• 한국초등과학교육학회지:초등과학교육
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• 제28권2호
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• pp.154-160
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• 2009

Correlational reasoning is used to analyze results from an experiment and create meaningful relationships among variables. Although there were many recognition development studies, not a single study found the optimal period for the development of logical thinking. Therefore, the purpose of this study is to find the optimal period for students whose logic for variable controlling and correlational reasoning are poor. This study made a logic program treatment subject for students between the 4th and 8th grade whose recognition in reasoning has not been developed in general in order to find the optimal period for their development. The variable-controlling reasoning was performed the program of voice survey and sugared-water melting in subsection survey and sugared-water melting in subsection. And, the correlation reasoning was performed the program of rat's size and tail color, treatment, and effect. As a result of research, students, who were not formed variable controlling and correlational reasoning, could be known to be enhanced through learning, but to fail to be formed the qualitative change like the cognitive development. In other words, the optimal period couldn't be found that is grown the formation of students, who are not formed the variable controlling and correlational reasoning, through learning. It is expected that this research can contribute to the improvement of students' cognitive level and there would be more active researches in different fields to improve the cognitive level.

• 전기의세계
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• 제17권1호
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• pp.48-50
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• 1968

The convergence rate of Bayes' learning process is investigated for a binomial random variable. A measure of the rate of convergence is proposed and it is found that such a measure can be approximated by an exponential function of the number of observations.

• 디지털융복합연구
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• 제8권3호
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• pp.115-127
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• 2010

본 연구는 현재 사이버 대학에서 제공하고 있는 강의서비스 품질이 학습자의 학습동기에 따라 학습 만족에 어떠한 영향을 미치고 있는지를 연구하였다. 강의서버스 품질은 기존의 서비스 품질 측정요인으로 사용되고 있는 SERVQUAL(유형성, 신뢰성, 반응성, 확신성, 공감성) 바탕으로 강의서비스 품질을 측정하였다. 분석결과 강의서비스 품질와 유형성, 확신성, 신뢰성, 공감성은 학습만족에 지지되었고 반응성은 기각되었다. 학습동기가 학습만족에 조절변수로서의 할 것이라는 가설을 검정하기 위하여 3단계 계층회귀분석을 실시하였다. 강의서비스 품질의 각 구성요인과 학습동기가 상호작용할 때 전반적 만족에 유의한 영향을 주고 있다는 3단계 모델의 설명력이 높게 나타남으로써 전체적으로 학습동기의 상호 작용 효과는 입증되었다.

• 대한기계학회논문집A
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• 제41권1호
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• pp.63-68
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• 2017

이 논문에서는 열간 사상압연 공정에서 스트립 통판성의 안정성과 판 품질 향상을 위하여 새로운 선진율 학습모델 개발에 관한 연구를 수행한다. 먼저 기존의 선진율 해석모델에 대한 고찰을 통해 스트립 장력, 루퍼 각도 그리고 롤 주속이 선진율 학습에 크게 영향을 미치는 주요 압연 인자들임을 보인다. 두 번째로는 선진율 학습의 주요 압연 인자들을 이용하여 새로운 선진율 학습모델을 도출한 후, 보조변수 규명 알고리즘을 이용하여 이산시간계 학습모델을 규명한다. 끝으로 컴퓨터 시뮬레이션을 통해 이 논문에서 제안한 새로운 학습모델이 기존의 학습모델보다 유용함을 보인다.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.651-661
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• 2020

This research aims to examine the relationships among entrepreneurial orientation, organizational learning capability, firm innovation, and firm performance. To achieve a data collection, a mail survey procedure via questionnaire was implemented by using executives or managers of gems & jewelry industries, textile and clothing industries, leather and accessories, fashion apparel industries in Thailand as the key informants. Of the surveys completed and returned, 388 were usable. Hence, a model with a structural equation was used to evaluate the data survey of 388 respondents. The results reveal that, in terms of the mediating effect, organizational learning capacity and firm innovation can complement each other in order to improve entrepreneurial orientation. Findings show that entrepreneurial orientation improves firm innovation, which in turn improves firm efficiency. Firm innovation acts as a variable mediating between enterprise orientation and firm performance. Our findings contribute to the current emergence of organizational learning capacity that mediated the relationship between entrepreneurial orientation and firm performance. Entrepreneurial orientation is normally a firm performance that enterprises develop which can have use the information available and make an impact. It can be considered through the mediation of organizational learning capability, and firm innovation variable and as stated in previous literature, it can influence firm performance.

• 유통과학연구
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• 제21권2호
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• pp.91-102
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• 2023

Purpose: to explore more deeply the variables of knowledge construction in influencing performance, through entrepreneurial leadership, motivation, organizational learning, and commitment to the performance of midwives in providing maximum service to patients and the community. Research design, data and methodology: using quantitative methods with hypothesis testing, data was obtained through direct visits and surveys to midwife practice locations through coordination with the Indonesian Midwives Association (IBI) regarding surveys to be carried out and needed. Results: there are 3 direct paths that have significant value. The path between the motivation variable to commitment was found to be significant, then the effect of organizational learning on commitment was found to be significant and finally the effect of the path variable from commitment to distribution performance was found to be significant. The indirect effect was found to be insignificant for the influence of entrepreneurial leadership through commitment to distribution performance, but different results found a significant indirect effect for the relationship between motivation through commitment to performance and organizational learning through commitment to distribution performance. Conclusion: there is a high commitment to the work of midwives, commitment as a good mediation in influencing distribution performance between organizational learning and work motivation.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.345-359
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• 2024

A regression model represents the relationship between explanatory and response variables. In real life, explanatory variables often affect a response variable with a certain time lag, rather than immediately. For example, the marriage rate affects the birth rate with a time lag of 1 to 2 years. Although deep learning models have been successfully used to model various relationships, most of them do not consider the time lags between explanatory and response variables. Therefore, in this paper, we propose an extension of deep learning models, which automatically finds the time lags between explanatory and response variables. The proposed method finds out which of the past values of the explanatory variables minimize the error of the model, and uses the found values to determine the time lag between each explanatory variable and response variables. After determining the time lags between explanatory and response variables, the proposed method trains the deep learning model again by reflecting these time lags. Through various experiments applying the proposed method to a few deep learning models, we confirm that the proposed method can find a more accurate model whose error is reduced by more than 60% compared to the original model.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.209-225
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• 2024

This research aims to use machine learning technology in human resource management to predict employees' work-life balance. The study utilized a dataset from IBM Watson Analytics in the IBM Community for the machine learning analysis. Multinomial dependent variables concerning workers' work-life balance were examined, categorized into continuous and categorical types using the Generalized Linear Model. The complexity of assessing variable roles and their varied impact based on the type of model used was highlighted. The study's outcomes are academically and practically relevant, showcasing how machine learning can offer further understanding of psychological variables like work-life balance through analyzing employee profiles.

• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.659-672
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• 2005

This paper evaluates discretization of continuous variables to select relevant variables for supervised learning using mutual information. Three discretization methods, MDL, Histogram and 4-Intervals are considered. The process of discretization and variable subset selection is evaluated according to the classification accuracies with the 6 real data sets of UCI databases. Results show that 4-Interval discretization method based on quantiles, is robust and efficient for variable selection process. We also visually evaluate the appropriateness of the selected subset of variables.

• 한국컴퓨터정보학회논문지
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• 제14권5호
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• pp.201-209
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• 2009

본 연구의 주요 목적은 교육공학 관점과 정보기술 관점의 통합적 연구모형을 통해 이러닝 특성과 이러닝 학업성과 간의 관계를 규명하는 것이다. 이에 본 연구에서는 이러닝 시스템 품질, 이러닝 콘텐츠 특성, 상호작용 등을 독립변수로, 이러닝 학업성과를 종속변수로, 학습동기를 매개변수로 설정, 이들 변수간의 관계를 검증해 보았다. 연구를 위해 212명의 사이버 대학 재학생들이 설문조사에 참여하였다. 연구의 주요 결과를 요약하면 첫째, 이러닝 특성 중 기술적 품질 컨텐츠 품질 학사지원 등이 학업성과에 유의한 영향을 미치는 것으로 나타났고, 둘째, 이러닝 특성과 학업성과간의 관계에 대한 학습동기의 매개효과 분석 결과, 학습 동기는 양자간의 관계에서 부분적인 매개 효과를 가지는 것으로 나타났다. 연구결과에 근거 향후 이러닝 이용자들의 학업성과 향상을 위한 몇 가지 시사점을 제시하면 이러닝 학습자들의 다양한 수준과 목적을 고려한 강좌 및 강의내용이 적절히 제공되고, 학습자와 이러닝 시스템 간 상호작용을 원활히 할 수 있는 기능이 적극 제공된다면 이러닝의 실질적 유효성을 훨씬 더 높일 수 있을 것으로 사려된다.