• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1796-1809
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• 2021

The subchannel of a research reactor used to generate high power density is designed to be narrow and rectangular and comprises plate-type fuels operating under downward flow conditions. Critical heat flux (CHF) is a crucial parameter for estimating the safety of a nuclear fuel; hence, this parameter should be accurately predicted. Here, machine learning is applied for the prediction of CHF in a narrow rectangular channel. Although machine learning can effectively analyze large amounts of complex data, its application to CHF, particularly for narrow rectangular channels, remains challenging because of the limited flow conditions available in existing experimental databases. To resolve this problem, we used four CHF correlations to generate pseudo-data for training an artificial neural network. We also propose a network architecture that includes pre-training and prediction stages to predict and analyze the CHF. The trained neural network predicted the CHF with an average error of 3.65% and a root-mean-square error of 17.17% for the test pseudo-data; the respective errors of 0.9% and 26.4% for the experimental data were not considered during training. Finally, machine learning was applied to quantitatively investigate the parametric effect on the CHF in narrow rectangular channels under downward flow conditions.

• Journal of Practical Engineering Education
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• v.6 no.1
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• pp.43-49
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• 2014

It is known that the ability and habit to "flow" could be one of the important indices to evaluate one's life. And the flow experience of university students who are in the important time transferring from the adolescence to the initial adult period will give an important effect firstly to study one's major and map out one's career path, finally to spread out the high quality life. This study investigated the university students who are in School of Mechatronic Engineering to experience the flow in the learning of PLC (Programmable Logic Controller) practice. For this, the flow condition was arranged. And in order to experience the flow in the learning of PLC, lecture plan was established, studying environment was changed and level of difficulty was controlled. Then the implications of the flow were explored by a 5-point Likert scale survey performed to 90 students.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1162-1181
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• 2023

Tourism flow is not only the manifestation of tourists' special displacement change, but also an important driving mode of regional connection. It has been considered as one of significantly topics in many applications. The existing research on tourism flow prediction based on tourist number or statistical model is not in-depth enough or ignores the nonlinearity and complexity of tourism flow. In this paper, taking Nanjing as an example, we propose a prediction method of urban tourism flow based on deep learning methods using travel diaries of domestic tourists. Our proposed method can extract the spatio-temporal dependence relationship of tourism flow and further forecast the tourism flow to attractions for every day of the year or for every time period of the day. Experimental results show that our proposed method is slightly better than other benchmark models in terms of prediction accuracy, especially in predicting seasonal trends. The proposed method has practical significance in preventing tourists unnecessary crowding and saving a lot of queuing time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.364-372
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• 2016

This study examined the multi-phrased effects and outcomes of adult female learners who participated in lifelong learning activities, as well as the proposed structural relationships among the five latent variables. Questions established to achieve the purpose of the study are as follow: What effects do the learner's characteristics, lifelong education institutions, learning flow, and learning satisfaction have on the learning come? The participants of the survey numbered 632, but 54 respondents who were unreliable or did not complete their survey were excluded. A total of 578 cases were analyzed for this research. The structural relationships among the five latent variables-learner's characteristics, lifelong education institutions, learning flow and learning satisfaction, and learning outcome of the adult female learners-AMOS 18.0 program were also used for structural analysis. The major findings of this research are as follows. First, the model fitness showed that the hypothetical model provided a reasonable fit to the data ${\chi}^2=224.267$ (df=69, p<.001), RMSEA=.062, TLI=.943, RFI=.920, CFI=.957, IFI=.957, NFI=.939. Second, the learner's characteristics ( =.218, p<.001) and lifelong education institutions ( =.301, p<.001) have a direct effect on the learning outcomes. The learning flow ( =-.149 p=.541) does not have a direct effect on the learning outcome. Learning satisfaction ( =.405 p<.001) have a direct effect on the learning outcome. To put findings above together, in respect to adult female learners' performances, the learning outcomes are influenced directly by the learner characteristics, conditions of the lifelong education institutions, and learning satisfaction, whereas satisfaction indirectly affects the learners' learning outcome.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.69-76
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• 2012

The purpose of the study is to identify the relationship among the variables related learner's satisfaction, flow experience and self-directedness and verify the path model of causal relationship among those variables in web based computer e-learning. Based on the theoretical rationale, we hypothesized the path model including learner's satisfaction as outcome variable, flow experience and self-directedness as causal and mediating variables. A total of 193 students were participated in this study and the main results showed as follows: 1. Learner's self-directedness showed significant (p<.01), indirect effect on learner's satisfaction mediated by flow experience and the flow experience showed significant (p<.01), direct effect on learner's satisfaction; 2. Among 7 constructs of self-directedness, 'creative approach', 'love of learning', 'self-confidence as a learner' showed significant (p<.01), indirect effects on learner's satisfaction mediated by 'clear goals' construct among flow experience.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.71-90
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• 2010

Electronic learning(or e-learning) has created hype for companies, universities, and other educational institutions. It has led to the phenomenal growth in the use of web-based learning and experimentation with multimedia, video conferencing, and internet-based technologies. Many researchers are interested in the factors that affect to the performance of e-learning or e-learning services. In this sense, this study is aimed at proposing e-learning system reuse prediction models in which e-learner intention to reuse influence factors(i.e., system accessibility, system stability, information clarity, information validity, self-regulated efficacy, computer self-efficacy, perceived usefulness, perceived ease of use, flow, and parental expectation) affect e-learner intention to reuse positively. A web survey was conducted for the full members of the e-learning education institute A in Seoul, Republic of Korea, an exclusive e-learning company that provides real time video lectures via the desktop conferencing system. The web survey was conducted for 20 days from November 5, 2009, through the e-learning web site of the company A. In this study, three data mining techniques were used : the multivariate discriminant analysis, CART, and C5.0 algorithm. This study was conducted to provide the e-learning service providers, e-learning operators, and contents developers with marketing and management strategies for improving the e-learning service companies, based on the data mining analysis results.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.107-114
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• 2021

The purpose of this study is to investigate whether there is a difference in the effect of learning flow and teaching presence according to the lecturer's appearance and students' behavioral patterns in video learning. For this experiment, 183 freshmen from Xingtai University in China were selected as subjects. After being classified according to DISC, students were assigned to study the lecture videos with the appearance of the lecturer and the video without the appearance of the lecturer. After testing the level of their learning flow and teaching presence, the differences between groups were analyzed. According to the results of the analysis, the learning flow and teaching presence of groups who learned the videos in which the lecturer appeared were significantly higher than the groups who learned the videos without the appearance of the lecturer. Second, the effects of whether the lecturer appears or not according to DISC on learning flow were significant. However, the effects of DISC, and the interactive effect of DISC and the lecturer appearance were found to have no significant interactive effect on learning flow. Third, the effects of whether the lecturer appears or not according to DISC on teaching presence were significant, and the effects of DISC on teaching presence were not significant, but the interactive effect of lecturer appearance and DISC was significant. These findings suggest that lecture videos with the appearance of the lecturer generally have better effect. In particular, in order to enhance teaching presence, it is effective to decide whether the lecturer appears or not by considering its interactive effects with learners' DISC.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.597-604
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• 2020

This is a narrative research study conducted on the subject in order to understand the relationship between the meta-cognition, learning flow, and problem solving ability of nursing students in online class, and to find out the factors that influence problem solving ability, 88 students enrolled in 2nd and 3rd grade students who participated in online classes at G city universities. The analysis method was analyzed by means, standard deviation, t-test, one-way ANOVA, Pearson correlation, and stepwise multiple regression using SPSS version WIN 23.0. As a result of the study, the difference between learning flow and problem-solving ability according to general characteristics was significantly different depending on the perception of nurses after learning and the motivation for admission to the department of nursing, and the problem-solving ability was positively correlated with metacognition and learning flow. There was a relationship, and metacognition and learning flow were significant variables that influenced problem solving ability. The conclusion of the study is considered to be the basic data for the development of a systematic program that can increase the learning flow and meta-cognition to increase problem solving ability amid the change from nursing education to online classes, and to change the teaching method.

• Journal of The Korean Association of Information Education
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• v.21 no.4
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• pp.403-413
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• 2017

The purpose of this paper is to verify whether the entry programming course applied with the flow based learning type is to affect the flow of students' learning. The subjects of the study were the students in the 3rd grade of the National University of education who had not experienced the coding before, and conducted two hours of programming lessons per week for three months. Learning contents and learning materials of beginner course in Entry Homepage were used as learning materials. The teaching and learning process consisted of clear goals setting, motivation, follow-up and immediate feedback, providing application problems, and providing reflection time for students. As a result of the study, the nine factors of flow were compared before and after the experiment. The seven factors - A balance between challenges and skills, Immediate feedback, Action and awareness are merged, Distractions are excluded from consciousness, No worry of failure. Self-consciousness disappears, The activity becomes autotelic-were obtained.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.674-679
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• 2017

As the importance of the 4th industrial revolution and ICT technology increased, it became a software centered society. Existing software training was limited to the composition of the learning environment, and a lot of costs were incurred early. In order to solve these problems, a learning method using a web compiler was developed. The web compiler supports various software languages and shows compilation results to the user via the web. However, Web compilers that support artificial intelligence technology are missing. In this paper, we designed and implemented a tensor flow based web compiler, Google's artificial intelligence library. We implemented a system for learning artificial intelligence by building a meteorJS based web server, implementing tensor flow and tensor flow serving, Python Jupyter on a nodeJS based server. It is expected that it can be utilized as a tool for learning artificial intelligence in software centered society.