• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.9
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• pp.877-882
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• 1991

The idea of expert control is to incoporate a rule based expert system in a feedback control system. In this paper, We present some heuristic rules about input regulation and supervision and turning for D.C. servo motor speed control. The expert auto-turning PID Controller which Heuristic rules are used as an element of the feedback control system is implemented with the numerical algorithms and Heuristic logics. The robust and accurate control function is confirmed by computer simulation..

• International conference on construction engineering and project management
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• 2013.01a
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• pp.300-303
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• 2013

On BIPV systems, especially roof-top PV systems, the power generation is easier to be reduced due to the shades of facilities nearby, or roof itself. To secure profitability of roof-top PV systems, the optimal design of solar arrays through the precise shading analysis is an important item of design considerations. In this paper, an optimization system for array design of roof-top PVs is to be developed using three-dimensional Geospatial Information System(GIS). The profitability of income and expense is considered through the shading analysis of entire roofs. By applying the system to project for validation, the adequacy and the improvement of NPV of the system were verified compared to expert's design. The system has significance by reason that PV modules are placed through rules established with expert knowledge and geometric rules were applied to reflect the constructability and maintainability.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.11-21
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• 2008

This paper focuses on finding the way of aerospace industry promotion in Korea compatible with fair trade system under international rules by considering and analysing the WTO subsidy rules and WTO dispute settlement cases. As for subsidy rules in WTO, the paper deals with two matters such as financial contribution and benefit and further studies provisions on the prohibited subsidies and actionable subsidies. And as for the dispute settlement matters, it reviews the Brazil-Canada case and the US-EC case on civil aircraft export subsidies. While aerospace industry in Korea is not yet internationally competitive still requiring government's continuous supports, it must not be in conflict with subsidy rules under WTO mechanism. This paper makes several suggestions to meet these conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.46-50
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• 1997

In fuzzy logic control, static fuzzy rules cannot cope with significant changes of parameters of plants or environment. To solve this prohlem, self-organizing fuzzy control. neural-network-hased fuzzy logic control and so on have heen introduced so far. However, dynamically changed fuzzy rules of these schemes may make a fuzzy logic controller Fall into dangerous situations because the changed fuzzy rules may he incomplete or inconsistent. This paper proposes a new adaptive filzzy logic control scheme using a predictivc neural network. Although some parameters of a controlled plant or environment are changed, proposed fuzzy logic controller changes its decision outputs adaptively and robustly using unchanged initial fuzzy rules and the predictive errors generated hy the predictive neural network by on-line learning. Experimental results with a D<' servo-motor position control problem show that propnsed cnntrol scheme is very useful in the viewpoint of adaptability.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.591-594
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• 2000

This paper describes a research work of developing a computer-aided design of 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 module. Based on knowledge-based rules, the system is designed by considering several factors such as radius and angle of bend, material and thickness of product, complexities of blank geometry and punch profile, bending sequence, and availability of press. Strip layout drawing generated by the piercing processes with punch profiles divided into for external area is simulated in 3-D graphic forms, including bending sequences for the product with piercing and bending. Results obtained using the modules enable the manufacturer for progressive working of electronic products to be more efficient in this field.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.789-796
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• 2006

Context-aware is the core in ubiquitous environment of sensor network to support intelligent and contextual adaptation service. The new context information model is demanded to support context-aware applications. The model should not depend on a specified application and be shareable between applications in the same environment. Also, it should support various context representation and complex context-aware. In this paper, we define the context information according to context-aware process. Also we design the knowledge of domain as well as applications using ontologies and rules. The domain spatial ontology and application knowledge are represented using the spatial object model and the rules of expanded ontologies, respectively. The expression of abundant spatial ontology represents the context information about distance between objects and adjacent object as well as the location of the object. The proposed context information model which is able to exhibit various spatial context and recognizes complex spatial context through the existing GIS. This model shows that it can adapt to a large scale outdoor context-aware applications such as air pollution and prevention of disasters as well as various context-aware applications.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.765-774
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• 2006

An association rule discovery, a technique to analyze the stored data in databases to discover potential information, has been a popular topic in stream data system. Most of the previous researches are concerned to single stream data. However, this approach may ignore in mining to multidimensional stream data. In this paper, we study the techniques discovering the association rules to multidimensional stream data. And we propose a AR-MS method reflecting the characteristics of stream data since make the summarization information by one data scan and discovering the association rules for significant rare data that appear infrequently in the database but are highly associated with specific event. Also, AR-MS method can discover the maximal frequent item of multidimensional stream data by using the summarization information. Through analysis and experiments, we show that AR-MS method is superior to other previous methods.

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.483-490
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• 2007

Recently mining techniques that analyze the data stream to discover potential information, have been widely studied. However, most of the researches based on the support are concerned with the frequent event, but ignore the infrequent event even if it is crucial. In this paper, we propose SM-AF method discovering association rules to an abnormal event. In considering the window that an abnormal event is sensed, SM-AF method can discover the association rules to the critical event, even if it is occurred infrequently. Also, SM-AF method can discover the significant rare itemsets associated with abnormal event and periodic event itemsets. Through analysis and experiments, we show that SM-AF method is superior to the previous methods of mining association rules.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.423-432
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• 2009

Advances in information and communication technologies are changing our society greatly. In knowledge-based society, information can be obtained easily via communication tools such as web and e-mail. However, obtaining right and up-to-date information is difficult in spite of overflowing information. The concept of adaptive web site has been initiated recently. The purpose of the site is to provide information only users want out of tons of data gathered. In this paper, an algorithm is developed for adaptive web site construction. The proposed algorithm is based on association rules that are major principle in adaptive web site construction. The algorithm is constructed by analysing log data in web server and extracting meaning documents through finding behavior patterns of users. The proposed algorithm has the following characteristics. First, it is superior to existing algorithms using association rules in time complexity. Its superiority is proved theoretically. Second, the proposed algorithm is effective in space complexity. This is due to that it does not need any intermediate products except a linked list that is essential for finding frequent item sets.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.691-700
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• 2009

An event means a flow which has a time attribute such as the a symptom of patients, an interval event has the time period between the start-time-point and the end-time-point. Although there are many studies for temporal data mining, they do not deal with discovering knowledge from interval event such as patient histories and purchase histories. In this paper, we suggest a method of temporal data mining that finds association rules of event causal relationships and predicts an occurrence of effect event based on discovered rules. Our method can predict the occurrence of an event by summarizing an interval event using the time attribute of an event and finding the causal relationship of event. As a result of simulation, this method can discover better knowledge than others by considering a lot of supports of an event and finding the significant rare relation on interval events which means an essential cause of an event, regardless of an occurrence support of an event in comparison with conventional data mining techniques.