• Journal of Korean Library and Information Science Society
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• v.35 no.3
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• pp.271-291
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• 2004

Such information services source like digital library has been asked information services of atypical multimedia database like image, voice, VOD/AOD. Examined in this study are suggestions such as word-phrase generator, syllable recoverer, morphological analyzer, corrector for voice processing. Suggested voice processing technique transform voice database into tort database, then extract index database from text database. On top of this, the study suggest a information retrieval model to use in extracted index database, voice full-text information retrieval.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.389-405
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• 2015

Most traditional database systems exploit a record-oriented model where the attributes of a record are placed contiguously in a hard disk to achieve high performance writes. However, for read-mostly data warehouse systems, the column-oriented database 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 a column-oriented database model based on flash memory and then propose a new column-aware flash indexing scheme for the high-speed column-oriented data warehouse systems. Our index management scheme, which uses an enhanced $B^+$-Tree, achieves superior search performance by indexing an embedded segment and packing an unused space in internal and leaf nodes. Based on the performance results of two test databases, we concluded that the column-aware flash index management outperforms the traditional scheme in the respect of the mixed operation throughput and its response time.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1299-1313
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• 2010

Top-k queries return k objects that users most want in the database. The Partitioned-Layer Index (simply, the PL -index) is a representative method for processing the top-k queries efficiently. The PL-index partitions the database into a number of smaller databases, and then, for each partitioned database, constructs a list of sublayers over the partitioned database. Here, the $i^{th}$ sublayer in the partitioned database has the objects that can be the top-i object in the partitioned one. To retrieve top k results, the PL-index merges the sublayer lists depending on the user's query. The PL-index has the advantage of reading a very small number of objects from the database when processing the queries. However, since many random accesses occur in merging the sublayer lists, query performance of the PL-index is not good in environments like disk-based databases. In this paper, we propose the Abstracted Partitioned-Layer Index (simply, the APL-index) that significantly improves the query performance of the PL-index in disk-based environments by reducing the number of random accesses. First, by abstracting each sublayer of the PL -index into a virtual (point) object, we transform the lists of sublayers into those of virtual objects (ie., the APL-index). Then, we virtually process the given query by using the APL-index and, accordingly, predict sublayers that are to be read when actually processing the query. Next, we read the sublayers predicted from each sublayer list at a time. Accordingly, we reduce the number of random accesses that occur in the PL-index. Experimental results using synthetic and real data sets show that our APL-index proposed can significantly reduce the number of random accesses occurring in the PL-index.

• Journal of Information Technology Applications and Management
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• v.10 no.2
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• pp.19-31
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• 2003

We propose an indexing technique and an index selection algorithm for optimal OLAP query processing in object database systems, Although there are many research results on the relational database systems for OLAP Query processing, few researches have been done on the object database systems. Since OLAP queries represent complex business logic on a huge data ware-house, object database systems supporting the OLAP queries should have higher performance. Proposed bitmap index structure is an extension of conventional bitmap indexes for adapting object databases and provides higher performance with lower space overhead. We also propose a linear time solution of the index selection problem that will be used in the OLAP query optimization process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1867-1879
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• 1997

DREAM-S is a distributed main-memory database system for the real-time processing of shared operational datra in ATM switching systems. DREAM-S has a client-server architecture in which only the server has the diskstorage, and provides the T-Tree index structure for efficient accesses to the data. We propose a recovery technique for the T-Tree index structre in DREAM-S. Although main-memory database system offer efficient access performance, the database int he main-memory may be broken when system failure such as database transaction failure or power failure occurs. Therfore, a recovery technique that recovers the database (including index structures) is essential for fault tolerant ATM switching systems. Proposed recovery technique relieves the bottleneck of the server processors disk operations by maintaining the T-Tree index structure only in the main-memory. In addition, fast recovery is guaranteed even in large number of client systems since the T-Tree index structure(s) in each system can be recovered cncurrently.

• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.103-114
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• 2001

In this paper, we propose an efficient index mechanism for real-time main memory database systems. Existing main memory index structures based on the tree can effectively support range searches. However, it doesn't guarantee the real-time characteristic because difference between the access time of a node and an average access time can be high. The index structures based on the hash have always a regular random access time on the simple searches and that speed is very fast. However they do not support range searches. To solve such problems, we propose a new index mechanism called Hyper Tree-Hash (Hyper-TH) that combines ECBH (Extendible Chained Bucket Hashing) and T＊-tree. ECBH can be dynamically extended and has a very fast access time. T＊-tree effectively supports the range searches. We show through our experiments that the proposed mechanism outperforms existing other index structures.

• Health Policy and Management
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• v.26 no.1
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• pp.71-78
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• 2016

The value of using health insurance claim database is continuously rising in healthcare research. In studies where comorbidities act as a confounder, comorbidity adjustment holds importance. Yet researchers are faced with a myriad of options without sufficient information on how to appropriately adjust comorbidity. The purpose of this study is to assist in selecting an appropriate index, look back period, and data range for comorbidity adjustment. No consensus has been formed regarding the appropriate index, look back period and data range in comorbidity adjustment. This study recommends the Charlson comorbidity index be selected when predicting the outcome such as mortality, and the Elixhauser's comorbidity measures be selected when analyzing the relations between various comorbidities and outcomes. A longer look back period and inclusion of all diagnoses of both inpatient and outpatient data led to increased prevalence of comorbidities, but contributed little to model performance. Limited data range, such as the inclusion of primary diagnoses only, may complement limitations of the health insurance claim database, but could miss important comorbidities. This study suggests that all diagnoses of both inpatients and outpatients data, excluding rule-out diagnosis, be observed for at least 1 year look back period prior to the index date. The comorbidity index, look back period, and data range must be considered for comorbidity adjustment. To provide better guidance to researchers, follow-up studies should be conducted using the three factors based on specific diseases and surgeries.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.898-899
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• 2013

There are numerous approaches to improve the performances of database systems. The most efficient ones are considered to be implementing an effective database indexing technique. This must guarantee the balance between the memory, storage resources and processor of the database server according to the type, structure, the physical organization and the cardinality of data, the type of queries and the number of competing transactions. The challenge is to find an appropriate index type that would suite these requirements. In this paper, we provide an overview of the most used database indexing techniques such as B-tree index and Bitmap index, present an analysis of these techniques and discuss their limitations.

• International Journal of Contents
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• v.3 no.2
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• pp.6-17
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• 2007

Emerging modem database applications require multi-dimensional index structures to provide high performance for data retrieval. In order for a multi-dimensional index structure to be integrated into a commercial database system, efficient techniques that provide transactional access to data through this index structure are necessary. The techniques must support all degrees of isolation offered by the database system. Especially degree 3 isolation, called "no phantom read," protects search ranges from concurrent insertions and the rollbacks of deletions. In this paper, we propose a new phantom protection method for multi-dimensional index structures that uses a multi-level grid technique. The proposed mechanism is independent of the type of the multi-dimensional index structure, i.e., it can be applied to all types of index structures such as tree-based, file-based, and hash-based index structures. In addition, it has a low development cost and achieves high concurrency with a low lock overhead. It is shown through various experiments that the proposed method outperforms existing phantom protection methods for multi-dimensional index structures.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.40-46
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• 2013

In the chemical process industries, accidents have a high potential and large effects on catastrophic results. Therefore the safety management for accident prevention plays a crucial role to guarantee the process safety. For these reasons, many systematic methods for safety management system have been widely employed in the fields of chemical processes. PSM (Process safety management) is one of most representative methods. The audit system, which is one of PSM system components, evaluates the performance of PMS system. However, most existing safety audit systems are not systematic and these are performed based on knowledges and experiences of various specialist. Moreover, the safety audit is only performed based on each independent technical component. So, the results of safety audit are not a quantitative index but only a series of commentaries. Finally, it is very difficult to obtain the comparison with other plants or industries. In this study, the novel systematic method and index-based accident database of auditing safety management systems for quantitative assessment are proposed. First, the elements of safety audit replace technical methods to categories of accident database. The F-N curve of each category for accident database is employed to derive the index for quantitative assessment. The Accidental Factor Risk Index (AFRI) is suggested for evaluating the effect of each element in accident database and safety audit system. The safety audit can be modified according to the proposed index.