• Journal of KIISE
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• v.41 no.10
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• pp.792-798
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• 2014

In spatial databases, R-tree is one of the most widely used indexing structures and many variants have been proposed for its performance improvement. Among these variants, Hilbert R-tree is a representative method using Hilbert curve to process large amounts of data without high cost split techniques to construct the R-tree. This Hilbert R-tree, however, is hardly applicable to large-scale applications in practice mainly due to high pre-processing costs and slow bulk-load time. To overcome the limitations of Hilbert R-tree, we propose a novel approach for parallelizing Hilbert mapping and thus accelerating bulk-loading of Hilbert R-tree on GPU memory. Hilbert R-tree based on GPU improves bulk-loading performance by applying the inversed-cell method and exploiting parallelism for packing the R-tree structure. Our experimental results show that the proposed scheme is up to 45 times faster compared to the traditional CPU-based bulk-loading schemes.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.261-273
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• 2004

Advances in information and communication technologies have been creating new classes of applications in the area of databases. For example, in moving object databases, which track positions of a lot of objects, or stream databases, which process data streams from a lot of sensors, data Processed in such database systems are usually changed very rapidly and continuously. However, traditional database systems have a problem in processing these rapidly and continuously changing data because they suppose that a data item stored in the database remains constant until It is explicitly modified. The problem becomes more serious in the R-tree, which is a typical index structure for multidimensional data, because modifying data in the R-tree can generate cascading node splits or merges. To process frequent updates more efficiently, we propose a novel update technique for the R-tree, which we call the leaf-update technique. If a new value of a data item lies within the leaf MBR that the data item belongs, the leaf-update technique changes the leaf node only, not whole of the tree. Using this leaf-update manner and the leaf-access hash table for direct access to leaf nodes, the proposed technique can reduce update cost greatly. In addition, the leaf-update technique can be adopted in diverse variants of the R-tree and various applications that use the R-tree since it is based on the R-tree and it guarantees the correctness of the R-tree. In this paper, we prove the effectiveness of the leaf-update techniques theoretically and present experimental results that show that our technique outperforms traditional one.

• Tunnel and Underground Space
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• v.11 no.4
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• pp.289-300
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• 2001

In the design of tunnel, it contains inaccuracy of data, fuzziness of evaluation, observer error and so on. The face observation during tunnel excavation, therefore, plays an important role to raise stability and to reduce supporting cost. This study is carried out to minimize the subjectiveness of observer and to exactly evaluate the natural properties of ground during the face observation. For these purpose, fuzzy set theory and neuro-fuzzy techniques in artificial intelligent techniques are applied to the inference of the RMR value from the observation data. The correlation between original RMR vague and inferred RM $R_{_FU}$ and RM $R_{_NF}$ values from fuzzy set theory and neuro-fuzzy techniques is investigated using 46 data. The results show that good correlation between original RMR value and infected RM $R_{_FU}$ and RM $R_{_NF}$ value is observed when the correlation coefficients are ｜R｜=0.96 and ｜R｜=0.95 respectively. From these results, applicability of fuzzy set theory and neuro-fuzzy techniques to rock mats classification is proved to be sufficiently high enough. enough.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.465-466
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• 2011

본 논문에서는 순간정전 발생시 전압강하 보상 알고리즘을 통하여 AC Drive의 신뢰성을 높이는 제어 기법들에 대해 알아본다. 부하 특성에 따라 제어 기법이 나누어지며 각각 제어 기법은 시뮬레이션 및 시험을 통해 그 타당성을 검증 하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.743-745
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• 2003

R-tree는 공간 데이터나 다차원 데이터의 효율적인 질의 처리를 위한 인덱스 구조이다. 다량의 데이터로부터 빠르게 인덱스를 생성하기 위해서 많은 다량로딩 기법들이 제안되었으나 이들은 공간이용률을 극대화하는 데에 초점을 맞춰 R-tree의 목적인 효율적인 질의 처리를 위한 개선의 여지가 남아 있다. 본 논문에서는 다량로딩 과정에서 인접한 노드들간의 겹치는 영역을 감소시켜 전체적으로 질의 처리 성능을 향상시킬 수 있는 기법을 제안한다. 실험 결과에서 보이듯이 지금까지 가장 효율적이라고 알려져 있는 STR 기법보다 질의 성능이 좋게 나오는 것을 확인할 수 있다.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.11-23
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• 2007

Applications involving moving objects require index structures to handle frequent updates of objects' locations efficiently. Several methods to index the current, the past and the future positions of moving objects have been proposed for the applications. Most of them are based on R-tree like index structures. Some researches have made efforts to improve update performance of R-trees that are actually focused on query performance. Even though the update performance is improved by researchers' efforts, the overhead and immaturity of concurrency control algorithms of R-trees makes us hesitate to choose them for moving objects. In this paper, we propose an update efficient indexing method that can be applicable for indexing the past, the current and the future locations. The proposed index is based on B+-Trees and Hilbert curve. We present an advanced Hilbert curve that adjusts automatically the order of Hilbert curve in subregions according to the data distribution and the number of data objects. Through empirical studies, we show that our strategy achieves higher response time and throughput.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.143-150
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• 2004

Nowaday, The tendency of complexity and extension of construction fields increase the need for efficient works managements like a construction management. Consequently, by the introduction of Decision-Making Theories, researches for improving construction field's efficiencies are actively performed. Fuzzy Analytical Hierarchy Process method is invented, so that describes a decision maker's ambiguous linguistic judgment with fuzzy numbers. but most of researches on Fuzzy-AHP use symmetric triangular fuzzy function for estimating each evaluation item with the consequence that exact judgments are impossible. those limits are caused by the point that employed fuzzy ranking methods can not support dissymmetric fuzzy numbers. In this research, we aims to overcome this problem with R.P.R(Relative Preference Ratio) method and suggest improved Fuzzy-AHP method which can use dissymmetric fuzzy triangular numbers.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.153-164
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• 2004

In this study, we compare multivariate R-techniques in the up-to-date versions of SAS, SPSS, Minitab and S-plus. The direct input method by typing in command is considered for SAS, while the menu-driven method is considered for SPSS, Minitab and S-plus. Comparison was made in terms of input data format, input option, charts and outputs.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.145-153
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• 2001

The Pyramid-Technique is based on mapping n-dimensional space data into one-dimensional data and expressing it as B-tree ; and by solving the problem of search time complexity the pyramid technique also prevents the effect \"phenomenon of dimensional curse\" which is caused by treatment of hypercube range query in n-dimensional data space. The Spherical Pyramid-Technique applies the pyramid method’s space division strategy, uses spherical range query and improves the search performance to make it suitable for similarity search. However, depending on the size of data and change in dimensions, the two above technique demonstrate significantly inferior search performance for data sizes greater than one million and dimensions greater than sixteen. In this paper, we propose a new index-structured PdR-Tree to improve the search performance for high dimensional data such as multimedia data. Test results using simulation data as well as real data demonstrate that PdR-Tree surpasses both the Pyramid-Technique and Spherical Pyramid-Technique in terms of search performance.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.67-69
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• 2002

여러 사이트에서 구축된 공간 데이터를 효율적으로 관리 및 공유하기 위해서는 대용량의 정보를 처리할 수 있는 분산 공간 데이터베이스 시스템의 사용이 필수적이다. 이러한 분산 공간 데이터베이스 시스템상에서의 분산 공간 죠인 질의는 공간 데이터의 대용량성과 그 복잡성으로 인하여 공간 연산의 지펴져 부하와 네트워크상의 전송 부하를 발생시킨다. 이러한 문제를 해결하기 위해 세미죠인 기반의 공간 죠인 기법들이 제안되었으나 공간 죠인 연산을 특정 서버에서만 수행하여 병목현상을 발생시키기 때문에 결국 질의 처리시간이 증가된다. 본 논문은 이러한 분산 공간 데이터베이스 시스템에서 수행 비용이 많이 드는 원격 사이트간의 공간 죠인 연산에 대해 R+-tree 공간 색인을 사용하여 병렬적으로 수행하는 기법을 제안한다. 본 기법은 R+-tree 공간 색인을 이용하여 공간 죠인 연산의 대상이 되는 릴레이션들을 중첩이 없는 두개의 릴레이션들로 분할한 후 질의 수행에 참여하는 두 서버에 죠인 연산을 분배하고 병렬적으로 처리하여 결과들을 병합한 다음 클라이언트에게 전송만다. 본 기법은 릴레이션을 분할하여 각 서버에서 공간 죠인 연산을 병렬적으로 처리하므로 처리 비용을 절반으로 감소시키며. R+-tree의 영역에 해당하는 객체들만 죠인 연산에 참여하게 함으로써 네트워크 전송 비용을 감소시킨다