• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.4
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• pp.60-72
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• 2019

The purpose of this study was to identify detailed factors that affect visitor satisfactions of the plants on display, environments of pedestrian road and facility of each theme garden by conducting a survey of visitors to Jade Garden. The 400 data including 100 copies per theme garden were used for statistical analysis. The statistical techniques used in the survey analysis include multi-regression analysis, t-test, and analysis of variance(ANOVA). As a result of the analysis, most of theme gardens tended to have the greatest impact on the satisfaction of the plants on display and the lowest level of facility satisfaction. According to detailed factors analysis of the satisfaction of plants on display satisfaction of plant diversity and the method of plant display were most affected in most of the theme gardens. Among them, promoting the satisfaction of plant diversity is necessary to plant various species, but in case of Ginkgo Maze Garden, a type of tree community as one tree(Ginkgo biloba), the satisfaction of plants diversity did not show a rising-up value. Therefore, it was confirmed that the appropriate degree of plants diversity depends on the theme or environment of the garden. In the case of the pedestrian-road-satisfaction, the width of the pedestrian road was the most affected, It was analyzed that whether the point of intersection can be easily available during peak season has a significant impact on the satisfaction of visitors. In the case of facility satisfaction, it was analyzed that the presence of rest and convenience facilities had the most direct influence on visitors, so the facility diversity had the greatest influence. Therefore, it is necessary to more systematically categorize and consider the influential detailed factors such as plants diversity and methods of plant display, width of pedestrian road and facilities diversity for the management and development of the arboretum.

• Journal of The Korean Society of Grassland and Forage Science
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• v.4 no.1
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• pp.35-40
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• 1983

This study was conducted to investigate the effect of some kinds of tree litters covered the soil surface on the germination, establishment, sward composition, and herbage production of the grasses sown by the oversowing method. The litters were leaves of Pinus rigida Miller, Quercus variabilis Blume, Larix leptolepis Gord, and Alnus hirsuta Rupr. The results obtained were as follows; 1. In the Petri dish, germination was affected by grass species and kinds of litters, especially the percolate from Pinus litter seriously suppressed the early germination of small size seeds such as ladino clover and timothy. 2. In the pot, establishment was slightly suppressed in ladino and timothy by the percolate from Pinus litter, while in others it was decreased relatively. 3. Among the 6 species investigated, the small size seeds of ladino clover and timothy and the large size seeds of red clover, they could be early put into the litter spaces and established well. 4. In Larix litter, the establishment percentage of all species were decreased seriously owing to low moisture retention capacity. 5. Grass height and root length were different in kinds of litters and species. 6. The percentages of establishment on each surface treatments of burning, treading, raking, and the control under Quercus tree were 36, 46, 37, and 31%, respectively. 7. The sward percentage of oversown grasses and legumes was 57.8% in burning, 70.9% in treading, 59.6% in raking, and 54.0% in the control. 8. Treading treatment was most effective to destroy existing vegetation and improve soil-seed contact when oversowing and showed the best result. 9. Yield of dry matter per unit area in treading treatment was higher (p<0.05) than those of the other treatments. The above experimental results suggest the importance of direct oversowing on the litters in the mountainous land and forest land.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.105-115
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• 2007

Data mining extracts interesting knowledge from a large database. Among numerous data mining techniques, research work is primarily concentrated on clustering and association rules. The clustering technique of the active research topics mainly deals with analyzing spatial and attribute data. And, the technique of association rules deals with identifying frequent patterns. There was an advanced apriori algorithm using an existing bit-clustering algorithm. In an effort to identify an alternative algorithm to improve apriori, we investigated FP-Growth and discussed the possibility of adopting bit-clustering as the alternative method to solve the problems with FP-Growth. FP-Growth using bit-clustering demonstrated better performance than the existing method. We used chess data in our experiments. Chess data were used in the pattern mining evaluation. We made a creation of FP-Tree with different minimum support values. In the case of high minimum support values, similar results that the existing techniques demonstrated were obtained. In other cases, however, the performance of the technique proposed in this paper showed better results in comparison with the existing technique. As a result, the technique proposed in this paper was considered to lead to higher performance. In addition, the method to apply bit-clustering to GML data was proposed.

• Korean Journal of Environment and Ecology
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• v.27 no.6
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• pp.718-732
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• 2013

The purpose of this study was to provide data for the basic research to found the effective conservation and management plan for the Geumdangsil Pine Forest of Yecheon designated as Natural Monument No. 469. Furthermore, this paper suggest efficient sustainable forest preservation and using. In order to achieve the sustainable forest preservation, this study was to analyse topography, land use, tree growth, soil environment, forest usage and forest management, etc. According to analysis the results, the site area is located in the flatlands where is from 130 to 140 m above sea level. The around forest was transformed into agricultural land. The 565 individuals of Pinus densiflora grows in the forest, whereas, 25 trees was cut down or died. There are signs of 25 stumps. The most of 565 trees' diameter at breast height(DBH) was centerized between 30 cm and 50 cm, moreover, the average life expectancy of trees were 85.4 years. The oldest age of tree was estimated to be 200 years. The Sample trees of rate of branch growth is from 4.3 cm to 5.1 cm per year. The middle branch which is more vigorous growth grow 24.2 cm for 3 years. Moreover, the result of soil physico-chemical properties analysis of 7 plots, 4 categories which is soil organic matter, total nitrogen, available phosphoric acid, specific electrical conductance was generally good, however, the 2 categories which is soil pH, exchangeable cation needed improvement. Currently, the site was not pressured by facilities and usage, however, there might be threaten by agriculture such as encroaching on forest. Therefore, there should establish comprehensive ecosystem management such as facility management, visitors management and operation management In this paper considered 4 fields that is ecosystem management, facility management, visitors management and operation management for sustainable management.

• Journal of Korean Society of Forest Science
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• v.17 no.1
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• pp.1-15
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• 1973

In an effort to improve the major tree species in Korea, the seed of Robinia pseudoacacia, Pinus rigida, Pinus densiflora, Pinus thunbergii and Larix leptolepis were treated with X-ray and thermal neutron at the Brookhaven National Laboratory, and germination rate of the seed and some characteristics of the seedlings from irradiated seed were investigated and the results were summarized as follows. 1. The germination rate of the irradiated seed of Robinia pseudoacacia, Pinus densiflora, Pinus thunbergii and Pinus rigida was decreased, when the irradiation time of thermal neutron increased from 3 hours to 9 hours. The seed of Larix leptolepis was completely died out in all range of irradiation time. 2. The seed of Pinus densiflora, Robinia pseudoacacia and Pinus rigida showed low germination rate, when the dosage of radiation increased in the range of 10,000r-30,000r X-ray. This dosage of radiation was almost lethal to the seed of Pinus thunbergii and Larix leptolepis. 3. The growth rate of radiated Robinia pseudoacacia has been decreased when the dosage of X-ray and thermal neutron increased. However, the trees treated with thermal neutron for 3 hours showed 14.9 percent-increase in seedling height and some thornless individuals appeared in this treatment. 4. Individuals with variegated leaf, rugose leaf and albino were appeared in X-ray and thermal neutron treatment. 5. Abnormal mitosis of somatic cell, cell with two nucleoli, cell with two nuclei and chromosome clump in mitosis of somatic cell were observed in Robinia pseudoacacia irradiated with thermal neutron. 6. Resistanty against pawdery mildew was decreased in Robinia pseudoacacia radiated with X-ray and thermal neutron. 7. Length of stomata did not show any difference however number of stomata per unit area decreased in Robinia pseudoacacia radiated with thermal neutron. The leaves of Robinia pseudoacacia radiated with thermal neutron were thicker than those of non-treated one, but width of palisade tissue was decreased. The most sensitive one among those species to the thermal neutron treatment was Larix leptolepis, followed by Pinus densiflora, Robinia pseudoacacia, Pinus thunbergii and Pinus rigida in the order. In X-ray treatment, the most sensitive one was Larix leptolepis, followed by Pinus densiflora, Pinus thunbergii, Pinus rigida and Robinia pseudoacacia in the order. Morphological, cytological variation of the radiated Robinia pseudoacacia seemed to indicate some possibility to be used for tree improvement.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.201-220
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• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.1-11
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• 2021

The purpose of this study is to find out the main factors affecting air quality in urban physical space factors, and provide clues for environmental improvement. Nine monitoring stations in China's industrial city, Changchun, collected AQI concentration data from January 1, 2018 to December 31, 2019. This paper analyzes the types and distribution characteristics of urban physical facilities within a radius of 300m with the detection station as the center. The monitoring station is divided into three groups, and the difference in floating dust concentration among the three groups in different seasons is analyzed. The results show that AQI concentration is the highest in spring and winter, followed by summer, and the lowest in autumn. The place with the highest concentrations of AQI in spring are F (93.00), D (91.10), I (89.20), in summer are D (69.05), A (67.89), B (84.44), in autumn are I (62.80), G (60.84), D (53.27), D (53.27), in winter are I (95.82), H (95.60), f (94.04). Through SPSS analysis, it shows that the air index in a space with a diameter of 600 meters is related to forest land, grassland, bare land, water space, tree height, building area (average value), and building volume (average value). According to the statistical analysis results of spring and winter with the most serious pollution, forest land area (43,637m², 15.44%) and water surface area (18,736m², 6.63%) accounted for the majority, and group 1 (A, B, C) with the least average building area (448m², 0.17%) and average building volume (10,201m²) had the lowest pollution concentration. On the contrary, group 2 (D, E, F) had the highest AQI concentration, with less or no woodland (1,917m², 0.68%) and water surface area (0m², 0%), and the highest average building area (1,056m², 0.37%) and average building volume (17,470m³). It is confirmed that the characteristics of the area with the highest AQI concentration are that the more the site ratio of tree height above 12m, the smaller the site ratio of bare land, and the lower the pollution degree. On the contrary, the larger the area of bare land, the higher the pollution degree. By analyzing the characteristics of nine monitoring stations in Changchun, it can be seen that the air quality brought by the physical characteristics of urban space is closely related to the above factors.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.2
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• pp.19-25
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• 2023

This study aimed to analyze the current status of planted trees in Seoul Forest and propose improvement plans to improve the naturalness in the park. A comprehensive survey of the trees in the park was conducted, and the data gathered was used to build a list of planting trees suitable for an urban park. The analysis of the characteristics of landscape trees in Seoul Forest by type was about the presence or absence of leaves, and they were classified into deciduous trees, evergreen trees, deciduous shrubs, and evergreen shrubs, and herbaceous plants such as groundcover plants separately classified. The study found that Seoul Forest had 57 species of native and naturalized trees, with 27 deciduous trees, 35 deciduous shrubs, 15 evergreen trees, and 98 evergreen shrubs. The park also had 472 species of herbaceous plants, totaling 320,000. The majority of planted trees in Seoul Forest were native species, comprising 59% of the total planted trees, while naturalized species made up 41%. Furthermore, the ratio of deciduous trees to evergreen trees was 81% to 19%, with deciduous trees being the dominant species. The evergreen trees showed a similar trend, with a total of 23 species, including 15 native and 8 foreign species, accounting for 65% of native species. In addition, the study identified six common deciduous shrubs, including Forsythia koreana, orbaria sorbifolia var. stellipila, Deutzia parviflora, Rhododendron lateritium, and Spiraea prunifolia var. simpliciflora, which are frequently planted in areas with abundant water. The study also revealed that among the 10 evergreen shrub species, 9 were native and 1 was foreign. The study aimed to classify the species planted in Seoul Forest into native and foreign species and to provide a data-driven plan to encourage the planting of native species. This study offers valuable insights into planting planning and design for urban parks, which is essential for enhancing naturalness, as most studies have primarily focused on usage patterns and satisfaction in urban parks. By promoting the planting of native species, the naturalness of Seoul Forest can be improved.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.439-446
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• 2011

In this research, enhanced land-cover classification methods using high-resolution satellite image (HRSI) and GIS in terms of practicality and accuracy was proposed. It aims for understanding non-point pollutant origin/loading, assessment the efficiency of rainfall storage/infiltration facilities and sounds water-environment management. The result of applying enhanced land-cover classification methods to the urban region verifies that roof and road area are including various vegetations such as roof garden, flower bed in the median strip and street tree. This accounts for 3% of total study area, and more importantly it was counted as impervious area by GIS alone or conventional indoor work. The feasibility of the method was assessed by applying to rainfall-runoff analysis for three weak rainfall in the range of 7.1-10.5 mm events in 2000, Chiba, Japan. A good agreement between simulated and observed runoff hydrograph was obtained. In comparison, the hydrograph simulated with land-use parameters by the detailed land-use information of 10m grid had an error between 31%~71%, while enhanced method showed 4% to 29%, and showed the improvement particularly for reproducing observed peak and recession flow rate of hydrograph in weak rainfall condition.