• 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.

• Korean Journal of Ecology and Environment
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• v.37 no.3 s.108
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• pp.297-303
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• 2004

Two dimensional cellular automaton (CA) models were developed to investigate growth of biofilms in aquatic ecosystems. Simple local rules on CA were applied to governing growth of bacterial populations in relation to different nutrient concentrations. Initial bacterial distribution played an important role in determining population size and morphology of biofilm at low concentrations of nutrition. With clumped distribution, population size increased slowly compared with uniform and random distributions, while the porosity tented to be higher with uniform distribution compared with other initial distributions.

• Journal of Korean Elementary Science Education
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• v.38 no.3
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• pp.375-386
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• 2019

This study explores how elementary school students construct food pyramid prediction models using scientific reasoning. Thirty small groups of sixth-grade students in the Kyoungki province (n=138) participated in this study; each small group constructed a food pyramid prediction model based on scientific reasoning, utilizing prior knowledge on topics such as biotic and abiotic factors, food chains, food webs, and food pyramid concepts. To understand the scientific reasoning applied by the students during the modeling process, three forms of qualitative data were collected and analyzed: each small group's discourse, their representation, and the researcher's field notes. Based on this data, the researcher categorized the students' model patterns into three categories and identified how the students used scientific reasoning in their model patterns. The study found that the model patterns consisted of the population number variation model, the biological and abiotic factors change model, and the equilibrium model. In the population number variation model, students used phenomenon-based reasoning and relation-based reasoning to predict variations in the number of producers and consumers. In the biotic and abiotic factors change model, students used relation-based reasoning to predict the effects on producers and consumers as well as on decomposers and abiotic factors. In the equilibrium model, students predicted that "the food pyramid would reach equilibrium," using relation-based reasoning and model-based reasoning. This study demonstrates that elementary school students can systematically elaborate on complicated ecology concepts using scientific reasoning and modeling processes.

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.111-123
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• 2019

In this paper, software activity, software activity instance, and the quality of the activity instance are defined as the 'activity which is performed on the software product by a person or a group of persons,' the 'distinctive and individual performance of software activity,' and the 'performer's evaluation on how good or bad his/her own activity instance is,' respectively. The representative values of the instance quality population associated with a product and its sub-population are defined as the (software) activity quality and activity quality characteristic of the product, respectively. The activity quality model in this paper classifies activity quality characteristics according to the classification hierarchy of software activity by the goal. In the model, a quality characteristic can have two types of sub-characteristics : Special sub-characteristic and component sub-characteristic, where the former is its super-characteristic too simultaneously and the latter is not its super-characteristic but a part of its super-characteristic. The activity quality model is parsimonious, coherent, and easy to understand and use. The activity quality model can serve as a corner stone on which a software quality body of knowledge, which constituted with a set of models parsimonious, coherent, and easy to understand and use and the theories explaining the cause-and-relationships among the models, can be built. The body of knowledge can be called the (grand) activity-centric quality model of software.

• Korean journal of applied entomology
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• v.56 no.1
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• pp.1-18
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• 2017

Temperature-dependent development model is an essential component for forecasting models of insect pests as well as for insect population models. This study reviewed the nonlinear models which explain the relationship between temperature and development rate of insects. In the present study, the types of models were classified largely into empirical and biophysical model, and the groups were subdivided into subgroups according to the similarity of mathematical equations or the connection with original idea. Empirical models that apply analytical functions describing the suitable shape of development curve were subdivided into multiple subgroups as Stinner-based types, Logan-based types, performance models and Beta distribution types. Biophysical models based on enzyme kinetic reaction were grouped as monophyletic group leading to Eyring-model, SM-model, SS-mode, and SSI-model. Finally, we described the historical development and characteristics of non-linear development models and discussed the availability of models.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.467-484
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• 2024

Longitudinal data are measured repeatedly over time from the same subject, so there is a correlation from the repeated outcomes. Therefore, when analyzing this correlation, both serial correlation and between-subject variation must be considered in longitudinal data analysis. In this paper, we will focus on the marginalized models to estimate the population average effect of covariates among models for analyzing longitudinal binary data. Marginalized models for longitudinal binary data include marginalized random effects models, marginalized transition models, and marginalized transition random effect models, and in this paper, these models are first reviewed, and simulations are conducted using complete data and missing data to compare the performance of the models. When there were missing values in the data, there is a difference in performance depending on the model in which the data was generated. We analyze Korea Health Panel data using marginalized models. The Korean Medical Panel data considers subjective unhealthy responses as response variables as binary variables, compares models with several explanatory variables, and presents the most suitable model.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.773-779
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• 2015

We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2005.06a
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• pp.54-62
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• 2005

While genomics (the set of experimental and computational tools that allows the blueprints of life to be read) opens the doors to a more rational approach to the design and use of living cells to bring about desirable chemical transformations, genomics is, by itself, insufficient. We need tools that allow us to relate genomic and molecular information to cellular physiology and then to the response of a population of cells. We propose the development of hybrid computer cellular models. In such models genomics and chemical detail for a cellular subsystem (e.g. pathogenesis) is embedded in a coarse-grain cell model. Such a construct allows the quantitative and explicit linkage of genomic detail to cell physiology to the extracellular environment. To illustrate the principles involved we are constructing a model for a minimal cell. A minimal cell is a bacterial cell with the fewest number of genes necessary to sustain life as a free living microbe.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.1-8
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• 1999

This study was conducted to collect data concerning the preferred driving postures and adopted seat adjustment levels and to grasp relationships among drivers' body sizes, postural angles, and adopted seat positions and angles. Also optimum driving posture and seat adjustment level estimation models were constructed. An experiment was conducted to investigate observed optimum driving posture, and seat adjustment level. Thirty-six subjects (male=20, female=16) was selected to include a wide range of percentiles in the dimensions important for automotive driving workstation design and to be representative of the automotive driving population in Korea. New guidelines and estimation models for optimum postural comfort were developed. There were significant differences between male and female in postural angles but not in seat adjustment levels. Taller subjects preferred a more open and reclined posture. Estimation models enable us to estimate the quantitative optimum driving posture and seat adjustment level with some drivers' physical dimensions.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1263-1272
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• 2014

Longitudinal categorical data commonly occur from medical, health, and social sciences. In these data, the correlation of repeated outcomes is taken into account to explain the effects of covariates exactly. In this paper, we introduce marginalized random effects models that are used for the estimation of the population-averaged effects of covariates. We also review how these models have been developed. Real data analysis is presented using the marginalized random effects.