• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.155-160
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• 1992

Liver function test is one of the most common tests for diagnosis and follow-up of patients and for heal th screening. Automatic interpretation and suggestions on the diagnostic possibilities contribute to shorten the interpretation time of the test results and help to provide qualified health care. Fuzzy logic has been recently introduced and being spread for these purposes. The present study aims at model Ins the foray rule-based laboratory diagnosis system. The fuzzy rule-based laboratory diagnosis system was applied to the diagnosis regarding liver function test. The system was evaluated by comparing with the stepwise multivariate discriminant function analysis, which showed similar results, and the overall accuracy of the fuzzy diagnosis system was about 80%.

• 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.

• Asia pacific journal of information systems
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• v.14 no.1
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• pp.79-100
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• 2004

As a part of ebXML(Electronic Business using eXtensible Markup Language) framework, BPSS(Business Process Specification Schema) has been provided to support the direct specification of the set of elements required to configure a runtime system in order to execute a set of ebXML business transactions. The BPS,' is available in two stand-alone representations, a UML version and an XML version. Due to the limitations of UML notations and XML syntax, however, current ebXML BPSS specification fails to specify formal semantic constraints completely. In this study, we propose a constraint classification scheme for the BPSS specification and describe how to formally represent those semantic constraints using OCL(Object Constraint Language). As a way to validate p Business Process Specification(BPS) with the formal semantic constraints, we suggest a rule-based approach to represent the formal constraints and demonstrate its detailed mechanism for applying the rule-based constraints to the BPS with a prototype implementation.

• Asia pacific journal of information systems
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• v.14 no.4
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• pp.87-97
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• 2004

One of the most fundamental problems in business is ranking items with respect to profit based on historical transactions. The difficulty is that the profit of one item comes from its influence on the sales of other items as well as its own sales, and that there is no well-developed algorithm for estimating overall profit of selected items. In this paper, we developed a product network based on association rule and an algorithm for profit estimation and item selection using the estimated profit ranking(EPR). As a result of computer simulation, the suggested algorithm outperforms the individual approach and the hub-authority profit ranking algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.3 s.246
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• pp.219-230
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• 2006

Digital CAD models are one of the most important assets the manufacturer holds. The trend toward concurrent engineering and outsourcing in the distributed development and manufacturing environment has elevated the importance of high quality CAD model and its efficient exchange. But designers have spent a great deal of their time repairing CAD model errors. Most of those poor quality models may be due to designer errors caused by poor or incorrect CAD data generation practices. In this paper, we propose a rule-based approach for healing CAD model errors. The proposed approach focuses on the design history data representation from a commercial CAD model, and the procedural method for building knowledge base to heal CAD model. Through the use of rule-based approach, a CAD model healing system can be implemented, and experiments are carried out on automobile part models.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.357-360
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• 2008

There are many control strategies for HEV in today. Expanding motor-driving and operating at good-efficient point in engine is the key of the HEV control to increase fuel economy. There are two types of HEV supervisory control. One is rule-based control and the other is optimization control. MAX-SOC control, thermostat control, baseline status control and state-machine control are in deterministic RBC. It is simple, but powerful and easy to apply in real-time circumstance. In this study, we analysis these four control strategies in RBC (Rule-based control) and identify the each advantage and disadvantage.

• Journal of Ship and Ocean Technology
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• v.6 no.1
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• pp.16-26
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• 2002

In this paper, a motion identification method using neural networks is applied to automatic ship berthing to overcome disturbance effects. Motion identification is used to estimate the effect of environmental disturbance. Two rule-based algorithms have been developed to over-come disturbance. The first rule based-algorithm was designed to overcome lateral disturbance when a ship's lateral speed is affected by it. The second rule-based algorithm was also designed to overcome longitudinal disturbance when a ship's angular velocity is changed by it. Finally, numerical simulations for automatic berthing are carried out, and the suggested control system is proved to be more practical under disturbance circumstances.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.43-52
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• 1994

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.1-7
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• 2014

This paper presents a novel method for simultaneously and automatically choosing the nonlinear structures of regressors or discriminant functions, as well as the number of terms to include in a rule-based regression model or pattern classifier. Variables are first partitioned into subsets each of which has a linguistic term (called a causal condition) associated with it; fuzzy sets are used to model the terms. Candidate interconnections (causal combinations) of either a term or its complement are formed, where the connecting word is AND which is modeled using the minimum operation. The data establishes which of the candidate causal combinations survive. A novel theoretical result leads to an exponential speedup in establishing this.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.88-97
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• 2018

Chronic diseases management can be effectively achieved through early detection, continuous treatment, observation, and self-management, rather than a radar approach where patients are treated only when they visit a medical facility. However, previous studies have not been able to provide integrated chronic disease management services by considering generalized services such as hypertension and diabetes management, and difficult to expand and link to other services using only specific sensors or services. This paper proposes clinical rule flow model based on medical data analysis to provide personalized care for chronic disease management. Also, we implemented that as Rule-based Smart Healthcare System (RSHS). The proposed system executes chronic diseases management rules, manages events and delivers individualized knowledge information by user's request. The proposed system can be expanded into a variety of applications such as diet and exercise service in the future.