• Korean Journal of Heritage: History & Science
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• v.42 no.1
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• pp.88-99
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• 2009

This study was conducted to formulate management guidelines for Natural monumental old trees in Korea through survey of tree vigor and analysis of growing environments. A total of 20 old trees designated as natural monuments in Seoul, Incheon, and Gyeonggi Province were surveyed. The biological characteristics were surveyed with 4 items of species, ages and height of trees. The surrounding environments were surveyed with 2 items of location types and surroundings. The root conditions were surveyed with 2 items of denudation and molding depth. The health conditions were surveyed with 5 items of withering rate, cavity size, bark breakaway rate, damages by blight and insects, and growing tips. The soil conditions were surveyed with 6 items of PH, organic contents, valid phosphoric acid, transposal cations(K, Ca) and soil compaction. On the basis of outcomes of these research items, mutual relations among locations, growings and soil conditions of old trees were analyzed by carring out cross tabulation, correlation, and simple and multiple regression. Management guidelines were presented searching the factors effecting on the health of the monumental old trees. On the biological characteristics, the old trees designated as natural monuments were Pinus bungeana(4 trees), Juniperus chinensis(3 trees), Ginkgo biloba(3 trees), Poncirus trifoliata(2 trees). Actinidia arguta, Wisteria floribunda, Thuja orientalis, Quercus mongolica, Sophora japonica, Fraxinus rhynchophylla, Zelkova serrata, and Pinus densiflora. The tree height ranged from 4.2 to 39.2m, and root collar rounds ranged from 1.01 to 15.2m. On the surrounding environments, The location types ; Gardens(4), historical sites(5), residental sections(3) open agricultural fields(3), mountain hills(3), and near ocean beaches(1) and stream site(1). The surroundings ; 75% denudation of roots, molded more than 10cm except 4 trees(25%). On the health conditions, 1)Withering rate ; Ginkgo biloba(20%) in Yongmoon temple, (5%) in Saki-ri, kanwha-gun, and others had no withering rate. 2) Cavity size ; all subject had $5{\sim}100cm^3$ of cavity. 3) Bark breakaway rate ; Pinus bungeana in Soosong-dong, in the shrine of Confucius, in Samchung-dong, especially high rate of cavity(5~50%) in Seoul area and in Saki-ri, Kangwha-gun were high 45% brakeaway rate. 4) Damages by blight and insects was slight due to managements. 5Growing tips ; In cases of Juniperus chinensis in Changdeok palace and SunnogDang, seoul, growing tips were 1/2, presumably cause by air pollution, and in cases of Fraxinus rhynchophylla in Paju city and Pinus densiflora in BacksaDorip-ri, Icheon city, growing tips were fine, presumably because there were no moldings. On the Soil conditions, Soil pH ranged from 5.2 to 8.3, organic matter contents from 12% to 56%, phosphorus contents from 104 to 618ppm, soil compaction ranged from 7 to 28mm( among them, Denudation was severe with 21~28mm soil compactions in cases of Pinus bungeana in Soosong -dong, Thuja orientalis in Samchung -dong, Ginkgo biloba in the shrine of Confucius and in Yongmoon temple.) Results of cross tabulation, correlation, and regression analysis showed that molding depth was the most serious factor to deteriorate the tree vigor and cambium conductivity. In addition, soil acidity, organic matter contents, disease and insect damages and cambial detachment were also related to the tree vigor. Additional research of these relationships will be needed to conduct more detailed studies. Based on the relationships between the tree vigor and growing environments, it is considered that old trees should be managed to give them more growing spaces and less abuses. Also, molded soils should be removed and further soil-molding around the tree collar should be prohibited. For the construction of systematic management and removal of harmful factors, appropriative management according to spices, persistent monitering of damaged cases and construction of management system through the accumulation of data on the relationships of soil conditions are required.

• Journal of Ecology and Environment
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• v.32 no.2
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• pp.87-96
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• 2009

Pinus thunbergii plantations in Pohang-si, Gyeongsangbuk-do, Korea, are of low ecological quality, with arrested succession and a high proportion of ruderal species. To improve the quality of the habitat, we created canopy gaps ($\sim42\;m^2$) and monitored changes in abiotic (light availability, canopy openness) and biotic (survival and growth of seedlings and understory communities) variables in 2007 and 2008 in plots that had received one of five types of treatment: cutting of canopy trees and removal of the understory (CU), cutting of canopy trees only (C), girdling of canopy trees and removal of the understory (GU), girdling of canopy trees (G) or control. Each treatment was applied to three replicate plots. Abiotic variables did not significantly differ among treatments. Survival rates of target species were slightly lower in the CU, G and control conditions. Based on logistic regression analysis, the only significant growth factor affecting survival was height growth. Positive effects of seedling height and leaf area growth on survival were also detected, but did not reach statistical significance. In treatment G, gradual improvement of overstory conditions and mitigation of competition by limitation of disturbance to the understory community were likely to have promoted seedling growth. There were no significant effects of gap treatments on changes in species abundance (cover and richness) and composition of understory between the study years. This result implies that the small gaps created in our study may be below the threshold size to affect understory growth. However, the results of this study are based on a short-term investigation of only two years. Long-term research is strongly recommended to clarify the effects of gap treatment on plant communities in afforested areas.

• Journal of the Korean Institute of Landscape Architecture
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• v.32 no.3
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• pp.51-59
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• 2004

Focusing on WBGT(Wet Bulb Globe Thermometer Index) according to the LAI(Leaf Area Index) variation of trees, this study verifies the effects of urban shade trees on the outdoor thermal environment. As for methodology, air$.$globe temperature, air humidity and WBGT were measured under three shade trees whose LAIs were 2.1, 4.0 and 8.2 respectively at midday(12:00-13:00) of 14 sunny days from the 4th through the 29th day of September 2003. Those factors were also measured at the unshaded areas and compared with the values of shaded areas. The measured site was paved with interlocking concrete bricks. The measurements were analyzed through the ANCOV A(Analysis of Covariance) and the regression routines of SPSS11 for windows (SPSS Inc., 2001). The major findings were as follows. 1. The direct correlation between WBGT and LAI was very low. On the contrary, the WBGT showed close correlation with air$.$globe temperature and air humidity, and the LAI also showed very close correlation with globe temperature. These results tell that dominant shading effect by the tree is on the screening of direct solar radiation which lower the globe temperature and WBGT consequently. 2. While the average globe temperatures and WBGT at unshadowed area were 40.4$^{\circ}C$ and 26.2$^{\circ}C$ respectively, the former under the shade tree with LAI 2.1, 4.0 and 8.2 were 34.5$^{\circ}C$, 32.6$^{\circ}C$ and 30.2$^{\circ}C$, and the latter were 24.6$^{\circ}C$, 24$^{\circ}C$ and 23.4$^{\circ}C$ respectively. 3. The relationship between LAI(x) and WBGT(y) can be presented with the following equation: y = 24.23+1.53 $e^{-x}$+0.36x $e^{-x}$+0.46 $x^2$ $e^{-x}$ ($R^2$ =.98) =.98)

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.15-19
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• 2022

This study is to understand the relationship between turnover and various conditions. Turnover refers to workers moving from one company to another, which exists in various ways and forms. Currently, a large number of workers are considering many turnover rates to satisfy their income levels, distance between work and residence, and age. In addition, they consider changing jobs a lot depending on the type of work, the decision-making ability of workers, and the level of education. The company needs to accept the conditions required by workers so that competent workers can work for a long time and predict what measures should be taken to convert them into long-term workers. The study was conducted because it was necessary to predict what conditions workers must meet in order to become long-term workers by comparing various conditions and turnover using regression and decision trees. It used Microsoft Azure machines to produce results, and it found that among the various conditions, it looked for different items for long-term work. Various methods were attempted in conducting the research, and among them, suitable algorithms adopted algorithms that classify various kinds of algorithms and derive results, and among them, two decision tree algorithms were used to derive results.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.135-138
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• 1998

본 논문에서는 트리 기반 모델링 기법 중 하나인 CART(Classification And Regression Trees) 방법을 이용하여, 운율구 추출, 운율구 사이의 휴지 기간, 음소 지속 시간을 모델링 하고자 한다. 총 400문장(약 33분)의 코퍼스를 수집한 후, 그 중 240문장(약 20분)을 이용하여 결정 트리와 회귀 트리를 학습시키고 160문장(약 13분)에 대해 실험하였다. 운율구 경계를 결정하는 결정 트리의 오류율은 14.6%이었고, 운율구 사이의 휴지 기간과 음소 지속 시간을 예측하는 회귀 트리들의 평균 제곱 오류근(RMSE)이 각각 132.61msec, 21.97msec이었다.

• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.535-549
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• 2022

Damage to forests, such as broken or falling trees, has increased due to the increased intensity and frequency of abnormal climate events, such as strong winds and heavy rains. However, it is difficult to respond to them in advance based on prediction since structural defects such as cavities and bumps inside trees are difficult to identify with a visual inspection. Non-invasive sonic tomography (SoT) is a method of estimating internal defects while minimizing physical damage to trees. Although SoT is effective in diagnosing internal defects, its accuracy varies depending on the species. Therefore, it is necessary to analyze the reliability of its measurement results before applying it in the field. In this study, we measured internal defects in wood by cross-applying destructive resistance micro drilling on old Pinus densifloraSiebold & Zucc. and Ginkgo bilobaL., which are representative tree species in Korea, to verify the reliability of SoT and compared the evaluation results. The t-test for the mean values of the defect measurement between the two groups showed no statistically significant difference in pine trees and some difference in ginkgo trees. Linear regression analysis results showed a positive correlation with an increase in defects in SoT images when the defects in the drill resistance graph increased in both species.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1253-1262
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• 2014

Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.593-601
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• 2017

In this paper, we constructed the model of production/investment, distribution, and screening by using variables that can be considered at each stage according to the value chain stage of the movie industry. To increase the predictive power of the model, a regression analysis was used to derive meaningful variables. Based on the given variables, we compared the difference in predictive power between the artificial neural network, which is a machine learning analysis method, and the decision tree analysis method. As a result, the accuracy of artificial neural network was higher than that of decision trees when all variables were added in production/ investment model and distribution model. However, decision trees were more accurate when selected variables were applied according to regression analysis results. In the screening model, the accuracy of the artificial neural network was higher than the accuracy of the decision tree regardless of whether the regression analysis result was reflected or not. This paper has an implication which we tried to improve the performance of movie prediction model by using machine learning analysis. In addition, we tried to overcome a limitation of linear approach by reflecting the results of regression analysis to ANN and decision tree model.

• Journal of Korean Society for Quality Management
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• v.36 no.1
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• pp.72-79
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• 2008

The policy for credit card approval/disapproval is based on the applier's personal and financial information. In this paper, we will analyze 2 credit card approval data with several classification methods. We identify which variables are important factors to decide the approval of credit card. Our main tool is an open-source statistical programming environment R which is freely available from http://www.r-project.org. It is getting popular recently because of its flexibility and a lot of packages (libraries) made by R-users in the world. We will use most widely used methods, LDNQDA, Logistic Regression, CART (Classification and Regression Trees), neural network, and SVM (Support Vector Machines) for comparisons.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.239-246
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• 2003

Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.