• Journal of KIISE:Databases
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• v.34 no.6
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• pp.493-502
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• 2007

Due to a growing interest in searching and expressing knowledge effectively, knowledge management methods such as Topic Map are becoming more important. Topic Map organizes knowledge that is full of intricate relations, so maintaining and managing Topic Map consistently is very essential. TMCL and other constraint languages have limits as they can check simple constraints but can not support complex constraints like dependence constraints. Current constraint checking systems operating at the application level are also showing an inferiority in performance. In this paper, we extend TMCL based on the characteristics of other constraint languages in the information system field and related fields. We build and propose an RDBMS-based Topic Map constraint checking system to support the extended constraint language effectively. This new system handles complex types of constraints like dependency constraint as well as basic Topic Map constraints present in the TMCL. As the system examines each constraint it uses templates to generate queries for effective checking and overall shows a higher performance level than current systems.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.241-246
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• 2003

• Journal of KIBIM
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• v.5 no.4
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• pp.53-62
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• 2015

Korea has been at the forefront of green growth initiatives. In 2008, the government declared the new vision toward 'low-carbon society and green growth'. The government subsidies and Feed-in Tariff (FIT) increased domestic usage of solar power by supplying photovoltaic housing and photovoltaic generation systems. Since 2000, solar power industry has been the world's fastest growing source with the annual growth rate of 52.5%. Especially, BIPV(Building Integrated Photovoltaic) systems are capturing a growing portion of the renewable energy market due to several reasons. BIPV consists of photovoltaic cells and modules integrated into the building envelope such as a roof or facades. By avoiding the cost of conventional materials, the incremental cost of photovoltaics is reduced and its life-cycle cost is improved. When it comes to atypical building, numerous problems occur because PV modules are flat, stationary, and have its orientation determined by building surface. However, previous studies mainly focused on improving installations of solar PV technologies on ground and rooftop photovoltaic array and developing prediction model to estimate the amount of produced electricity. Consequently, this paper discusses the problem during a planning and design stage of BIPV systems and suggests the method to select optimal design of the systems by applying the national strategy and economic policies. Furthermore, the paper aims to develop BIM tool based on the engineering knowledge from experts in order for non-specialists to design photovoltaic generation systems easily.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.521-524
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• 2003

In this paper, we propose a design process of 'personalized' classification with soft computing techniques. Based on human's thinking way, a construction methodology for personalized classifier is mentioned. Here, two fuzzy similarity measures and ensemble of classifiers are effectively used. As one of the possible applications, facial expression recognition problem is discussed. The numerical result shows that the proposed method is very useful for on-line learning, reusability of previous knowledge and so on.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.719-724
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• 1998

This paper presents a systematic developement of a formal approach to inference in approximate reasoning. We introduce some measures of similarity and discuss their properties. Using the concept of similarity index we formulate two methods for inferring from vague knowledge. In order to illustrate the effectiveness of the proposed technique we use it to develop a vowel recognition system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.253-258
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• 2010

The causal network represents the knowledge related to the dependency relationship between all attributes. If the causal network is available, the dependency relationship can be employed to estimate the missing values for improving the estimation performance. However, the previous method had a limitation in that it did not consider the bidirectional characteristic of the causal network. The proposed method considers the bidirectional characteristic by applying prior and posterior conditions, so that it outperforms the previous method.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.196-200
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• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used fur on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• The Journal of Information Systems
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• v.3
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• pp.171-201
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• 1994

I wish to acknowledge the people who inspired me to believe that a machine can have intelligence. They are the ones who envisioned the future of mankind. I specially appreciate to my advisor Dr. Srivasan raghunathan, who was always supportive and encouraged to finish this research. I also sincerely thank for my parents who are always concerned of my well-being. Without them, what I achived here cannot be possible.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.49.2-49
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• 2002

This paper describes the configuration of a multi-agent system that can recognize human intentions. This system constructs ontologies of human intentions and enables knowledge acquisition and sharing between intelligent agents operating in different environments. This is achieved by using a bi-directional associative memory network. The process of intention recognition is based on fuzzy association inferences. This paper shows the process of information sharing by using ontologies. The purpose of this research is to create human-centered systems that can provide a natural interface in their interaction with people.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.136-139
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• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used for on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.