• 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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• 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.

• 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.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.47
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• pp.403-428
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• 2010

Our country's sustainable trade growth fundamentally depends on the supply of excellent labors called global trade expert. He or she is required several knowledge and skills not only trade, marketing, information technology, foreign languages but also global mind. Universities have to supply excellent global trade expert to companies according to needs and wants. The object of this paper is to propose some ideas for training of global trade expert of Korea university under global trade environment. First, global companies prefer labors who have not only some skills about specialty and communication skill but also personality on passion, creativity, leadership and so on. Second, The university's curriculum needs to improved in terms of "convergence" and "specialty". In nature, trade major treats lots of subjects such as trade, business adminstration, economics, international law, international commerce, logistics, marketing, etc to catch up changing global business circumstances and companies' needs. Therefore convergence of adjacent field is very important in study and training. Finally, Universities need to use field-specialist to supplement of trade working experience as instructors and practitioners. The concept of convergence and specialty is not separated but harmonious each other.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.37-44
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• 1995

Grinding is used for machining high precision parts with high additional value. However, the grinding operation needs high skill and long experience of an operator because of a lack of the scientific knowledge and engineering principles. Also, the wheel and grinding conditions affect grinding results. For these reasons, it is difficult to construct computer integrated manufacturing system(CIMA). Therefore, it is necessary for Expert System to be informed of qualitative knowledge of grinding expert's skills and experiences. In this research, the Grinding Expert System is constructed by Fuzzy Decision Making Algorithm. Using this system, unskilled workers will be able to use the knowledge and experience of an expert.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.143-154
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• 2023

The purpose of this study is to present the role and function of Smart Training Education Platform(STEP) as a public online platform that should be aimed at for the development of customized lifelong vocational skills as the existing Occupational Skills Development Act was revised to the National Lifelong Vocational Skills Development Act. To this end, the role and function of STEP's public service was derived based on domestic public online platform service case studies and expert FGI, and an expert verification meeting was held. Based on this, implications for the role and function of STEP as a public online platform were presented.

• 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.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• Information Systems Review
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• v.4 no.2
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• pp.343-360
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• 2002

Ideal project manager is a critical factor for successful IS development. The purpose of this paper is to investigate the knowledge and skills requirement of IS project managers and to suggest ideas of a career path development for powerful IS project managers. From a previous research work, this paper was conducted to classify 6 domains-strategic management, business function, innovation, general management, personnel management, and technical expert- as knowledge and skills of IS project managers, and to generate IS project manager's career path which is developed through engineer, analyst and designer, planner, and project leader. The results provide a good framework to train and develop knowledge and skills of IS project mangers.