• Journal of Information Technology Services
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• v.13 no.2
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• pp.151-161
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• 2014

KOSPI 200 index options market has the highest trading volume in the global options markets. The risk and return structure of options contracts are very complex. Volatility complicates options trading because volatility plays a central role in options pricing process. This study develops a trading system for KOSPI 200 index options trading using KOSPI 200 volatility index. We design a database system to handle the complex options information such as price, volume, maturity, strike price, and volatility using Oracle DBMS. We then develop options trading strategies to test how the volatility index is related to the prices of complicated options trading strategies. Back test procedure is presented with PL/SQL of Oracle DBMS. We simulate the suggested trading system using historical data set of KOSPI 200 index options from December 2008 to April 2012.

• International Journal of Contents
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• v.3 no.3
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• pp.1-5
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• 2007

The main memory DBMS (MMDBMS) efficiently supports various database applications that require high performance since it employs main memory rather than disk as a primary storage. An index manager is an essential sub-component of a DBMS used to speed up the retrieval of objects from a large volume of a database in response to a certain search condition. Previous research efforts on indexing proposed various index structures. However, they hardly dealt with the practical issues occurred in implementing an index manager on a target DBMS. In this paper, we touch these issues and present our experiences in developing the index manager. The main issues are (1) compact representation of an index entry, (2) support of variable-length keys. (3) support of multiple-attribute keys, and (4) support of duplicated keys.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.33-46
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• 2003

A Home Location Register(HLR) database system manages each subscriber's location information, which continuously changes in a cellular network. For this purpose, the HLR database system provides table management, index management, and backup management facilities. In this thesis, we propose using a two-level index method for the mobile directory number(MDN) as a suitable method and a chained bucket hashing method for the electronic serial number(ESN). Both the MDN and the ESN are used as keys in the HLR database system. We also propose an efficient backup method that takes into account the characteristics of HLR database transactions. The retrieval speed and the memory usage of the two-level index method are better than those of the R-tree index method. The insertion and deletion overhead of the chained bucket hashing method is less than that of the modified linear hashing method. In the proposed backup method, we use two kinds of dirty flags in order to solve the performance degradation problem caused by frequent registration-location operations. For a million subscribers, proposed techniques support reduction of memory size(more than 62%), directory operations (2500,000 times), and backup operations(more than 80%) compared with current techniques.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.987-997
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• 2008

Successful design, construction and maintenance of geotechnical structure in soft ground and marine clay demands prediction, control, stability estimation and monitoring of settlement with high accuracy. It is important to predict and to estimate the compression index of soil for predicting of ground settlement. Lab. and field tests have been and are indispensable tools to achieve this goal. In this paper, Artificial Neural Networks (ANNs) model with Levenberg-Marquardt Algorithm and field database were used to predict compression index of soil in Korea. Based on soil property database obtained from more than 1800 consolidation tests from soils samples, the ANNs model were proposed in this study to estimate the compression index, using multiple soil properties. The compression index from the proposed ANN models including multiple soil parameters were then compared with those from the existing empirical equations.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.157-159
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• 2007

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 to support databases for desktops and server computers. 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 node management schemes based on B-Tree due to the relatively slow characteristics of hard disk operations, as compared to flash memory. In order to achieve this goal, we propose a new index node management scheme called FNC-Tree. FNC-Tree-based index node 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.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.593-604
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• 2001

A database sharing system (DSS) refers to a system for high performance transaction processing. In the DSS, the processing nodes are coupled via a high speed network and share a common database at the disk level. Each node has a local memory and a separate copy of operating system. To reduce the number of disk accesses, the node caches data pages and index pages in its memory buffer. In general, B-tree index pages are accessed more often and thus cached at more processing nodes, than their corresponding data pages. There are also complicated operations in the B-tree such as Fetch, Fetch Next, Insertion and Deletion. Therefore, an efficient cache consistency scheme supporting high level concurrency is required. In this paper, we propose cache consistency schemes using identifiers of index pages and page_LSN of leaf page. The propose schemes can improve the system throughput by reducing the required message traffic between nodes and index re-traversal.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2911-2921
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• 1999

We present new methods for an efficient retrieval of SGML documents. We define IDDL (index database description language) which is able to describe various information such as meta data, an indexing range, and the creation and manipulation of a database. In addition, we design IDQL (index database query language) that can deal with querying meta data as well as logical structure. Especially, the retrieval system based on IDDL and IDQL has been developed and implemented, and has been experimented on large number of documents. Experimental result shows that the proposed method provides the dynamic creation of an index database and a convenient retrieval environment.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.223-225
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• 2001

• ETRI Journal
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• v.34 no.1
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• pp.66-75
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• 2012

This paper proposes a privacy-preserving database encryption scheme that provides access pattern hiding against a service provider. The proposed scheme uses a session key to permute indices of database records each time they are accessed. The proposed scheme can achieve access pattern hiding in situations in which an adversary cannot access the inside of the database directly, by separating the entity with an index table and data table and permuting both the index and position where the data are stored. Moreover, it is very efficient since only O(1) server computation and communication cost are required in terms of the number of the data stored. It can be applied to cloud computing, where the intermediate entities such as cloud computing service provider can violate the privacy of users or patients.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1259-1266
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• 2013

Nowadays, the databases are getting larger and larger. As the company has difficulty in managing the database, they want to outsource the database to the cloud system. In this case the database security is more important because their database is managed by the cloud service provider. Among database security techniques, the encryption method is a well-certified and established technology for protecting sensitive data. However, once encrypted, the data can no longer be easily queried. The performance of the database depends on how to encrypt the sensitive data, and on the approach for searching, and the retrieval efficiency that is implemented. In this paper we propose the new suitable mechanism to encrypt the database and lookup process on the encrypted database under control of the cloud service provider. This database encryption algorithm uses the bloom filter with the variable keyword based index. Finally, we demonstrate that the proposed algorithm should be useful for database encryption related research and application activities.