• The KIPS Transactions:PartD
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• v.14D no.2
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• pp.157-168
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• 2007

For effective analyses in various business applications, OLAP(On-Line Analytical Processing) systems represent the multidimensional data as the horizontal format of tables whose columns are corresponding to values of dimension attributes. Because the traditional RDBMSs have the limitation on the maximum number of attributes in table columns(MS SQLServer and Oracle permit each table to have up to 1,024 columns), horizontal tables cannot be directly stored into relational database systems. In this paper, we propose various efficient optimization strategies in transforming horizontal queries to equivalent vertical queries. To achieve this goral, we first store a horizontal table using an equivalent vertical table, and then develop various query transformation rules for horizontal table queries using the PIVOT operator. In particular, we propose various alternative query transformation rules for the basic relational operators, selection, projection, and join. Here, we note that the transformed queries can be executed in several ways, and their execution times will differ from each other. Thus, we propose various optimization strategies that transform the horizontal queries to the equivalent vertical queries when using the PIVOT operator. Finally, we evaluate these methods through extensive experiments and identify the optimal transformation strategy when using the PIVOT operator.

• Journal of Applied Reliability
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• v.14 no.2
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• pp.103-107
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• 2014

An algorithm to get network reliability, where each link has probability of fuzzy number, is proposed. Decomposition method and fuzzy numbers arithmetic are applied to the algorithm. Pivot link is chosen one by one from start node recursively at time of decomposition, and arithmetic of fuzzy complementary numbers is included at the same time. No criteria of pivot link selection and the recursive calculation make the algorithm simple.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.18-34
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• 2007

In order to provide various business analysis methods, OLAP(On-Line Analytical Processing) systems represent their data with multidimensional structures. These multidimensional data are often delivered to users in the horizontal format of tables whose columns are corresponding to values of dimension attributes. Since the horizontal tables nay have a large number of columns, they cannot be stored directly in relational database systems. Furthermore, the tables are likely to have many null values (i.e., sparse tables). In order to manage the horizontal tables efficiently, we can store them as the vertical format of tables which has dimension attribute names as their columns thus transforms the columns of horizontal tables into rows. In this way, every queries for horizontal tables have to be transformed into those for vertical tables. This paper proposed a technique for transforming horizontal table queries into vertical table ones by utilizing not only traditional relational algebraic operators but also the PIVOT operator which recent DBMS versions are providing. For achieving this goal, we designed a relational algebraic expression equivalent to the PIVOT operator and we formally proved their equivalence. Then, we developed a transformation technique for horizontal table queries using the PIVOT operator. We also performed experiments to analyze the performance of the proposed method. From the experimental results, we revealed that the proposed method has better performance than existing methods.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.463-474
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• 2009

To analyze multidimensional data conveniently and efficiently, OLAP (On-Line Analytical Processing) systems or e-business are widely using views in a horizontal form to represent measurement values over multiple dimensions. These views can be stored as materialized views derived from several sources in order to support accesses to the integrated data. The horizontal views can provide effective accesses to complex queries of OLAP or e-business. However, we have a problem of occurring maintenance of the horizontal views since data sources are distributed over remote sites. We need a method that propagates the changes of source tables to the corresponding horizontal views. In this paper, we address incremental maintenance of horizontal views that makes it possible to reflect the changes of source tables efficiently. We first propose an overall framework that processes queries over horizontal views transformed from source tables in a vertical form. Under the proposed framework, we propagate the change of vertical tables to the corresponding horizontal views. In order to execute this view maintenance process efficiently, we keep every change of vertical tables in a differential file and then modify the horizontal views with the differential file. Because the differential file is represented as a vertical form, its tuples should be converted to those in a horizontal form to apply them to the out-of-date horizontal view. With this mechanism, horizontal views can be efficiently refreshed with the changes in a differential file without accessing source tables. Experimental results show that the proposed method improves average performance by 1.2$\sim$5.0 times over the existing methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.397-400
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• 2010

우리는 지난 연구에서 변형 비속어 필터링 시스템을 위하여 근사 문자열 검색 시스템을 적용하여 서열 정렬 횟수를 비약적으로 줄일 수 있었다. 다차원 데이터 구조를 이용한 한글 근사 검색 시스템은 기준축인 Base-Pivot의 숫자에 따라 검색 결과의 정확도를 높일 수 있으나 BP이 증가한 만큼 질의 단어의 좌표를 계산하기 위한 시간이 오래 걸린다. 소규모 데이터 검색에는 문제가 되지 않으나 60,000단어 이상의 데이터가 수록되는 국어사전과 같은 대규모 데이터를 검색하게 될 경우 요구되는 BP의 숫자도 증가하여 많은 연산시간을 필요로 한다. 본 논문에서는 기존의 근사 단어 검색 시스템을 계층구조화 하여 요구되는 BP 숫자를 감소 시켜 성능을 향상 시키는 방법을 제안하고자 한다. 그리고 실험을 통하여 본 아이디어의 실효성을 증명하였다. 본 아이디어는 기존의 6000개의 비속어에 대하여 약 20%정도의 성능향상을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.870-878
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• 2008

The level of security of most sensor nodes that comprise the sensor networks is low, but because of the low computing power and small storage capacity, it is even very difficult to apply a security algorithm efficiently to the sensor nodes. Therefore, preventing the join of an illegal node to a sensor network is impossible, and the transmitting information is easily exposed and overheard when the transmitting algorithm of the sensor node is hewn. In this paper, we propose a group key management scheme for the sensor network using polar coordinates, so that the sensor nodes can deliver information securely inside a cluster and any illegal node is prevented from joining to the cluster where a sensor network is composed of many clusters. In the proposed scheme, all of the sensor nodes in a cluster set up the authentication keys based on the pivot value provided by the CH. The intensive simulations show that the proposed scheme outperforms the pair-wise scheme in terms of the secure key management and the prevention of the illegal nodes joining to the network.