• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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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

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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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.

• 한국정밀공학회지
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• 제15권9호
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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.

• 한국정밀공학회지
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• 제13권3호
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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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• 제9권5호
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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.

• 수산해양기술연구
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• 제34권1호
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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.

• 한국도서관정보학회지
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• 제51권3호
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• pp.223-250
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• 2020

본 연구의 목적은 미디어정보 리터러시 개념을 규정하고 교육내용을 개발하는 데 있다. 연구 목적을 달성하기 위하여 문헌 분석과 현장 전문가 대상 인터뷰, 사서교사 대상 설문조사가 수행되었다. 분석 결과, 현장 전문가들은 미디어를 정보를 활용하는 도구로 인식하였으며 정보문제해결능력과 독해능력, 미디어의 기능, 사례 활동, 정의적 영역을 미디어정보 리터러시의 교육의 영역으로 인식하였다. 사서교사들은 미디어정보 리터러시의 역량과 교육내용에 있어서 정보 리터러시와 미디어 리터러시의 역량과 교육내용을 디지털 리터러시의 역량과 교육내용에 비해 중요하게 인식하고 있었다. 연구 결과로 미디어정보 리터러시의 개념을 리터러시와 미디어 리터러시, 정보 리터러시, 디지털 리터러시가 중복된 영역으로 지식, 기능, 태도가 포함된 개념으로 정의하였다. 그리고 민주사회에 참여, 미디어 도구와 콘텐츠의 종류, 인간의 기본권, 기능, 디지털 도구 조작, 정보 문제 해결 과정이 맥락에 따라 결합되어 응용될 수 있도록 미디어정보 리터러시의 교육내용을 개발하였다.

• Asian Journal of Innovation and Policy
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• 제3권2호
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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.

• 전기학회논문지P
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• 제53권3호
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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.