• Journal of Digital Convergence
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• v.15 no.10
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• pp.243-251
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• 2017

As external data have become important corporate information resources, there are growing needs to combine them with internal data. This paper proposes an ontology-based scheme to combine external data with multi-dimensional databases, which shall be called multi-dimensional event ontology. In the ontology, external data are represented as events. Event characteristics such as actors, places, times, targets are linked to dimensions of a multi-dimensional database. By mapping event characteristics to database dimensions, external event data are shared via multi-dimensional hierarchies. This paper proposes rules to synchronize information sharing in multi-dimensional event ontology such as upward event information sharing, downward event information sharing and complex event information sharing. These rules are implemented using Protege. This study has a value in suggesting Big Data information sharing processes using an event database framework.

• 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.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.10a
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• pp.27-40
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• 2004

When we derive multi-scale databases from a source spatial database, thegeometries and topological relations in the source database are transformed according to a predefined set of constraints. This means that the derived databases should be checked to see if the constraints are respected during the construction or updates of databases and to maintain the consistency of multi-scale databases. In this paper, we focus on the topological consistency between the source and derived databases, which is one of the important constraints to respect. In particular, we deal with the method of assessment of topological consistency, when 2-dimensional objects are collapsed to 1-dimensional ones. We introduce eight types of topological relations between 2-dimensional objects and 19 topological ones between 1-dimensional objects and propose four different strategies to convert 2-dimensional topological relations in the source database to 1-dimensional ones objects in the target database. With these strategies, we guarantee the topological consistency between multi-scale databases.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.837-848
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• 2005

A multi-scale database is a set of spatial database, covering same geographic area with different scales and it can be derived from pre-existing databases. In the derivation processes of a new multi-scale spatial database, the geometries and topological relations on the source database can be transformed and the transformation can be the cause of the lack of integrity Therefore, it is necessary to assess the transformation whether it is consistent or not after the derivation process of a new multi-scale database. Thus, we propose assessment methods for the topological consistency between a source database and a derived multi-scale database in this paper. In particular, we focus on the case that 2-dimensional objects are collapsed to 1-dimensional ones in the derivation process of a multi-scale database. We also describe implementation of the assessment methods and show the results of the implementation with experimental data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.154-173
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• 2010

Database outsourcing is unavoidable in the near future. In the scenario of data stream outsourcing, the data owner continuously publishes the latest data and associated authentication information through a service provider. Clients may register queries to the service provider and verify the result's correctness, utilizing the additional authentication information. Research on On-line Stream Analytics (OLSA) is motivated by extending the data cube technology for higher multi-level abstraction on the low-level-abstracted data streams. Existing work on OLSA fails to consider the issue of database outsourcing, while previous work on stream authentication does not support OLSA. To close this gap and solve the problem of OLSA query authentication while outsourcing data streams, we propose MDAHRB and MDAHB, two multi-dimensional authentication approaches. They are based on the general data model for OLSA, the stream cube. First, we improve the data structure of the H-tree, which is used to store the stream cube. Then, we design and implement two authentication schemes based on the improved H-trees, the HRB- and HB-trees, in accordance with the main stream query authentication framework for database outsourcing. Along with a cost models analysis, consistent with state-of-the-art cost metrics, an experimental evaluation is performed on a real data set. It exhibits that both MDAHRB and MDAHB are feasible for authenticating OLSA queries, while MDAHRB is more scalable.

• Journal of The Korean Digital Architecture Interior Association
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• v.11 no.2
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• pp.61-70
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• 2011

This study aims to establish the concept about a new approaching method dor remodeling in the planning step. also, this study sets up the way how to approach in a dimensional way by classifying the conceptual composition of the target housing as a method. The dimensional definition is as below. The one dimensional approach: the spot. the two dimensional approach: the line, the three dimensional approach: the apatial mass, the four dimensional approach: space + time, the n dimensional (multi-dimensional) approach: the space + time + emotion. The research findings are as follows : For the purpose of remodeling, the old housing should be viewed in the three dimensional shape and space. It is defined as multi-dimensional module method to design the shape and space of the target housing in a multi-dimensional point, considering the three dimensional space composition, the emotion of the user, the housing itself. and the time of the user.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.429-437
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• 2003

Over the last decades, improvements in CPU speed have greatly exceeded those in memory and disk speeds by orders of magnitude and this enabled the use of compression techniques to reduce the database size as well as the query cost. Although compression techniques are employed in various database researches, there is little work on compressing multi-dimensional index structures. In this paper, we propose an efficient compression method called the hybrid encoding method (HEM) that is tailored to multi-dimensional indexing structures. The HEM compression significantly reduces the query cost and the size of multi-dimensional index structures. Through mathematical analyses and extensive experiments, we show that the HEM compression outperforms an existing method in terms of the index size and the query cost.

• Management Science and Financial Engineering
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• v.7 no.1
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• pp.27-39
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• 2001

The multi-projective model considers attributes and the relationships among attributes called projections. The critical features of the multi-projective model are the way of relating attributes in the description of the system, the way of reasoning incomplete projections, and the determination of connected patterns between projection. In order to get a full picture of the system, we build a set of projections. The multi-projective model can be thought of as projections of a multi-dimensional reality onto simplified “model space”. The multi-projective database modeling approach used in this paper unified the ideas and terminology of various database models. Most importantly, the multi-projective modeling is presented as a tool of database design in the relational and other database models.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.732-736
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• 2010

Processing a large amount of data becomes more important than ever. Particularly, the information queries which require multi-dimensional record scan can be efficiently implemented with SIMD instruction sets. In this article, we present a SIMD record scan technique which employs row-based scanning. Our technique is different from existing SIMD techniques for predicate processes and aggregate operations. Those techniques apply SIMD instructions to the attributes in the same column of the database, exploiting the column-based record organization of the in-memory database systems. Whereas, our SIMD technique is useful for multi-dimensional record scanning. As the sizes of registers and the memory become larger, our row-based SIMD scan can have bigger impact on the performance. Moreover, since our technique is orthogonal to the parallelization techniques for multi-core processors, it can be applied to both uni-processors and multi-core processors without too many changes in the software architectures.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.1-11
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• 2000

Up to the present, many GIS logical data models have been proposed to incorporate time dimension into traditional 2-dimensional (2D space) GIS databases. However, these models are difficult to implementation of multi-dimensional GIS and have problems of significant data redundancy and search performance. This paper proposes a new storage strategy and a separate storage structure, that is composed of current database and past database, in order to reduce data redundancy and improve search performance of temporal query. Also we design moving algorithm for migration from current database to past database, and design efficient search algorithm for temporal query.