• 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.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2294-2304
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• 1999

Our research purpose in this paper is to improve the performance of query processing in GIS(Geographic Information System) by enhancing the I/O performance exploiting parallel I/O and efficient disk access. By packing adjacent spatial data, which are very likely to be referenced concurrently, into one block or continuous disk blocks, the number of disk accesses and the disk access overhead for query processing can be decreased, and this eventually leads to the I/O time decrease. So, in this paper, we proposes EPR(Enhanced Parallel R-tree) indexing method which integrates the parallel I/O method of the previous Parallel R-tree method and a packing-based clustering method. The major characteristics of EPR method are as follows. First, EPR method arranges spatial data in the increasing order of proximity by using Hilbert space filling curve, and builds a packed R-tree by bottom-up manner. Second, with packing-based clustering in which arranged spatial data are clustered into continuous disk blocks, EPR method generates spatial data clusters. Third, EPR method distributes EPR index nodes and spatial data clusters on multiple disks through round-robin striping. Experimental results show that EPR method achieves up to 30% or more gains over PR method in query processing speed. In particular, the larger the size of disk blocks is and the smaller the size of spatial data objects is, the better the performance of query processing by EPR method is.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.187-197
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• 2005

In this paper, we propose an extended TB-tree, called ETB-tree, which can improve the performance of an existing TB-tree proposed for indexing the trajectories of moving objects in Location-Based Service(LBS). The proposed ETB-tree directly accesses the preceding node by maintaining a direct table, called D-Table which contains the page number in disk and memory pointers pointing the leaf node with the first and last lines segment of moving objects. It can improve the insertion performance by quick searching the preceding node of a moving object and retrieval performance owing to accessing directly the corresponding trajectories In disk for the trajectory-based query. In addition, the ETB-tree provides consistency of a tree by reflecting a newly inserted line segment to the tree both in memory and disk. The experimental results show that the proposed indexing technique gains better performance than other traditional ones with respect to the insertion and retrieval of a trajectory query.

• Journal of the Korean Wood Science and Technology
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• v.29 no.3
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• pp.21-26
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• 2001

Acquisition of precise information on drying characteristics of wood is indispensable for the improvement of drying schedules and wood quality. Recognition of the exact moisture content at which drying defects such as checks occur during drying with given drying conditions may be essential to reduce drying losses. In this study an image-processing system was combined with a laboratory-scale wood dry kiln for experiments and the surface of tree disk of black locust (Robinia pseudoacacia L.) was monitored to investigate the behavior of check formation over all the drying process. This system showed good potential for improving drying schedules and wood product quality.

• The Journal of the Korea Contents Association
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• v.13 no.9
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• pp.28-38
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• 2013

During the past decades, the B+-tree has been most widely used as an index file structure for disk-resident databases. For the disk based B+-tree, a node update can be cheaply performed just by modifying its associated disk page in place. However, in case that the B+-tree is stored on flash memory, the traditional algorithms of the B+-tree come to be useless due to the prohibitive cost of in-place updates on flash memory. For this reason, the earlier schemes for flash memory B+-trees usually take an approach that saves B+-tree changes from real-time updates into extra temporary storage. Although that approach can easily prevent frequent in-place updates in the B+-tree, it can suffer from a waste of storage space and prolonged search times. Particularly, it is not allowable to process range searches on the leaf node level. To resolve such problems, we devise a new scheme in which the leaf nodes and their parent node are stored together in a single flash block, called the p-node block.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.673-676
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• 2004

To manage and query moving objects efficiently in MMDBMS, a memory index structure should be used. The most popular index structure for storing trajectories of moving objects is 3DR-tree. The 3DR-tree also can be used for MMDBMS. However, the volume of data can exceed the capacity of physical memory since moving objects report their locations continuously. To accommodate new location reports, old trajectories should be migrated to disk or purged from memory. This paper focuses on migration policies of a main memory index structure. Migration policies consist of two steps: (i) node selection, (ii) node placement. The first step (node selection) selects nodes that should be migrated to disk. The criteria of selection are the performance of insertion or query. The second step (node placement) determines the order of nodes written to disk. This step can be thought as dynamic declustering policies.

• Korean Journal of Clinical Laboratory Science
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• v.50 no.4
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• pp.431-437
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• 2018

Acinetobacter baumannii is categorized as a red alert pathogen that is increasingly associated with a high mortality rate in infected patients because of its resistance to extensive antibiotics. This study evaluated the antibacterial activities of some essential oils (tee tree, rosemary, and lavender oils) against 18 clinical isolates of multidrug-resistant A. baumannii (MRAB). The carbapenemase screening Hodge test showed that all 20 strains of A. baumannii were resistant to imipenem. The identification of multidrug-resistant microbes was carried out using the VITEK system. The antimicrobial activity of essential oils was tested by a disk diffusion method against MRAB. In the disk diffusion method, tea tree showed the largest increase in inhibition size compared to lavender oil, and rosemary had no antibacterial effect. These results proved the antimicrobial effect of multidrug resistance A. baumannii. Tee tree oil would be a useful alternative natural product for the treatment and prevention of most common human pathogens and MRAB infections. This is expected to be used as an antimicrobial agent, such as hand disinfectant using natural essential oil in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.1
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• pp.37-46
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• 2010

A Suffix Tree is an efficient data structure that exposes the internal structure of a string and allows efficient solutions to a wide range of complex string problems, in particular, in the area of computational biology. However, as the biological information explodes, it is impossible to construct the suffix trees in main memory. We should find an efficient technique to construct the trees in a secondary storage. In this paper, we present a method for constructing a suffix tree in a disk for large set of DNA strings using new index scheme. We also show a typical application example with a suffix tree in the disk.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.