• Journal of Microbiology and Biotechnology
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• v.12 no.3
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• pp.449-456
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• 2002

The objective of this study was to optimize medium composition of initial pH, tryptone, glucose, yeast extract, and mineral mixture for production of bacteriocin by Lactobacillus acidophilus ATCC 4356, using response surface methodology. A response surface approach including new statistical and plotting methods was employed for design and analysis of the experiment. An interiorly augmented central composite design was used as an experimental design. A normal-distribution log-link generalized linear model based on a subset fourth-order polynomial ($R^2$=0.94, Mean Error Deviance=0.0065) was used as an analysis model. This model was statistically superior to the full second-order polynomial-based generalized linear model ($R^2$=0.80, Mean Error Deviance=0.0140). Nonlinear programming determined the optimum composition of the medium as initial pH 6.35, typtone $1.21\%$, glucose $0.9\%$, yeast extract $0.65\%$, and mineral mixture $1.17\%$. A validation experiment confirmed that the optimized medium was comparable to the MRS medium in bacteriocin production, having the advantage of economy and practicality.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.189-199
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• 2020

This paper studies a Bayesian ordered multiple linear regression model with skew normal error. It is reasonable that the kind of inherent information available in an applied regression requires some constraints on the coefficients to be estimated. In addition, the assumption of normality of the errors is sometimes not appropriate in the real data. Therefore, to explain such situations more flexibly, we use the skew-normal distribution given by Sahu et al. (The Canadian Journal of Statistics, 31, 129-150, 2003) for error-terms including normal distribution. For Bayesian methodology, the Markov chain Monte Carlo method is employed to resolve complicated integration problems. Also, under the improper priors, the propriety of the associated posterior density is shown. Our Bayesian proposed model is applied to NZAPB's apple data. For model comparison between the skew normal error model and the normal error model, we use the Bayes factor and deviance information criterion given by Spiegelhalter et al. (Journal of the Royal Statistical Society Series B (Statistical Methodology), 64, 583-639, 2002). We also consider the problem of detecting an influential point concerning skewness using Bayes factors. Finally, concluding remarks are discussed.

• Journal of Food Hygiene and Safety
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• v.19 no.1
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• pp.19-24
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• 2004

Dose-response models in microbial risk assessment can be divided into biologically plausible models and empirical models. Biologically plausible models are formed by the assumptions in dose distribution of microbes, host sensitivity to microbes, and minimal infectious dose of microbes : there are Exponential model and $\beta$-Poisson model, representatively. Empirical models are mainly used to express the toxicity of chemicals : there are Weibull-Gamma model etc. Deviance function (Y) is used to fit available data to dose-response models, and some dose-response models for food-borne pathogens are developed in humans and experimental animals.

• Safety and Health at Work
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• v.7 no.4
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• pp.322-325
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• 2016

Background: Musculoskeletal disorders (MSDs) are a common problem among carpet weavers. This study was undertaken to introduce affecting personal and occupational factors in developing the number of MSDs among carpet weavers. Methods: A cross-sectional study was performed among 862 weavers in seven towns with regard to workhouse location in urban or rural regions. Data were collected by using questionnaires that contain personal, workplace, and information tools and the modified Nordic MSDs questionnaire. Statistical analysis was performed by applying Poisson and negative binomial mixed models using a full Bayesian hierarchical approach. The deviance information criterion was used for comparison between models and model selection. Results: The majority of weavers (72%) were female and carpet weaving was the main job of 85.2% of workers. The negative binomial mixed model with lowest deviance information criterion was selected as the best model. The criteria showed the convergence of chains. Based on 95% Bayesian credible interval, the main job and weaving type variables statistically affected the number of MSDs, but variables age, sex, weaving comb, work experience, and carpet weaving looms were not significant. Conclusion: According to the results of this study, it can be concluded that occupational factors are associated with the number of MSDs developing among carpet weavers. Thus, using standard tools and decreasing hours of work per day can reduce frequency of MSDs among carpet weavers.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.17-25
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• 2001

Tree model is the most popular classification algorithm in data mining due to easy interpretation of the result. In CART(Breiman et al., 1984) and C4.5(Quinlan, 1993) which are representative of tree algorithms, the split fur classification proceeds to attain the homogeneous terminal nodes with respect to the composition of levels in target variable. But, fur instance, in the chum prediction modeling fur CRM(Customer Relationship management), the rate of churn is generally very low although we are interested in mining the churners. Thus it is difficult to get accurate prediction modes using tree model based on the traditional split rule, such as mini or deviance. Buja and Lee(1999) introduced a new split rule, one-sided purity for classifying minor interesting group. In this paper, we compared one-sided purity with traditional split rule, deviance analyzing churning vs. non-churning data of ISP company. Also reviewing the result of tree model based on one-sided purity with some simulated data, we discussed problems and researchable topics.

• Korean Security Journal
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• no.42
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• pp.423-447
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• 2015

This paper gives analyses on the historical origin where features from social punishment and re-socialization in North Korea have been developed. The process of the development largely consists of three periods, that is, the period of nation construction (1945-1950), the period of Korean War (1950-1953), the period of nation reconstruction (1950-1961). This paper provides that features from punishment and re-socialization have been developed during the historical transformation from pre-Korean War to post-Korean War. The 'wartime socialism system' had been established in the course of reconstruction of postwar nation. In the system, North Korean had been embraced into the structure of re-socialization in its production unit and living space.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.335-345
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• 2009

This paper is 1) to find out what make cause in the emotional labor and emotional dissonance on hotel employee, 2) to investigate relationship between burnout and turnover intention on the personal character, 3) finally to suggest strategical implications for hotel management decision-maker. The questionnaires are distributed 400 on hotel employees, then used for data analysis 351. The results are as followed. First, the higher surface acting, deep acting, and emotional deviance in the emotional labor, the higher emotional dissonance. But the higher expression of natural emotions, it was showed lowly in the emotional dissonance. Second, the higher emotional dissonance, it was revealed highly burnout and turnover intention.

• Journal of the Korean Statistical Society
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• v.30 no.3
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• pp.347-366
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• 2001

Robust analogues of the likelihood ratio test are considered for testing of hypotheses involving multiple discrete distributions. The test statistics are generalizations of the Hellinger deviance test of Simpson(1989) and disparity tests of Lindsay(1994), obtained by looking at a 'penalized' version of the distances; harris and Basu (1994) suggest that the penalty be based on reweighting the empty cells. The results show that often the tests based on the ordinary and penalized distances enjoy better robustness properties than the likelihood ratio test. Also, the tests based on the penalized distances are improvements over those based on the ordinary distances in that they are much closer to the likelihood ratio tests at the null and their convergence to the x$^2$ distribution appears to be dramatically faster; extensive simulation results show that the improvement in performance of the tests due to the penalty is often substantial in small samples.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.187-194
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• 2014

We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.971-984
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• 2015

Imputation procedures fill-in missing values, thereby enabling complete data analyses. Fully efficient fractional imputation (FEFI) and multiple imputation (MI) create multiple versions of the missing observations, thereby reflecting uncertainty about their true values. Methods have been described for hypothesis testing with multiple imputation. Fractional imputation assigns weights to the observed data to compensate for missing values. The focus of this article is the development of tests of independence using FEFI for partially classified two-way contingency tables. Wald and deviance tests of independence under FEFI are proposed. Simulations are used to compare type I error rates and Power. The partially observed marginal information is useful for estimating the joint distribution of cell probabilities, but it is not useful for testing association. FEFI compares favorably to other methods in simulations.