• Journal of the Korean Society for Library and Information Science
• /
• v.52 no.4
• /
• pp.179-194
• /
• 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 the Korean Society for Library and Information Science
• /
• v.57 no.1
• /
• pp.45-68
• /
• 2023

The purpose of this study is to longitudinally analyze impact factors on library use. One of library use indicators, the number of circulated books was statistically analyzed with latent growth model and growth mixture model. Library data from 2014 to 2019 were collected from the National Library Statistics System, and 846 public libraries were analyzed. As results, the number of circulated books were decreased, but it was tempered. Next, with controlling the factor affecting the dependent variable, the size of collection and the number of participants in reading programs provided by public libraries were statistically significant. Lastly, 5 classes were identified by applying the growth mixture model, and the number of librarians was significantly associated with trajectory class membership.

• Research in Mathematical Education
• /
• v.27 no.1
• /
• pp.129-150
• /
• 2024

This study utilized South Korean elementary and middle school student data to examine the longitudinal change trajectories of learning motivation types according to the longitudinal change trajectories of mathematics academic achievement. Growth mixture modeling, latent growth model, and multiple indicator latent growth model were used to examine various change trajectories for longitudinal data. As a result of the analysis, it was classified into 4 subgroups with similar longitudinal change trajectories of mathematics academic achievement, and the characteristics of the mathematics subject, which emphasize systematicity, appeared. Furthermore, higher mathematics academic achievement was associated with higher self-determination and higher academic motivation. And as the grade level increases, amotivation increases and self-determination decreases. This study suggests that teaching and learning support using this is necessary because the level of learning motivation according to self-determination is different depending on the level of mathematics academic achievement reflecting the characteristics of the student.

• The Mathematical Education
• /
• v.63 no.1
• /
• pp.19-33
• /
• 2024

This study investigates longitudinal patterns in middle school students' mathematics interest and achievement using panel data from the 4th to 6th year of the Gyeonggi Education Panel Study. Results from the multivariate growth mixture model confirmed the existence of heterogeneous characteristics in the longitudinal trajectory of students' mathematics interest and achievement. Students were classified into four latent classes: a low-level class with weak interest and achievement, a high-level class with strong interest and achievement, a middlelevel-increasing class where interest and achievement rise with grade, and a middle-level-decreasing class where interest and achievement decline with grade. Each class exhibited distinct patterns in the change of interest and achievement. Moreover, an examination of the correlation between intercepts and slopes in the multivariate growth mixture model reveals a positive association between interest and achievement with respect to their initial values and growth rates. We further explore predictive variables influencing latent class assignment. The results indicated that students' educational ambition and time spent on private education positively affect mathematics interest and achievement, and the influence of prior learning varies based on its intensity. The perceived instruction method significantly impacts latent class assignment: teacher-centered instruction increases the likelihood of belonging to higher-level classes, while learner-centered instruction increases the likelihood of belonging to lower-level classes. This study has significant implications as it presents a new method for analyzing the longitudinal patterns of students' characteristics in mathematics education through the application of the multivariate growth mixture model.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.9
• /
• pp.4115-4121
• /
• 2015

Background: Colorectal cancer is the second most common cause of cancer death with half a million deaths per year. Incidence and mortality rates have demonstrated notable changes in Asian and African countries during the last few decades. In this study, we first aimed to determine the trend of colorectal cancer mortality rate in each Institute for Health Metrics and Evaluation (IHME) region, and then re-classify them to find more homogenous classes. Materials and Methods: Our study population consisted of 52 countries of Asia and North Africa in six IHME pre-defined regions for both genders and age-standardized groups from 1990 to 2010.We first applied simple growth models for pre-defined IHME regions to estimate the intercepts and slopes of mortality rate trends. Then, we clustered the 52 described countries using the latent growth mixture modeling approach for classifying them based on their colorectal mortality rates over time. Results: Statistical analysis revealed that males and people in high income Asia pacific and East Asia countries were at greater risk of death from colon and rectum cancer. In addition, South Asia region had the lowest rates of mortality due to this cancer. Simple growth modeling showed that majority of IHME regions had decreasing trend in mortality rate of colorectal cancer. However, re-classification these countries based on their mortality trend using the latent growth mixture model resulted in more homogeneous classes according to colorectal mortality trend. Conclusions: In general, our statistical analyses showed that most Asian and North African countries had upward trend in their colorectal cancer mortality. We therefore urge the health policy makers in these countries to evaluate the causes of growing mortality and study the interventional programs of successful countries in managing the consequences of this cancer.

• Biotechnology and Bioprocess Engineering:BBE
• /
• v.10 no.6
• /
• pp.587-592
• /
• 2005

Hydrolyzates from lignocellulosic biomass contain a mixture of simple sugars; the predominant ones being glucose, cellobiose and xylose. The fermentation of such mixtures to ethanol or other chemicals requires an understanding of how each of these substrates is utilized. Candida lusitaniae can efficiently produce ethanol from both glucose and cellobiose and is an attractive organism for ethanol production. Experiments were performed to obtain kinetic data for ethanol production from glucose, cellobiose and xylose. Various combinations were tested in order to determine kinetic behavior with multiple carbon sources. Glucose was shown to repress the utilization of cellobiose and xylose. However, cellobiose and xylose were simultaneously utilized after glucose depletion. Maximum volumetric ethanol production rates were 0.56, 0.33, and 0.003 g/L h from glucose, cellobiose and xylose, respectively. A kinetic model based on cAMP mediated catabolite repression was developed. This model adequately described the growth and ethanol production from a mixture of sugars in a batch culture.

• Journal of Microbiology and Biotechnology
• /
• v.19 no.7
• /
• pp.718-726
• /
• 2009

The objective of this study was to develop and validate secondary models that can predict growth parameters of L. monocytogenes Scott A as a function of concentrations (0-3%) of a commercial potassium lactate (PL) and sodium diacetate (SDA) mixture, pH (5.5-7.0), and temperature (4-37DC). A total of 120 growth curves were fitted to the Baranyi primary model that directly estimates lag time (LT) and specific growth rate (SGR). The effects of the variables on L. monocytogenes Scott A growth kinetics were modeled by response surface analysis using quadratic and cubic polynomial models of the natural logarithm transformation of both LT and SGR. Model performance was evaluated with dependent data and independent data using the prediction bias ($B_f$) and accuracy factors ($A_f$) as well as the acceptable prediction zone method [percentage of relative errors (%RE)]. Comparison of predicted versus observed values of SGR indicated that the cubic model fits better than the quadratic model, particularly at 4 and $10^{\circ}C$. The $B_f$and $A_f$for independent SGR were 1.00 and 1.08 for the cubic model and 1.08 and 1.16 for the quadratic model, respectively. For cubic and quadratic models, the %REs for the independent SGR data were 92.6 and 85.7, respectively. Both quadratic and cubic polynomial models for SGR and LT provided acceptable predictions of L. monocytogenes Scott A growth in the matrix of conditions described in the present study. Model performance can be more accurately evaluated with $B_f$and $A_f$and % RE together.

• Convergence Security Journal
• /
• v.7 no.3
• /
• pp.51-60
• /
• 2007

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, exponential distribution and Rayleigh distribution model was reviewed, proposes the mixture reliability model, which made out efficiency substituted for situation for failure time Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using S27 data set for the sake of proposing shape parameter of the mixture distribution was employed. This analysis of failure data compared with the mixture distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of Korean Society of Water and Wastewater
• /
• v.19 no.5
• /
• pp.639-646
• /
• 2005

In this research, we tried to develop the application method to water management and treatment using toxicity test method. When we measure the toxicity of environmental samples, we have to decide whether we take some countermeasures to reduce the toxicity or not. The first issue is how to set these action levels in each bioassays. A new idea was attempted to authorize indirect approach of each bioassays through the response characteristics against mixture of chemicals in water quality standard. The significant response in the cell-growth-inhibition bioassay was detected for standards-mixture(STDs). For acute toxicity assay, STDs-based implicit correlation between risks to humans and bioassay data showed a rational approach to set action levels in practical management. A simple model was proposed to describe and predict the changes in the total toxicity based on the concentrations of toxic-controlling chemicals during the ozonation of landfill leachates. On the basis of this simple model, toxicity reduction was predicted for pre-aggregation treatment before ozonation and ozone concentration during the ozonation. The method proposed in this study would be useful in optimizing water treatment processes and their running conditions in terms of the toxicity reduction efficacy.

• Food Science of Animal Resources
• /
• v.38 no.3
• /
• pp.442-450
• /
• 2018

Liquid egg products can be contaminated with Salmonella spp. during processing. A predictive model for the growth of Salmonella spp. in unpasteurized liquid eggs was developed and validated. Liquid whole egg, liquid yolk, and liquid egg white samples were prepared and inoculated with Salmonella mixture (approximately 3 Log CFU/mL) containing five serovars (S. Bareilly, S. Richmond, S. Typhimurium monophasic, S. Enteritidis, and S. Gallinarum). Salmonella growth data at isothermal temperatures (5, 10, 15, 20, 25, 30, 35, and $40^{\circ}C$) was collected by 960 h. The population of Salmonella in liquid whole egg and egg yolk increased at above $10^{\circ}C$, while Salmonella in egg white did not proliferate at all temperature. These results demonstrate that there is a difference in the growth of Salmonella depending on the types of liquid eggs (egg yolk, egg white, liquid whole egg) and storage temperature. To fit the growth data of Salmonella in liquid whole egg and egg yolk, Baranyi model was used as the primary model and the maximum growth rate and lag phase duration for each temperature were determined. A secondary model was developed with maximum growth rate as a function of temperature. The model performance measures, bias factor ($B_f$, 0.96-0.99) and $r^2$ (0.96-0.99) indicated good fit for both primary and secondary models. In conclusion, it is thought that the growth model can be used usefully to predict Salmonella spp. growth in various types of unpasteurized liquid eggs when those are exposed to various temperature and time conditions during the processing.