• Journal of Digital Convergence
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• v.18 no.7
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• pp.229-236
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• 2020

This study aimed to analyze the effects of nursing students' select task value and academic self-efficacy on learner's learning engagement. The subjects of this study consisted of 186 nursing students who completed the major course with Smart Learning of a university in G city. Data were collected from September 1 to November 30. 2018. This study was designed as a research study and multiple regression analysis was conducted to analyze the effects of task value and academic self-efficacy on learning engagement. The results showed that the degree of influence on learning engagement was in order of academic self-efficacy(β=.515) and task value(β=.244). It was found that both task value (r=.52, p<.001)and academic self-efficacy(r=.64, p<.001) had a significant positive effect on learning engagement. Based on the results of this study, we proposed teaching and learning strategies and suggestions for strengthening learner's learning engagement in smart learning which has recently been applied to increase the effectiveness of education.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.285-291
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• 2010

In this paper, we propose a new paradigm of weighting methods for naive Bayesian learning. We propose more fine-grained weighting methods, called value weighting method, in the context of naive Bayesian learning. While the current weighting methods assign a weight to an attribute, we assign a weight to an attribute value. We develop new methods, using Kullback-Leibler function, for both value weighting and feature weighting in the context of naive Bayesian. The performance of the proposed methods has been compared with the attribute weighting method and general naive bayesian. The proposed method shows better performance in most of the cases.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.30-31
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• 2021

This study aims to build a deep learning model that can predict the value of concrete mixing properties according to a given concrete strength value. A model was created for a total of 1,291 concrete data, including 8 characteristics related to concrete mixing elements and environment, and the compressive strength of concrete. As the deep learning model, DNN-3L-256N, which showed the best performance on the prior study, was used. The average value for each characteristic of the data set was used as the initial input value. In results, in the case of 'curing temperature', which had a narrow range of values in the existing data set, showed the lowest error rate with less than 1% error based on MAE. The highest error rate with an error of 12 to 14% for fly and bfs.

• International Commerce and Information Review
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• v.9 no.4
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• pp.3-19
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• 2007

The purpose of this paper is to study the pattern of interactive learning in strategic networks. Interactive learning is defined as the exchange and sharing of knowledge resources conducive to innovation between an innovator firm, its suppliers, and/or its customers. The strength of internal knowledge resources can either hamper or facilitate levels of interactive learning. We assume that more complex innovative activities urge firms to co-ordinate and exchange information between users and producers, which implies a higher level of interactive learning. To test our theoretical claims, we estimated the level of interactive learning of firms in strategic networks with: (1) their customers, (2) their suppliers. Theses analyses allow a comparison of the antecedents of interactive learning of firms participating in strategic networks. Our findings suggest that interactive learning with customers is positively affected by company's capabilities and value-created activities, and with supplies is positively affected by value-created activities and technology innovation centers.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.2
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• pp.180-202
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• 2012

The purpose of this study was to extract an u-PBL support system core value and design strategy based upon field experience learning. To accomplish this the study, first of all, analyzed the core values, design strategy which was selected after needs analysis and literature review of theories and cases regarding the PBL, e-PBL, blended-PBL, Field experience learning based on ubiquitous environment, and learning model based on ubiquitous technology. This study identified the three core values as; systemic support for instructional activity, just in time support for instructional activity and support for interaction facilitation. As further research areas, it might be useful to develop u-PBL instructional support system based upon the model designed from this study. Also, research concerning the verification of the model based upon implementation of the program case might be necessary.

• Journal of the Daesoon Academy of Sciences
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• v.34
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• pp.293-321
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• 2020

The value embodied by "Ascending to Heaven and Being an Immortal" (Yuhua Dengxian in Chinese) implies the core gist of Daoist culture as well as its ultimate value. From the perspective of Philology, each word, "Yu", "Hua", "Deng", and "Xian" benefits us through a philosophy of life, learning skills, the pursuit of the mysteries of Daoist immortality, and the ways of life characteristics and spiritual transcendence. "To become an immortal" is becoming adept at life. "Yuhua" refers to learning transcendental skills, and "Deng" expresses the promotion of life. "Ascending to Heaven and Becoming an Immortal" integrates the goal- oriented values of Daoist Culture, learning transcendental skills, and the state of being alive into a unified whole. Namely, it is the perfect combination of an adept's supreme pursuit of value and zenith of life. By way of contrast, in Daesoon Jinrihoe, the concepts of "Daesoon" and "Perfected Unification with the Dao" not only advocate "physical and mental transformation" and "spiritual development" for Dao cohorts, but also personal cultivation and service to society, and participation in "The Creation of an Earthly Paradise." These are unified under the ideal humanistic value of "the earthly paradise of the Later World."

• The Journal of Korean Association of Computer Education
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• v.16 no.1
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• pp.81-95
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• 2013

Academic procrastination has been a concern for educators. The purpose of this study is to investigate the relationship among task value, academic self-efficacy, autonomous motivation, self-regulated learning, and academic procrastination in e-learning courses. Based on the literature review, the path model was proposed and tested with 212 university students who registered in e-learning courses. The results showed that task value and academic self-efficacy positively influenced autonomous motivation and self-regulated learning, and autonomous motivation and self-regulated learning reduced the level of academic procrastination directly or indirectly. Implications and strategies to reduce procrastination were discussed based on the findings.

• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.341-353
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• 2010

The purpose of the present study is to verify the structural relationship among on-line task value, university support, satisfaction, learning persistence in Cyber University. For this study, W cyber university in Korea was chosen to conduct web survey. A hypothetical model was proposed, which was composed of on-line task value, university support as exogenous variables, satisfaction, learning persistence as endogenous variables. And satisfaction have been suggested as intervening endogenous variables. The result of this study is as follows: First, on-line task value and university support affect satisfaction. Second, university support and satisfaction affect learning persistence. Lastly, satisfaction mediated on-line task value, university support and learning persistence.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.157-162
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• 2010

The cart-pole balancing problem is a pseudo-standard benchmark problem from the field of control methods including genetic algorithms, artificial neural networks, and reinforcement learning. In this paper, we propose a novel approach by using online reinforcement learning(OREL) to solve this cart-pole balancing problem. The objective is to analyze the learning method of the OREL learning system in the cart-pole balancing problem. Through experiment, we can see that approximate faster the optimal value-function than Q-learning.

• Journal of information and communication convergence engineering
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• v.19 no.1
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• pp.1-7
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• 2021

Reinforcement learning is an area of machine learning that studies how an intelligent agent takes actions in a given environment to maximize the cumulative reward. In this paper, we propose a new MAC protocol based on the Q-learning technique of reinforcement learning to improve the performance of the IEEE 802.11 wireless LAN CSMA/CA MAC protocol. Furthermore, the operation of each access point (AP) and station is proposed. The AP adjusts the value of the contention window (CW), which is the range for determining the backoff number of the station, according to the wireless traffic load. The station improves the performance by selecting an optimal backoff number with the lowest packet collision rate and the highest transmission success rate through Q-learning within the CW value transmitted from the AP. The result of the performance evaluation through computer simulations showed that the proposed scheme has a higher throughput than that of the existing CSMA/CA scheme.