• Spatial Information Research
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• v.19 no.2
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• pp.47-56
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• 2011

Typical tree-based spatial index structures are divided into a data-partitioning index structure such as R-Tree and a space-partitioning index structure such as KD-Tree. In recent years, researches on hybrid index structures combining advantages of these index structures have been performed extensively. However, because the split boundary extension of the node to which a new spatial object is inserted may extend split boundaries of other neighbor nodes in existing researches, overlaps between nodes are increased and the query processing cost is raised. In this paper, we propose a hybrid index structure, called SQR-Tree that can support efficient processing of spatial queries to solve these problems. SQR-Tree is a combination of SQ-Tree(Spatial Quad- Tree) which is an extended Quad-Tree to process non-size spatial objects and R-Tree which actually stores spatial objects associated with each leaf node of SQ-Tree. Because each SQR-Tree node has an MBR containing sub-nodes, the split boundary of a node will be extended independently and overlaps between nodes can be reduced. In addition, a spatial object is inserted into R-Tree in each split data space and SQ-Tree is used to identify each split data space. Since only R-Trees of SQR-Tree in the query area are accessed to process a spatial query, query processing cost can be reduced. Finally, we proved superiority of SQR-Tree through experiments.

• Spatial Information Research
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• v.19 no.4
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• pp.45-54
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• 2011

In this paper, we propose a hybrid index structure, called the SQMR-tree(Spatial Quad MR-tree) that can process spatial data efficiently by combining advantages of the MR-tree and the SQR-tree. The MR-tree is an extended R-tree using a mapping tree to access directly to leaf nodes of the R-tree and the SQR-tree is a combination of the SQ-tree(Spatial Quad-tree) which is an extended Quad-tree to process spatial objects with non-zero area and the R-tree which actually stores spatial objects and are associated with each leaf node of the SQ-tree. The SQMR-tree consists of the SQR-tree as the base structure and the mapping trees associated with each R-tree of the SQR-tree. Therefore, because spatial objects are distributedly inserted into several R-trees and only R-trees intersected with the query area are accessed to process spatial queries like the SQR-tree, the query processing cost of the SQMR-tree can be reduced. Moreover, the search performance of the SQMR-tree is improved by using the mapping trees to access directly to leaf nodes of the R-tree without tree traversal like the MR-tree. Finally, we proved superiority of the SQMR-tree through experiments.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.771-772
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• 2009

최근 대표적인 공간 인덱스 구조인 R-tree를 기반으로 KD-tree나 Quad-tree와 같은 공간 분할 특성을 이용하여 인덱싱 성능을 향상시키기 위한 연구가 활발하다. 본 논문에서는 기존에 제시된 R-tree 기반 인덱스 구조인 SQR-tree와 PMR-tree의 특성을 결합하여 대용량 공간 데이타를 보다 효율적으로 처리하는 인덱스 구조인 MSQR-tree(Mapping-based SQR-tree)를 제시한다. SQR-tree는 Quad-tree를 확장한 SQ-tree와 각 SQ-tree 리프 노드마다 실제로 공간 객체를 저장하는 R-tree가 연계되어 있는 인덱스 구조이고, PMR-tree는 R-tree에 R-tree 리프 노드를 직접 접근할 수 있는 매핑 트리를 적용한 인덱스 구조이다. 본 논문에서 제시하는 MSQR-tree는 SQR-tree를 기본 구조로 가지고 R-tree마다 매핑 트리가 적용된 구조를 갖는다. 따라서, MSQR-tree에서는 SQR-tree와 같이 질의가 여러 R-tree에서 분산 처리되고, PMR-tree와 같이 매핑 트리를 통해 R-tree 리프 노드를 빠르게 접근할 수 있다. 마지막으로 성능 실험을 통해 MSQR-tree의 우수성을 입증하였다.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.511-537
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• 2013

Numerous data intensive applications demand the efficient processing of a new type of query, which is called a progressive query (PQ). A PQ consists of a set of unpredictable but inter-related step-queries (SQ) that are specified by its user in a sequence of steps. A conventional DBMS was not designed to efficiently process such PQs. In our earlier work, we introduced a materialized view based approach for efficiently processing PQs, where the focus was on selecting promising views for materialization. The problem of how to efficiently find usable views from the materialized set in order to answer the SQs for a PQ remains open. In this paper, we present a new index technique, called the Dynamic Materialized View Index (DMVI), to rapidly discover usable views for answering a given SQ. The structure of the proposed index is a special ordered tree where the SQ domain tables are used as search keys and some bitmaps are kept at the leaf nodes for refined filtering. A two-level priority rule is adopted to order domain tables in the tree, which facilitates the efficient maintenance of the tree by taking into account the dynamic characteristics of various types of materialized views for PQs. The bitmap encoding methods and the strategies/algorithms to construct, search, and maintain the DMVI are suggested. The extensive experimental results demonstrate that our index technique is quite promising in improving the performance of the materialized view based query processing approach for PQs.

• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.15-26
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• 2007

In this study, a SOHO (Small Office Home Office) bankruptcy prediction model is proposed using Modified Bagging Predictors which is modification of traditional Bagging Predictors. There have been several studies on bankruptcy prediction for large and middle size companies. However, little studies have been done for SOHOs. In commercial banks, loan approval processes for SOHOs are usually less structured than those for large and middle size companies, and largely depend on partial information such as credit scores. In this study, we use a real SOHO loan approval data set of a Korean bank. First, decision tree induction techniques and artificial neural networks are applied to the data set, and the results are not satisfactory. Bagging Predictors which has been not previously applied for bankruptcy prediction and Modified Bagging Predictors which is proposed in this paper are applied to the data set. The experimental results show that Modified Bagging Predictors provides better performance than decision tree inductions techniques, artificial neural networks, and Bagging Predictors.

• Journal of Plant Biology
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• v.9 no.1_2
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• pp.7-16
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• 1966

In order to determine the factors related to site quality, 13 areas of Larch growing in the Kwangung and its vicinity forest as sample plots, were examined. Sample plots included various site classes as well as age classes. Three were divided into two groups (major and minor trees). Average height of dominant trees was determined through messurement of 5 to 6 dominant tree in each sample plots. Average height of dominant 30 year-old trees was the basis for site index. A Standard Yield Table for the larch produced in Kwangnung forest was made by various data, which included age class 5, ranging from 10 to 45 years. The relationship of the height of the trees, the site conditions, and ground vegetation are investigated in this paper. The site indexes of 40 forest class age in 28-B and 28-G forest classes of the larch associations for ground vegetation had comparatively rarge differences due to the sampled areas. The relation of the direction of forest communities to the height and the diameter of the tree shwoed that its communiteis of northest and northwest parts appeared higher valueof the height and the diameter. The diameter and the height of trees were closely realted to each other. The samller the occupied area per tree and the smaller the average distance among trees, the more density was increased. The larger the density was the lower height of the trees. In the ground vegetation of the larch communities, there seems to be a definite correlation between the height of trees and the occupied area per tree or the average distance among the trees. The height of trees and site index of two larch communities were as follow: 28-B forest class site index 20.8, height 24.0m, 28-G forest class site index 18.4, height 20.9m. The ground layer was analyzed by the method of Quadrat(20/20sq. cm) with an interval of 1M. It set up 40 Quadrats of the larch communiteis. The community structure of the ground vegetation of two larch was analyzed, and important value was calculated and then evaluated. The ground vegetation under the larch had developed Burmannii Beauv stratal society below the 28-B and 28-G the forest class. Accordingly, the first important value of Burmannii Beauv was found in two ground vegetation below the larch. Therefore, this species could be quantitatively considered as the forest indicator species. Common species of each community appeared 18 species out of 34 species in the ground vegetation under two larch communities. The ground vegetation of the 28-B forest class showed more than that of the 28-G forest class. the similarity of the ground vegetation was measrued by the Frequency Index Community Coefficient. The differences between the associations were lcearly manifested by the ground vegetation tested by Gleason's Frequency Index of Community Coefficient for the analysis of each stratal society of all associations. According to F.I.C.C. the ground vegetation under two larch(28-B and 28-G) forest classes showed higher value. An investigation into the relationship of physical and chemical properties of soil and site was considered the next step to be taken in the study of the larch site classification.

• Imaging Science in Dentistry
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• v.36 no.2
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• pp.95-101
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• 2006

Purpose : Bony strength is dependent on bone mass and bony structure. So this study was designed to investigate the relationship between the bone mass and bony trabecular characteristics. Subjects and Methods : Study subjects were 51 females (average age 68.6 years) and 20 males (average age 66.4 years). Bone mineral density (BMD, $grams/cm^2$) of proximal femur was measured by a dual energy X-ray absorptiometry (DEXA). Regions of interest (ROIs) were selected from the digitized radiographs of proximal femur. A customized computer program processed morphologic operations (MO) of ROIs. 44 skeletal variables of MO were calculated from ROIs on the Ward's triangle and greater trochanter of femur. WHO BMD classes were predicted by MO variables of the same ROI. Classification and Regression Tree analysis was used for calculating weighted kappa values, sensitivity and specificity of MO. Results : The discriminating factors of morphologic operation were branch point, branch point [per cm sq]. Age also played important role in distinguishing osteoporotic classes. The sensitivity of MO at Ward's triangle and Greater Trochanter was 91.8%, 65.6%, respectively. The specificity of MO was 100% at Ward's triangle and Greater Trochanter. Conclusion : Bony trabecular characteristics obtained using radiological bone morphometric analysis seem to be related to bone mass.