• International Journal of Contents
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• v.3 no.1
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• pp.19-23
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• 2007

Recently, several main-memory index structures have been proposed to reduce the impact of secondary cache misses. In mainmemory storage systems, secondary cache misses have a substantial effect on the performance of index structures. However, recent studies still stiffer from secondary cache misses when visiting each level of index tree. In this paper, we propose a new index structure that minimizes the total amount of cache miss latency. The proposed index structure prefetched grandchildren of a current node. The basic structure of the proposed index structure is based on that of the CSB+-Tree, which uses the concept of a node group to increase fan-out. However, the insert algorithm of the proposed index structure significantly reduces the cost of a split. The superiority of our algorithm is shown through performance evaluation.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.377-382
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• 2010

With the advent of flash memory based new storage device (SSD), there is considerable interest within the computer industry in using flash memory based storage devices for many different types of application. The dynamic index structure of large text collections has been a primary issue in the Information Retrieval Applications among them. Previous studies have proven the three approaches to be effective: In- Place, merge-based index structure and a combination of both. The above-mentioned strategies have been researched with the traditional storage device (HDD) which has a constraint on how keep the contiguity of dynamic data. However, in case of the new storage device, we don' have any constraint contiguity problems due to its low access latency time. But, although the new storage device has superiority such as low access latency and improved I/O throughput speeds, it is still not well suited for traditional dynamic index structures because of the poor random write throughput in practical systems. Therefore, using the experimental performance evaluation of various index maintenance schemes on the new storage device, we propose an efficient index structure for new storage device that improves significantly the index maintenance speed without degradation of query performance.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.325-336
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• 2006

For supporting LBS service, recent studies on spatial network databases (SNDB) have been done actively. In order to gain good performance on query processing in SNDB, we, in this paper. design efficient storage and index structures for spatial network data, point of interests (POIs), and moving objects on spatial networks. First, we design a spatial network file organization for maintaining the spatial network data itself consisting of both node and edges. Secondly, we design a POI storage and index structure which is used for gaining fast accesses to POIs, like restaurant, hotel, and gas station. Thirdly, we design a signature-based storage and index structure for efficiently maintaining past, current, and expected future trajectory information of moving objects. Finally, we show that the storage and index structures designed in this paper outperform the existing storage structures for spatial networks as well as the conventional trajectory index structures for moving objects.

• ETRI Journal
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• v.22 no.2
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• pp.32-42
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• 2000

The existing multi-dimensional index structures are not adequate for indexing higher-dimensional data sets. Although conceptually they can be extended to higher dimensionalities, they usually require time and space that grow exponentially with the dimensionality. In this paper, we analyze the existing index structures and derive some requirements of an index structure for content-based image retrieval. We also propose a new structure, for indexing large amount of point data in a high-dimensional space that satisfies the requirements. in order to justify the performance of the proposed structure, we compare the proposed structure with the existing index structures in various environments. We show, through experiments, that our proposed structure outperforms the existing structures in terms of retrieval time and storage overhead.

• The Korean Journal of Food And Nutrition
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• v.24 no.1
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• pp.71-78
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• 2011

Peeled chestnuts were stored at different temperatures($-10^{\circ}C$ and $-20^{\circ}C$) and for different times(0, 10, and 20 min at $90^{\circ}C$) for blanching over a 6 month period. Analyses were conducted for moisture content, total sugar content, browning index, polyphenol compounds, PPO activity, and SEM. Moisture content and PPO activity were increased by storage time. The increments for the samples stored at $-20^{\circ}C$ were lower that for the samples stored at $-10^{\circ}C$. The Browning index was increased by storage time, and increments for the samples stored at $-20^{\circ}C$ were lower that for the samples stored at $-10^{\circ}C$. Scanning electronic microscopy(SEM) studies were performed on peeled chestnuts. Results showed that the wrinkle structure of the cell wall was enhanced by storage time, and the level of enhancement was higher at $-10^{\circ}C$ than at $-20^{\circ}C$.

• International Journal of Contents
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• v.1 no.1
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• pp.50-58
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• 2005

Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1109-1118
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• 1998

Recently, much attention has been focused on video databases. Video documents also have a hierarchical logical structure like text documents. By exploiting this structure using structure queries, users can obtain greater benefits than by using only content queries. In order to process structure queries efficiently, an index structure supporting fast video element access must be provided. However, there has been little attention to the index structure for video documents. In this paper, we present a tree-structured video document model and a new inverted index structure for video documents. We evaluate the storage requirement and the disk access time of the scheme and present the analytical results.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1033-1043
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• 2000

Recently as the user request on NoD (News-on-Demand) is largely increasing, there are a lot of researches to fulfill it. However, because of short life-cycle of new video data and periodical change of video data depending on anchor, it is difficult to apply the conventional video storage techniques to NOD applications directly. For this, we design and implement low-level storage manager for efficient storage and retrieval of multimedia data in NOD Services. Our low-level storage manager not only efficiently sotres video stream dat of new video itself, but also handles its index information. It provides an inverted file method for efficient text-based retrieval and an X-tree index structure for high-dimensional feature vectors. In addition, our low-level storage manager provides some application program interfaces (APIs) for storing video objects itself and index information extracted from hierarchial new video and some APIs for retrieving video objects easily by using cursors. Finally, we implement our low-level storage manager based on SHORE (Scalable Heterogeneous Object REpository) storage system by sunig a standard C++ language under UNIX operating system.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.105-120
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• 1997

One of the most important issues of object-oriented geographical database system is to develop an indexing technique which enables more efficient I/O processing within aggregation hierarchy or inheritance hierarchy. Up to present, several indexing schemes have been developed for this purpose. However, they have separately focused on aggregation hierarchy or inheritance hierarchy of object-oriented data model. A recent research is proposing a nested-inherited index which combines these two hierarchies simultaneously. However, this new index has some weak points. It has high storage costs related to its use of auxiliary index. Also, it cannot clearly represent the inheritance relationship among classes within its index structure. To solve these problems, this thesis proposes a pointer-chain index. Using pointer chain directory, this index composes a hierarchy-typed chain to show the hierarchical relationship among classes within inheritance hierarchy. By doing these, it could fetch the OID list of objects to be retrieved more easily than before. In addition, the pointer chain directory structure could accurately recognize target cases and subclasses and deal with "select-all" typed query without collection of schema semantic information. Also, it could avoid the redundant data storing, which usually happens in the process of using auxiliary index. This study evaluates the performance of pointer chain indexing technique by way of simulation method to compare nested-inherited index. According to this simulation, the pointer chain index is proved to be more efficient with regard to storage cost than nested-inherited index. Especially in terms of retrieval operation, it shows efficient performance to that of nested-inherited index.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.328-331
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• 2000

In this paper , we propose a texture feature extraction method of reduce the massive computational time on extracting texture, features of large sized medical such as MRI, CT-scan , and an index structure, called GLTFT, to speed up the retrieval performance. For these, the original image is transformed into a compressed image by Wavelet transform , and textural features such as contrast, energy, entropy, and homogeneity of the compressed image is extracted by using GLCM(Gray Level Co-occurrence Metrix) . The proposed index structure is organized by using the textural features. The processing in compressed domain can give the solution of storage space and the reduction of computational time of feature extracting . And , by GLTFT index structure, image retrieval performance can be expected to be improved by reducing the retrieval range . Our experiment on 270 MRIs as image database shows that shows that such expectation can be got.