• Journal of Korean Academy of Nursing
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• v.42 no.2
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• pp.199-206
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• 2012

Purpose: This study was done to identify the impact of physical activity on healthcare utilization among Korean adults. Methods: Drawing from the 2008 Korean National Health and Nutrition Examination Survey (NHANES IV-2), data from 6,521 adults who completed the Health Interview and Health Behavior Surveys were analyzed. Association between physical activity and healthcare utilization was tested using the $X^2$-test. Multiple logistic regression analysis was used to calculate the odds ratios of using outpatient and inpatient healthcare for different levels of physical activity after adjusting for predisposing, enabling, and need factors. A generalized linear model applying a negative binomial distribution was used to determine how the level of physical activity was related to use of outpatient and inpatient healthcare. Results: Physically active participants were 16% less likely to use outpatient healthcare (OR, 0.84; 95% CI, 0.74-0.97) and 23% less likely to use inpatient healthcare (OR, 0.77; 95% CI, 0.63-0.93) than physically inactive participants. Levels of outpatient and inpatient healthcare use decreased as levels of physical activity increased, after adjusting for relevant factors. Conclusion: An independent association between being physically active and lower healthcare utilization was ascertained among Korean adults indicating a need to develop nursing intervention programs that encourage regular physical activity.

• Genomics & Informatics
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• v.2 no.3
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• pp.131-133
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• 2004

MediScore is an information retrieval system, which helps to search for the set of genes associated with a specific disease or the set of diseases associated with a specific gene. Despite recent improvement of natural language processing (NLP) and other text mining approaches to search for disease associated genes, many false positive results come out due to diversity of exceptional cases as well as ambiguities in gene names. In order to overcome the weak points of current text mining approaches, MediScore introduces statistical normalization based on binomial to normal distribution approximation which corrects inaccurate scores caused by common words not representing genes and interactive rescoring by the user to remove the false positive results. Interactive rescoring includes individual alias scoring for each gene to remove false gene synonyms, referring MEDLINE abstracts, and cross referencing between OMIM and other related information.

• Journal of the Korean Chemical Society
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• v.60 no.2
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• pp.111-117
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• 2016

In this article, new Gibbs free energy of mixing is derived when there are specific interactions between solvent-solute molecules and between solute-solute molecules in binary solutions. It is asssumed that a probability of specific interactions satisfies a binomial distribution. Using this Gibbs free energy of mixing, we investigate possible types of partial miscibilities and show that Ω-shaped temperature-composition phase diagrams can exist. We calculate Ω-shaped temperature-composition phase diagram of water-2-butanol system and compare that with result calculated by the method of Hino⁵ et al. and the experimental data.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2829-2840
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• 2018

The random variable with an arbitrary value or more is called semi-continuous variable or zero-inflated one in case that its boundary value is more frequently observed than expected. This means the boundary value is likely to be practically observed more than it should be theoretically under certain probability distribution. When the distribution considered is continuous, the variable is defined as semi-continuous and when one of discrete distribution is assumed for the variable, we regard it as zero-inflated. In this study, we introduce the two-part model, which consists of one part for modelling the binary response and the other part for modelling the variable greater than the boundary value. Especially, the zero-inflated regression models are explained by using Poisson distribution and negative binomial distribution. In real data analysis, we employ the zero-inflated regression models to estimate the number of days under extreme heat-wave circumstances during the last 10 years in South Korea. Based on the estimation results, we create prediction maps for the estimated number of days under heat-wave advisory and heat-wave warning by using the universal kriging, which is one of the spatial prediction methods.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.335-344
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• 2010

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9859-9863
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• 2014

Genetic epidemiological studies have shown that genetic susceptibility to esophageal cancer (EC) is an important cause of its high incidence within families in some areas of China. The purpose of this study was to obtain evidence of a genetic basis of EC in Xin-an and Xin-xiang counties in China. Familial aggregation and complex segregation analyses were performed of 79 EC families in these counties. The heritability of EC was examined using Falconer's method and complex segregation analysis was conducted with the SEGREG program in Statistical Analysis for Genetic Epidemiology (SAGE version 5.3.1). The results showed that the distribution of EC in families did not fit well into a binomial distribution. The heritability of EC among first-degree and second-degree relatives was $67.0{\pm}7.31%$ and $43.1%{\pm}9.80%$, respectively, and the summing up powered heritability was $53.2{\pm}6.74%$. The segregation ratio was 0.045. Complex segregation analysis showed that the genetic model of EC was additive. The current results provide evidence for an inherited propensity to EC in certain high-risk groups in China, and support efforts to identify the genes that confer susceptibility to this disease.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.652-658
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• 2008

In this paper, a new random access scheme is proposed to improve the probability of successful access. In the conventional scheme, a packet is transmitted by a user using one slot and considered successfully transmitted if a collision does not occur. In comparison, a packet of the proposed scheme is transmitted by a user using one or more slots and considered successfully transmitted if there is at least one slot without collision. We evaluate the optimal number of slots selected by users to maximize the probability of successful access when the probability distribution functions for the number of users are given such as Binomial and Poission distribution. From the numerical analysis, it is shown that the proposed scheme performs better than conventional scheme.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.101-116
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• 2012

Accident prediction models have been utilized to predict accident possibilities in existing or projected freeways and to evaluate programs or policies for improving safety. In this study, a traffic accident prediction model for freeways was developed for the above purposes. When selecting variables for the model, the highest priority was on the ease of both collecting data and applying them into the model. The dependent variable was set as the number of total accidents and the number of accidents including casualties in the unit of IC(or JCT). As a result, two models were developed; the overall accident model and the casualty-related accident model. The error structure adjusted to each model was the negative binomial distribution and the Poisson distribution, respectively. Among the two models, a more appropriate model was selected by statistical estimation. Major nine national freeways were selected and five-year dada of 2003~2007 were utilized. Explanatory variables should take on either a predictable value such as traffic volumes or a fixed value with respect to geometric conditions. As a result of the Maximum Likelihood estimation, significant variables of the overall accident model were found to be the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volume to the number of curved segments between ICs(or JCTs). For the casualty-related accident model, the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volumes had a significant impact on the accident. The likelihood ratio test was conducted to verify the spatial and temporal transferability for estimated parameters of each model. It was found that the overall accident model could be transferred only to the road with four or more than six lanes. On the other hand, the casualty-related accident model was transferrable to every road and every time period. In conclusion, the model developed in this study was able to be extended to various applications to establish future plans and evaluate policies.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.369-379
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• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.

• Parasites, Hosts and Diseases
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• v.23 no.2
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• pp.241-246
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• 1985

The epidemiological status of ascariasis was analyzed in 8 rural villages in Korea, through observation of its epidemiological parameters such as prevalence, worm burden and basic reproductive rate. Total 978 inhabitants were subjected to stool examination and recovery of worms after chemotherapy with pyrantel pamoate. The results were as follows: 1. The worm positive rate in each village was 16.5~79.5%, while the egg positive rate was 9~18% lower, 3.3~66.7%. The average worm burden (among all inhabitants) ranged from O. 21 to 8. 44 by villages and the frequency of cases with each worm burden showed negative binomial distributions with 'k' values of O. 38-0. 54. 2. The prevalence rates (worm) in each village was almost identical with the theoretical ones from Anderson and May's equation; $p=1-(1+M^*/k)^{-k}$, where 'p' is worm prevalence and '$M^*$' equilibrium average worm burden. The basic reproductive rate 'R' was calculated from 1.03 to 2.11. lt is suggested that, although 'R' in lower endemic areas is approaching to the breakpoint of reinfection (R=1), control programs of ascariasis in Korea should be continued until it becomes below the level nationwidely.