• Journal of Nutrition and Health
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• v.32 no.8
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• pp.957-966
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• 1999

Underreporting of dietary intake is common and might distort analysis and interpretation of dietary surveys. This study was designed to investigate the degree of underreporting and characterastics of under-reporting group in Korean college female students. Dietary survey of 1-day 24-hour recall method was conducted on 379 college students in Seoul and Chonan areas. Physical activity and life style were aquired from questionnnaires. Underreporting was defined as energy intake(EI) lower than 0.9BMR(based metabolic rate), since EI<0.98BMR is statistically judged as bias in 1-day 24 hour recall. BMR was calculated from Schofield's equation. Proportion of underreporting was 18.7% and it's not so different from one of American or European women. Intake of nutrients except vitamin A by underreporting group was lower than other groups(p<0.001). Proportions of subjects with nutrient intake level less than 75% of Korean RDA were more than 80% in protein, Ca, Fe, vitamin A, riboflavin, niacin, zinc as well as energy. Dietary quality of underreporting group was also worse than other groups. Proportion of subjects less than 3 food groups among 5 food group was higher in underreporting group. The number of foods eaten by underreporting group were also less than those of other groups. BMI and body weight were the largest in underreporting group(p<0.05) and the trial of weight reduction was shown higher trend(p<0.01). Different in PAC and other characteristics between underreporting group and other group were not significant. Not only dietary quantity but also dietary quality were worse in the underreporting group. Furthermore underreporting in college female students seemed to be affected by body weight and concern for weight reduction.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.143-159
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• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.

• Asia Marketing Journal
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• v.17 no.1
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• pp.123-148
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• 2015

Built on regulatory focus theory, this article develops a research model proposing the relationship between management controls (outcome, activity and capability), sales employees' prevention and promotion focus and their behavioral responses (feedback seeking from different sources and relationship investment). The model also suggests that salesperson perceived organizational fit (P-O fit) contributes by influencing the situational self-regulatory mechanism based on regulatory fit theory. To analyze the data, a structural equation model procedure using LISREL 8.5 was employed. To access the potential common method bias, the MV" marker method was applied using a scale theoretically unrelated to at least one scale in the analysis as the MV marker. The results showed that the greater the salesperson's perceived activity control system, the greater the extent of employee prevention focus. The findings also showed that output control and capability control system are positively related to the promotion focus of salespeople. Salespeople's prevention focus relates negatively to the relational investment and positively to organization feedback seeking. The results indicate that salespeople who have promotion focus exhibit the predicted positive influence on their relationship investment. A significant contribution of this research framework is suggesting salesperson regulatory focus as a mediator and its' effects on different types of sales-related behaviors. The author suggests that the motivational orientations of salespeople play key roles in shaping feedback seeking behaviors from different sources; broadly, that employees with a promotion focus will be more sensitive to customers' feedback, and employees with a prevention focus will seek more feedback from the organization. Furthermore, salespeople with a promotion focus will invest more resources to build relationships with customers than salespeople with a prevention focus. This research also explains the moderating role of person-organization fit on the effect of salespeople's regulatory focus and behavioral responses based on regulatory fit theory

• Management & Information Systems Review
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• v.36 no.5
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• pp.61-83
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• 2017

The purpose of this study is to investigate the mediating effects of psychological empowerment between participative leadership and creative behavior. Especially, it aims to analyze the unidimension and multidimension of psychological empowerment in an integrated manner, and to suggest effective practice of participative leadership together with theoretical and methodological implications. In this study, the dependent variable was measured separately with time lag as a method to solve the common method bias that can be shown by the self-report type survey method, and positive emotions and negative emotions expressing emotional states in job situations were employed as control variables along with rank. A total of 283 questionnaires were collected from employees who work for companies in various industries with more than 300 domestic employees. SPSS PROCESS macro program('model 4') was used for statistical analysis. Results, First, the full mediation effect of psychological empowerment(unidimension) was confirmed in the relationship between participative leadership and creative behavior. Second, the analysis of the multidimension of psychological empowerment revealed the full mediating effect of meaning, self-determination, and impact, and the mediating effect of competence was not significant. Third, as a result of comparing the mediating effects of unidimension of psychological empowerment and the mediating effects of multidimension, the magnitude of mediating effect of unidimension was found to be much greater than mediating effect of multidimension. And The magnitudes of the three multidimensional mediating effects were similar. This is a case in which the motivational model of participative leadership revealed in the overseas study is proven in the domestic management environment and is significant in that it is the basis of future research. Based on the results of the empirical studies, the implications and limitations of the study and future research directions are presented.

• Structural Engineering and Mechanics
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• v.37 no.4
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• pp.427-442
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• 2011

In fatigue life design of mechanical components, uncertainties arising from materials and manufacturing processes should be taken into account for ensuring reliability. A common practice is to apply a safety factor in conjunction with a physics model for evaluating the lifecycle, which most likely relies on the designer's experience. Due to conservative design, predictions are often in disagreement with field observations, which makes it difficult to schedule maintenance. In this paper, the Bayesian technique, which incorporates the field failure data into prior knowledge, is used to obtain a more dependable prediction of fatigue life. The effects of prior knowledge, noise in data, and bias in measurements on the distribution of fatigue life are discussed in detail. By assuming a distribution type of fatigue life, its parameters are identified first, followed by estimating the distribution of fatigue life, which represents the degree of belief of the fatigue life conditional to the observed data. As more data are provided, the values will be updated to reduce the credible interval. The results can be used in various needs such as a risk analysis, reliability based design optimization, maintenance scheduling, or validation of reliability analysis codes. In order to obtain the posterior distribution, the Markov Chain Monte Carlo technique is employed, which is a modern statistical computational method which effectively draws the samples of the given distribution. Field data of turbine components are exploited to illustrate our approach, which counts as a regular inspection of the number of failed blades in a turbine disk.

• Journal of Korean Medicine Rehabilitation
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• v.20 no.4
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• pp.105-130
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• 2010

Objectives : The purpose of this study was to assess the statistical methods errors used in the journal of Oriental Rehabilitation Medicine(JORM) and to identify the types of errors in statistical analysis. Methods : We reviewed quantitative articles that were published in the JORM from January 2005 through October 2009. Those were not used by statistical analysis such as literature studies, case study, review articles were not included in this analysis. A total of 296 articles was reviewed. We evaluated the adequacy and the validity of the statistical techniques with our checklist established be modified Lee's checklist, and three statistical evaluators assessed together to minimize bias. Results : Of the 222 articles, 213 were used in inferential and descriptive statistics. Of those 80% of articles adopting descriptive and inferential statistics were detected having statistical errors. One articles used 1.7 statistical method unit generally. Most frequently employed statistics were student t-test, one way ANOVA. pearson correlation analysis, Mann-whitney U test, paired t-test, and chi-square test in their order. However, most frequent statistics having errors were similar in order. The most common statistic errors were as follow: 1. absence of normality test, 2. misuse between paired test and unpaired test, 3. wrong choice of repeated measures analysis without consideration of time variables, 4, increase of Type I error by using inappropriate multiple test, 5. inappropriate application of discrete or categorical data instead of continuous data in correlation analysis, 6. poor consideration of basic consumption in chi-square test, 7. confusion between frequency comparison and average comparison, 8. mentioning the statistical technique without using it. Conclusions : We found various mistake or misuses in the applications of statistical methodologies in the articles published in the JORM. Careful consideration of statistical use and review from the specialist of statistics are warranted for improving the quality of JORM.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.564-578
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• 2015

The present study is aimed to investigate antecedents(person-job fit, human capital investment) and outcome variable(subjective career success) of continuous-related career learning, and to demonstrate mediating effects of continuous-related career learning. The data which was applied to analysis was collected from 241 office workers who have worked for automobile company in Ulsan and public companies in Jeju and applied temporal separation of measurement as an alternative for common method bias. The results are as follows. First, person-job fit, human capital investment affected to career-related continuous learning positively. Second, the impacts of career-related continuous learning to subjective career success was positively significant. Third, the mediating effects by career-related continuous learning demonstrated statistically significant in the links between antecedents-outcome variables as partial mediation. Implications of this study contribute to expand research area of continuous-related career learning with regard to job and organizational variables, and to facilitate of research interests on subjective career success. In addition, the mechanism of career advance was empirically proved by continuous-related career learning.

• Knowledge Management Research
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• v.18 no.4
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• pp.63-96
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• 2017

In a competitive organizational environment, members view completing tasks to perfection without mistakes as the requirement for success and good evaluation from others. However, unrealistically strong perfectionism can have negative effects on members' psychological states and organizational performance. This study focuses on evaluative concerns perfectionism, the negative aspect of perfectionism, based on positive psychology theory to explore the positive mechanism that comes into place in the process of strengthening organization members' resilience. For this purpose, we performed a moderated moderation analysis to investigate whether the moderating effect of leaders' social support (primary moderator) is moderated by their emotional intelligence (secondary moderator). To verify our research model, we conducted a two-part survey of 252 employees in various industries with a time interval to minimize the common method bias. Job rank and positive affectivity were set as control variables to identify the clear causal relationship among variables. Our findings showed that first, evaluative concerns perfectionism reduced resilience; second, leaders' social support positively moderated the relationship between evaluative concerns perfectionism and resilience; and third, the leaders' emotional intelligence positively moderated the two-way interaction between evaluative concerns perfectionism and the leaders' social support, confirming a moderated moderation. Our findings suggest the need for leaders to assume multidimensional roles to enhance the positive traits of organization members, especially in today's complex business environment. The implications of our findings are further discussed in relation to knowledge management and the development of organization members who exhibit evaluative concerns perfectionism, along with suggestions for future research.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.527-540
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• 2015

The current study empirically tests the mediating effects of political skills on the relationship between proactive personality and upward influence. In this study, we attempted to mitigate common method bias by collecting data from two sources. 275 pairs of returned questionnaires were utilized to verify the hypotheses. According to the hierarchical regression, proactive personality and 4 political skills have impact on upward influence positively. proactive personality was positively related to political skills. In addition social astuteness, interpersonal influence and apparent sincerity mediate relationship between proactive personality and upward influence. but networking ability does not have mediating effect. Based on these results, implications and limitations of this study arediscussed and future research direction are suggested.

• Child Health Nursing Research
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• v.22 no.2
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• pp.153-162
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• 2016

Purpose: It is critical that evidence from research is applied to everyday nursing practice to improve the quality of care and health outcomes. Aims of this study were to review high-risk infant related studies published in major nursing and non-nursing journals in Korea and to assess the quality of intervention studies. Methods: Through the Korean literature search engine of RISS.KR the authors identified 132 studies, and two researchers evaluated each of these studies using the analysis criteria. The quality of intervention studies was assessed using the van Tulder Scale. Results: Among the studies, 40.2% were either thesis or dissertation and 86.4% were quantitative studies. Convenience sampling was the most commonly used sampling method. All experimental studies were quasi-experiment except one pre-experiment study. Sensory stimulation and kangaroo care were the most common interventions for high-risk infants. Over half of the intervention studies were assessed to be "low risk of bias" but both randomization and blinding processes were not adequately satisfied in most of the studies. Conclusion: Findings of this study suggest that high-risk infants are more likely to be recruited for experimental studies but types of interventions were very limited. To provide evidence-based care for high-risk infants, rigorously conducted experimental studies should be encouraged.