• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.59-62
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• 2000

In cope with insufficient agricultural labor and requirement of high quality product Hydroponics is a really good method. It makes the high density agriculture possible and all the growing environments controllable. So its research is so much progressing to maximize the quantity and quality of farm products. Furthermore, the big progress, in the research of a future agriculture, is systematically conducted for the automatic controlled system. In this paper, a new approach to the automation of the cultivation in a green house is suggested and a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA; Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system(FMES; Fuzzy Model-based Expert System) is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller is incorporated to solve the time-variance of the growth of farm products. Finally, the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultiviation results.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2992-2994
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• 2000

In cope with insufficient agricultural labor and requirement of high quality product Hydroponics is a really good method. It makes the high density agriculture possible and all the growing environments controllable. So its research is so much progressing to maximize the quantity and quality of farm products. Furthermore, the big progress, in the research of a future agriculture. is systematically conducted for the automatic controlled system. In this paper, a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA: Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system (FMES: Fuzzy Model-based Expert System) is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller is incorporated to solve the time-variance of the growth of farm products. Finally. the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultivation results.

• Journal of Radiation Industry
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• v.7 no.2_3
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• pp.209-219
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• 2013

RI-Biomics field comes into the limelight as a new fusion radiation technology. These rapid development of RI-Biomics cause the necessity of establishment of a new methodical education program model for consistent training of professional manpower in RI-ADME, Biomics field. But domestic current status is not satisfied to training human resource development in RI-Biomics. Actually domestic educational organization related to RI-Biomics just run educational programs oriented basic theory, so practical and fusion education are not existed nowadays for preliminary RI-Biomics expert. Therefore we established a new education program model for educate of the expert in RI-Biomics field to overcome current problem about the route of knowledge that has more monotonous and concentrated tendency and non-professional education. To improve universality and practicality, we conduct education-training model survey about domestic and foreign country. This new human resource development model will contribute to fostering new expert in RI-Biomics field.

• Transactions of Materials Processing
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• v.8 no.6
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• pp.591-603
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• 1999

A computer-aided process planning system for rotationally symmetric deep drawing products has been developed. The application for non-axisymmetric components, however, has been reported yet. Therefore, this study investigates process sequence design in deep drawing process and constructs a computer-aided process planning system for non-axisymmetric motor frame products with elliptical shape. The system developed consists of three modules. The first one os a 3-dimensional modeling module to calculate surface area for non-axisymmetric products. The second one is a blank design module that creates an oval-shaped blank with the identical surface area. The third one is a process planning module based on production rules that play the best important roles in an expert system for manufacturing. The production rules are generated and upgraded by interviewing with field engineers. Especially, drawing coefficient, punch and die radii are considered as main design parameters. The constructed system for elliptical deep drawing products would be very useful to reduce lead time and improve accuracy for production.

• Journal of Yeungnam Medical Science
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• v.24 no.2
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• pp.137-147
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• 2007

Background : Interpretative reporting is an important aspect of laboratory medicine. The large menu of laboratory tests available today makes it increasingly difficult for the non-specialist to order and interpret all laboratory tests. The aim of this study was to determine the usefulness of an expert system to interpret laboratory tests and help physicians order the appropriate tests. Materials and Methods : In order to interpret laboratory tests, a rules-based expert system was developed. In this module, if-then rules were used to interpret the given test result patterns (e.g. urinalysis, anemia, hepatitis B virus, hypercholesterolemia, glucose, syphilis, and tumor markers) and select matching text elements. The system was used to evaluate 535 subjects who visited a health-check program. Results : The overall abnormal rate was 50.5% in the expert system; 34% for cholesterol, 9.9% for urinalysis, 8.0% for anemia, 7.7% for thyroid function tests, 4.5% for tumor marker study, 4.7% for hepatitis virus antigen, 4.3% for serum glucose, and 1.1% for syphilis. Conclusion : These results indicate that the application of the expert system for the interpretation of laboratory tests may provide a useful method for the interpretation of reports. However more rules are needed for the application to in-patients.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.271-275
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this Purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between $0\∼1$. Second, RDB and SQL(Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS(Knowledge Management Systems)

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2058-2064
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• 2014

In transformer fault diagnosis, dissolved gas analysis (DGA) is been widely employed for a long period and numerous methods have been innovated to interpret its results. Still in some cases it fails to identify the corresponding faults. Due to the limitation of training data and non-linearity, the estimation of key-gas ratio in the transformer oil becomes more complicated. This paper presents Intuitionistic Fuzzy expert System (IFS) to diagnose several faults in a transformer. This revised approach is well suitable to diagnosis the transformer faults and the corresponding action to be taken. The proposed method is applied to an independent data of different power transformers and various case studies of historic trends of transformer units. It has been proved to be a very advantageous tool for transformer diagnosis and upkeep planning. This method has been successfully used to identify the type of fault developing within a transformer even if there is conflict in the results of AI technique applied to DGA data.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.222-227
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• 2008

The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.410-415
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• 1997

Recently, The manufacturing companies are introducing the CAD/CAM systems to solve problems for the lack of experts, the higher cost of manufacturing and the difficulties of process. Knowledge engineering approach makes it possible to change a know-how of experts to computerized information effectivly. The proposal of this paper is the development of an interactive knowledge-based CAM system to disign and manufacture the mold with non-expert engineers used easily. This system is composed of two functional parts. One is the geometric modeler that used the technique of a feature modeling. The other is the expert system module that composed inference engine and databas which contains characteristics of materials and cutting tools setc.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.10a
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• pp.30-36
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• 1995

Conventionally design for multi-stage cold forging depends on the designer's experience and decision-making. Due to such non-deterministic nature of the process sequence design, a flexible inference engine is needed for process design expert system. In this study, A* searching algorithm was introduced to arrive at the vetter process sequence design considering the number of forming stages and levels of effective strain, effective stress, and forming load during the porcess. In order to optimize the process sequence in producing the final part, cost function was defined and minimized using the proposed A* searching algorithm. For verification of the designed forming sequences, forming experiments and finite element analyses were carried out in the present investigation. The developed expert system using A* searching algorithm can produce a flexible design system based on changes in the number of forming stages and weights.