• Journal of East-West Nursing Research
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• v.24 no.2
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• pp.101-109
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• 2018

Purpose: The purpose of this study was to construct and test a structural equation model of health behavior compliance among patients with percutaneous coronary intervention based on self-determination theory. Methods: A total of 227 participants who received follow-up care after percutaneous coronary intervention were recruited. A structured questionnaire was used to assess health providers' autonomous support, basic psychological needs, autonomous motivation, controlled motivation, type D personality, and health behavior compliance. Collected data were analyzed using SPSS 21.0 and AMOS 21.0 program. Results: The final hypothetical model showed a good fitness with data: GFI=.94, RMSEA=.07, CFI=.96, NFI=.92, TLI=.94. The results revealed that autonomous support of health care providers, basic psychological needs, and autonomous motivation, and D-type personality accounted for 51.8% of health behavior compliance. Conclusion: The findings of this study indicate that enhanced autonomous support of health care providers is essential to promote patients' basic psychological needs and autonomous motivation. This leads to maximized compliance to the health behaviors among patients who underwent percutaneous coronary intervention. We recommend that health care institutions establish various measures to foster the special environments in which health care providers can actively provide and utilize autonomous support for their patients.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.293-294
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• 2022

In recent years, the maritime industry system including port facilities, VTS(Vessel traffic service) is rapidly evolving with the development of technology. The connection between systems has been greatly expanded, and many research cases using this connectivity have been reported. This paper deals with the structural design of the arrival/departure support system for an autonomous ship. The system requires navigation data from the autonomous ship and radar/AIS data from the port. In this paper, design result on how the arrival/departure support system interacts with the autonomous ship and port system are addressed.

• Educational Technology International
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• v.22 no.2
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• pp.285-309
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• 2021

It is commonly understood that students' autonomous motivation and individualistic orientations and instructors' autonomy support are important for student-centered learning (SCL). However, few studies have examined this assumption. To help researchers and practitioners design more engaging SCL experiences across diverse cultural contexts, this study examines the associations of these factors with SCL engagement and how these associations compare in different cultures. University students in South Korea and the United States participated in a bold SCL assignment, called Pink Time, in which students decide what and how they learn. Linear, multivariate models were estimated in each context to identify and compare relationships between SCL engagement and student characteristics and perceptions. We found that engagement was high in both contexts. Autonomous motivation, individualism, and perceived instructor support each had significant associations with SCL engagement in South Korea. In the US, which had a smaller sample size, only perceived instructor support was significantly associated. These findings suggest that SCL strategies can be effective across cultures. Also, the narrower classroom context, specifically instructors' support, may be a stronger driver of engagement than the broader societal context. This study contributes to the scholarly discussion regarding SCL in diverse settings and offers several implications for instructors.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.41-44
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• 2020

In autonomous driving, object recognition based on machine learning is one of the core software technologies. In particular, the object recognition using deep learning becomes an essential element for autonomous driving software to operate. In this paper, we introduce a drivable area detection method based on Region-based CNN model to support autonomous driving. To effectively detect the drivable area, we used the BDD dataset for model training and demonstrated its effectiveness. As a result, our R-CNN model using BDD datasets showed interesting results in training and testing for detection of drivable areas.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.523-531
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• 2018

The purpose of this study based on descriptive research is to examine the influences on the self-regulated learning ability due to nursing students' achievement-goal and to make sure mediating effect of autonomous support of professor. A convenience sample of 294 nursing students were recruited from a college in C province from April to May, 2018. Data are analyzed using SPSS/WIN 21.0 program. As a result, it is turned out that there are positive correlation between mastery goal, performance approach goal, self-regulated learning ability and autonomous support of professor. In the Sobel test results, autonomous support of professor had a partial mediating effect between mastery goal and self-regulated learning ability(Z=3.922, p<.001). So, a new teaching method should be developed through the convergence of related factors of self - regulated learning ability.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.89-99
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• 1999

The major objective of this research is to propose a design architecture for autonomous defense systems for supporting highly intelligent behavior by combining decision, perception, and action components. Systems with such high levels of autonomy are critical for advanced battlefield missions. By integrating a plenty of advanced modeling concepts such as system entity structure, endomorphic modeling, engine-based modeling, and hierarchical encapsulation & abstraction principle, we have proposed four layered design methodology for autonomous defense systems that can support an intelligent behavior under the complicated and unstable warfare. Proposed methodology has been successfully applied to a design of autonomous tank systems capable of supporting the autonomous planning, sensing, control, and diagnosis.

• Transportation Technology and Policy
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• v.12 no.3
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• pp.7-13
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• 2015

• Journal of Navigation and Port Research
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• v.46 no.2
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• pp.134-144
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• 2022

The development and operation of autonomous ships are spotlighted as a next-generation technology that will provide newbenefits for the maritime business during the fourth industrial revolution. To expand the adoption of autonomous ships, the much more interest of the nation and the industries will have to be changed to actual adoption in shipping companies. For this, it is judged that research to identify the factors impacting the adoption intention of autonomous ships should be preceded. However, most studies on autonomous ships have focused on developing the technology, revising the law, establishing policies, and managing human resources, with few studies on influencing factors in the adoption of autonomous ships. A model, to identify the factors that impact the intention to the adoption of autonomous ships, based on the theory of diffusion of innovation and the TOE framework was developed. The suggested model was verified through empirical analysis targeting the shipping companies and the marine industries in Korea. As the result of this study, it was found that top management support, financial slack, and competitive intensity significantly impacted the intention to adopt autonomous ships. Additionally, it was revealed that the overall awareness of autonomous ships among Korean shipping companies is poor.

• Journal of Korean Academy of Nursing
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• v.52 no.2
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• pp.157-172
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• 2022

Purpose: This study aimed to construct and test a hypothetical model to explain the predictive factors and causal pathways for exercise levels in patients with ankylosing spondylitis based on the self-determination theory. A conceptual framework was constructed assuming that autonomy support by health care providers would satisfy the three basic psychological needs of patients, which would increase their autonomous motivation for exercise, resulting in its initiation and continuation. Methods: This cross-sectional study included 221 patients with ankylosing spondylitis who were visiting rheumatology clinics in two tertiary hospitals. Health Care Climate Questionnaire-exercise regularly, Basic Psychological Needs Satisfaction scale, Behavior Regulation in Exercise Questionnaire-2, and exercise level were used to collect data. Results: The fitness of the hypothetical model met the recommended level (𝛘²/df ≤ 3, SRMR ≤ .08, RMSEA ≤ .08, GFI ≥ .90, AGFI ≥ .85, NFI ≥ .90, TLI ≥ .90, CFI ≥ .90). The model effect analysis revealed that autonomy support by health care providers had a positive effect on patients' autonomy, competence, relatedness, autonomous motivation, and exercise level. Competence and relatedness had positive effects on autonomous motivation and exercise level, respectively. Autonomous motivation had a positive effect on exercise level. Conclusion: The predictive factors of exercise level in patients with ankylosing spondylitis were autonomous motivation, health care providers' autonomy support, competence, and relatedness. Considering these factors, we recommend the development of an effective program for improving exercise levels in these patients.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.71-77
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• 2021

Recently, there is a demand for efficient program development of an IoT application support frameworks considering heterogeneous hardware characteristics. In addition, the scope of hardware support is expanding with the development of neuromorphic architecture that mimics the human brain to learn on their own and enables autonomous computing. However, most existing IoT IDE(Integrated Development Environment), it is difficult to support AI(Artificial Intelligence) or to support services combined with various hardware such as neuromorphic architectures. In this paper, we design an AI component abstract model that supports the second-generation ANN(Artificial Neural Network) and the third-generation SNN(Spiking Neural Network), and implemented an autonomous IoT IDE based on the proposed model. IoT developers can automatically create AI components through the proposed technique without knowledge of AI and SNN. The proposed technique is flexible in code conversion according to runtime, so development productivity is high. Through experimentation of the proposed method, it was confirmed that the conversion delay time due to the VCL(Virtual Component Layer) may occur, but the difference is not significant.