• Korean Journal of Soil Science and Fertilizer
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• v.43 no.3
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• pp.356-362
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• 2010

This research studied the bio-methane potential of several waste biomass materials as alternative sources for biogas production, and the laboratory procedure for measuring the biochemical methane potential was described. The wastes from four agro-industries (sewage, livestock, food wastewater treatment sludge and cattle rumen substance generating in slaughter house) were evaluated as substrates for the assay of biochemical methane potential. In order to estimate the ultimate methane yield, two empirical equations (modified Gompertz equation and exponential equation) was investigated. The ultimate methane yield of sewage, livestock, food sludge and lumen substance estimated by the modified Gompertz equation were 0.086, 0.147, 0.146, and 0.121 L $CH_{4}\;g^{-1}\;VS_{added}$, respectively. The ultimate methane yield estimated by the exponential equation were 0.109, 0.246 and 0.174 L $CH_{4}\;g^{-1}\;VS_{added}$ in sewage, livestock sludge and lumen substance. And the ultimate methane yield estimated by the exponential equation showed more high values in the range of 26.7 ~67.3% than the ultimate methane yield estimated by the modified Gompertz equation.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.6
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• pp.19-26
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• 2010

Batch experiments were conducted to investigate growth and nutrient removal performance of microalgae Chlorella vulgaris by using piggery wastewater in different concentration of pollutants and the common growth models (logistic, Gompertz and Richards) were applied to compare microalgal growth parameters. Removal of nitrogen (N) and phosphorus (P) by Chlorella vulgaris showed correlation with biomass increase, implying nutrient uptake coupled with microalgae growth. The higher the levels of suspended solids (SS), COD and ammonia nitrogen were in the wastewater, the worse growth of Chlorella vulgaris was observed, showing the occurrence of growth inhibition in higher concentration of those pollutants. The growth parameters were estimated by non-linear regression of three growth curves for comparative analyses. Determination of growth parameters were more accurate with population as a variable than the logarithm of population in terms of R square. Richards model represented better fit comparing with logistic and Gompertz model. However, Richards model showed some complexity and sensitivity in calculation. In the cases tested, both logistic and Gompertz equation were proper to describe the growth of microalgae on piggery wastewater as well as easy to application.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6B
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• pp.399-406
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• 2012

The objective of this research is to develop greenhouse gas generation models and estimation method of their parameters for solid waste landfills. Two models obtained by differentiating the Modified Gompertz and Logistic models were employed to evaluate two parameters of a first-order decay model, methane generation potential ($L_0$) and methane generation rate constant (k). The parameters were determined by the statistical comparison of predicted gas generation rate data using the two models and actual landfill gas collection data. The values of r-square obtained from regression analysis between two data showed that one model by differentiating the Modified Gompetz was 0.92 and the other model by differentiating the Logistic was 0.94. From this result, the estimation methods showed that $L_0$ and k values can be determined by regression analysis if landfill gas collection data are available. Also, new models based on two models obtained by differentiating the Modified Gompertz and Logistic models were developed to predict greenhouse gas generation from solid waste landfills that actual landfill generation data could not be available. They showed better prediction than LandGEM model. Frequency distribution of the ratio of Qcs (LFG collection system) to Q (prediction value) was used to evaluate the accuracy of the models. The new models showed higher accuracy than LandGEM model. Thus, it is concluded that the models developed in this research are suitable for the prediction of greenhouse gas generation from solid waste landfills.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.192-200
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• 2021

In the mid of the December 2019, the virus has been started to spread from China namely Corona virus. It causes fatalities globally and WHO has been declared as pandemic in the whole world. There are different methods which can fit such types of values which obtain peak and get flattened by the time. The main aim of the paper is to find the best or nearly appropriate modeling of such data. The three different models has been deployed for the fitting of the data of Coronavirus confirmed patients in Pakistan till the date of 20^th November 2020. In this paper, we have conducted analysis based on data obtained from National Institute of Health (NIH) Islamabad and produced a forecast of COVID-19 confirmed cases as well as the number of deaths and recoveries in Pakistan using the Logistic model, Gompertz model and Auto-Regressive Integrated Moving Average Model (ARIMA) model. The fitted models revealed high exponential growth in the number of confirmed cases, deaths and recoveries in Pakistan.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.149-150
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• 2023

This study proposes the most suitable strength prediction model equation for UHPC by calculating the apparent activation energy of UHPC according to the curing temperature and deriving the integrated temperature and compressive strength prediction equation. The results are summarized as follows. The apparent activation energy was calculated using the Arrhenius function, which was calculated as 21.09 KJ/mol. A model equation suitable for UHPC was calculated, and when the Flowman model equation was used, it was confirmed that it was suitable for the properties of UHPC using a condensation promoting super plasticizing agent.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.467-483
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• 2023

In this research, a conversion function and a distortion associated with the conversion function are defined and used to derive a unit power Gompertz distortion. A new family of copulas is built using the global distorted function. Four base copulas, namely Clayton, Gumbel, Frank, and Gaussian, are distorted into the family. Some properties including tail dependence coefficients and tail order are examined. Kendall's tau formula is derived for new copulas when the base copula is Clayton, Gumbel, or Frank. The maximum pseudo-likelihood estimation method is employed, and a simulation study was performed. The log-likelihood and AIC are reported to compare the performance of the fitted copulas. According to the applied data, the results indicate that new distorted copulas with additional parameters improve the fit.

• Journal of Korean Society for Quality Management
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• v.23 no.1
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• pp.95-105
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• 1995

The error structure of nonlinearized technological growth models, such as, the Pearl curve, the Gompertz curve and the Wei bull growth curve, has zero mean and a constant variance over time. Transformed models, however, like the linearized Fisher-Pry model. the linearized Gompertz growth curve, and the linearized Weibull growth curve have increasing variance from t = 0 to the inflection point.

• Journal of Animal Science and Technology
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• v.48 no.1
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• pp.29-38
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• 2006

The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were －0.47 and －0.67 using modelⅠand －0.56 and －0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were －0.26 and 0.01 using modelⅠand －0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were －0.49 and －0.67 suing model Ⅰ and －0.57 and －0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were －0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were －0.43 and －0.67 using model Ⅰ and －0.50 and －0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were －0.09 and 0.02 using model Ⅰ and －0.02 and 0.13 using model Ⅱ.

• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.403-414
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• 2014

Forecasting technology in economic activity is a quite intricate procedure so researchers should grasp the point of the data to use. Diffusion models have been widely used for forecasting market demand and measuring the degree of technology diffusion. However, there is a question that a model, explaining a certain market with goodness of fit, always shows good performance with markets of different conditions. The primary aim of this paper is to explore diffusion models which are frequently used by researchers, and to help readers better understanding on those models. In this study, Logistic, Gompertz and Bass models are used for forecasting Global Wireline Subscribers and the performance of models is measured by Mean Absolute Percentage Error. Logistic model shows better MAPE than the other two. A possible extension of this study may verify which model reflects characteristics of industry better.

• Korea journal of population studies
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• v.16 no.2
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• pp.65-83
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• 1993

The purpose of this study is estimate limits of Korean life expectancy at birth by 'Gompertz growth curse Model', 'Cause-Elimination Model' and Multidimensional models of Senescencee and Mortality'. Data used in Gompertz curve were obtained from all life tables published from 1905 to 1990 in Korea, and life expectancies at birth of eighteen groups were selected at five-year interval in consideration of time-series changes. Data used in Cause-Elimination Model are 'Cause of Death statistics in 1991' published in 1992 by National Bureau of Statistics of Korea and 'life table of 1989' published in 1990 by National Bureau of Statistics, Economic Planning Board of Korea. The materials are all classifiable death data, 119, 253 cases of male and 82, 420 cases of female, which is from 1991 Causes of Death statistics. The cases of death analyzed belong to one of 8 categories; i.e., Infectious and Parasitic Diseases(001-139; with notation of Infectious Diseases), Malignant Neoplasms(140-208), Hypertensive Diseases(401-405), Ischemic Heart Dieases and Diseases of Pulmonary Circulation and Other Forms of Heart Diseases(410-429;with notation of Heart Disease), Cerebrovascular Diseases(430-438), Chronic Liver Diseases and Cirrhosis(571; with notation of Liver Diseases), Injury and Poisoning(800-999) and all other disease. Data used in 'Multidimensional models of senescence and mortality' were life table of 1989 published by National Bureau of statistics, Economic Planning Board of Korea and life table of 1970, 1978-79, 1983, 1985 and 1987. The major findings may be summarised as follows: 1. Estimate equations of Gompertz growth curve using life expectancy at birth during the 1905-1990 period are as the following. Male : y = 88.047697 $\times$ $0.199690^{0.903381x}$ Female : y = 95.632828 $\times$ $0.199690^{0.903381x}$ Limits of life expectancy at birth, which were estimated by Gompertz growth curve, are 88.05 for male and 95.63 for female. 2. The effect on life expectancy at birth eliminationg all causes death is 14.04 years(for male) and 10.86 years(for female). Astonishingly, eliminating the malignant neoplasms increase life expectancy at birth by 2.85 years for male 2.03 years for female in 1991. In table 8 we show the effect on life expectancy at birth of separately eliminating each of the 8 categorical causes of death. The theoretical limit to life expectancy by Cause-Elimination Model is 80.96 for male and 85.82 for female. 3. If the same rate of delay [0.376 year(male), 0.435 year(femable) per calendar year] continued, then life expectancy at birth would reach 74.82(male) years and 84, 10(female) years in 2010. With 14.04-years(male) and 10.86-years(female) effect attributable in 2010 would be 88.86 years(male) and 94.96(femable) years. 4. 'Multidimensional models of senescence and death' permits calculations of the value of the attribution coefficient (B), percent of loss per year of physiologic function. The results of Ro and B during the 1970-1989 period are listed in table 9. Estimate of limit to Korean life expectancy at birth by 'Multidimensional models of senescence and death' is 99.47 years for male and 104.74 years for female in 1989.