• Journal of Forest and Environmental Science
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• v.39 no.3
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• pp.119-127
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• 2023

In this study, quantitative models were applied to case parks to estimate the carbon reduction by trees, which was compared and analyzed at the tree and park levels. At the tree level, quantitative models of carbon storage and uptake differed by up to 7.9 times, even for the same species and size. At the park level, the carbon reduction from quantitative models varied by up to 3.7 times for the same park. In other words, carbon reduction by quantitative models exhibited considerable variation at the tree and park levels. These differences are likely due to the use of different growth environment coefficients and annual diameter at breast height growth rates and the overestimation of carbon reduction due to the substitution of the same genus and group model for each tree species. Extending the annual carbon uptake per unit area of the case park to the total park area of Chuncheon a carbon uptake ranging from a minimum of 370.4 t/yr and a maximum of 929.3 t/yr, and the difference can reach up to 558.9 t/yr. This is equivalent to the carbon emissions from the annual household electricity consumption of approximately 2,430 people. These results suggest that the indiscriminate application of quantitative models to estimate carbon reduction in urban trees can lead to significant errors and deviations in estimating carbon storage and uptake in urban greenspaces. The findings of this study can serve as a basis for estimating carbon reduction in urban greening research, projects, and policies.

• Journal of Food Hygiene and Safety
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• v.28 no.2
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• pp.168-173
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• 2013

This study was carried out to develop and validate predictive models of E. coli O157:H7 growth. Growth data of E. coli O157:H7 in Paprika were collected at 12, 24, 30 and $36^{\circ}C$. The population increased into 3.0 to 3.8 log10 CFU/g within 4 days, then continued to increase at a slower rate through 10 days of storage at $12^{\circ}C$. The lag time (LT) and maximum specific growth rate (SGR) obtained from each primary model was then modeled as a function of temperature using Davey and square root equations, respectively. For interpolation of performance evaluation, growth data for a mixture of E. coli O157:H7 were collected at time intervals in paprika incubated at the different temperatures, which was not used in model development. Results of model performance for interpolation data demonstrated that induced secondary models showed acceptable goodness of fit. Relative errors in the LT and SGR model for interpolation data (18 and $27^{\circ}C$) was 100%, which show acceptable goodness of fit and validated for interpolation. The primary and secondary models developed in this study can be used to establish tertiary models to quantify the effects of temperature on the growth of E. coli O157:H7 in paprika.

• Journal of Korean Society of Forest Science
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• v.90 no.5
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• pp.650-662
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• 2001

The growth and yield models for five different kinds of natural forest types were systemically developed in the natural Broadleaved-Korean pine Forests in Northeast China. The data were collected from 359 temporary plots and 58 permanent plots with area ranged from 0.06 ha to 1.0 ha, ranging in stand age from 43 to 364 years. The Site Class Index (SCI) was introduced to evaluate site quality and the Crown Competition Factor (CCF) was selected as a measure of stand density for the mixed natural forest. The Chapman-Richards function was adopted to develop SCI equation and height-diameter curve. The Schumacher growth function was selected as base model to develop the DBH, basal area, and stand volume growth models by using re-parameterized method. In modeling mean DBH and basal area growth, it was found that the asymptotic parameter A of Schumacher function was exponentially related to site quality (SCI) and stand density (CCF). The rate parameter k was related to stand density and it was independent of SCI. Several validation measures for predicted stand variables were evaluated in the growth and yield models using independent data sets. The results indicated that relative mean errors (RME) in predicted stand attributes were less than ${\pm}5%$ and the estimated precision values of the stand variables were all greater than 95%.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.233-243
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• 2001

중장기 수요예측을 위해 자주 사용되는 방법으로 확산모형과 성장곡선모형을 들 수 있다. 본 논문에서는 이들 방법론의 성격 및 실제 적용에 있어 모수추정에 따른 문제점들을 살펴보고, 모수추정을 효율적으로 수행하기 위한 전략을 제시한다. 또한 실제 자료에 각 방법론들을 적용하여 예측결과를 비교한다.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.229-239
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• 2020

This article aims to measure the impact of economic growth and urbanization on poverty reduction in Vietnam, and verify whether economic growth and urbanization will help reduce poverty rates. Data for this study are tabular data related to growth, urbanization and poverty at the provincial level for the period of nine years, from 2006 to 2014 provided by the Vietnam General Statistics Office and the Vietnam General Department of Customs. The level of economic growth and urbanization mentioned in the study is reflected in such indicators as GDP value, exports value, imports value, urbanization rate and employment rate. The authors used logistic regression models with fixed-effects and logistic regression models with random effects. With 5% confidence level tested by the Chi-Square test of Hausman trial with the fixed-effect model, research results show that: (1) factors with significant negative impact on the poverty rate include imports value, urbanization rate and, employment rate; (2) factors that do not affect the poverty rate include exports value and GDP value. Based on the research results, this study proposes a number of policy recommendations to help promote economic growth, to sustain the urbanization process, and to contribute directly and positively to poverty reduction in Vietnam.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.195-202
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• 2023

In this study, we sought to compare and evaluate the accuracy and predictive performance of machine learning algorithms for estimating the growth of individual Larix kaempferi trees in Gangwon Province, Korea. We employed linear regression, random forest, XGBoost, and LightGBM algorithms to predict tree growth using monitoring data organized based on different thinning intensities. Furthermore, we compared and evaluated the goodness-of-fit of these models using metrics such as the coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE). The results revealed that XGBoost provided the highest goodness-of-fit, with an R² value of 0.62 across all thinning intensities, while also yielding the lowest values for MAE and RMSE, thereby indicating the best model fit. When predicting the growth volume of individual trees after 3 years using the XGBoost model, the agreement was exceptionally high, reaching approximately 97% for all stand sites in accordance with the different thinning intensities. Notably, in non-thinned plots, the predicted volumes were approximately 2.1 m³ lower than the actual volumes; however, the agreement remained highly accurate at approximately 99.5%. These findings will contribute to the development of growth prediction models for individual trees using machine learning algorithms.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.130-140
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• 1998

Studies present a guide to parameter estimation of software reliability models using SAS JMP. In this paper, we consider only software reliability growth model(SRGM), where mean value function has a S-shaped growth curve, such as Yamada et al. model, and ohba inflection model. Besides these stochastic SRGM, deterministic SRGM's, by fitting Logistic and Gompertz growth curve, have been widely used to estimate the error content of software systems. Introductions or guide lines of JMP are concerned. Estimation of parameters of Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is discussed, along with the variability in the estimates or error sum of squares. This paper have shown that JMP can be an effective tool I these research.

• International Journal of Reliability and Applications
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• v.7 no.2
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• pp.155-166
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• 2006

Many software reliability growth models (SRGMs) based on nonhomogeneous Poisson process (NHPP) have been developed and applied in practice. NHPP SRGMs are characterized by their mean value functions. Mean value functions are usually derived from differential equations representing the fault detection/removal process during testing. In this paper such differential equations are regarded as frameworks for generating mean value functions. Currently available frameworks are theoretically discussed with respect to capability of representing the fault detection/removal process. Then two general frameworks are proposed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.1
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• pp.27-35
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• 2015

The material properties of crack growth models at an elevated temperature were derived from the results of numerous crack growth tests for Mod.9Cr-1Mo (ASME Grade 91) steel specimens under fatigue loading and creep loading at an elevated temperature. These crack growth models were needed for defect assessment under creep-fatigue loading. The mathematical crack growth rate models for fatigue crack growth (FCG) and creep crack growth (CCG) were determined based on the test results, and the models were compared with those of the French design code RCC-MRx to investigate the conservatism of the code. The French design code RCC-MRx provides an FCG model and a CCG model for Grade 91 steel in Section III Tome 6. It was shown that the FCG model of RCC-MRx is conservative, while the CCG model is non-conservative compared with the present test data. Thus, it was shown that further validation of the property was required. Mechanical strength tests and creep tests were also conducted, and the test results were compared with those of RCC-MRx.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.62-69
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• 2011

Six commonly used non-linear growth functions were fitted to individual tree height-dbh data of eight major tree species measured by the $5^{th}$ National Forest Inventory in Chungcheong province. A total of 2,681 trees were collected from permanent sample plots across Chungcheong province. The available data for each species were randomly splitted into two sets: the majority (90%) was used to estimate model parameters and the remaining data (10%) were reserved to validate the models. The performance of the models was compared and evaluated by $R^2$, RMSE, mean difference (MD), absolute mean difference (AMD) and mean difference(MD) for diameter classes. The combined data (100%) were used for final model fitting. The results showed that these six sigmoidal models were able to capture the height-diameter relationships and fit the data equally well, but produced different asymptote estimates. Sigmoidal growth models such as Chapman-Richards, Weibull functions provided the most satisfactory height predictions. The effect of model performance on stem volume estimation was also investigated. Tree volumes of different species were computed by the Forest Resources Evaluation and Prediction Program using observed range of diameter and the predicted tree total height from the six models. For trees with diameter less than 30 cm, the six height-dbh models produced very similar results for all species, while more differentiation among the models was observed for large-sized trees.