• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.15-20
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• 2024

Path planning for unmanned aerial vehicles (UAV) is crucial in avoiding collisions with obstacles in complex environments that include both static and dynamic obstacles. Path planning algorithms like RRT and A^* are effectively handle static obstacle avoidance but have limitations with increasing computational complexity in high-dimensional environments. Reinforcement learning-based algorithms can accommodate complex environments, but like traditional path planning algorithms, they struggle with training complexity and convergence in higher-dimensional environment. In this paper, we proposed a reinforcement learning model utilizing a cell decomposition algorithm. The proposed model reduces the complexity of the environment by decomposing the learning environment in detail, and improves the obstacle avoidance performance by establishing the valid action of the agent. This solves the exploration problem of reinforcement learning and improves the convergence of learning. Simulation results show that the proposed model improves learning speed and efficient path planning compared to reinforcement learning models in general environments.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.43-52
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• 2022

This study used a descriptive survey design to examine the impact of the clinical learning environments and learning transition nursing students experienced the gerontological nursing clinical on the satisfaction with clinical practice. A convenient sample of 211 4^th year nursing students who had the gerontological nursing clinical practicum from one College of Nursing at Private University in South Korea was recruited and completed the surveys from October to December 2019. This study showed that the satisfaction with a gerontological nursing clinical practicum was significantly correlated with clinical learning environments and learning transition. The results of this study highlights the need to create a safe and positive clinical learning environment for quality gerontological nursing clinical practicum, so hospitals and nursing schools need to make efforts to promote clinical sites as an educational learning environment in collaborative relationships.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.712-717
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• 2008

In swarm robot systems, each robot must act by itself according to the its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method with SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of SVM is adopted in this paper.

• Journal of Korean Dental Hygiene Science
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• v.1 no.2
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• pp.21-39
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• 2018

The purpose of this study was to examine the learning competencies of students at a college from September 1 to November 30, 2017, in an effort to provide some information on how to foster learning competencies in college years, which lay the foundation for work and social lives. 1. The learning competencies of the subjects consisted of academic vision, student identity, cognitive regulation, emotional regulation, learning management and creating learning environments. Out of five points, they scored the highest in academic vision and student identity with 3.34, followed by learning management with 3.20, creating learning environments with 3.18, emotional regulation with 3.16 and cognitive regulation with 3.14. 2. There were statistically significant differences in academic vision according to age, the area of major, the academic credential of their fathers, commuting time, military service experience and career plans. 3. There were statistically significant differences in student identity and cognitive regulation according to gender, age, the area of major, the academic credential of their fathers, commuting time, military service experience and career plans. 4. There were statistically significant differences in emotional regulation according to age, the area of major, the academic credential of their fathers, commuting time, career plans and daily mean study hours. 5. There were statistically significant differences in learning management according to gender, age, the area of major, grade point average, the academic credential of their fathers, career plans and daily mean study hours. 6. There were statistically significant differences in creating learning environments according to gender, age, the area of major, the academic credential of fathers, commuting time, career plans and daily mean study hours. As they were poorest at the cognitive regulation area among the areas of learning competencies, self-directed learning programs that deal with how to study, learning process, how to take notes and arrange them, how to link different pieces of acquired knowledge and how to map out study plans should be developed to give support to students.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.45-46
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• 2012

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.31-41
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• 2000

Since the use of computer-mediated communication(CMC) systems has been steadily increasing in the teaching and learning environments, this study attempted to describe some of instructional strategies which can be employed as a medium of cooperative learning. One of the best way to conduct network-assisted instruction is to embed such a medium into cooperative learning. Network-assisted cooperative learning maximizes students' own learning and each other's learning using CMC, in which students can actively participate in their learning processes. The characteristics of CMC-transmission and search of information, interactivity, time and place independence-assist and enhance cooperative learning. In this study, the instructional strategies for cooperative learning via CMC are suggested as following: (1) choose the instructional goals, (2) structure positive interdependence, (3) select guidelines for grouping, (4) train cooperative skills to students, (5) set up the environments such as electronic bulletin-board, and (6) develop assessment tools. Finally, this study suggests that potentials of network-assisted cooperative learning can be realized by providing environments and thinking tools for cooperative learning. Appropriate theory and practice need to be followed up to support the cooperative learning systems.

• Knowledge Management Research
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• v.17 no.2
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• pp.205-229
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• 2016

Owing to the current economic downturn, one of the most important goals of the organizations who are actively involved in Information Technology Outsourcing (ITO) is the cost efficiency. We focus on supplier firm's domain understanding to make the cost efficiency; therefore, we examine how the disadvantages from lower domain knowledges affect outsourcing performance moderated by outsourcing ratio and knowledge change environments. That is, if clients can endure disadvantage from service providers' lower domain knowledge, they can achieve cost efficiency by choosing lower domain knowledge suppliers with less expensive cost. To examine performance gap depending on the environments, we applied 'A Learning Model of IT Outsourcing' which is suggested by previous literature. As a result, we suggest five strategies for clients to contract with suppliers which have lower domain knowledge: (1) Prepare the strategy to endure disadvantages from the early stage. (2) Make the strategy depending on outsourcing ratio. (3) Knowledge transfer between organizations is important. (4) Make a short-term contract if they do not have good environments for organizational learning. (5) Client's knowledge change environments are more important than those of supplier's. Finally, we offer various implications for clients and suppliers in IT outsourcing.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.259-264
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• 2019

In this paper, the prototyping process for developing syllable-initial consonant-based game 'Korean Guards' is described. Users may effectively learn Korean words using alphabetically sequential approaches, but the easiness of access bestowed on the smart environments and game algorithms could be fully utilized for the functional advantages for educational purposes. This functional game is developed on Android OS and the prototypical outcome is shown.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.35.3-35
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• 2002

Reinforcement Learning (RL) is one of machine learning methods and an RL agent autonomously learns the action selection policy by interactions with its environment. At the beginning of RL research, it was limited to problems in environments assumed to be Markovian Decision Process (MDP). However in practical problems, the agent suffers from the incomplete perception, i.e., the agent observes the state of the environments, but these observations include incomplete information of the state. This problem is formally modeled by Partially Observable MDP (POMDP). One of the possible approaches to POMDPS is to use historical nformation to estimate states. The problem of these approaches is how t..

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.56-64
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• 1997

In distributed autonomous robotic systems, each robot must behaves by itself according to the its states and environements, and if necessary, must cooperates with other orbots in order to carray out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new learning and evolution method based on reinforement learning having delayed reward ability and distributed genectic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. Reinforement learning having delayed reward is still useful even though when there is no immediate reward. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the perfodrmance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper, we verify the effectiveness of the proposed method by applying it to cooperative search problem.