• Proceedings of the Korea Association of Information Systems Conference
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• 2003.05a
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• pp.271-285
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• 2003

In the conduct of this study, a web-enabled healthcare system for the management of hypertension was implemented through a hyperlink-based inference approach. The hyperlink-based inference platform implemented using the hypertext capacity of HTML which ensured accessibility, multimedia facilities, fast response, stability, ease of use and upgrade, and platform independency of expert systems. Many HTML documents, which are hyperlinked to each other based on expert rules, were uploaded beforehand to perform the hyperlink-based inference. The HTML documents were uploaded and maintained automatically by our proprietary tool called the Web-Based inference System (WeBIS) that supports a graphical user interface (GUI) for the input and edit of decision graphs. Nevertheless, the editing task of the decision graph using the GUI tool is a time consuming and tedious chore when the knowledge engineer must perform it manually. Accordingly, this research implemented an automatic generator of the decision graph for the management of hypertension. As a result, this research suggests a methodology for the development of Web-enabled healthcare systems using the hyperlink-based inference approach and, as an example, implements a Web-enabled healthcare system for hypertension, a platform which peformed especially well in the areas of speed and stability.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.142-159
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• 1996

Engineering of automated tools for the agro-food industries and the rural world activities have to pick up two challenges : to answer the immediate important problems related to the situation of these industries, and to imaging the tools that their professional will need next century. Creating or modifying automated tools in the next few will be made taking into account parameters either technical (environmental protection, health and safety), or social and economical (investment , employment). There will be a strong interaction with disciplines like ecology, medicine, ergonomy, psycho-sociology , etc. , The partners for such a research, tools manufactures and users, should have an early involvement in its content, in order to find rapidly the solution to the drastic problems they are meeting. On a longer term , during the next 20 years , there will be an important evolution of the rural space management and of the food processes. This will imply the emergence of new types of activities and know-how's , with lines of automated tools to be invented and developed , like : micro-system for organic localized tasks -mobile and adaptive equipments highly autonomous for natural space actions - device for perception , decision and control reproducing automatically the expert behaviors of human operators. Design of such automated tools need to overcome technological difficulties like the automation of the expert-decision process, or the management of complex design.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.237-247
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• 2004

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.69-77
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• 2014

Because smart televisions (TVs) have various and innovative functions that are different from traditional TVs, consumers are front with a complex decision-making problem when they want to buy a best TV among alternatives made by many TV makers. TV manufactures have developed and announced different types of smart TV models and they need a comparative study for evaluating their characteristics. In this paper, we suggest the Analytic Hierarchy Process(AHP) method for deciding the best smart TVs regarding many selection criteria. The method provides a decision support for consumers who like to purchase a smart TV. We describe criteria affecting the smart TV selection through a literature review and suggest a user testing method in order to derive accurate judgments from consumers. Using the Expert Choice software package, we show a an numerical example how the priority of smart TVs are computed.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.8
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• pp.580-586
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• 2011

In this study, 3 cooling systems of apartment which are air-cooled air conditioner with indoor unit, water-cooled air conditioner with indoor unit and small capacity absorption chiller-heater with FCU have been evaluated by Multi-Criteria Decision Making Analysis. Weights of 7 selected factors which are economics, space, billing, constructability, human comfort, visibility and reliability are determined by expert group of 30 system designers and 30 construction engineers. Final weights were derived for 101 and 166 $m^2$ apartments. Analysis shows that small capacity absorption chiller-heater with FCU is the most favorable system for apartment cooling system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.255-264
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• 2006

The auxiliary reinforcement method is normally applied to prevent a possible collapse of the tunnel face where the ground condition is not favorable or geologic information is not sufficient. Recently, several engineering approaches have been made to choose the effective reinforcement methods using expert system such as neural network and fuzzy theory field, among others. Even if the expert system has offered many decision aid tools to properly select the reinforcement method, the quantitative assessment items are not easy to estimate and this is why the data mining technique, widely used in the field of social science, medical treatment, banking and agriculture, is introduced in this study. Using decision tree together with PDA, the decision aids for reinforcement method based on field construction data are created to derive the field rules and future study will be concentrated on the application of the proposed methods in a variety of underground development cases.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.214-217
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• 1996

Early decision support systems (DSS) were the "passive" decision support systems in the sense that the systems only able to do what the users explicitly direct them to do. But some researchers such as Raghav Rao et al. [51 showed architectures to suggest general idea of the innovative DSS systems which offer active form of decision support, say, "active Intelligent Decision Support Systems(active IDSS)". The system can perform not only what the users want to do but some voluntary (or involuntary) intelligent works. This paper presents the issues in the design of the active IDSS in the domain of investment evaluation, a domain area where few researchers have suggested frameworks or architectures to discriminate good investment from bad one. We propose a new paradigm, by utilizing historical investment results using neural network and Multivariate Discriminant Analysis(MDA), to identify goodness of investment. A new active IDSS architecture which consists of neural network, expert system and three components of the traditional passive DSS is suggested with some scenario based results.nario based results.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.2
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• pp.171-182
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• 2000

For the last five years, data mining has drawn much attention by researchers and practitioners because of its many applicable domains. This article presents an adaptive decision tree algorithm for dynamically reasoning machine failure cause out of real-time, large-scale machine status database. Among many data mining methods, intelligent decision tree building algorithm is especially of interest in the sense that it enables the automatic generation of decision rules from the tree, facilitating the construction of expert system. On the basis of experiment using semiconductor etching machine, it has been verified that our model outperforms previously proposed decision tree models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.87-93
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• 2006

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.321-331
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• 1997

Measurement of attributes is often highly subjective and imprecise, yet most MADM methods lack provisions for handling imprecise data. Frequently, decision makers must establish a ranking within a finite set of alternatives with respect to multiple attributes which have varying degrees of importance. The problem is more complex if the evaluations of alternatives according to each attribute are not expressed in precise numbers, but rather in fuzzy numbers. Analysis must allow for lack of precision and partial truth. The advantages of a fuzzy approach for MADM are that a decision maker can obtain efficient solutions all at once without trial and error, and that this approach provides better support for judging the interactive improvement of solutions in comparison with o decision making method. The algorithm used in this study is based on the concepts of vague set theory. Linguistic variables and vague values are used to facilitate a decision maker's subjective assessment about attribute weightings and the appropriateness of alternative versus selection attributes in order to obtain final scores which are called vague appropriateness indices. A numerical example is presented to show the practical applicability of this approach.