• Journal of the Korean Society for Library and Information Science
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• v.52 no.4
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• pp.179-194
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• 2018

The purpose of this study is to discuss the application of the Latent Growth Model to measure the outcomes of public library. For outcome measurements, library circulation data were collected to identify longitudinal changes of library users' reading habit. The latent growth model was applied to statistically test the changes over time. The circulation data of 95,962 users registered in some public libraries in Seoul, ranged between 2010 and 2015, were analyzed using unconditional model, conditional model, and growth mixture model which all are called the latent growth model. The results show that the intercept of the model is 4.19 and the slop is 0.24 in the linear growth model. The gender difference in two latent variables including intercept and slop was a shade difference. The result from the growth mixture model analysis, additionally indicates that the number of books checked out by children under age 10 is rapidly increased. The application of the latent growth model in library fields is expected to widely spread out for the longitudinal data analysis.

• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.326-331
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• 2018

Crop growth models are useful tools for understanding and integrating knowledge about crop growth. Models for predicting plant height, net photosynthesis rate, and plant growth of quinoa (Chenopodium quinoa Willd.) as a leafy vegetable in a closed-type plant factory system were developed using empirical model equations such as linear, quadratic, non-rectangular hyperbola, and expolinear equations. Plant growth and yield were measured at 5-day intervals after transplanting. Photosynthesis and growth curve models were calculated. Linear and curve relationships were obtained between plant heights and days after transplanting (DAT), however, accuracy of the equation to estimate plant height was linear equation. A non-rectangular hyperbola model was chosen as the response function of net photosynthesis. The light compensation point, light saturation point, and respiration rate were 29, 813 and $3.4{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. The shoot fresh weight showed a linear relationship with the shoot dry weight. The regression coefficient of the shoot dry weight was 0.75 ($R^2=0.921^{***}$). A non-linear regression was carried out to describe the increase in shoot dry weight of quinoa as a function of time using an expolinear equation. The crop growth rate and relative growth rate were $22.9g{\cdot}m^{-2}{\cdot}d^{-1}$ and $0.28g{\cdot}g^{-1}{\cdot}d^{-1}$, respectively. These models can accurately estimate plant height, net photosynthesis rate, shoot fresh weight, and shoot dry weight of quinoa.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.85-93
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• 2018

The Latent Growth Modeling(LGM) is known as the arising analysis method of longitudinal data and it could be classified into unconditional model and conditional model. Unconditional model requires estimated value of intercept and slope to complete a model of fitness. However, the existing LGM is in absence of a structured methodology to estimate slope when longitudinal data is neither simple linear function nor the pre-defined function. This study used Sequential Pattern of Association Rule Mining to calculate slope of unconditional model. The applied dataset is 'the Youth Panel 2001-2006' from Korea Employment Information Service. The proposed methodology was able to identify increasing fitness of the model comparing to the existing simple linear function and visualizing process of slope estimation.

• Korean journal of applied entomology
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• v.26 no.1 s.70
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• pp.31-36
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• 1987

A piecewise linear regression model able to describe disease progress curves with simplicity and flexibility was developed in this study. The model divides whole epidemic into several pieces of simple linear regression based on changes in pattern of disease progress in the epidemic and then incorporates the pieces of linear regression into a single mathematical function using indicator variables. When twelve epidemic data obtained from the field experiments were fitted to the piecewise linear regression model, logistic model and Gompertz model to compare statistical fit, goodness of fit was greatly improved with piecewise linear regression compared to other two models. Simplicity, flexibility, accuracy and ease in parameter estimation of the piece-wise linear regression model were described with examples of real epidemic data. The result in this study suggests that piecewise linear regression model is an useful technique for modeling plant disease epidemic.

• Journal of the Korean Operations Research and Management Science Society
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• v.11 no.2
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• pp.69-78
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• 1986

The outlook for the Civil Service Pension (CSP) program in Korea indicates several problems. First, the balance of the benefit among the pension recipients is not well maintained. Second, the program is running out of funds as benefit increases exceed the growth in revenues. In this article, we analyze these problems by using linear programming model and discuss the alternatives. We propose an addition of the age limit to the benefit eligibility and a reconsideration of the government subsidy's level.

• Smart Media Journal
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• v.8 no.1
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• pp.82-91
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• 2019

This study provides the analysis and prediction of fruits diseases related to weather conditions (temperature, wind speed, solar power, rainfall and humidity) using Linear Model and Poisson Regression. The main goal of the research is to control the method of fruits diseases and also to prevent diseases using less agricultural pesticides. So, it is needed to predict the fruits diseases with weather data. Initially, fruit data is used to detect the fruit diseases. If diseases are found, we move to the next process and verify the condition of the fruits including their size. We identify the growth of fruit and evidence of diseases with Linear Model. Then, Poisson Regression used in this study to fit the model of fruits diseases with weather conditions as an input provides the predicted diseases as an output. Finally, the residuals plot, Q-Q plot and other plots help to validate the fitness of Linear Model and provide correlation between the actual and the predicted diseases as a result of the conducted experiment in this study.

• Journal of Environmental Science International
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• v.2 no.4
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• pp.271-278
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• 1993

Optimal biodegradation kinetics models to the initial nonylphenol ethoxylates-30 concentration were investigated and had been fitted by the linear regression. Microorganisms capable of degrading nonylphenol ethoxylates-30 were isolated from sewage near Ulsan plant area by enrichment culture technique. Among them, the strain designated as EL-10K had the highest biodegradability and was identified as Pseudomonas from results of taxonomical studies. The optimal conditions for the biodegradation were 1.0 g/ι of nonylphenol ethoxylates-30 and 0.02 g/ι of ammonium nitrate at pH 7.0 and 3$0^{\circ}C$. The highest degradation rate of nonylphenol ethoxylates-30 was about 89% for 30 hours incubation on the optimal condition. Biodegradation data were fit by linear regression to equations for 3 kinetic models. The kinetics of biodegradation of nonylphenol ethoxylates was best described by first order model for 0.1 $\mu\textrm{g}$/ι nonylphenol ethoxylates-30 ; by Monod no growth model and Monod with growth model for 0.5 $\mu\textrm{g}$/mι and 1.0, 5.0 $\mu\textrm{g}$/mι, respectively.

• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.717-734
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• 2004

This paper examined the statistical goodness-of-fit tests for biological growth model in bioeconomic analysis. Some authors estimated usually growth function for fish in the world. However, few studies have estimated growth equations for the bivalve species. Thus, this paper studied the common functional forms of fitting growth equations for cham scallops considering environmental factors and production styles. The following functional forms are considered: linear, log-reciprocal, double log, polynomial and linear with interactions. Results of fitting these various functional forms with real data are compared and evaluated using standard statistical goodness-of-fit tests. Results also indicate that log-reciprocal function is statistically the best fit to the real data. Therefore, the log-reciprocal function is decided the best function describing cham scallop biological growth and hence might be useful for economic evaluation(i.e., optimal harvesting time).

• Korean Journal of Health Education and Promotion
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• v.12 no.2
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• pp.36-47
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• 1995

This research was obtained from analyzing how the physiques of the 3rd grade students of high school for males and females and developed for the last eleven years(from 1983 to 1993). By the physiques and nutritional index of physical growth and development, Relative Body Weight of 36.62 exceeded the standard, on the other hand females showed lower records than the standard. Relative Chest Girth Index belonged to the normal type of males and females in all, in the comparison of the records between 1983 and 1993, males increased in average 0.29 and females in average 0.55. Relative Chest Girth Index of females was greater than that of females. By the results of Relative Sitting Height Index, growth of the lower body for males and females was greater than that of males. In case of Vervaeck Index, males increased in average 2.04 but females increased in average 1, 20 relatively less than males. These phenomena provided for the evidence of the deficient nutrition in females. In the regression models of body height and body weight within a certain period, statistical regression model types which best indicated chronological average changes of body height and body weight, took 3rd Order Polynomial Regression Model rather than linear regression model. In females, statistical regression model types which best is suitable for chronological average change of body height and body weight, took 4th and 2nd Order Polynomial Regression Model respectively. The prediction value of 1995 by estimated polynomial regression model anticipated that body height of 3rd grade year students of high school of males in 1993 went on increasing from 170.87cm to 171.79cm in average 0.92cm growth and that of females from 158.99cm to 160.79cm in average 1.80cm growth. In addition, body weight of males seemed to increase from 62.58kg to 64.52kg in average 1.94kg growth and that of females seemed to increase from 54.05kg to 54.19kg in average 0.14kg growth. Linear Regression Model was suitable for the regression model of body weight for body height. Prediction on increase of an average body weight for body height was that, according to growth of body height 1cm in males, body weight increased 1.41kg averagely and that of females 0.86kg. For that reason, we came to conclusion that body weight increase for body height 1cm in males was greater than that in females on average.

• Journal of the Korean GEO-environmental Society
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• v.9 no.1
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• pp.17-25
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• 2008

In this study, external and internal pit growth rate model and external non-linear regression corrosion model were proposed by measuring pit depths and evaluating various soil factors known to contribute to the corrosion for metallic water pipes. Average pit depths of external and internal for metallic water pipes were measured 1.38 mm and 2.13 mm, and internal pit growth rate also fasted twice than external pit growth rate. This means the corrosion potential of water quality was higher than soil. The corelation between external corrosion rate and each soil corrosion factor was low. However, proposed external non-linear regression corrosion model considering all soil corrosion factors showed a little higher correlation ($R^2=0.46$) than conventional model.