• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.163-167
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• 2000

The eligibility is used to solve the credit-assignment problem which is one of important problems in reinforcement learning. Conventional eligibilities which are accumulating eligibility and replacing eligibility make ineffective use of rewards acquired in learning process. Because only an executed action in a visited state is learned by these eligibilities. Thus, we propose a new eligibility, called the weighted eligibility with which not only an executed action but also neighboring actions in a visited state are to be learned. The fuzzy Q-learning algorithm using proposed eligibility is applied to a cart-pole balancing problem, which shows improvement of learning speed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1044-1047
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• 2005

In this paper, we present the strategy of object search for distributed autonomous robotic systems (DARS). The DARS are the systems that consist of multiple autonomous robotic agents to whom required functions are distributed. For instance, the agents should recognize their surrounding at where they are located and generate some rules to act upon by themselves. In this paper, we introduce the strategy for multiple DARS robots to search a hidden object at the unknown area. First, we present an area-based action making process to determine the direction change of the robots during their maneuvers. Second, we also present Q learning adaptation to enhance the area-based action making process. Third, we introduce the coordinate system to represent a robot's current location. In the end of this paper, we show experimental results using hexagon-based Q learning to find the hidden object.

• 수산해양교육연구
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• 제22권3호
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• pp.431-444
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• 2010

This research aims at developing a teachers' training program to reinforce teachers' capability to perform the action learning program. To accomplish this goal, the key value of the training program based on action learning, the process of the core learning activities, and the elements to support learners and facilitators respectively were deducted on the foundation of documentary research and case study, based on which, the program was developed through the formative test by professionals and application to the field. This research was applied to 105 middle or high school teachers, the participants of the in-service training on creative problem solving hosted by B metropolitan city for one week (30 hours) from 9 a.m. on Monday, January 25th, 2010 to 4 p.m. on Friday, January 29th. The result of this research is as follows. First, as for the key values of this study, (1) the team-based learning centered on the trainees, not lecturers-oriented, knowledge-transmitting training, is possible, (2)for each process, guidelines, related information, tools, and various kinds of media are supported just in time, and (3)a focus is given on fostering facilitators centered on teachers. Second, the process of the core learning activities of the teachers' training program based on action learning consists of the procedure of a prior lecture${\rightarrow}$break${\rightarrow}$investigation into problems${\rightarrow}$clarification of problems${\rightarrow}$drawing possible solutions${\rightarrow}$decision on the priority${\rightarrow}$making an action plan${\rightarrow}$performance${\rightarrow}$evaluation, and on each stage, the contents for the activities of teachers and learners and detailed supportive elements are offered.

• 한국멀티미디어학회논문지
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• 제22권4호
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• pp.432-442
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• 2019

Most current human action recognition methods based on deep learning methods. It is required, however, a very high computational cost. In this paper, we propose an action change detection method to reduce repetitive human action recognition tasks. In reality, simple actions are often repeated and it is time consuming process to apply high cost action recognition methods on repeated actions. The proposed method decides whether action has changed. The action recognition is executed only when it has detected action change. The action change detection process is as follows. First, extract the number of non-zero pixel from motion history image and generate one-dimensional time-series data. Second, detecting action change by comparison of difference between current time trend and local extremum of time-series data and threshold. Experiments on the proposed method achieved 89% balanced accuracy on action change data and 61% reduced action recognition repetition.

• 디지털융복합연구
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• 제19권8호
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• pp.397-404
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• 2021

본 연구는 기초간호과학 수업에 적합한 액션러닝 수업을 설계하고 이를 적용한 후 간호학생의 교육 경험의 의미를 알아보기 위해 시행되었다. 연구대상은 S시 소재 K대학의 간호학과에서 기초간호과학 수업에 참여한 학생 100명이었고 자료수집은 2019년 3월부터 2020년 6월까지 진행되었다. 기초간호과학 수업은 팀 당 5-6명, 총 18개 팀이 액션러닝을 진행하였고. 수업 후 성찰일지를 수집한 후 내용분석법으로 분석하였다. 연구결과 액션러닝 기반 기초간호 과학 수업에 대한 경험은 45개의 의미 있는 진술과 8개의 주제, 4개의 범주로 도출되었고, 4개의 범주는 「해부학에 대한 자신감」, 「성장하는 팀워크」, 「학습법을 터득함」, 「진행과정의 어려움」이었다. 액션러닝 적용 수업은 문제해결능력, 팀워크, 자기 주도적 학습에 효과적인 것으로 나타나 다른 간호학 교과목에서도 액션러닝을 적용하여 효과를 평가해 볼 것을 제안한다.

• 영어어문교육
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• 제7권1호
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• pp.1-19
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• 2001

The current status of in-service teacher development shows that teachers' awareness can be enhanced through critical reflection. This study shows how an English teacher improved her own teaching situation through action research. It reports back the action research the teacher-researcher carried out in the EFL classroom setting. Aiming to improve the pupils' English speaking ability, the teacher introduced 'Task-based Language Teaching (TBLT)' to the English class. The teacher and the pupils took part in the evaluation process of learning and teaching. It was found that the new approach to teaching speaking helped the pupils improve speaking ability and take an active role in learning process. It is further suggested that teacher-initiated action research can be done in collaboration with colleagues, administrators and researchers.

• 한국멀티미디어학회논문지
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• 제12권12호
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• pp.1819-1826
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• 2009

To enhance the automatic performance of existing predicting and planning algorithms that require a predefined probability of the states' transition, this paper proposes a multiple sequence generation system. When interacting with unknown environments, a virtual agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. We describe a sequential behavior generation method motivated from the change in the agent's state in order to help the virtual agent learn how to adapt to unknown environments. In a sequence learning process, the sensed states are grouped by a set of proposed motivation filters in order to reduce the learning computation of the large state space. In order to accomplish a goal with a high payoff, the learning agent makes a decision based on the observation of states' transitions. The proposed multiple sequence behaviors generation system increases the complexity and heightens the automatic planning of the virtual agent for interacting with the dynamic unknown environment. This model was tested in a virtual library to elucidate the process of the system.

• 한국가정과교육학회지
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• 제9권1호
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• pp.53-69
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• 1997

The purpose of this study was to develop a Home Economics curriculum for high school students based on practical problems focusing on Food and Nutrition. This study developed practical-problem based approach to curriculum development. This curriculum provided a series of the objectives, contents, learning activities, and assessments. The objectives were divided into process objectives and content objectives. The objectives focused on three systems of action which were technical action, communicative action, and emancipatory action. The contents of this curriculum focused on three practical problems； 1) What should I do regarding my well-being\ulcorner ； 2) What should I do regarding my family’s well-being\ulcorner ； 3) What should I do regarding my society’s well-being\ulcorner The cooperative learning strategies were mainly used in this curriculum. Students were assessed through learning experiences and achievement.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권3호
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• pp.264-269
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• 2006

This paper presents the strategy for searching a hidden object in an unknown area for using by multiple distributed autonomous robotic systems (DARS). To search the target in Markovian space, DARS should recognize th ε ir surrounding at where they are located and generate some rules to act upon by themselves. First of all, DARS obtain 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to research for a target object while navigating in a un known hallway where some obstacles were placed. In the end of this paper, we present the results of three algorithms - a random search, an area-based action making process to determine the next action of the robot and hexagon-based Q-learning to enhance the area-based action making process.

• 한국콘텐츠학회논문지
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• 제16권1호
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• pp.285-294
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• 2016

본 연구의 목적은 액션러닝에 기반을 둔 영적간호 교육 프로그램이 간호대학생의 영적요구, 영적안녕 그리고 영적간호역량에 미치는 효과를 평가하기 위함이다. 단일군 사전 사후 설계이며 연구 참여자는 간호대학생 2학년이었다. 학생들은 2014년 9월부터 12월까지 16회에 걸친 액션러닝 기반 영적간호 교육 프로그램에 참여하였다. 가설검증은 SPSS WIN 23.0 통계프로그램을 이용하여 paired t-test로 분석하였다. 본 연구의 결과, 액션러닝 기반 영적간호 교육 프로그램은 간호대학생의 영적요구를 감소시키고, 영적안녕과 영적간호역량을 증진시켰다. 아울러 총체적인 간호를 제공하는 전문적인 간호사의 역량 강화에 기여하였다는 점에서 의의가 있으며, 추후 다양한 교육 분야에서 액션러닝 기반 교육 프로그램을 개발하고 적용할 것을 제언한다.