• ETRI Journal
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• v.38 no.6
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• pp.1229-1239
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• 2016

For efficient interaction between humans and robots, robots should be able to understand the meaning and intention of human behaviors as well as recognize them. This paper proposes an interactive human intention reading method in which a robot develops its own knowledge about the human intention for an object. A robot needs to understand different human behavior structures for different objects. To this end, this paper proposes a hierarchical behavior knowledge network that consists of behavior nodes and directional edges between them. In addition, a human intention reading algorithm that incorporates reinforcement learning is proposed to interactively learn the hierarchical behavior knowledge networks based on context information and human feedback through human behaviors. The effectiveness of the proposed method is demonstrated through play-based experiments between a human and a virtual teddy bear robot with two virtual objects. Experiments with multiple participants are also conducted.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.571-589
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• 2005

Nowadays, demand for human resource for the e-learning industry is rapidly increasing along with the expansion of e-learning market capacity. However, there arc numerous difficulties in expansion and industrialization of e-learning due to insufficient supply of human resources to meet the demand. Therefore, the goal of this study is to present various policy measures that can supplement the supply of e-learn ing manpower. Overall contents of this study focus on presenting the long-term directions for fostering of human resources for e-learning industry. Among these, role of government policies for fostering of human resources for e-learning industry is being particularly emphasized because e-learning industry is still at its infant stage.

• Korean Medical Education Review
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• v.18 no.3
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• pp.150-155
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• 2016

Learning objectives for human and society-centered basic medical education to improve physicians' ability to practice in a Korean context were developed by the Korean Association of Medical Colleges in 2015-2016. The task-force committee identified eight domains for medical practitioners: human illness, reflection and self-improvement, patient safety, communication and collaboration, medical ethics, legal issues, social accountability, and professionalism. A total of 172 enabling learning outcomes and 42 terminal learning outcomes were identified by the workshop. The workshop members were representatives from 41 medical schools, the Korean Medical Association, and a scientific group (medical ethics, legal issues, and medical communication). The curriculum for "medical humanity and social medicine" was first published in 2007. The human and society-centered learning objectives that were developed will be revised annually.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.264-272
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• 2022

Human-robot cooperative tasks are increasingly required in our daily life with the development of robotics and artificial intelligence technology. Interactive reinforcement learning strategies suggest that robots learn task by receiving feedback from an experienced human trainer during a training process. However, most of the previous studies on Interactive reinforcement learning have required an extra feedback input device such as a mouse or keyboard in addition to robot itself, and the scenario where a robot can interactively learn a task with human have been also limited to virtual environment. To solve these limitations, this paper studies training strategies of robot that learn table balancing tasks interactively using deep reinforcement learning with human's facial expression feedback. In the proposed system, the robot learns a cooperative table balancing task using Deep Q-Network (DQN), which is a deep reinforcement learning technique, with human facial emotion expression feedback. As a result of the experiment, the proposed system achieved a high optimal policy convergence rate of up to 83.3% in training and successful assumption rate of up to 91.6% in testing, showing improved performance compared to the model without human facial expression feedback.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1459-1466
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• 2018

Robots which detect human and recognize action are important factors for human interaction, and many researches have been conducted. Recently, deep learning technology has developed and learning based robot's technology is a major research area. These studies require a database to learn and evaluate for intelligent human perception. In this paper, we propose a multi-modal sensor-based image database condition considering the security task by analyzing the image database to detect the person in the outdoor environment and to recognize the behavior during the running of the robot.

• Journal of the HCI Society of Korea
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• v.12 no.3
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• pp.5-11
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• 2017

Korean traditional dance has cultural value and is human's cultural heritage. But they are in danger which is caused by lack of bearers and public interest. E-Learning of traditional dance using network technology and digital media can be a solution to extinction problem. The aim of this study is to propose the E-Learning courses and systems for learning traditional dance. E-Learning systems were evaluated in accordance with the HCI (Human Computer Interaction) user evaluation. This study contribute to overcoming distance constraints by offering synchronous E-Learning education system of traditional dance as intangible cultural heritage through new media experience.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.85-90
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• 2008

This paper describes the human body learning system using the multi-modal user interface. Through our learning system, students can study about human anatomy interactively. The existing learning methods use the one-way materials like images, text and movies. But we propose the new learning system that includes 3D organ surface models, haptic interface and the hierarchical data structure of human organs to serve enhanced learning that utilizes sensorimotor skills.

• Research in Mathematical Education
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• v.14 no.3
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• pp.309-322
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• 2010

What is learning in the math classroom? Does a new term need to be coined for learning? Is the term over-used and it has lost it meaning? The responses of one hundred five teacher-candidates and graduate students were coded using the five levels researcher designed rubric which was modeled after Bloom's Taxonomy for depth of knowledge. The effects of understanding learning include the preparation of lesson plans, classroom instruction, the guiding of student learning, and the professional development of teacher leaders.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.22-30
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• 2019

For effective human-robot interaction, robots need to understand the current situation context well, but also the robots need to transfer its understanding to the human participant in efficient way. The most convenient way to deliver robot's understanding to the human participant is that the robot expresses its understanding using voice and natural language. Recently, the artificial intelligence for video understanding and natural language process has been developed very rapidly especially based on deep learning. Thus, this paper proposes robot vision to audio description method using deep learning. The applied deep learning model is a pipeline of two deep learning models for generating natural language sentence from robot vision and generating voice from the generated natural language sentence. Also, we conduct the real robot experiment to show the effectiveness of our method in human-robot interaction.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.31-41
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• 2019

The purpose of this study is to investigate the participation of vocational training program of construction engineers and the impact of workplace learning (formal learning and informal learning) on human resource performances of construction engineers. The data of 306 construction engineers were extracted from 10,069 workers in various industries those were collected by 6th human resource company panel survey done by Korea Research Institute of Vocational Education & Training. This study found that, compared with workers in other industries, participation rate of construction engineers in workplace learning (formal learning, informal learning) was relatively low, and especially the participation rate of informal learning was significantly low. Regression analysis showed that participation in formal learning did not affect positive job performance and job satisfaction. On the other hand, informal learning has a positive effect on job capability, job satisfaction, and organizational commitment.