• Title/Summary/Keyword: Tree Structure

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Bit-Vector-Based Space Partitioning Indexing Scheme for Improving Node Utilization and Information Retrieval (노드 이용률과 검색 속도 개선을 위한 비트 벡터 기반 공간 분할 색인 기법)

  • Yeo, Myung-Ho;Seong, Dong-Ook;Yoo, Jae-Soo
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.7
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    • pp.799-803
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    • 2010
  • The KDB-tree is a traditional indexing scheme for retrieving multidimensional data. Much research for KDB-tree family frequently addresses the low storage utilization and insufficient retrieval performance as their two bottlenecks. The bottlenecks occur due to a number of unnecessary splits caused by data insertion orders and data skewness. In this paper, we propose a novel index structure, called as $KDB_{CS}^+$-tree, to process skewed data efficiently and improve the retrieval performance. The $KDB_{CS}^+$-tree increases the number of fan-outs by exploiting bit-vectors for representing splitting information and pointer elimination. It also improves the storage utilization by representing entries as a hierarchical structure in each internal node.

Design and Implementation of the dynamic hashing structure for indexing the current positions of moving objects (이동체의 현재 위치 색인을 위한 동적 해슁 구조의 설계 및 구현)

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    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.6
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    • pp.1266-1272
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    • 2004
  • Location-Based Services(LBS) give rise to location-dependent queries of which results depend on the positions of moving objects. Because positions of moving objects change continuously, indexes of moving object must perform update operations frequently for keeping the changed position information. Existing spatial index (Grid File, R-Tree, KDB-tree etc.) proposed as index structure to search static data effectively. There are not suitable for index technique of moving object database that position data is changed continuously. In this paper, I propose a dynamic hashing index that insertion/delete costs are low. The dynamic hashing structure is that apply dynamic hashing techniques to combine a hash and a tree to a spatial index. The results of my extensive experiments show the dynamic hashing index outperforms the $R^$ $R^*$-tree and the fixed grid.

Adaptive block tree structure for video coding

  • Baek, Aram;Gwon, Daehyeok;Son, Sohee;Lee, Jinho;Kang, Jung-Won;Kim, Hui Yong;Choi, Haechul
    • ETRI Journal
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    • v.43 no.2
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    • pp.313-323
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    • 2021
  • The Joint Video Exploration Team (JVET) has studied future video coding (FVC) technologies with a potential compression capacity that significantly exceeds that of the high-efficiency video coding (HEVC) standard. The joint exploration test model (JEM), a common platform for the exploration of FVC technologies in the JVET, employs quadtree plus binary tree block partitioning, which enhances the flexibility of coding unit partitioning. Despite significant improvement in coding efficiency for chrominance achieved by separating luminance and chrominance tree structures in I slices, this approach has intrinsic drawbacks that result in the redundancy of block partitioning data. In this paper, an adaptive tree structure correlating luminance and chrominance of single and dual trees is presented. Our proposed method resulted in an average reduction of -0.24% in the Y Bjontegaard Delta rate relative to the intracoding of JEM 6.0 common test conditions.

Study on Tree-Structured Database and Language MUMPS (트리형 데이터베이스 및 언어 MUMPS 활용)

  • Im, Ji-Hyeon;Kim, Jin-Doeg
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.108-110
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    • 2019
  • A Database is a collection of data that does not have redundancy, and it is essential to easily use and share information in an information society where the amount of information is increasing. A typical structure of a Database is a relational database and a tree-structure Database. This research studies the programming language MUMPS, which is a tree structure database. This language constructs the database by storing arrays in a dynamic or B-Tree format. Unlike SQL, which must be used in languages such as Java and C #, MUMPS supports language and database independently and can manage data, so the data porting rate is high. In fact, in U.S. hospitals, the MUMPS-based platform has a high market share.

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The Vegetation Structure and Management Solution of the Natural Monument (No.374) Pyeongdae-ri Torreya nucifera forest of Jeju (천연기념물 제374호 제주 평대리 비자나무 숲의 식생구조 및 관리방안)

  • Lee, Won-Ho;Oh, Hae-Sung
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.31 no.3
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    • pp.54-60
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    • 2013
  • This study carried out a phytosociological research by Z.-M. school's method describing vegetation structure and management solution about nutmeg tree's(Torreya nucifera ) forests. The nutmeg tree's forests have developed intervale and hills in warm-temperate evergreen broad-leaved forests zone. The nutmeg tree's forests composed 50 familly, 80 genus, 88 species divided two syntaxa(typical sub-community, Arachniodes aristata sub-community) by species composition and correspond to habitat condition. The nutmeg tree's forests show a uniform forest's structure which composed 3~4 layer of sub-tree and shrub. And it was worthy of special mention which characterized diagnostic species of Camellietea japonicae in the warm-temperate evergreen broad-leaved forests. In case of forests floor, were a high rate in order of Ophiopogon japonicus, Polystichum tripteron, Arisaema ringens. And Oplismenus undulatifolius which represent mantle communities as well. This indicates that the nutmeg tree's forests are exposed by humman effects sustainedly. The nutmeg tree's young trees appeared a high rate at half shade and shade. The vigorous tree species have to spacing cutting instead of the heavy thinning that consist in with a shout of declining astructur and function of the forest ecosystem for maintaining a nutmeg tree's forests. And we suggest for the density regulation of the sub-tree and shrub. In conclusion, need to the continuous monitoring about the vegetation structure and management solution for the sustainable nutmeg tree's forests.

H*-tree/H*-cubing-cubing: Improved Data Cube Structure and Cubing Method for OLAP on Data Stream (H*-tree/H*-cubing: 데이터 스트림의 OLAP를 위한 향상된 데이터 큐브 구조 및 큐빙 기법)

  • Chen, Xiangrui;Li, Yan;Lee, Dong-Wook;Kim, Gyoung-Bae;Bae, Hae-Young
    • The KIPS Transactions:PartD
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    • v.16D no.4
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    • pp.475-486
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    • 2009
  • Data cube plays an important role in multi-dimensional, multi-level data analysis. Meeting on-line analysis requirements of data stream, several cube structures have been proposed for OLAP on data stream, such as stream cube, flowcube, S-cube. Since it is costly to construct data cube and execute ad-hoc OLAP queries, more research works should be done considering efficient data structure, query method and algorithms. Stream cube uses H-cubing to compute selected cuboids and store the computed cells in an H-tree, which form the cuboids along popular-path. However, the H-tree layoutis disorderly and H-cubing method relies too much on popular path.In this paper, first, we propose $H^*$-tree, an improved data structure, which makes the retrieval operation in tree structure more efficient. Second, we propose an improved cubing method, $H^*$-cubing, with respect to computing the cuboids that cannot be retrieved along popular-path when an ad-hoc OLAP query is executed. $H^*$-tree construction and $H^*$-cubing algorithms are given. Performance study turns out that during the construction step, $H^*$-tree outperforms H-tree with a more desirable trade-off between time and memory usage, and $H^*$-cubing is better adapted to ad-hoc OLAP querieswith respect to the factors such as time and memory space.

IRFP-tree: Intersection Rule Based FP-tree (IRFP-tree(Intersection Rule Based FP-tree): 메모리 효율성을 향상시키기 위해 교집합 규칙 기반의 패러다임을 적용한 FP-tree)

  • Lee, Jung-Hun
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.3
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    • pp.155-164
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    • 2016
  • For frequency pattern analysis of large databases, the new tree-based frequency pattern analysis algorithm which can compensate for the disadvantages of the Apriori method has been variously studied. In frequency pattern tree, the number of nodes is associated with memory allocation, but also affects memory resource consumption and processing speed of the growth. Therefore, reducing the number of nodes in the tree is very important in the frequency pattern mining. However, the absolute criteria which need to order the transaction items for construction frequency pattern tree has lowered the compression ratio of the tree nodes. But most of the frequency based tree construction methods adapted the absolute criteria. FP-tree is typically frequency pattern tree structure which is an extended prefix-tree structure for storing compressed frequent crucial information about frequent patterns. For construction the tree, all the frequent items in different transactions are sorted according to the absolute criteria, frequency descending order. CanTree also need to absolute criteria, canonical order, to construct the tree. In this paper, we proposed a novel frequency pattern tree construction method that does not use the absolute criteria, IRFP-tree algorithm. IRFP-tree(Intersection Rule based FP-tree). IRFP-tree is constituted with the new paradigm of the intersection rule without the use of the absolute criteria. It increased the compression ratio of the tree nodes, and reduced the tree construction time. Our method has the additional advantage that it provides incremental mining. The reported test result demonstrate the applicability and effectiveness of the proposed approach.

Single Image-Based 3D Tree and Growth Models Reconstruction

  • Kim, Jaehwan;Jeong, Il-Kwon
    • ETRI Journal
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    • v.36 no.3
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    • pp.450-459
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    • 2014
  • In this paper, we present a new, easy-to-generate system that is capable of creating virtual 3D tree models and simulating a variety of growth processes of a tree from a single, real tree image. We not only construct various tree models with the same trunk through our proposed digital image matting method and skeleton-based abstraction of branches, but we also animate the visual growth of the constructed 3D tree model through usage of the branch age information combined with a scaling factor. To control the simulation of a tree growth process, we consider tree-growing attributes, such as branching orders, branch width, tree size, and branch self-bending effect, at the same time. Other invisible branches and leaves are automatically attached to the tree by employing parametric branch libraries under the conventional procedural assumption of structure having a local self-similarity. Simulations with a real image confirm that our system makes it possible to achieve realistic tree models and growth processes with ease.

Bayesian-based seismic margin assessment approach: Application to research reactor

  • Kwag, Shinyoung;Oh, Jinho;Lee, Jong-Min;Ryu, Jeong-Soo
    • Earthquakes and Structures
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    • v.12 no.6
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    • pp.653-663
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    • 2017
  • A seismic margin assessment evaluates how much margin exists for the system under beyond design basis earthquake events. Specifically, the seismic margin for the entire system is evaluated by utilizing a systems analysis based on the sub-system and component seismic fragility data. Each seismic fragility curve is obtained by using empirical, experimental, and/or numerical simulation data. The systems analysis is generally performed by employing a fault tree analysis. However, the current practice has clear limitations in that it cannot deal with the uncertainties of basic components and accommodate the newly observed data. Therefore, in this paper, we present a Bayesian-based seismic margin assessment that is conducted using seismic fragility data and fault tree analysis including Bayesian inference. This proposed approach is first applied to the pooltype nuclear research reactor system for the quantitative evaluation of the seismic margin. The results show that the applied approach can allow updating by considering the newly available data/information at any level of the fault tree, and can identify critical scenarios modified due to new information. Also, given the seismic hazard information, this approach is further extended to the real-time risk evaluation. Thus, the proposed approach can finally be expected to solve the fundamental restrictions of the current method.

An Improved Multi-resolution image fusion framework using image enhancement technique

  • Jhee, Hojin;Jang, Chulhee;Jin, Sanghun;Hong, Yonghee
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.12
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    • pp.69-77
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    • 2017
  • This paper represents a novel framework for multi-scale image fusion. Multi-scale Kalman Smoothing (MKS) algorithm with quad-tree structure can provide a powerful multi-resolution image fusion scheme by employing Markov property. In general, such approach provides outstanding image fusion performance in terms of accuracy and efficiency, however, quad-tree based method is often limited to be applied in certain applications due to its stair-like covariance structure, resulting in unrealistic blocky artifacts at the fusion result where finest scale data are void or missed. To mitigate this structural artifact, in this paper, a new scheme of multi-scale fusion framework is proposed. By employing Super Resolution (SR) technique on MKS algorithm, fine resolved measurement is generated and blended through the tree structure such that missed detail information at data missing region in fine scale image is properly inferred and the blocky artifact can be successfully suppressed at fusion result. Simulation results show that the proposed method provides significantly improved fusion results in the senses of both Root Mean Square Error (RMSE) performance and visual improvement over conventional MKS algorithm.