• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.39-48
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• 1997

This paper describes the process planning system of a computer-aided design of blanking and piercing for irregularly shaped sheet metal products. An approach to the system is based on knowledge-based rules. The process planning system is designed by considering several factors, such as the complexity of blank geometry, production feasibility of products, and punch profile complexity. Therefore this system which was implemented production feasibility check and strip layout module can carry out a process planning considering a production feasibility area of both internal and external features, a dimension of blanked hole, a coner and a fillet radius for irregualrly shaped sheet metal products and generate the strip layout in graphic froms. Knowledges for process planning are extracted from plasticity theories, handbooks, relevant references and empirical know- hows of experts in blanking companies. This provides powerful capabilities for process planning system of irregularly shaped sheet metal products.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1566-1574
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• 2008

Researches of current information searching focus on providing personalized results as well as matching needed queries in an enormous amount of information. This paper aims at discovering hidden knowledge to provide personalized and inferred search results based on the ontology with categorized concepts and relations among data. The current searching occasionally presents too much redundant information or offers no matching results from large volumes of data. To lessen this disadvantages in the information searching, we propose an inference algorithm that supports associated and inferred searching through the Jess engine based on the OWL ontology constraints and knowledge expressed by SWRL with association rules. After constructing the personalized preference ontology for domains such as restaurants, gas stations, bakeries, and so on, it shows that new knowledge information generated from the ontology and the rules is provided with an example of the domain of gas stations.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.79-92
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• 2002

This paper describes a research work of developing computer-aided design of a product with bending and piercing for progressive working. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of four main modules, which are input and shape treatment, flat pattern layout, strip layout and die layout modules. The system is designed by considering several factors, such as bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic farms, including bending sequences and piercing processes with punch profiles divided into for external area. The die layout module carries out die design for each process obtained from the results of the strip layout. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.970-974
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• 1993

This paper is concerned with an automatic generation of BOM (Bill Of Material) for a bicycle frame set using a knowledge based system. The major components module system includes : (1) Part information retrieval in CAD drawing, (2) BOM code generation rule, and (3) Database interface. The knowledge based system includes a rule base and a fact base. The fact base consists of basic, variant, and optional components of the standard BOMs of frame sets. The rule contains rules for generating new BOM code in case that the specified is not in the database. The system was implemented on a SUN workstation under Open Windows environments. AutoCAD for CAD drawing was also used.

• Journal of the Microelectronics and Packaging Society
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• v.8 no.3
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• pp.11-17
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• 2001

The design and manufacture of injection molded polymeric parts with desired properties is a costly process dominated by empiricism, including the repeated modification of actual tooling. This paper presents an expert design evaluation system which can predict the mechanical performance of a molded product and diagnose the design before the actual mold is machined. The knowledge-based system synergistically combines a rule-based expert system with CAE programs. Heuristic knowledge of injection molding is formalized as rules of an expert consultation system. The expert system interprets the analytical results of the process simulation, predicts the performance, evaluates the design and generates recommendations for optimal design alternatives.

• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.93-104
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• 1997

The major economic health problem of dairy cattle is mastitis which can affect 10 to 50% of cow-quarters. This health problem is difficult for many dairy farmers and health advisors to understand, diagnose and control. Without special laboratory testing, most mastitis is overlooked. Estimates of annual mastitis cast per cow vary from $50 to $200. For the nearly 9 million cows in the United States, annual loss to the dairy industry amounts to over one billion. A knowledge-based decision aid has been developed to evaluate mastitis data retrieved electronically from two of nine U. S. regional dairy records processing centers. Heuristic rules to diagnose herd mastitis problems were collected and incorporated into the system from various domain experts. This system information. It allows users to select mastitis control schemes with various degrees of aggressiveness and teaches commonly accepted mastitis control practices.

• Journal of the Society of Naval Architects of Korea
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• v.29 no.1
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• pp.1-13
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• 1992

The objective of this study is to develop knowledge-based system for the preliminary design and midship section design of bulk carrier and to enhance the applicability of knowledge engineering in the field of Naval Architecture. First, expert system shell called E.1 is developed in C language. E.1 supports backward-chaining, automatic iteration procedure and reiterative inference mechanism for efficient application of knowledge-based system in structural design. Knowledge representation in E.1 includes IF-THEN rules, 'facts'and 'tables'. Second, knowledge bases for the principal particulars and midship section design are developed by experimental formula, design standard and experiential knowlege. Third, hybrid system combined this knowledge-based system with the optimization program of midship section is developed. Finally, the simplified design method utilizing the regression analysis of the optimum results of stiffened plate is developed for facilitating the design process. Using this knowledge-based system, the design process and results for Bulk carrier and stiffened plates are discussed. It is concluded that knowledge-based system is efficient for preliminary design and midship section design of the ship. It is expected that the performance of the CAD system would be enhanced if the better knowledge-base is accumulated in the E.1 tool.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.161-172
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• 1996

Although conventional computer programs use efficient and precise optimization algorithms, they can not emulate the problem solving capabilities of human experts. A design optimization process involves a number of tasks which require human expertise and experience. Traditional optimization systems have concentrated on numerical aspects of a design process and have not been successful in integrating the numerical parts with human expertise. On the other hand, most knowledge-based systems focus on symbolic reasoning and have been little concerned with the numerical processes. The objective of this paper is to develop a knowledge-based multiobjective optimum design system which has the capabilities of knowledge processing and numerical computation by integrating the multiobjective optimization method and the knowledge-based system. The knowledge-based system for symbolic processing is developed. Rules for knowledge representation and the inference mechanism of the system are written in LISP. The knowledge-based multiobjective optimum design system is finally developed by integrating the multiobjective optimization method and the knowledge-based system by applying shell programming technique. The system is applied to an optimum design model of a LNG carrier in the preliminary design stage. It is found that the system well simulate design variables and objective functions of the design model.

• Journal of Mechanical Science and Technology
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• v.15 no.5
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• pp.580-591
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• 2001

This paper proposes a fuzzy-sliding mode control which is designed by a self tuning fuzzy inference method based on a genetic algorithm. Using the method, the number of inference rules and the shape of the membership functions of the proposed fuzzy-sliding mode control are optimized without the aid of an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. It is further guaranteed that the selected solution becomes the global optimal solution by optimizing Akaikes information criterion expressing the quality of the inference rules. In order to evaluate the learning performance of the proposed fuzzy-sliding mode control based on a genetic algorithm, a trajectory tracking simulation of the polishing robot is carried out. Simulation results show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-sliding mode control which is selected through trial error by an expert. Therefore, a designer who does not have expert knowledge of robot systems can design the fuzzy-sliding mode controller using the proposed self tuning fuzzy inference method based on the genetic algorithm.

• Korean Management Science Review
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• v.17 no.3
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• pp.19-30
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• 2000

Customization and personalization services are considered as a critical success factor to be a successful Internet store or web service provider. As a representative personalization technique, personalized recommendation techniques are studied and commercialized to suggest products or services to a customer of Internet storefronts based on demographics of the customer or based on an analysis of the past purchasing behavior of the customer. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customers data. however, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed knowledge base. In this paper, we proposed a marketing rule extraction technique for personalized recommendation on Internet storefronts using market basket analysis technique, a well-known data mining technique. Using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store. An experiment has been performed to evaluate the effectiveness of proposed approach comparing with preference scoring approach and random selection.