• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.428-437
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• 2011

This study examines how caregivers' academic motivation to participate in training affects their learning flow with their training. This study surveyed 230 trainees at a caregiver training agency in City B. A survey was conducted, and questionnaire was conceived to obtain the measure of two latent variables: learning flow, motivation to learning. Descriptive statistics, factor analysis, correlation analysis and regression analysis were used. Intrinsic motivation and extrinsic motivation had positive effects on learning flow. However Intrinsic motivation had high level of correlation than extrinsic motivation on learning flow. Therefore, learning flow had not alone intrinsic motivation but also partial correlation with extrinsic motivation. The multidirectional study is require the caregivers' training for development, caregivers' training and Management.

• The Journal of Korean Academic Society of Nursing Education
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• v.26 no.2
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• pp.185-197
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• 2020

Purpose: The purpose of this study was to investigate the mediating effect of self-regulated learning ability on the relationship between experiencing a good class and problem solving ability in nursing college students. Methods: A structured self-report questionnaire was used to measure experiencing a good class, self-regulated learning ability, and problem solving ability. During June, 2019, data were collected from 130 nursing students in D city. Data were analyzed using t-test, One-way ANOVA, Pearson's correlation coefficients, and hierarchical multiple linear regression with SPSS/WIN 23.0. Results: Importance of good class (r=.50, p<.001), satisfaction of good class (r=.42, p<.001), and self-regulated learning ability (r=.71, p<.001) were positively correlated with the problem solving ability of participants. Also, self-regulated learning ability had a partial mediating effect on the relationship between experiencing a good class and problem solving ability. Conclusion: Considering the findings of this study, developing programs that can improve the self-regulated learning ability of nursing students who experience a good class are needed to increase their level of problem solving ability.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.852-858
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• 1991

An adaptive hierarchical classifier(AHCL) for Korean character recognition using a neural net is designed. This classifier has two neural nets: USACL (Unsupervised Adaptive Classifier) and SACL (Supervised Adaptive Classifier). USACL has the input layer and the output layer. The input layer and the output layer are fully connected. The nodes in the output layer are generated by the unsupervised and nearest neighbor learning rule during learning. SACL has the input layer, the hidden layer and the output layer. The input layer and the hidden layer arefully connected, and the hidden layer and the output layer are partially connected. The nodes in the SACL are generated by the supervised and nearest neighbor learning rule during learning. USACL has pre-attentive effect, which perform partial search instead of full search during SACL classification to enhance processing speed. The input of USACL and SACL is a directional edge feature with a directional receptive field. In order to test the performance of the AHCL, various multi-font printed Hangul characters are used in learning and testing, and its processing its speed and and classification rate are compared with the conventional LVQ(Learning Vector Quantizer) which has the nearest neighbor learning rule.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.4
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• pp.359-368
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• 2021

Purpose: The purpose of this study was to investigate the mediating effect of self-leadership on the relationship between media literacy and learning agility in nursing students based on their experiences in online classes during the Coronavirus Disease-19 pandemic. Methods: A descriptive survey was conducted among 165 nursing students from four universities in Busan. Data were collected from June 2 to 13, 2021, and was analyzed using a t-test, one-way ANOVA, Pearson's correlation coefficients, and stepwise multiple regression with SPSS/WIN 26.0. Results: Significant relationships were found between learning agility and media literacy (r=.62, p<.001), between learning agility and self-leadership (r=.58, p<.001), and between media literacy and self-leadership (r=.53, p<.001). Additionally, self-leadership had a partial mediating effect on the relationship between media literacy and learning agility (Z=4.30, p<.001); its explanatory power was 46.0%. Conclusion: These results indicate that interventions to increase the level of media literacy, along with self-leadership, are necessary to improve the level of learning agility of nursing students who will be essential human resources in a rapidly changing healthcare field.

• Korea Trade Review
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• v.45 no.2
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• pp.87-102
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• 2020

While many previous studies have emphasized that technological and learning capabilities have an important impact on internationalization, however, there have been few attempts to directly identify the mediating role of innovative performance in the relationship between them. Therefore, we tested the relationships among two organizational capabilities such as technological capability and learning capability, innovative performance and internationalization. Specifically, we explored the impact of two organizational capabilities on innovative performance and the mediating role of innovative performance on internationalization. We tested hypotheses based on 206 survey data of Gwangju and Jeonnam provinces' small and medium-sized enterprises (SMEs). The empirical results showed that both technological capability and learning capability had a significantly positive (+) effect on SMEs' innovation performance, and both technological capability and learning capability had a significantly positive (+) effect on internationalization performance. In addition, it was confirmed that the innovation performance is not only related to the relationship between technological capability and internationalization performance but also acts as a partial mediation role in the relationship between the learning capability and internationalization performance. Based on the results of this study, theoretical and practical implications were provided, and the limitations of this study and future research directions were also discussed.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.28-37
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• 1999

Differentially Responsible Adaptive Critic Learning technique is proposed for learning the control technique with multiple control inputs as in robot system using reinforcement learning. The reinforcement learning is a self-learning technique which learns the control skill based on the critic information Learning is a after a long series of control actions. The Adaptive Critic Learning (ACL) is the representative reinforcement learning structure. The ACL maximizes the learning performance using the two learning modules called the action and the critic modules which exploit the external critic value obtained seldomly. Drawback of the ACL is the fact that application of the ACL is limited to the single input system. In the proposed Differentially Responsible Action Dependant Adaptive Critic learning structure, the critic function is constructed as a function of control input elements. The responsibility of the individual control action element is computed based on the partial derivative of the critic function in terms of each control action element. The proposed learning structure has been constructed with the CMAC neural networks and some simulations have been done upon the two dimensional Cart-Role system and robot squatting problem. The simulation results are included.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.251-259
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• 2023

This study is prepared to provide fundamental data for constructing learning system to reinforce learning facilitation and improve learning effect for adult college students by testing the medium effect of learning motivation in the relation of social support, service quality of university education, and learning engagement. For this objective, A survey was conducted with 573 adult college students attending 2-to-3-year colleges and universities located in Daegu metropolitan City and Gyeongsangbuk-do. The analyzed research results are as follows. First, learning motivation had partial medium effect in the relation of social support and learning engagement. Second, learning motivation seemed to have complete medium effect in the relation of service quality of university education and learning engagement. The above research results suggest that continuous development and efforts are needed to establish various support systems and improve educational services in order to increase adult college students' immersion in learning.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.221-230
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• 2017

BL(Blended Learning) has been presented as a promising alternative learning approach. BL is defined as a learning approach that combines e-learning and face-to-face classroom learning. The adoption of BL in computer practice class is necessary due to the characteristics of computer practice class itself. This study proposes a research model that examines the determinants of learner's satisfaction of computer practice classes in BL environment. Considering the characteristics of computer practices classes contents and instructor interaction were identified as the determinants. The research model is tested using a questionnaire survey of 141 participants. Confirmatory factor analysis (CFA) was performed to test the reliability and validity of the measurements. The partial least squares (PLS) method was used to validate the measurement and hypotheses. The empirical findings shows that contents easiness and contents constructs are the primary determinants of instructor interaction in BL. Instructor interaction was also found to be related to the learner's satisfaction resulting in re-using. The findings provide insight into the planning and utilizing BL in computer practice classes to enhance learner's satisfaction.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.481-489
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• 2020

The study examines the role of facilitating conditions and user habits in the use of technology in Online Learning Platform (OLP) in Indonesia. The adoption of online learning, persistence, and learning results in online platforms is essential for ensuring that education technology is implemented and gets as much value as possible. People who use technology and systems will embrace new technologies even more. This quantitative study is based on a survey of 254 respondents, who were active users of the technology, and considers the facilitating conditions and user habits variables. Two research hypotheses were tested using the Partial Least Square-Structural Equation Modeling method. Cronbach's Alpha, path coefficient, AVE, R-square, T-test were applied. The results showed that the factors significantly influence the Online Learning Platform technology behavioral intention. This impact is primarily associated with the availability of the resources required to use OLP technology. The availability of these resources includes supporting infrastructures such as widespread Internet access, easy access to mobile devices, and file sizes that affect access speed. The findings of this study suggest that it is necessary to introduce and increase the availability of resources for using OLP technology, and familiarize people with the technology features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4816-4834
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• 2020

This paper proposes transfer learning and fine-tuning techniques for a deep learning model to detect three distinct brain tumors from Magnetic Resonance Imaging (MRI) scans. In this work, the recent YOLOv4 model trained using a collection of 3064 T1-weighted Contrast-Enhanced (CE)-MRI scans that were pre-processed and labeled for the task. This work trained with the partial 29-layer YOLOv4-Tiny and fine-tuned to work optimally and run efficiently in most platforms with reliable performance. With the help of transfer learning, the model had initial leverage to train faster with pre-trained weights from the COCO dataset, generating a robust set of features required for brain tumor detection. The results yielded the highest mean average precision of 93.14%, a 90.34% precision, 88.58% recall, and 89.45% F1-Score outperforming other previous versions of the YOLO detection models and other studies that used bounding box detections for the same task like Faster R-CNN. As concluded, the YOLOv4-Tiny can work efficiently to detect brain tumors automatically at a rapid phase with the help of proper fine-tuning and transfer learning. This work contributes mainly to assist medical experts in the diagnostic process of brain tumors.