• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.982-983
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• 2005

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2010.04a
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• pp.122-127
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• 2010

• Proceedings of the Korean Society For Composite Materials Conference
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• 1999.04a
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• pp.152-157
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• 1999

• Korean Journal of Adult Nursing
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• v.20 no.1
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• pp.113-125
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• 2008

Purpose: This research was conducted to explore the experiences of graduate student women with children fulfilling multiple roles and to generate a substantive theory. Methods: This study uses the grounded theory method based on Strauss and Corbin(1988)'s method. Interviews were conducted with 11 graduate student women who had children aged three of older. Results: The core category of this research is 'Role balancing for self-generativity'. Based on the core category, three types of married women graduate students' experiences were found. They are 'concentrating on graduate-work' 'postponing graduate-work' and 'adjustment between two roles' Conclusions: Through understanding the married women's multiple roles experience process, there can be a basis for making a women's health system and social support system for the married women graduate student. Also, this research is to generate a substantive theory which can helps to change social perspectives on the quality of life for the women who will contribute in Korean society as professionals.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.476-477
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• 2005

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.225-234
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• 2021

This research aimed to investigate the key factors affecting student satisfaction and loyalty in selected private universities in Cambodia. The study implemented a quantitative survey designed and guided by seven hypotheses to test the causal relationships among variables, such as academic experience, faculty services, campus life, social integration, student support facilities, student satisfaction, university image, and student loyalty. The research applied a multi-stage sampling technique of probability procedures to guarantee the presence of the research population. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were applied for data analysis to test the hypotheses model. The collected survey totaled 543 from three universities. The purposive sampling methods were used to select the three target universities, based on their reputation, the number of students, year of establishment, and the recognition from the Ministry of Education, Youth, and Sport. The stratified random sampling method was employed to select target respondents for data collection by dividing the population into subgroups to ensure a random sample. The results showed that student support facilities, campus life, and social integration, faculty services, and university image play very important roles in the satisfaction and loyalty of the students in three universities.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.513-514
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• 2005

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1555-1560
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• 2004

We made a simplified eddy-current-tester, and observed some materials for the ingredients and mass and locations. The tester detects the current as frequency shifts of a LC-resonance circuit, which are caused by the eddy currents. Using air-wick coil and a multi-piled ceramic capacitor, we made a resonance system whose frequency was 100KHz. The shift quantity is few; so, to detect it, we used a frequency counter, and counted the shift. We can detect 10Hz order's shift.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.325-333
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• 1996

This study was conducted to develop neural networks of predicting the sugar content of fruits based on the optical densities obtained from a spectrophotometer. Pear, apple and peach were used in investigating the feasbility of the developed neural networks as a nondestructive measurement. A spectrophotometer was used to measure the optical densities of test fruits. The neural networks suggested in this study consisted of multi-layers having one hidden layer and one output layer. The correlation coefficients between the predicted and the measured sugar content for most fruits were high. The neural networks using 2nd derivatives of optical density spectrum produced a better results in predicting the sugar content of fruits. This study contributed to develop a method for nondestructively predicting the sugar content of fruits.

• Korean Medical Education Review
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• v.25 no.2
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• pp.126-131
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• 2023

The aim of this study was to systematically collect data for evaluating short- and long-term outcomes using Kirkpatrick's four-level evaluation model, Chonnam National Medical School has established plans for developing and managing a database of student and graduate cohorts. The Education Evaluation Committee, with assistance from the Medical Education Office, manages the development and maintenance of cohort data. Data collection began in the 2022 academic year with first- through fourth-year medical students and graduates of the year 2022. The collected data include sociodemographic characteristics, admission information, psychological test results, academic performance data, extracurricular activity data, scholarship records, national medical licensing exam results, and post-graduation career paths. The Education Evaluation Committee and the Medical Education Office analyze the annually updated student and graduate cohort data and report the results to the dean and relevant committees. These results are used for admissions processes, curriculum improvement, and the development of educational programs. Applicants interested in using the student and graduate cohort data to evaluate the curriculum or conduct academic research must undergo review by the Educational Evaluation Committee before being granted access to the data. It is expected that the collected data from student and graduate cohorts will provide a sound and scientific basis for evaluating short- and long-term achievements based on student, school, and other characteristics, thereby supporting medical education policies, innovation, and implementation.