• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.36-43
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• 2016

The transformation time among queries in the database management system (DBMS) is responsible for the execution time of users' queries, because a conventional DBMS does not consider the transformation cost when queries are transformed for execution. To reduce the transformation time (cost reduction) during execution, we propose an optimal query transformation method by exploring queries from a cost-based point of view. This cost-based point of view means considering the cost whenever queries are transformed for execution. Toward that end, we explore and compare set off heuristic, linear, and exhaustive cost-based transformations. Further, we describe practical methods of cost-based transformation integration and some query transformation problems. Our results show that, some cost-based transformations significantly improve query execution time. For instance, linear and heuristic transformed queries work 43% and 74% better than exhaustive queries.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.150-159
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• 2008

Lots of EDI-VAN companies are in need of transforming their business transaction systems into Web-based e-Business frameworks because of high cost and closed structure of EDI systems. This research proposes several e-Transformation strategies for EDI-VAN companies to adopt Web-based e-Business frameworks such as ebXML and RosettaNet. Four transformation alternatives are presented and transformation procedure for a medium-sized company is described. The result of this work can be used as a practical guideline for EDI companies to develop their own transformation strategy suitable to its scale and capability, while minimizing the impacts on the pre-existing business processes and information systems.

• Journal of Computing Science and Engineering
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• v.3 no.1
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• pp.27-58
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• 2009

Aggregation join queries are an important class of queries over data streams. These queries involve both join and aggregation operations, with window-based joins followed by an aggregation on the join output. All existing research address join query optimization and aggregation query optimization as separate problems. We observe that, by putting them within the same scope of query optimization, more efficient query execution plans are possible through more versatile query transformations. The enabling idea is to perform aggregation before join so that the join execution time may be reduced. There has been some research done on such query transformations in relational databases, but none has been done in data streams. Doing it in data streams brings new challenges due to the incremental and continuous arrival of tuples. These challenges are addressed in this paper. Specifically, we first present a query processing model geared to facilitate query transformations and propose a query transformation rule specialized to work with streams. The rule is simple and yet covers all possible cases of transformation. Then we present a generic query processing algorithm that works with all alternative query execution plans possible with the transformation, and develop the cost formulas of the query execution plans. Based on the processing algorithm, we validate the rule theoretically by proving the equivalence of query execution plans. Finally, through extensive experiments, we validate the cost formulas and study the performances of alternative query execution plans.

• Journal of Ocean Engineering and Technology
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• v.37 no.5
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• pp.190-197
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• 2023

In the shipbuilding and marine industry, digital transformation activities are promoted primarily by large shipyards. However, bottlenecks are observed across value chains, and digital transformation effects are reducing because of the cost and technical challenges encountered by supplies. In this study, we proposed a win-win cooperation model for large, small, and medium-sized companies using digital transformation based on the characteristics of the shipbuilding and marine industry through case studies. We investigated the digital transformation progress in German and Korean small and medium-sized enterprises (SMEs). In addition, we identified information-sharing methods and management challenges encountered in enterprise resource planning and manufacturing execution systems in the collaboration process of pipes, panels, blocks, etc. of SMEs that are suppliers of a Korean shipyard, and clarified communication by building a platform based on a common format between shipyards and suppliers. Further, we proposed a standard model of a digital transformation system for enhancing the collaboration between large companies and suppliers and proposed a basic plan including strategies to efficiently and effectively build a digital transformation system based on the standard model.

• Proceedings of the CALSEC Conference
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• 2005.03a
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• pp.149-154
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• 2005

Recently, lots of EDI-VAN (Electronic Data Interchange-Value Added Network) companies challenge to convert their business systems into Web-based e-business frameworks to avoid high cost and closed structure of EDI system. This research proposes e-Transformation strategies for EDI-VAN companies to adopt Web-based e-business standard frameworks such as ebXML (e-business using XML) and RosettaNet. Four migration strategies for EDI companies are presented, and their properties are described in detail. Transformation procedures of two representative strategies are also provided fur the convenience of medium-sized companies. The result of this work can be used as a practical guideline for EDI companies to develop there own transformation strategy suitable to its scale and capability, while minimizing the impacts on the pre-existing business processes.

• ETRI Journal
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• v.34 no.6
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• pp.847-857
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• 2012

Intrusion detection systems (IDSs) have an important effect on system defense and security. Recently, most IDS methods have used transformed features, selected features, or original features. Both feature transformation and feature selection have their advantages. Neighborhood component analysis feature transformation and genetic feature selection (NCAGAFS) is proposed in this research. NCAGAFS is based on soft computing and data mining and uses the advantages of both transformation and selection. This method transforms features via neighborhood component analysis and chooses the best features with a classifier based on a genetic feature selection method. This novel approach is verified using the KDD Cup99 dataset, demonstrating higher performances than other well-known methods under various classifiers have demonstrated.

• ETRI Journal
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• v.38 no.5
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• pp.807-817
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• 2016

A novel fast algorithm is suggested for a coding unit (CU) mode decision using pseudo rate-distortion based on a separated encoding structure in High Efficiency Video Coding (HEVC). A conventional HEVC encoder requires a large computational time for a CU mode prediction because prediction and transformation procedures are applied to obtain a rate-distortion cost. Hence, for the practical application of HEVC encoding, it is necessary to significantly reduce the computational time of CU mode prediction. As described in this paper, under the proposed separated encoder structure, it is possible to decide the CU prediction mode without a full processing of the prediction and transformation to obtain a rate-distortion cost based on a suitable condition. Furthermore, to construct a suitable condition to improve the encoding speed, we employ a pseudo rate-distortion estimation based on a Hadamard transformation and a simple quantization. The experimental results show that the proposed method achieves a 38.68% reduction in the total encoding time with a similar coding performance to that of the HEVC reference model.

• Journal of Software Engineering Society
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• v.26 no.1
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• pp.17-29
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• 2013

Software System Evolution is more planned and systematic maintenance process as well as a type of maintenance. The research of software evolution provides basis of decisions for maintenance value through cost-benefit analysis of legacy system and architecture-based software evolution enables engineers to reduce maintenance cost by automation of repetitive evolution tasks. This paper proposes a framework for software system evolution using architectural transformation pattern.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.214-216
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• 2004

XML 문서에 대한 데이터의 통계 정보는 XML 어플리케이션에 유용하다. 특히 XML 어플리케이션에 대해 RDBMS 테이블 형U로 유도하는 방법 중 cost-based approach를 적용할 때 다양한 Schema 변환 중 어플리케이션에 가장 적합한 것을 선택하는 데 사용한다. 본 논문에서는 정차한 통계 정보를 모으기 위해 Shared type과 변환 과정에 생기는 잠재적인 Shared type에 대해 해결한 X2R System을 개발하였고. 효율적으로 통계를 유지하도록 하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2454-2468
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• 2019

The existing direct position determinations(DPD) for coherently distributed(CD) sources are mostly applicable for uniform linear array(ULA), which result in a low degree of freedom(DOF), and it is difficult for them to realize the effective positioning in underdetermined condition. In this paper, a novel DPD algorithm for coherently distributed sources based on compressed sensing with a moving nested array is present. In this algorithm, the nested array is introduced to DPD firstly, and a positioning model of signal moving station based on nested array is constructed. Owing to the features of coherently distributed sources, the cost function of compressed sensing is established based on vectorization. For the sake of convenience, unconstrained transformation and convex transformation of cost functions are carried out. Finally, the position coordinates of the distribution source signals are obtained according to the theory of optimization. At the same time, the complexity is analyzed, and the simulation results show that, in comparison with two-step positioning algorithms and subspace-based algorithms, the proposed algorithm effectively solves the positioning problem in underdetermined condition with the same physical element number.