• The Korean Journal of Applied Statistics
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• v.1 no.2
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• pp.45-60
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• 1987

Deciding whether a certain cancer patient is suffering from a bone marrow metastasis is quite essential to clinicians. To find a set of explanatory variables of the bone marrow metastasis, we employed the logistic regression analysis on 60 cancer patients with bone marrow metastasis (the case group) and 41 cancer patients without bone marrow metastasis (the control group). These data shown in Append were collected retrospectively from the record of Severance Hospital of Yonsei University College of Medicine from January, 1977 to December, 1985. We could establish a set of decision rules of the bone marrow metastasis specially designed for clinicians based on the explanatory variables of the best fitting logistic regression equation. We also compute the specifity and the sensistivity of our decision rules.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.550-558
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• 2015

This study investigates the degree of intention-behavior gap in the entertainment tourism. Using the sample of international visitors to South Korea, we identified the inclined actor (who are interested in the entertainment performance and actually went to the entertainment performance) and inclined abstainer (who are interested in the entertainment performance but did not go to the entertainment performance). The results of logistic regression analysis show that the sample was more accurately classified when attitude and knowledge on K-entertainment were included as explanatory variables. More findings and implications are provided.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.90-95
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• 2001

Electric arc furnaces (EAFs) has a process to cause the degradation of the electric power quality such as voltage flicker. In order to adequately understand and analyze the effects on the power system from these loads, obtaining an accurate representation of the characteristics of the loads is crucial. In this paper, a mixed chaotic EAF model to represent the low frequency and high frequency variations of the arc current respectively has been proposed. The Lorenz system may contribute to the low frequency components of arc current and the logistic equation may contribute to the high frequency components, and the proposed mixed model will be a combination of both Lorenz and logistic model. The concept of chaotic parameters, such as chaotic resistance, inductance of admittance has been also proposed for the characterization of arc furnace operation and the highly nonlinear physical processes. The power quality indices are calculated from the simulated waveforms and compared with the actual power quality indices statistics in order to illustrate the model's capabilities.

• 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 Plant Pathology
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• v.14 no.2
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• pp.150-156
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• 1998

To develop a model for prediction of turnip mosaic virus(TuMV) disease progress of Chinese cabbage based on weather information and number of TuMV vector aphids trapped in Taegwallyeong alpine area, data were statistically processed together. As the variables influenced on TuMV disease progress, cumulative portion(CPT) above 13$^{\circ}C$ in daily average temperature was the most significant, and solar radiation, duration of sunshine, vector aphids and cumulative temperature above $0^{\circ}C$ were significant. When logistic model and Gompertz model were compared by detemining goodness of fit for TuMV disease progress using CPT as independent variable, regression coefficient was higher in the logistic model than in the Gompertz model. Epidemic parameters, apparent infection rate and initial value of logistic model, were estimated by examining the relationship between disease proportion linearized by logit transformation equation, In(Y/Yf-Y) and CPT. Models able to describe the progression of TuMV disease were formulated in Y=100/(1+128.4 exp(-0.013.CPT.(-1(1/(1+66.7.exp(-0.11.day). Calculated disease progress from the model was in good agreement with investigated actual disease progress showing high significance of the coefficient of determination with 0.710.

• Journal of Distribution Science
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• v.21 no.1
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• pp.53-63
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• 2023

Purpose: Big Data analytics (BDA) has been recognized to improve firm performance because it can efficiently manage and process large-scale, wide variety, and complex data structures. This study examines the determinants of Big Data analytics adoption toward marketing and financial performance of global logistic companies in Thailand. The research framework is adopted from the technology-organization-environment (TOE) model, including technological factors (relative advantages), organizational factors (technological infrastructure and absorptive capability), environmental factors (industry competition and government support), Big Data analytics adoption, marketing performance, and financial performance. Research design, data, and methodology: A quantitative method is applied by distributing the survey to 450 employees at the manager's level and above. The sampling methods include judgmental, stratified random, and convenience sampling. The data were analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The results showed that all factors significantly influence Big Data analytics adoption, except technological infrastructure. In addition, Big Data analytics adoption significantly influences marketing and financial performance. Conversely, marketing performance has no significant influence on financial performance. Conclusions: The findings of this study can contribute to the strategic improvement of firm performance through Big Data analytics adoption in the logistics, distribution, and supply chain industries.

• Journal of Technology Innovation
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• v.16 no.1
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• pp.215-237
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• 2008

KIPRIS patent database was analyzed for identifying the technological status of Daedeok Innopolis Biocluster. It was found that the pattern of activities among various technological areas in Daedeok Biocluster is similar to that of an advanced country rather than those of other cities in Korea. The technological growth in Daedeok Innopolis Biocluster is in the progressive stage, which may be due to the innovative activities rather than the rise in the number of new firms or institutes. The concentration of technology in Daedeok Innopolis Biocluster is a favorable condition for the innovation activities. The trend for the technological concentration was remarkably consistent with the growth curve that a population increases according to the logistic equation. The logistic growth may be represented by the result of competition due to the limited resource allocation and then innovation cluster is corresponding to the ecosystem composed by biological individuals. There is strong competition in Daedeok Innopolis Biocluster in around 2009, so the government might make a policy to encourage the technological diversity for healthy knowledge ecosystem.

• ALGAE
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• v.27 no.1
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• pp.43-54
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• 2012

A mathematical model of the commercial harvest of Palmaria palmata (Dulse) is presented based on a logistic model and field data collected on Digby Neck, Nova Scotia from 14 harvested shores during May to August, 2010. Field observations used to estimate model parameters included cover of Dulse before and after harvest from Dulse dominated boulders for which surface area was estimated, and from which fresh biomass of harvested Dulse was weighed. Over all the surveys the average harvest fraction was about 50%, and the total resource was about $1,600g\;m^{-2}$. With growth rates in excess of 4% per day and a 50% harvest of the standing crop each month, the model suggests that the Dulse resource is sustainable at current harvest levels.

• Child Studies in Asia-Pacific Contexts
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• v.2 no.1
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• pp.1-10
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• 2012

The present study, based on Tiffany Field's model of violence and intimacy as well as other previous research, examines the relationship between parents' physical affection and their child's aggressive behavior. One hundred seventy-five mothers and 124 fathers of Japanese preschoolers answered a questionnaire that included a parental physical affection scale developed for this study. Children's aggressive behaviors were rated by their teachers on the hostile-aggressive subscale of the Preschool Behavior Questionnaire. Consistent with Field's model and previous studies, the results of logistic regression analyses indicated that children who received more physical affection from mothers or fathers during daily parenting were less likely to be aggressive at preschool. When the mother's and the father's physical affection scores were simultaneously entered in the equation, only the father's score was significant. Implications and limitations of the research are discussed.

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.585-596
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• 2022

This study determined major factors influencing landslide occurrence along a forest road near Sangsan village, Sancheok-myeon, Chungju-si, Chungcheongbuk-do, South Korea. Within a 2 km radius of the study area, landslides occur intensively during periods of heavy rainfall (August 2020). This makes study of the area advantageous, as it allows examination of the influence of only geological and tomographic factors while excluding the effects of rainfall and vegetation. Data for 82 locations (37 experiencing landslides and 45 not) were obtained from geological surveys, laboratory tests, and geo-spatial analysis. After some data preprocessing (e.g., error filtering, minimum-maximum normalization, and multicollinearity), structural equation model (SEM) and logistic regression (LR) analyses were conducted. These showed the regolith thickness, porosity, and saturated unit weight to be the factors most influential of landslide risk in the study area. The sums of the influence magnitudes of these factors are 71% in SEM and 83% in LR.