• Journal of KIISE:Databases
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• v.27 no.2
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• pp.141-150
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• 2000

There are three significant drawbacks in extant fuzzy rule-based expert system languages. First, they lack the functionality of composite object inference. Second, they do not support fuzzy reasoning semantically easy to understand and conceptually simple to use. Third, knowledge representation and reasoning style of their model have a great semantic gap with those of current database models. Therefore, it is very difficult for the two models to be seamlessly integrated with each other. This paper provides the formal specification of a fuzzy object inference model to solve the three drawbacks. GIS(Geographic Information System) application domain is used to demonstrate that our model naturally models complex GIS information in terms of composite objects and successfully performs fuzzy inference between them.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.2 no.1
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• pp.13-17
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• 2001

The configuration design of kinematic mechanisms of industrial sewing machine has been studied using a functional approach. The configuration design methodology has been applied to shorten the development cycle time of mechanisms and to manage design data efficiently Expert system has been used to embody the decomposition of functional requirements. It has been interfaced with a CAD system through the API program to show the assembly and parts of the mechanism. Constraints also can be handled by the expert system through the rule induction and the case based reasoning process. The configuration design system includes the kinematical analysis and optimization of the mechanisms of an industrial sewing machine by the interface between the expert system and an analysis program by means of API Program supplied by expert system. The conceptual design of sewing machine mechanism can be Performed rapidly and efficiently.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.7-12
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• 2005

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper. The expert system which introduces fuzzy logic in order to process uncertainties is called fuzzy expert system. The fuzzy expert system, however, has a potential problem which may lead to inappropriate results due to the ignorance of some information by applying fuzzy logic in reasoning process in addition to the knowledge acquisition problem. In order to overcome these problems, We construct fuzzy inference network by extending the concept of reasoning network in this paper. In the fuzzy inference network, the propositions which form fuzzy rules are represented by nodes. And these nodes have the truth values representing the belief values of each proposition. The logical operators between propositions of rules are represented by links. And the traditional propagation rule is modified.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.31-40
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• 2000

A robust scheme of locating and counting the number of vehicles m urban traffic scenes, a core component of vision-based traffic monitoring systems, is presented The method is based on the evidential reasoning, where vehicle evidences m the background subtraction Image are obtained by a new locally optimum thresholding, and the evidences are merged by three heuristic rules using the geometric constraints The locally optimum thresholding guarantees the separation of bright and dark evidences of vehicles even when the vehicles are overlapped or when the vehicles have similar color to the background Experimental results on diverse traffic scenes show that the detection performance is very robust to the operating conditions such as the camera location and the weather The method may be applied even when vehicle movement is not observed since a static Image IS processed without the use of frame difference.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.21-26
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the user's access pattern to web site and their following purchasable items and improves their web page on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning, it employs Apriori algorithm, which is a method that searches the association rule. It reasons the web pages by considering the user's access pattern and time by using the web log and reasons the user's purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of user's web pages and displays the inferred goods on user's web pages.

• The Journal of Information Technology
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• v.7 no.3
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• pp.127-137
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• 2004

A Project planning is one of the most important processes that determines success and failure of a project. Scope management for a project planning is also essential job in system integration project. However project planning is very difficult because lots of factors and their relationships should be considered. Therefore project planning of system integration project has been done by project manager's own knowledge and experience. It is necessary to develop an algorithm of WBS(Work Breakdown Structure) identification & document selection along to project's specificity in project management system using AI technique. This study presents a methodology to cope with the limitations of the existing studies that have uniformly been customizing the methodology by only project complexity. We propose PPSM(Project planning support module) based on determination rules regarding route maps and document levels, and CBR(Case-Based Reasoning) for WBS identification.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.452-456
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• 2011

Context-awareness system can provide an optimized services to users. Analyzing physical and complex circumstance elements which give direct or indirect influence to users can tell what users want. However, there are various situation informations around users and it requires high level technology to extract the service what users really want among those informations. The circumstance of the user can be changed from moment to moment, even the service what users want also can be changed in every minutes. Recently the researches to provide the service which a user demands has been progressed actively. Web based filtering method which reaches commercialization is a one of good examples. This method extracts necessary data according to users' demands from the documents on the Web or multimedia informations. However, there is a limit to use it to provide Context-awareness service because it extracts static data, not dynamic data. There is also other researches with a rule based filtering method in progress to filter situation information but this method doesn't have mechanism for dynamic data as well. We would like to solve these problems by providing a dynamic situation information filtering mechanism applying an weighted value about each property of objects and also applying Web based dynamic categories in this paper when unnecessary data should be filtered.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.29-32
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the users' access pattern to web site and their following purchasable items and improves their web pare on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning it employs Rough Set, which is a method that searches the association rule and offers most suitable cases by reduces cases. It reasons the web pages by considering the users' access pattern and time by using the web log and reasons the users' purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of users' web pages and displays the inferred goods on users' web pages.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.378-382
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• 2001

The purpose of this study was to develop an expert system supporting the diagnosis of diffuse interstitial lung disease by high resolution computed tomography. CLIPS(C language integrated production system) with rule-based reasoning was used to develop the system. Development of expert system had three stages knowledge acquisition, knowledge representation, and reasoning. Knowledge was obtained and integrated, from tables and figure legends of a representative textbook in the domain of this expert system, High-Resolution CT of the Lung, by Webb WR, Mueller NL, and Naidich DP. The acquired knowledge was analyzed to form a knowledge base. Overlapping knowledge was eliminated, similar pieces of knowledge were combined and professional terms were defined. The most important knowledge of findings was then selected for each disease. After groupings of combined findings were made, disease groups were analyzed sequentially to determine final diagnoses. The system was based upon the input of 69 diseases, 185 findings, 73 conditions, 387 status, and 62 rules. The system was set up to determine the diagnoses of diseases from the combination of findings using forward reasoning. In an empirical trial, the system was applied to support the diagnosis of 40 cases of diffuse interstitial lung diseases. The performance of two doctors with support of the system was compared to that of another two doctors without support of the system. The two doctors with the support of the system made more accurate diagnoses than the doctors without the support of the system. The system is believed to be useful for the diagnosis of rare diseases and for cases with many possible differential diagnoses. In conclusion, an expert system supporting the high resolution computed tomographic diagnosis of diffuse interstitial lung disease was developed and the system is thought to be useful for medical practice.

• Journal of The Korean Association For Science Education
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• v.26 no.4
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• pp.546-558
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• 2006

The purpose of this study was to identify heuristically how abduction was used in a context of solving an earth-environmental problem. Thirty two groups of participants with different institutional backgrounds, i,e., inservice earth science teachers, preservice science teachers, and high school students, solved an open-ended earth-environmental problem and produced group texts in which their ways of solving the problem were written, The inferential processes in the texts were rearranged according to the syllogistic form of abduction and then analyzed iteratively so as to find thinking strategies used in the abductive reasoning. The result showed that abduction was employed in the process of solving the earth-environmental problem and that several thinking strategies were used for inferring rules from which abductive conclusions were drawn. The strategies found included data reconstruction, chained abduction, adapting novel information, model construction and manipulation, causal combination, elimination, case-based analogy, and existential strategy. It was suggested that abductive problems could be used to enhance students' thinking abilities and their understanding of the nature of earth science and earth-environmental problems.