• Journal of Nutrition and Health
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• 제32권8호
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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.

• 한국IT서비스학회지
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• 제18권2호
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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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• 제17권1호
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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

• 경영과정보연구
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• 제36권5호
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• pp.61-83
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• 2017

본 연구는 참여적 리더십과 창의적 행동 간 심리적 임파워먼트의 매개효과를 규명하고자 한다. 특히 심리적 임파워먼트의 단일차원과 다차원을 통합적으로 분석하고 이를 통해 이론적 방법론적 시사점과 함께 참여적 리더십의 효과적 실천방안을 제시하는 것을 목적으로 한다. 자기보고형 설문방식의 측정으로 나타날 수 있는 동일방법편의(common method bias)를 해결하기 위하여 종속변수는 시차를 두고 측정하였고, 직무상황에서의 정서 상태(긍정정서, 부정정서)를 직급과 함께 통제변수로 채택하였다. 국내 300인 이상 규모의 다양한 업종의 기업에 근무하는 직장인들로부터 획득된 283부의 설문지가 분석에 사용되었고, SPSS PROCSS macro 프로그램(model 4)을 이용하여 분석하였다. 연구 결과, 첫째, 참여적 리더십과 창의적 행동 간의 관계에서 심리적 임파워먼트(단일차원)의 완전매개효과가 확인되었다. 둘째, 심리적 임파워먼트의 다차원별 분석 결과, 의미(meaning), 자기결정(self-determination), 영향(impact)의 완전매개 효과가 확인되었고, 역량의 매개효과는 유의하지 않았다. 셋째, 심리적 임파워먼트의 단일차원(1개 요인)과 다차원(4개 요인)의 매개효과를 비교한 결과, 단일차원의 매개효과가 다차원의 매개효과보다 큰 것으로 확인되었고 다차원별 매개효과의 크기는 비슷한 수준으로 나타났다. 이는 해외 연구에서 밝혀진 참여적 리더십의 동기부여모델(motivational model)을 국내 경영환경에서 입증한 사례로서 향후 연구의 기반이 된다는 점에서 그 의미가 크다. 이상의 실증연구 결과를 바탕으로 연구의 의의 및 한계점, 향후 연구방향을 제시하였다.

• Structural Engineering and Mechanics
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• 제37권4호
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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.

• 한방재활의학과학회지
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• 제20권4호
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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.

• 한국콘텐츠학회논문지
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• 제15권8호
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• pp.564-578
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• 2015

본 연구는 지속경력학습 선행변인(개인-직무적합성, 인적자본투자)과 결과변인(주관적 경력성공)에 대한 인과관계 규명과 개인-직무적합성, 인적자본투자와 주관적 경력성공의 관계에서 지속경력학습 매개효과를 규명한다. 연구목적을 달성하기 위한 자료는 울산지역 자동차 및 제주지역 공기업 종사자 241명으로부터 수집되었으며, 동일방법편의 대안으로 측정환경 분리방법으로 자료를 수집하였다. 분석결과, 첫째, 개인-직무적합성과 인적자본투자가 지속경력학습에 긍정적인 영향을 미치고, 둘째, 지속경력학습인 주관적 경력성공을 촉진하는 주요원인으로 확인되었으며, 셋째, 지속경력학습은 개인-직무적합성 및 인적자본투자와 주관적 경력성공의 관계를 각각 부분매개 하는 것으로 규명되었다. 본 연구의 시사점으로는 직무 및 조직차원변인을 활용하여 지속경력학습의 선행변인을 실증적으로 규명하여 지속경력학습의 연구범위 확대에 기여하고 있으며, 주관적 경력성공 연구에 대한 연구자들의 관심을 촉발하는 계기를 제공하고 있다. 또한 지속 경력학습의 매개효과 규명을 통해 개인의 경력개선 과정 메커니즘을 실증적으로 규명하고 있다.

• 지식경영연구
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• 제18권4호
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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.

• 한국콘텐츠학회논문지
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• 제15권9호
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• pp.527-540
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• 2015

본 연구는 부서원이 지각하는 부서장의 주도적 성격과 상향 영향력간 관계에 있어서 부서원이 지각하는 부서장의 정치적 기술의 4가지 하위차원의 매개효과를 확인하고자 하였다. 동일방법 오류를 방지하기 위하여 자료 수집의 원천을 달리하였다. 연구결과, 첫째 부서원이 지각하는 부서장의 주도적 성격은 부서원이 지각하는 부서장의 정치적 기술의 4가지 차원과 부서장의 상향 영향력에 각각 정(+)의 영향을 미쳤다. 둘째, 부서장의 주도적 성격과 상향 영향력 간 관계에 있어서 사회적 통찰력과 대인관계 영향력은 부분 매개효과를 나타냈으며, 외형적 진실성은 완전 매개효과를 나타냈다. 반면, 네트워킹 능력은 매개효과를 나타내지 않았다. 즉, 부서장의 주도적 성격은 네트워킹 능력을 경로로 해서는 상향 영향력에 긍정적 영향을 주지 못함을 알 수 있었다. 학문적 및 실무적 시사점을 도출하였고, 연구 한계 및 향후 연구방향 등에 대해서 제시하였다.

• Child Health Nursing Research
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• 제22권2호
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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.