• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.685-688
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• 1996

In debureing process. Human experts who have long experenc in performing deburring tasks can manipulate tools efficiently and adapt the tool motions according to the state of the process based on their skills. However, human experts have difficulties in describing linguistically their control schemes and strategies because teey don't aware the detailed process in interpreting wensory information and adapting tool motion. Therefore, it is important to develop a mean of understanding the skills and acquiring the control schemes so that the robot can perform the same skillful motion as the human experts. In this paper, an expert's skill model is developed so that it can be transferred effectively from the expertt to the robot. Skills are represented by a mapping which is generated by using a neural network. Expert's skill shows that the robot is able to associate a correct control strategy with process characteristics which is acquired from a vision image in a similar manner to a human expert's

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.553-558
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• 1994

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy model that can express a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, cutting area are extracted from image processing by use of the vision system. Cutting depth, repeative number and normal cutting force are chosen as control signals representing actions of the human expert. It is verified that our processed fuzzy model can accurately express the skills of human experts for the deburring process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1110-1113
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• 1995

This study presents the new method which can transfer the expert's skill to deburring robot through neural network. The expert's skill is expressed as associationmapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring processcan be extracted via the visual sense of the human,we employ vision system for the perception and identification of the changing burr. Form the demonstration of human experts, force data are measured. Finally the characteristics of the burr and coressponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.9
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• pp.93-100
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• 1998

This study presents the new method which can transfer the expert's skill to deburring robot through neural network. The expert's skill is expressed as association mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured. Finally the characteristics of the burr and corresponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.102-109
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• 1996

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy mode that can wxpress a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, grinding area are extracted from image processing by use of the vision system. Grinding depth, repetitive number and normal grinding force are chosen as control signals representing actions of the human expert. It is verified that our proposed fuzzy model can accurately express the skills of human experts for the deburring process.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.53-61
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• 2022

As society evolves, people are making more of an effort to learn more about human aspects, one of which is emotional intelligence, a topic on which education experts have traditionally concentrated. This is due to the fact that emotional intelligence has a significant impact on how people think and manage their emotions. On the other side, it promotes the development of expressive ability and aids people in better adapting to life. This study explores the relationship between communication skills, leadership skills, stress management, adaptability, and emotional intelligence of FPT University students to determine the factors that affect students' emotional intelligence. To survey 500 FPT University students, this study used a sample size of 500. Previous studies used a 5-point Likert scale to assess the four skill elements. According to the results, students who completed the survey showed adequate communication skills, leadership qualities, stress management, adaptability, and emotional intelligence. Emotional intelligence is influenced by communication skills, leadership abilities, stress management, and flexibility. This suggests that students who master these four skills have higher levels of emotional intelligence. The outcomes of this study reveal that students have been conscious of Emotional Intelligence since a young age. The affirmations in this research paper will benefit students and young people interested in enhancing complimentary soft skills that boost Emotional Intelligence.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.34 no.1
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• pp.1-5
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• 1998

This study presents intelligent deburring system which can transfer the exper's skill to deburring robot through neural network. The expert's skill is expressed as associate mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured and fitted impedance model. Finally the characteristics of the burr and coressponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• Journal of Korean Library and Information Science Society
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• v.51 no.3
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• pp.223-250
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• 2020

The purpose of this study is to define the concept of media information literacy and to develop educational content. To achieve the purpose of the study, literature analysis, interviews with field experts, and surveys with teacher librarians were conducted. The field experts recognized the media as a tool to use information and recognized information problem-solving skills, reading comprehension ability, media functions, case activities, and affective domain as the areas of media information literacy education. The teacher-librarians thought that information and media literacy which include its competency and educational content are more important than the digital literacy. As a result of the study, the concept of media information literacy was defined as knowledge, skills, and attitudes including the concepts of literacy, media literacy, information literacy, and digital literacy. In addition, educational contents of media information literacy were developed so that 'participation in democratic society', 'classification of media tools and contents', 'basic human rights', 'skills', 'digital tool manipulation' and 'information problem solving process' can be combined and applied in context.

• Asian Journal of Innovation and Policy
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• v.3 no.2
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• pp.154-171
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• 2014

This article aims to examine the achievement and limitation of adaptation of supply chain management (SCM) to IT human resource development (HRD) in Korea and to derive the implication of the Korean experience to other countries. In late 1990s, the IT New Deal Policy and the quantitative expansion of IT HR were introduced. Since mid-2000s, there has been much innovation in IT products as well as increased demand of highly qualified IT experts. The SCM in IT HRD was introduced in 2004 and continuously developed more. Since the late 2000s, IT convergence expanded to traditional industries and the new IT-based-industries were created in Korea. In this regard, Korea established the Seoul Accord as an international IT engineering education accreditation system in 2008. In response to the paradigm change, in 2011, the Korean government developed TOPCIT, which is a kind of competency test for evaluating IT competency.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.3
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• pp.134-141
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• 2004

Recently, neural network techniques are widely used in adaptive and learning control schemes for production systems. However, in general it takes up a lot of time to learn in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult for the PID gains suitably, lots of researches have been reported with respect of turning schemes of PID gains. A neural network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed neural network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accidents.