• Journal of Information Science Theory and Practice
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• v.10 no.3
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• pp.24-39
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• 2022

Online learning is becoming ubiquitous worldwide because of its accessibility anytime and from anywhere. However, it cannot be successfully implemented without understanding constructs that may affect its adoption. Unlike previous literature, this research extends the Unified Theory of Acceptance and Use of Technology with three well-known theories, namely compatibility, online self-efficacy, and knowledge sharing and acquisition to examine online learning adoption. A total of 264 higher education students took part in this research. Partial Least Squares-Structural Equation Modeling was used to evaluate the proposed theoretical model. The findings suggested that performance expectancy and compatibility were significant predictors of behavioral intention, whereas behavioral intention, facilitating conditions, and compatibility had a significant and direct effect on online learning's actual use. The results also showed that knowledge acquisition, knowledge sharing, and online self-efficacy were determinates of performance expectancy. Finally, online self-efficacy was a predictor of effort expectancy. The proposed model achieved a high fit and explained 47.7%, 75.1%, 76.1%, and 71.8% of the variance of effort expectancy, performance expectancy, behavioral intention, and online learning actual use, respectively. This study has many theoretical and practical implications that have been discussed for further research.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.931-940
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• 2011

Classification is to generate a rule of classifying objects into several categories based on the learning sample. Good classification model should classify new objects with low misclassification error. Many types of classification methods have been developed including logistic regression, discriminant analysis and tree. This paper presents a new classification method using penalized partial least squares. Penalized partial least squares can make the model more robust and remedy multicollinearity problem. This paper compares the proposed method with logistic regression and PCA based discriminant analysis by some real and artificial data. It is concluded that the new method has better power as compared with other methods.

• Nuclear Engineering and Technology
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• v.39 no.1
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• pp.43-50
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• 2007

A partial flow blockage in an assembly of a liquid metal reactor could result in a cooling deficiency of the core. To develop a partial blockage detection system, we have studied the changes of the temperature fluctuation characteristics in the upper plenum according to changes of the t10w blockage conditions in an assembly. We analyzed the temperature fluctuation in the upper plenum with the Large Eddy Simulation (LES) turbulence model in the CFX code and evaluated its statistical parameters. Based on the results of the statistical analyses, we developed a neural network model for detecting a partial flow blockage in an assembly. The neural network model can retrieve the size and the location of a flow blockage in an assembly from a change of the root mean square, the standard deviation, and the skewness in the temperature fluctuation data. The neural network model was found to be a possible alternative by which to identify a flow blockage in an assembly of a liquid metal reactor through learning and validating various flow blockage conditions.

• International Area Studies Review
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• v.16 no.3
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• pp.3-25
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• 2012

This study is to look at the relationship of entrepreneurship(innovativeness, risk-taking), the learning competence, environmental factors(the domestic market hostility, the speed of technological change) and export performance in international new ventures(INVs). In addition, the integrated model is constructed for the purpose of analysis of the moderating effects of environmental factors. Through the existing investigation, nine hypotheses are set up. PLS(Partial Least Square) analysis method is used to sample of 115 INVs. Analysis, the two elements of entrepreneurship influenced the positive(+) in the learning competence and export performance. And the relationship of learning competence and export performance is significant. In the moderating effects, only the domestic market hostility has a significant moderating effects between the learning competence and innovativeness. The results of this research shows that innovativeness influence the learning competence playing a positive role in the performance in the domestic market is higher. This point illustrates the practical implications of the importance of innovation in learning empowerment.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.275-281
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• 2019

This study aimed to analyse the mediating effects of learning attitudes in respect to the correlation between achievement goal orientation and learning flow. For the purpose, this study surveyed achievement goal orientation, learning flow and learning attitude of beauty specialized high school students located in Jeonnam with the use of a questionnaire. 335 copies of the answers were analysed with the use of the SPSS(PASW, ver 21.0). The results are presented as follows: Mastery approach of the achievement goal orientation and learning attitude had a significant effect on learning flow. It was discovered that learning attitude had a partial effect on the relations between mastery approach and learning flow, but it was reported that it had a complete mediating effect on the relations between performance avoidance and learning flow.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1319-1328
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• 2018

A blockchain system developed for crypto-currency has attractive characteristics, such as de-centralization, distributed ledger, and partial anonymity, making itself adopted in various fields. Among those characteristics, partial anonymity strongly assures privacy of users, but side effects such as abuse of crime are also appearing, and so countermeasures for circumventing such abuse have been studied continuously. In this paper, we propose a machine-learning based method for classifying smart contracts in Ethereum regarding their functions and design patterns and for identifying user behaviors according to them.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.201-209
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• 2009

RThe main object of this study is to stipulate the relation between e-learning characteristics and e-learner's scholastic performance through the integrated study model of perspective of educational technology and information technology. Using e-learning system quality, e-learning contents characteristics and interaction as independent variable, e-learner's scholastic performance as dependent variable and learning motivation as mediator, this study has examined the relationship among these variables. Two hundreds and twelve undergraduates in cyber university participated in the survey and filled out questionnaires related to this study. The main results are as followed. First, content's quality, technical quality and the support of school affairs have a significant effect on the e-learner's scholastic performance. Second, Learning motivation plays a partial mediating role in the relationship between e-learning characteristics and e-learner's scholastic performance. The meaningful implication of this study is that to improve e-learner's scholastic performance, we have to offer e-learners more customized various learning plans, learning contents and interaction between e-learners and e-learning systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.91-97
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• 2016

The purpose of this study is to identify the mediating effect of team efficacy between interpersonal competence and perceived learning in project learning for pre-service early childhood teachers. Based on a literature review, team efficacy and interpersonal competence were identified as variables having an effect on project learning. The data were collected from 172 students who participated in a project learning course offered by a university located in Seoul, Korea, and were analyzed by Baron & Kenny's (1986) framework. As a result, team efficacy was found to act as a partial mediator between the two variables, understanding of and consideration for other people and perceived learning. This study suggests that team efficacy and understanding of and consideration for other people should be facilitated in project learning courses. The possibility that some teaching strategies could enhance the project learning effect for learners and pre-service teachers is discussed.

• Proceedings of the KIEE Conference
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• 2001.11a
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• pp.198-200
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• 2001

In this paper, we describe the developed learning tool of expert system for preventive diagnosis of substation power equipments. The expert system was programmed by using the diagnosis methods as like gas analysis in oil and partial discharge, hottest temperature, the current of OLTC driving meter, the current of fan and pump in MTr and driving coil current in GCB and leakage current in LA. The learning tool is composed of the expert system and the explanation of diagnosed examples and the applied rules and it well worked according to the rule.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.70-75
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• 1999

Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor the information about weld characteristics and process paramters as well as modification of those parameters to hold weld quality within the acceptable limits. Typical characteristics are the bead geometry composition micrrostructure appearance and process parameters which govern the quality of the final weld. The main objectives of this paper are to realize the mapping characteristicso f penetration through the learning. After learning the neural network can predict the pene-traition desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) were chosen from an error analysis. partial-penetration single-pass bead-on-plate welds were fabricated in 12mm mild steel plates in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the penetration with reasonable accuracy and gurarantee the uniform weld quality.