• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.6
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• pp.153-163
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• 1996

An expert system to design compressor valve systems has been developed. Design process is viewed as a chain of devisions based on the results of necessary analyses. Actual design is implemented by the interaction between the expert system and the user. In this work, it is demonstrated how a final design is achieved by utilizing the rule bases and analysis capability of the system. The structure of the rule bases and related parameter studies are also explained. Advantages of using an expert system approach for valve designs are explained using a practical example.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.92-99
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• 2010

This study aimed to provide empirical evidence about expert performance approach in aviation field and the results suggested that the amount of experience(e.g. total flight hour) is necessary but not sufficient index of a pilot's expertise or superior performance. 43 pilots participated and completed a spatial span task and SA (situation awareness) tasks. To explore the factors predicting the performance in routine and non-routine situations, discriminant analysis was conducted. The results of discriminant analysis indicated that different variables are related with the performance in routine and non-routine situation. The factors predicting performance in routine situation were the spatial span scores and total flight hours. On the other hand, the factors predicting performance in non-routine situation were age and the qualification for instrument flying. In real world, total flight time which represents the quantity of experience has been frequently used to predict flight abilities and as an important index of expertise. The results of this study suggest that these kinds of factors have to be used cautiously to predict the performance in abnormal situation.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.34-47
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• 1988

Decision support system (DSS) has been expected to be a powerful tool for aiding the decision making processes in business organizations. But it's contribution has turned to be somewhat doubtful, In this paper, an intergrated systems design apporach is suggested, which integrates DSS and expert system (ES) for the enhancement of performance of DSS, after carefully reviewing both DSS and ES.

• Knowledge Management Research
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• v.6 no.2
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• pp.67-90
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• 2005

Attention has been focused recently on the concept of shared cognition which encompasses the notion that effective team members hold knowledge that is overlapping and complementary with teammates. This shared cognition is expected to improve team effectiveness. In contrast to the continued efforts in developing theoretical approach of shared cognition, empirical studies are meager. Thus, we conducted an empirical study to investigate the role of shared cognition on team effectiveness. This study classifies shared cognition into two types, team mental model and transactive memory system, by shared meaning. A total of 121 new product development teams in the IT industry were surveyed for the data collection. The results of analysis can be summarized as follows: first, team mental model has a positive influence on team performance, team innovative behavior and team learning effect. And the relation with team mental model and team performance is moderated by the similarity of knowledge structure among the expert. Second, transactive memory system has a positive influence on team performance, team innovative behavior and team learning effect.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.492-495
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• 2003

Fuzzy Min-Max Neural Network(FMMNN) is a powerful classifier, It has, however, some problems. Learning result depends on the presentation order of input data and the training parameter that limits the size of hyperbox. The latter problem affects the result seriously. In this paper, the new approach to alleviate that without loss of on-line learning ability is proposed. The committee machine is used to achieve the multi-resolution FMMNN. Each expert is a FMMNN with fixed training parameter. The advantages of small and large training parameters are used at the same time. The parameters are selected by performance and independence measures. The Decision of each expert is guided by the gating network. Therefore the regional and parametric divide and conquer scheme are used. Simulation shows that the proposed method has better classification performance.

• IE interfaces
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• v.6 no.1
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• pp.31-45
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• 1993

Setup planning for machining processes is a part of fixture planning which is also a part of process planning. A setup of a part is defined as a group of features which are machined while the part is fixtured in one single fixture. Setup planning includes a number of tasks such as the selection of setup, sequence of setups and datum frame for each setup. Setup planning is an important function in fixture planning which must be able to support and to clamp a workpiece to prevent deflections caused by machining and clamping loads. This paper presents setup planning system using expert system approach(SPES) for prismatic parts which can be machined on vertical milling machine. SPES consists of preprocessing module and main processing module. Preprocessing module executes the conversion of feature data to frame type data and the determination of setups, and main processing module executes the determination of datum frame of each setup and sequance of setups. Preprocessing module is coded by C language and main processing module is a rule-based expert system using EXSYS pro. The performance of SPES is evaluated through case studies and the results show successful work except for operation sequence of machining holes. This is due to the limited rules for machining holes.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.405-418
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• 2018

This paper was carried out to provide basic data for career search of the free school system. Putting the goal of career education into cultivating expertise, the review was made on the results of the previous studies on the requirements of professional practice. However, As the controversy over the requirements of professional practice has not been solved, so the core elements related to expert performance were examined as a whole through a fundamental cognitive mechanism from which diverse human cognitive characteristics appear. The results show that expert domains consists of content and representation that can exist in an integrated to a great variety of combinations between the two or independent manner, and each domain or field expert performance require different levels of the elements such as intelligence, internal thinking, curiosity (motivation), and obsession (task commitment); and the birth of 1% experts in a domain or field is determined by the obsession. Based on the results, this paper discusses issues related to professionalism and provides a concrete approach to career search during the free semester.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.653-659
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• 1994

Human experts have the various own knowledges to be applied in specialized domains. The fact that knowledge itself becomes more critical in the context of textile knowledge with rapid development of new fibers, automated equipments, processes and applications. Diversity of worsted spun yarns, lack of human expertise, and inconsistency among manually generated process plans in consequency of adjustment machine parameters owing to change up raw materials frequently increase the necessity of developing computer aided process planning(CAPP) systems for spinning process. Expert systems offer one of techniques to develop CAPP systems which would behave in a knowledgeable manner. Expert systems are the problem-solving computer program that can reach a level of performance comparable to that of a human expert in some specialized problem domain. This paper is described as job justification module. The job justification module performs to consult with users on which worsted spun yarn manufacturing process planning under the various factors, e.g., raw materials, machine parameters and required yarn counts. Also, the developed module informs the various knowledges relevant process planning. The job justification module offers the control parameters at each process and includes the various standard process plans as database. These knowledges are generated by facts and rules within rule bases.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.7-11
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• 2013

Taking experts' knowledge to recommend items has shown some promising results in recommender system research. In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of a common expert group for all users. In this paper, we study a problem of identifying personalized experts within a user group, assuming each user needs different kinds and levels of expert help. To demonstrate this idea, we present a framework for using Support Vector Machine (SVM) to find varying expert groups for users; it is shown in an experiment that the proposed SVM approach can identify personalized experts, and that the person-alized expert-based collaborative filtering (CF) can yield better results than k-Nearest Neighbor (kNN) algorithm.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.