• Journal of Environmental Health Sciences
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• v.46 no.1
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• pp.96-102
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• 2020

Objectives: This study identified factors impacting radiation knowledge among aircrew, who are affected by cosmic radiation exposure due to their occupational environment. Methods: In September 2019 we conducted an online survey of aircrew through a Google link. We evaluated the level of radiation knowledge using a ten-item (10 points) questionnaire. The following exploratory variables were evaluated in relationship with the level of radiation knowledge using univariable linear regression models: sex, age, duration of employment, position level, company, marriage, education level, personal/family history of disease, and the number of times acquiring information on radiation through various channels (internet searching, watching television, reading newspaper, conversation about radiation with aircrew/non-aircrew, in-house training). With a p of 0.2 in univariable models, we built a multivariable linear regression model using a stepwise selection method. Results: The average radiation knowledge score of the 356 respondents was 7.22. Univariable linear regression analysis showed that radiation knowledge of the aircrew was associated with their company, position level, age, and number of conversations with other aircrew members. Our multivariable model showed that the radiation knowledge level of aircrew decreased as they had more conversations about radiation with other aircrew members and as their age increased. Conclusions: Korean air crew showed a lower level of radiation knowledge as their age and the number of conversations with colleagues increased. The study suggests that more education is needed in order for aircrew to gain accurate radiation knowledge.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.1
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• pp.14-28
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• 2007

This study presented the selection of ozone ($O_3$) potential factors and designed and assessed its potential prediction model using multiple-linear regression equations in Ulsan area during the springtime from April to June, $2000{\sim}2004$. $O_3$ potential factors were selected by analyzing the relationship between meterological parameters and surface $O_3$ concentrations. In addition, cluster analysis (e.g., average linkage and K-means clustering techniques) was performed to identify three major synoptic patterns (e.g., $P1{\sim}P3$) for an $O_3$ potential prediction model. P1 is characterized by a presence of a low-pressure system over northeastern Korea, the Ulsan was influenced by the northwesterly synoptic flow leading to a retarded sea breeze development. P2 is characterized by a weakening high-pressure system over Korea, and P3 is clearly associated with a migratory anticyclone. The stepwise linear regression was performed to develop models for prediction of the highest 1-h $O_3$ occurring in the Ulsan. The results of the models were rather satisfactory, and the high $O_3$ simulation accuracy for $P1{\sim}P3$ synoptic patterns was found to be 79, 85, and 95%, respectively ($2000{\sim}2004$). The $O_3$ potential prediction model for $P1{\sim}P3$ using the predicted meteorological data in 2005 showed good high $O_3$ prediction performance with 78, 75, and 70%, respectively. Therefore the regression models can be a useful tool for forecasting of local $O_3$ concentration.

• Journal of Preventive Medicine and Public Health
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• v.43 no.2
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• pp.159-165
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• 2010

Objectives: We evaluated the reliability of the possible covariates of the baseline survey data collected for the Epidemiological Investigation on Cancer Risk Among Residents Who Reside Near the Nuclear Power Plants in Korea. Methods: Follow-up surveys were conducted for 477 participants of the cohort at less than 1 year after the initial survey. The mean interval between the initial and follow-up surveys was 282.5 days. Possible covariates were identified by analyzing the correlations with the exposure variable and associations with the outcome variables for all the variables. Logistic regression analysis with stepwise selection was further conducted among the possible covariates to select variables that have covariance with other variables. We considered that these variables can be representing other variables. Seven variables for the males and 3 variables for the females, which had covariance with other possible covariates, were selected as representative variables. The Kappa index of each variable was calculated. Results: For the males, the Kappa indexes were as follow; family history of cancer was 0.64, family history of liver diseases in parents and siblings was 0.56, family history of hypertension in parents and siblings was 0.51, family history of liver diseases was 0.50, family history of hypertension was 0.44, a history of chronic liver diseases was 0.53 and history of pulmonary tuberculosis was 0.36. For females, the Kappa indexes were as follow; family history of cancer was 0.58, family history of hypertension in parents and siblings was 0.56 and family history of hypertension was 0.47. Conclusions: Most of the possible covariates showed good to moderate agreement.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.936-942
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• 2015

The purpose of this study was to characterize genetic architecture of behavior patterns in Sapsaree dogs. The breed population (n=8,256) has been constructed since 1990 over 12 generations and managed at the Sapsaree Breeding Research Institute, Gyeongsan, Korea. Seven behavioral traits were investigated for 882 individuals. The traits were classified as a quantitative or a categorical group, and heritabilities ($h^2$) and variance components were estimated under the Animal model using ASREML 2.0 software program. In general, the $h^2$ estimates of the traits ranged between 0.00 and 0.16. Strong genetic ($r_G$) and phenotypic ($r_P$) correlations were observed between nerve stability, affability and adaptability, i.e. 0.9 to 0.94 and 0.46 to 0.68, respectively. To detect significant single nucleotide polymorphism (SNP) for the behavioral traits, a total of 134 and 60 samples were genotyped using the Illumina 22K CanineSNP20 and 170K CanineHD bead chips, respectively. Two datasets comprising 60 (Sap60) and 183 (Sap183) samples were analyzed, respectively, of which the latter was based on the SNPs that were embedded on both the 22K and 170K chips. To perform genome-wide association analysis, each SNP was considered with the residuals of each phenotype that were adjusted for sex and year of birth as fixed effects. A least squares based single marker regression analysis was followed by a stepwise regression procedure for the significant SNPs (p<0.01), to determine a best set of SNPs for each trait. A total of 41 SNPs were detected with the Sap183 samples for the behavior traits. The significant SNPs need to be verified using other samples, so as to be utilized to improve behavior traits via marker-assisted selection in the Sapsaree population.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.2
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• pp.65-70
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• 2015

In the PCB(Printed Circuit Board) manufacturing industry, the yield is an important management factor because it affects the product cost and quality significantly. In real situation, it is very hard to ensure a high yield in a manufacturing shop because products called chips are made through hundreds of nano-scale manufacturing processes. Therefore, in order to improve the yield, it is necessary to analyze main fault process and equipment that cause low PCB yield. This paper proposes a systematic approach to discover fault-causing processes and equipment by using a logistic regression and a stepwise variable selection procedure. We tested our approach with lot trace records of real work-site. A lot trace record consists of the equipment sequence that the lot passed through and the number of faults for each fault type in the lot. We demonstrated that the test results reflected the real situation of a PCB manufacturing line.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.37-47
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• 2014

The characteristics of the spectrum, which are necessary for mobile telecommunication services, may determine the advantage of operators' competition for mobile services. We have a focus on the possibility that there would be the core spectrum within the frequencies. We define the core spectrum of frequencies in terms of 4 criteria (global source/roaming, cost-effectiveness, the experience of utilization and the possibility of use). They are based on the aspects of applicative and economic effectiveness by not technological and but market conditions. We have explored the current core spectrum by using the stepwise selection from these criteria. Our result indicates that the core spectrum may be movable with the development of technology and the flow of time. The results of this paper could be practically used as the reasonable justifications of the policies for not only the competition management but also the alignment about the frequencies for mobile telecommunication.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.219-225
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• 2019

There is a problem with the existing method of selecting the difficulty levels of Hanja characters. Some Hanja characters selected by the existing methods are different from Sino-Korean words used in real life and it is impossible to know how many times the Hanja characters are used. To solve this problem, we measure the difficulty of Hanja characters using the multiple regression analysis with the frequency as the features. Based on the elementary textbooks, FWS and FHU are counted. A questionnaire is written using the two frequencies and stroke together to answer the appropriate timing of learning the Hanja characters and use them as target variables for regression. Use stepwise regression to select the appropriate features and perform multiple linear regression. The R² score of the model was 0.1105 and the RMSE was 0.1105.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.819-827
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• 2009

This study was conducted to investigate the relationship between the sociodemographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender, occupation, monthly income, and beef cut and the the palatability grade as the dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to find the associations between categories.

• Journal of the Korean School Mathematics Society
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• v.10 no.1
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• pp.113-127
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• 2007

This study explored the possibility of building a statistical model predicting difficulty of mathematics test items through the analysis of nation-wide scholastic ability test results for the past 5 years. Multiple linear regression analysis was conducted in predicting difficulty of mathematics test items. We adopted three major areas for independent variables: the content area, the behavior area, and the test item format area, each of which was categorized into more detailed sub-areas. For the dependent variable, the proportion of correct answer was used to represent the item difficulty. Statistically significant independent variables were included in the regression model based on the stepwise selection method. Several important factors affecting difficulty of mathematics test items for each area were identified. R-squares for the final regression model were fairly high, implying that the regression equation can be used to predict difficulty of test items at an acceptable level. Lastly, the regression model was cross-validated using independently collected data. We believe that this study will provide basic but very critical information for predicting the proportion of correct answer by showing the factors that should be considered for developing mathematics test items for the college entrance examination or high school classroom test.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1261-1264
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• 2016

Background: In breast cancer (BC), it has been suggested that nuclear overexpression of p53 protein might be an indicator of poor prognosis. The aim of the current study was to evaluate the expression of p53 BC in Kurdish women from the West of Iran and its correlation with other clinicopathology figures. Materials and Methods: In the present retrospective study, 231 patients were investigated for estrogen receptor (ER) and progesterone receptor (PR) positivity, defined as ${\geq}10%$ positive tumor cells with nuclear staining. A binary logistic regression model was selected using Akaike Information Criteria (AIC) in stepwise selection for determination of important factors. Results: ER, PR, the human epidermal growth factor receptor 2 (HER2) and p53 were positive in 58.4%, 55.4%, 59.7% and 45% of cases, respectively. Ki67 index was divided into two groups: 54.5% had Ki67<20% and 45.5% had Ki67 ${\geq}20%$. Of 214 patients, 137(64%) had lymph node metastasis and of 186 patients, 122(65.6%) had vascular invasion. Binary logistic regression analysis showed that there was inverse significant correlation between lymph node metastasis (P=0.008, OR 0.120 and 95%CI 0.025-0.574), ER status (P=0.006, OR 0.080, 95%CI 0.014-0.477) and a direct correlation between HER2 (P=005, OR 3.047, 95%CI 1.407-6.599) with the expression of p53. Conclusions: As in a number of studies, expression of p53 had a inverse correlation with lymph node metastasis and ER status and also a direct correlation with HER2 status. Also, p53-positivity is more likely in triple negative BC compared to other subtypes.