• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.22-25
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• 1999

A dynamic explicit finite element code for simulating sheet forming processes has been developed The code utilises the discrete Kirchhoff shell element and contact force is treated by a conventional penalty method. In order to reduce the computational cost a new and robust contact searching algorithm has been developed and implemented into the code. in the method a hierarchical structure of tool segments called a tree structure is built for each tool at the initial stage of the analysis Tree is built in a way to divide a trunk to 8 sub-trunk 2 in each direction until the lowest level of the tree(leaf) contains exactly one segment of the tool. In order to have a well-balanced tree each box on each sub level contains one eighth of the segments. Then at each time step contact line from a node comes out of the surface of the tool. Simulation of various sheet forming processes were performed to verify the validity of the developed code with main focus on he usefulness of the developed contact searching algorithm.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2717-2722
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• 2009

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.175-177
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• 2018

This paper proposes an algorithm to speed up block structure partition of quad tree plus binary tree (QTBT) in Joint Exploration Test Model (JEM) encoder. The proposed fast encoding of QTBT block partition employs three spatially neighbor coded blocks, such as left, top-left, and top of current block, to early terminate QTBT block structure pruning. The propose algorithm is organized based on statistical similarity of those spatially neighboring blocks, such as block depths and coded block types, which are coded with overlapped block motion compensation (OBMC) and adaptive multi transform (AMT). The experimental results demonstrate about 30% encoding time reduction with 1.3% BD-rate loss on average compared to the anchor JEM-7.1 software under random access configuration.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.228-237
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• 2010

Although conventional index structures provide various nearest-neighbor search algorithms for high-dimensional data, there are additional requirements to increase search performances as well as to support index scalability for large scale data. To support these requirements, we propose a distributed high-dimensional indexing structure based on cluster systems, called a Distributed Vector Approximation-tree (DVA-tree), which is a two-level structure consisting of a hybrid spill-tree and VA-files. We also describe the algorithms used for constructing the DVA-tree over multiple machines and performing distributed k-nearest neighbors (NN) searches. To evaluate the performance of the DVA-tree, we conduct an experimental study using both real and synthetic datasets. The results show that our proposed method contributes to significant performance advantages over existing index structures on difference kinds of datasets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1228-1234
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• 2007

In this paper, we develop the thinking extension education program for the gifted students of information and prove the validity and effectiveness of the proposed model by presenting the Tic-tac-toe problem as the practical example of the information-gifted students. This model consists of four phases which has the game tree as data structure and the search of game lee as control structure. And the search of game tree becomes the basis of the thinking extension education program. This model gives the help for students to learn representing the problem as tree structure and solving the problem of tree structure using the search method of game tree. The internal ability of the information-gifted for thinking extension of this education program contains the fluency, perceptiveness, originality, power of concentration, imaginative power, analyzing skills, pattern recognition, space sense, synthesizing, problem-solving.

• Journal of Forest and Environmental Science
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• v.37 no.3
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• pp.169-192
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• 2021

Sacred groves are large areas of virgin or human-modified landscape with a diverse range of species that have been protected by local people for centuries due to cultural, religious beliefs, and taboo that the deities live in them and protect the villagers from various calamities. The present study was carried out for quantitative analysis of diversity, population structure, regeneration and conservation status of tree species in the four 36.86 ha sacred groves of Jhargram district in West Bengal. Tree species composition, population structure and regeneration status were analyzed by randomly establishing of 1 ha subplots within the sacred groves. Density, frequency, basal area, abundance, evenness, and other diversity indices were calculated for adult trees with girth at breast height (GBH) >31 cm. A total of 146 tree species belonging to 116 genera distributed in 44 families from 21 orders were recorded. Pterospermum suberifolium, family Malvaceae showed the highest Species Importance Value Index (SIVI, 21.33) and Fabaceae showed the highest Family Importance Value Index (FIVI, 35.59) values respectively. Individuals are categorised into three groups, seedling, sapling and adult based on girth classes. The majority of tree species exhibited good (52.74%) regeneration followed by fairly (24.66%), poor (15.75%) and no regeneration (6.85%) respectively. With the healthy existence of the sacred grove, the overall population structure of tree species showed a strong regeneration potential. The current data will be useful in determining the current status of tree species and will be used by the forest department, politicians, and conservationists to establish management plans for the conservation of priority species in the region. Since the study areas were sacred groves, tribal members were keen to preserve them due to their religious significance.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.305-312
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• 2001

Recently, high-dimensional index structures have been required for similarity search in such database applications s multimedia database and data warehousing. In this paper, we propose a new cell-based signature tree, called CS-tree, which supports efficient storage and retrieval on high-dimensional feature vectors. The proposed CS-tree partitions a high-dimensional feature space into a group of cells and represents a feature vector as its corresponding cell signature. By using cell signatures rather than real feature vectors, it is possible to reduce the height of our CS-tree, leading to efficient retrieval performance. In addition, we present a similarity search algorithm for efficiently pruning the search space based on cells. Finally, we compare the performance of our CS-tree with that of the X-tree being considered as an efficient high-dimensional index structure, in terms of insertion time, retrieval time for a k-nearest neighbor query, and storage overhead. It is shown from experimental results that our CS-tree is better on retrieval performance than the X-tree.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.

• Wind and Structures
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• v.18 no.1
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• pp.69-82
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• 2014

Flow around a small white fir tree was investigated with varying the length of the bottom trunk (hereafter referred to as bottom gap). The velocity fields around the tree, which was placed in a closed-type wind tunnel test section, were quantitatively measured using particle image velocimetry (PIV) technique. Three different flow regions are observed behind the tree due to the bottom gap effect. Each flow region exhibits a different flow structure as a function of the bottom gap ratio. Depending on the gap ratio, the aerodynamic porosity of the tree changes and the different turbulence structure is induced. As the gap ratio increases, the maximum turbulence intensity is increased as well. However, the location of the local maximum turbulence intensity is nearly invariant. These changes in the flow and turbulence structures around a tree due to the bottom gap variation significantly affect the shelter effect of the tree. The wind-speed reduction is increased and the height of the maximum wind-speed reduction is decreased, as the gap ratio decreases.

• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.984-990
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• 2007

As the amount of electronic documents increases explosively, automatic text categorization methods are needed to identify those of interest. Most methods use machine learning techniques based on a word set. This paper introduces a new method, called FPTC (FP-Tree based Text Classifier). FP-Tree is a data structure used in data-mining. In this paper, a method of storing text sentence patterns in the FP-Tree structure and classifying text using the patterns is presented. In the experiments conducted, we use our algorithm with a #Mutual Information and Entropy# approach to improve performance. We also present an analysis of the algorithm via an ordinary differential categorization method.