. Existing spatial index (Grid File, R-Tree, KDB-tree etc.) proposed as index structure to search static data effectively. There are not suitable for index technique of moving object database that position data is changed continuously. In this paper, I propose a dynamic hashing index that insertion/delete costs are low. The dynamic hashing structure is that apply dynamic hashing techniques to combine a hash and a tree to a spatial index. The results of my extensive experiments show the dynamic hashing index outperforms the $R^$ $R^*$-tree and the fixed grid.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3469-3476
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• 1999

In spatial database based on spatial data structures, instead of one-dimensional indexing structure, new indexing structure which corresponds to multi-dimensional features of spatial objects is required. In order to meet those requirements, in this paper we proposed new indexing structure for efficient retrieval of spatial database by carrying through the feature analysis of conventional multi-dimensional indexing structures. To improve the sequential search method of supernodes in the conventional X-tree and to reduce the retrieval time in case of generating the huge supernode, we proposed a indexing structure integrating the kd-tree based on point index structure into the X-tree. We implemented the proposed indexing structure and analyzed its retrieval time according to the dimension and distribution of experimental data.