• The Korean Journal of Ecology
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• v.18 no.2
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• pp.275-283
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• 1995

Seral changes in floristic composition during abandoned field succession after shifting cultivation was investigated in eastern Kangwon-Do, Korea. According to the DCA ordination based on the floristic composition, sere of the dominant species was shown as follows: Digitaria sanguinalis, Persicaria spp., Commelina communis etc. in the annual stage (0∼1 years); Erigeron spp., Artemisia spp., Rubus crataegus etc. in the Erigeron-Artemisia stage (2∼6 years); Pinus densiflora, Salix spp., Miscanthus sinensis, Arundinella hirta etc. in the shrub - earlier tree stage (10∼25 years); P. densiflora, Quercus mongolica, Spodiopogon sibiricus etc. in the mid-tree stage (25∼50 years); Q. mongolica, Tripterigium regelii, Lespedeza maximowiczii, Carex siderosticta etc. in the latter tree stage (50∼80 years). In mid-tree stage, size-frequency distribution of P. densiflora was plotted as a platycurtic curve and that of Q. mongolica as a reverse J-shaped curve, which meant P. densiflora was thinned through interspecific competition and Q. mongolica was regenerated by itself in the later tree stage.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.11a
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• pp.334-335
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• 2006

Solid insulation exposed to voltage is degraded by electrical tree process. And the degradation of the insulation is accelerated by voltage application. For this experimental, specimen of electrical tree model is made by XLPE (cross-linked polyethylene). And the size of the specimen is 7*5*7 $mm^3$. Distance of needle and plane is 2 mm. Voltages applied for acceleration test are 12 kV to 15 kV. And distribution characteristic of degraded stage is studied too. As a PD detecting and data process, discharge data acquire from PD detecting system (Biddle instrument). The system presents statistical distribution as phase resolved. Moreover the processing time of electrical tree is recorded to know the speed of degradation according to voltage.

• Spatial Information Research
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• v.19 no.2
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• pp.71-76
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• 2011

In this paper, for using emerging patterns to define and analyze the significant difference of safe and non-safe power load lines, and identify which line is potentially non-safe, we proposed an incremental TFP-tree algorithm for mining emerging patterns that can search efficiently within limitation of memory. Especially, the concept of pre-infrequent patterns pruning and use of two different minimum supports, made the algorithm possible to mine most emerging patterns and handle the problem of mining from incrementally increased, large size of data sets such as power consumption data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2292-2298
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• 2009

In this paper, the lossy image compression algorithm using the quad tree and the bandlets is proposed. The proposed algorithm transforms input images by the discrete wavelet transform (DWT) and represents the geometrical structures of high frequency bands using the bandlets with a 8 block- size. In addition, the proposed algorithm searches the position information of the significant coefficients by using the quad tree algorithm and computes the magnitude and the sign information of the significant coefficients by using the Embedded Image Coding using Zerotrees of Wavelet Coefficients (EZW) algorithm. The compression result by using the quad tree algorithm improves the PSNR performance of high frequency images up to 1 dB, compared to that of JPEG-2000 algorithm and that of S+P algorithm. The PSNR performance by using DWT and bandlets improves up to 7.5dB, compared to that by using only DWT.

• Environmental Engineering Research
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• v.14 no.2
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• pp.102-110
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• 2009

Application of artificial intelligence (AI) approaches in eco-environmental modeling has gradually increased for the last decade. Comprehensive understanding and evaluation on the applicability of this approach to eco-environmental modeling are needed. In this study, we reviewed the previous studies that used AI-techniques in eco-environmental modeling. Decision Tree (DT) and Artificial Neural Network (ANN) were found to be major AI algorithms preferred by researchers in ecological and environmental modeling areas. When the effect of the size of training data on model prediction accuracy was explored using the data from the previous studies, the prediction accuracy and the size of training data showed nonlinear correlation, which was best-described by hyperbolic saturation function among the tested nonlinear functions including power and logarithmic functions. The hyperbolic saturation equations were proposed to be used as a guideline for optimizing the size of training data set, which is critically important in designing the field experiments required for training AI-based eco-environmental modeling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3169-3181
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• 2015

Nowadays, online word-of-mouth has become a powerful influencer to marketing and sales in business. Opinion mining and sentiment analysis is frequently adopted at market research and business analytics field for analyzing word-of-mouth content. However, there still remain several challengeable areas for 1) sentiment analysis aiming for Korean word-of-mouth content in film market, 2) availability of machine learning models only using linguistic features, 3) effect of the size of the feature set. This study took a sample of 10,000 movie reviews which had posted extremely negative/positive rating in a movie portal site, and conducted sentiment analysis with four machine learning algorithms: naïve Bayesian, decision tree, neural network, and support vector machines. We found neural network and support vector machine produced better accuracy than naïve Bayesian and decision tree on every size of the feature set. Besides, the performance of them was boosting with increasing of the feature set size.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.2
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• pp.194-206
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• 1998

In 1977, Local governments' planting regulations for the development projects were established in accordance with the revised building law in Korea. A landscaped area, planting densities of trees and shrubs, a percentage of evergreen plants, minimum tree size and species were prescribed in the planting regulations. But the clauses for an excessive planting density and a high ratio of evergreen trees that the regulations includes, have been gradually in the way to a creative planting design, and raise a problem of poor growth of trees an a disordered planting landscape. Therefore, in this study the present planting regulations of 124 local governments throughout the country were analyzed and compared with 13 foreign local governments' of 4 countries ; Japan, the United States of America, Canada and Singapore. And the linitations and characteristics of the regulations are drawn as follows ; 1. The regulations focus on controlling the green spaces and plantings by quantitative methods such as controlling the number of trees and the landscaped area, which are inadequate for estimating the crown coverage of mature trees, and which areinadequate for estimating the crown coverage of mature trees, and implementing the function of polantings and the use of green spaces. 2. Minimums of tree densities are higher than those of foreign countries, especially higher about 10 times to 100 times than those of the United States of America. 3.Excessive number of evergreen trees and fruit trees should be planted under the present planting regulations, that results in constricting the creativity in planting design. 4. An article for using specific tree size, 2.0ms over in height makes it difficult to use a wide variety of different sizes of trees. And there is no incentive measures when larger trees are planted. To enhance the quality of green spaces and plantings, it is needed that the function and locating of green spaces and plantings have to be emphasized, and the planting density should be concerned about the mature tree size. The incentive measure to use various sizes of trees is also needed, and the regulations to use excessive number of evergreen trees or fruit trees should be loosened.

• Journal of Ecology and Environment
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• v.43 no.3
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• pp.320-331
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• 2019

Background: Dioecious plant species having both male and female plants have been investigated regarding sex-related characteristics such as sex ratio, sex-differential resource requirements, and spatial segregation of the sexes. Habitat loss and fragmentation are major threats to the survival of plant populations, but dioecious species are particularly more prone to such habitat degradation than non-dioecious species because of their dimorphic sexual system. We examined the sex-related demographics of two Ilex cornuta populations being different regarding land use history. Methods: During 2016-2017, we examined I. cornuta trees with a basal diameter ${\geq}1.5cm$ in the Yongsu-ri population (YS population) and the Gotjawal Provincial Park population (GP population). Plant sex (male, female, or unsexed) was identified. The tree size (basal diameter and height of the main stem), clonal production (the ramet numbers per genet), and vitality for each clone were measured. The associations between population, sex, tree size, clonal production, and vitality were examined using ANOVAs and contingency table analyses. Finally, point pattern analyses using O-ring statistics were conducted to assess spatial patterns. Results: Upon excluding unsexed trees, the YS population with 74 trees was significantly male-biased (0.66), while the GP population with only 26 trees had a 1:1 sex ratio. In both populations, males and females did not differ in tree size. Although the mean number of ramets differed significantly between populations, females tended to produce more ramets than males. The proportion of weak trees was significantly higher in the YS than in the GP population. Neither population showed evidence of spatial segregation of the sexes. Conclusions: The two populations of dioecious I. cornuta are characterized by the small number of trees and relatively high frequencies of non-reproductive trees. Both indicate that these populations are quite susceptible to environmental and genetic stochasticity. On the other hand, the differences between populations in sex ratio, clonal production, and vitality suggest that conservation efforts for I. cornuta need to be population-specific. In order to help recover and enable this vulnerable species to persist, it is necessary to find ways to enhance their sexual reproduction and simultaneously reduce habitat disturbances due to anthropogenic activities.