• Journal of Korean Society of Forest Science
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• v.106 no.2
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• pp.213-218
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• 2017

The purpose of this study was to develop age-biomass model in Chungnam region containing random effect. To develop the biomass model by species and tree component, data for Pinus densiflora in central region is collected to 30 plots (150 trees). The mixed model were used to fixed effect in the age-biomass relation for Pinus densiflora, with random effect representing correlation of survey area were obtained. To verify the evaluation of the model for random effect, the akaike information criterion (abbreviated as, AIC) was used to calculate the variance-covariance matrix, and residual of repeated data. The estimated variance-covariance matrix, and residual were -1.0022, 0.6240, respectively. The model with random effect (AIC=377.2) has low AIC value, comparison with other study relating to random effects. It is for this reason that random effect associated with categorical data were used in the data fitting process, the model can be calibrated to fit the Chungnam region by obtaining measurements. Therefore, the results of this study could be useful method for developing biomass model using random effects by region.

• Steel and Composite Structures
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• v.35 no.3
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• pp.439-447
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• 2020

This paper presents two sets of full three-dimensional thermoelastic finite element analyses of superimposed thermo-mechanically loaded Spar Wingskin Joints made with laminated Graphite Fiber Reinforced Plastic composites. The study emphasizes the influence of residual thermal stresses and material anisotropy on the inter-laminar delamination behavior of the joint structure. The delamination has been pre-embedded at the most likely location, i.e., in resin layer between the top and next ply of the fiber reinforced plastic laminated wingskin and near the spar overlap end. Multi-Point Constraint finite elements have been made use of at the vicinity of the delamination fronts. This helps in simulating the growth of the embedded delamination at both ends. The inter-laminar thermoelastic peel and shear stresses responsible for causing delamination damage due to a combined thermal and a static loading have been evaluated. Strain energy release rate components corresponding to the Mode I (opening), Mode II (sliding) and Mode III (tearing) of delamination are determined using the principle of Virtual Crack Closure Technique. These are seen to be different and non-self-similar at the two fronts of the embedded delamination. Residual stresses developed due to the thermoelastic anisotropy of the laminae are found to strongly influence the delamination onset and propagation characteristics, which have been reflected by the asymmetries in the nature of energy release rate plots and their significant variation along the delamination front.

• Journal of Environmental Science International
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• v.19 no.7
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• pp.889-900
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• 2010

The experimental design and response surface methodology (RSM) have been applied to the investigation of the electro-UV complex process for the disinfection of E. coli in the water. The disinfection reactions of electro-UV process were mathematically described as a function of parameters power ($X_1$), NaCl dosage ($X_2$), initial pH ($X_3$) and disinfection time ($X_4$) being modeled by use of the Box-Behnken technique. The application of RSM using the Box-Behnken technique yielded the following regression equation, which is an empirical relationship between the residual E. coli number and test variables in actual variables: Ln (CFU) = 23.57 - 0.87 power - 1.87 NaCl dosage - 2.13 pH - 2.84 time - 0.09 power time - 0.07 NaCl dosage pH + 0.14 pH time + 0.03 $power^2$ + 0.47 NaCl $dosage^2$ + 0.20 $pH^2$+ 0.33 $time^2$. The model predictions agreed well with the experimentally observed result ($R^2$ = 0.9987). Graphical response surface and contour plots were used to locate the optimum point. The estimated ridge of maximum response and optimal conditions for the E. coli disinfection using canonical analysis was Ln 1.06 CFU (power, 15.40 W; NaCl dosage, 1.95 g/L, pH, 5.94 and time, 4.67 min). To confirm this optimum condition, the obtained number of the residual E. coli after three additional experiments were Ln 1.05, 1.10 and Ln 1.12. These values were within range of 0.62 (95% PI low)~1.50 (95% PI high), which indicated that conforming the reproducibility of the model.

• Journal of Forest and Environmental Science
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• v.30 no.2
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• pp.201-207
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• 2014

This study was conducted to estimate the best-fit nonlinear height-DBH growth models for Larix kaempferi in Gangwon and North Gyeongsang province in South Korea. Exponential, Modified Logistic, Chapman-Richards, and Weibull function were used for estimating height-DBH models. To evaluate the selected models, $R^2$, RMSE, MD, MAD, and residual plots were performed in each model. Also, the coefficients and patterns in models of the previous studies were compared with those in this study. The result showed that Weibull equation was found to be the best-fit model with $R^2$=0.9837, RMSE=2.6133, MD=0.0089, and MAD=2.0896. All model parameters in our study had similar values to those in the previous models except for asymptotic parameter a. Our research result showed that Gangwon and North Gyeongsang province were superior to other provinces with regard to height growth for Larix kaempferi.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.347-358
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• 2012

Purpose: Given the mixture components - process variables experimental data, we propose the strategy to find the proper combined model. Methods: Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components - process variables experiments depend on the mixture components - process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. Results: First we choose the reasonable starting models among the class of admissible product models and practical combined models suggested by Lim(2011) based on the model selection criteria and then, search for candidate models which are subset models of the starting model by the sequential variables selection method or all possible regressions procedure. Conclusion: Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. The strategy to find the proper combined model is illustrated with examples in this paper.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.515-530
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• 2009

Evaporation from surface water bodies is influenced by a number of meteorological parameters. The rate of evaporation is primarily controlled by incoming solar radiation, air and water temperature and wind speed and relative humidity. In the present study, influence of weekly meteorological variables such as air temperature, relative humidity, bright sunshine hours, wind speed, wind velocity, rainfall on rate of evaporation has been examined using 35 years(1971-2005) of meteorological data. Statistical analysis was carried out employing linear regression models. The developed regression models were tested for goodness of fit, multicollinearity along with normality test and constant variance test. These regression models were subsequently validated using the observed and predicted parameter estimates with the meteorological data of the year 2005. Further these models were checked with time order sequence of residual plots to identify the trend of the scatter plot and then new standardized regression models were developed using standardized equations. The highest significant positive correlation was observed between pan evaporation and maximum air temperature. Mean air temperature and wind velocity have highly significant influence on pan evaporation whereas minimum air temperature, relative humidity and wind direction have no such significant influence.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.173-191
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• 1999

In this paper we suggest the visualized regression diagnosis tool. The tool is developed by Hangul Delphi on the basis of windows, so users can easily make use of this tool though they do not have the expert knowledge about statistics and computer. Especially, to apply this tool to teaching regression analysis or data analysis, we offer various residual plots in the tool and show the results of analysis graphically.

• Journal of Distribution Science
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• v.20 no.12
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• pp.99-108
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• 2022

Purpose: This study attempted to identify determinants affecting research collaboration and R&D distribution activities, especially regarding facility and equipment leasing of small and medium enterprises (SMEs) in South Korea. The objective of this study was to find the most significant firm characteristics that affect firms participating in an R&D collaboration and distribution program and investing in R&D in terms of leasing payment for equipment. Research design, data, and methodology: This study analyzes which SMEs' characteristics influence external research cooperation activities by examining the SMEs that received government support for equipment leasing using multiple regression analysis and residual plots. The survey combined two databases: 1) a fact-finding survey of participating firms by the Ministry of SMEs and Startups, and 2) leasing information by the Korea Association of University, Research Institute and Industry. Results: The study found that firm size positively impacts R&D investment, R&D collaboration and distribution. Conclusions: The study provided evidence to policymakers and government officials that firms with more employees will more likely participate in government support programs. The study results also prove that government officials believe firm location does not impact R&D investment, R&D collaboration and distribution.

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.103-114
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• 2021

Ultra high strength concrete (UHSC) originally proposed by Richards and Cheyrezy (1995) composed of cement, silica fume, quartz sand, quartz powder, steel fibers, superplasticizer etc. Later, other ingredients such as fly ash, GGBS, metakaoline, copper slag, fine aggregate of different sizes have been added to original UHSC. In the present investigation, the combined effect of coarse aggregate (6mm - 10mm) and steel fibers (0.50%, 1.0% and 1.5%) has been studied on UHSC mixes to evaluate mechanical and fracture properties. Compressive strength, split tensile strength and modulus of elasticity were determined for the three UHSC mixes. Size dependent fracture energy was evaluated by using RILEM work of fracture and size independent fracture energy was evaluated by using (i) RILEM work of fracture with tail correction to load - deflection plot (ii) boundary effect method. The constitutive relationship between the residual stress carrying capacity (σ) and the corresponding crack opening (w) has been constructed in an inverse manner based on the concept of a non-linear hinge from the load-crack mouth opening plots of notched three-point bend beams. It was found that (i) the size independent fracture energy obtained by using above two approaches yielded similar value and (ii) tensile stress increases with the increase of % of fibers. These two fracture properties will be very much useful for the analysis of cracked concrete structural components.

• The Korean Journal of Pesticide Science
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• v.7 no.4
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• pp.264-270
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• 2003

To control effectively and safely Phytophthora root rot caused by Phytophthora capsici on tomato in hydroponic culture, tank-mixing method was considered with two pesticides, metalaxyl copper oxychloride 50% WP and dimethomorph dithianon 38% WP. Forty days after transplanting of tomato seedlings, 4 mL of sporangia of P. capsici (about 25 sporangi/mL) per plot was inoculated around tomato plant roots, and at 5 days after inoculation, the pesticides tank-mixed at three dilution levels, 12,500, 25,000 and 50,000, were drenched 1, 2 or 3 times per plot on the culture cube every 15 days for metalaxyl copper oxychloride 50% WP and every 10 days for dimethomorph dithianon 38% WP. During the drenching period, the residue levels of metalaxyl and dimethomorph in hydroponic culture solution were similar to the initial levels but the level of dithianon was drastically decreased from one day after tank-mixing. In tomato drenched with metalaxyl copper oxychloride 50% WP, metalaxyl was detected $0.02\sim0.04$ mg/kg in all diluted plots. Dimethomorph was detected $0.012\sim0.021$, $0.001\sim0.006$ and $0.001\sim0.003$ mg/kg in 12,500, 25,000 and 50,000 times diluted plots, respectively, while dithianon was detected 0.005, 0.003 mg/kg in 12,500 and 50,000 times diluted plots, respectively. The detection levels of three pesticides were far below compared with the levels of Korean MRLs. Incidences of Phytophthora root rot were not found in all the plots, but phytotoxic responses were recognized in the 12,500 times diluted plots of both pesticides. Based on the above results, the drenching of the culture solution tank-mixed with these pesticides could be recommended as a very safe and effective method to control Phytophthora root rot in tomato in hydroponic culture.