• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.17-21
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• 2004

본 논문에서는 실시간으로 상수 및 변수의 병렬 매칭이 가능한 새로운 구조의 하드웨어 기반 룰-베이스시스템 구조를 제안한다. 이 시스템은 context-aware computing 시스템에서 상황 인식을 위한 기법으로 적용될 수 있다. 제안된 구조는 기존의 하드웨어 기반의 구조가 가지는 룰의 표현 및 룰의 구성에서 발생하는 제약을 상당히 감소시킬 수 있다. 이를 위해 변형된 형태의 content addressable memory(CAM)와 crossbar switch network(CSN)가 사용되었다. 변형된 형태의 CAM으로 구성된 지식-베이스는 동적으로 데이터의 추가 및 삭제가 가능하다. 또한 CSN은 input buffer와 working memory(WM) 사이에 위치하여, 시스템 외부 및 내부에서 동적으로 생성되거나, 시스템 설정에 의해 지정된 데이터들의 조합 및 pre-processing module(PPM)을 이용한 연산을 통하여 WM을 구성하는 데이터를 생성시킨다. 이 하드웨어 룰-베이스 시스템은 SystemC 2.0을 이용하여 설계하였으며 시뮬레이션을 통하여 그 동작을 검증하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.587-592
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• 2004

Context-aware computing systems require real-time context reasoning process for context awareness. Context reasoning can be done by comparing input information from sensors with knowledge-base within system. This method is identical with it of rule-based systems. In this paper, we propose hardware rule-based system architecture which can process context reasoning in real-time. Compared to previous architecture, hardware rule-based system architecture can reduce the number of constraints on rule representations and combinations of condition terms in rules. The modified content addressable memory, crossbar switch network and pre-processing module are used for reducing constraints. Using SystemC for description can provide easy modification of system configuration later.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.492-497
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• 1999

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skillful engineers. Grinding operations include a large number of functional parameters, since there are several ways of coping with grinding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workshop, the other is the quantitative method which utilizes the experimental data obtained by sensor. But, they are all difficult to accomplish from the grinding trouble-shooting system. The reason is that grinding troubles are not easily controlled in the quantitative method, and therefore, trouble-shooting has mainly relied on the knowledge of skilful engineers. Thus, there is an important issue of how a grinding trouble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper, basic strategy to develop the grinding database of rule-based rule, which is strongly depended upon experience and intuition, is described.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.106-112
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• 2000

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skiful engineers. grinding operations include a large number of functional parameters since there are several ways of coping with ginding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workshop the other is the quantitative method which utilizes the experimental data obtained by sensor. But they are all difficult to accomplish from the grinding trouble-shooting system The reason is that grinding troubles are not accomplish from the grinding trouble-shooting system,. The rason is that grinding troubles are not easily controlled in the quantitative method and therefore trouble-shooting has mainly relied on the knoledge of skiful engineers. Thus there is an important issue of how a grinding touble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper basic strategy to develop the grinding database by taking rule-based model which is strongly depended upon experience and intuition is described.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.772-775
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• 2008

본 논문은 퍼지 분류 시스템을 위한 퍼지 규칙베이스에 대한 최적화 해법으로서 유전 알고리즘에 대해 살펴본다. 즉 퍼지 규칙베이스를 이용하는 퍼지 분류 시스템을 최적화를 하는 유전 알고리즘을 제안한다. 제안하는 유전 알고리즘은 분류 성능을 보다 더 향상시키기 위해서 인식에 사용된 규칙에 대한 확실성 정도를 개선하는 방법을 포함한다. 본 논문에서 다루는 최적화는 추출되는 퍼지 규칙의 수와 퍼지 분류 시스템의 입력 패턴을 정확하게 분류하는 지에 대한 성능을 포괄적으로 수행하는 것을 의미한다. 마지막으로 본 논문에서 제안하는 유전 알고리즘을 이용하여 수치실험을 수행하고 그 결과를 통해 제안하는 알고리즘의 유효성과 효율성을 생성된 퍼지 규칙의 수와 퍼지 분류 시스템의 성능의 관점에서 논의한다.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.4
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• pp.56-61
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• 2000

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skilful engineers. Grinding operations include a large number of functional parameters, since there are several ways of coping with grinding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workship, the other is the quantitative method which utilizes the experimental data obtained by a sensor. But, they are all difficult to accomplish from the grinding trouble-shooting system. The reason is that grinding troubles are now easily controlled in the quantitative method, and therefore, trouble-shooting has mainly relied on the knowledge of skilful engineers. Thus, there is an important issue of how a grinding trouble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper, basic strategy to develop the grinding database of rule-based model, which is strongly depended upon experience and intuition , is described.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.134-137
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• 2004

지능 홈-케어 시스템 또는 외부 통신 채널의 환경 인식이 가능한 모바일 통신기기와 같은 상황 인식 시스템이 외부 상태를 감지하여 현재 상창을 인식하고 대처하기 위해서는 수 백개 이상의 규칙들을 이용한 추론을 필요로 한다. 이들 규칙들의 효과적인 추론을 위해서는 룰-베이스 시스템에 기반을 둔 추론 기법을 적용시킬 수 있다 이 룰-베이스 시스템의 추론 규칙의 매칭을 위해서 RETE 알고리즘이 사용되어 왔다. 하지만 RETE 알고리즘은 그 특성상 Von Neumann 구조의 컴퓨터 시스템에서는 규칙의 증가에 따른 그 성능의 저하가 필연적이다. 본 논문에서는 RETE 네트워크를 이용한 추론을 효과적으로 수행할 수 있는 RETE 네트워크 하드웨어 가속기의 구조에 대해서 논한다. 이 RETE 네트워크 하드웨어 가속기은 Von Neumann의 구조적 제약점을 병렬처리 구조를 사용하여 제거하였다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.7
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• pp.552-559
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• 2002

The fault detection and diagnosis (FDD) technology may be applied in order to decrease the energy consumption and the maintenance cost of the air conditioning system. In this study, rule bases and curve fitting models were used to detect faults in an air handling unit. Gradually progressed faults, such as the fan speed degradation, the coil water leakage, the humidifier nozzle clogging, the sensor degradation and the damper stoppage, were applied to the developed FBD system. Simulation results show good detections and diagnoses of these faults. Therefore, this method may be effectively used for the fault detection and diagnosis of the air handling unit.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.4
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• pp.301-319
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• 2017

The task of author name disambiguation involves identifying an author with different names or different authors with the same name. The author name disambiguation is important for correctly assessing authors' research achievements and finding experts in given areas as well as for the effective operation of scholarly information services such as citation indexes. In the study, we performed error correction and normalization of data and applied rules-based author name disambiguation to compare with baseline machine learning disambiguation in order to see if human intervention could improve the machine learning performance. The improvement of over 0.1 in F-measure by the corrected and normalized email-based author name disambiguation over machine learning demonstrates the potential of human pattern identification and inference, which enabled data correction and normalization process as well as the formation of the rule-based diambiguation, to complement the machine learning's weaknesses to improve the author name disambiguation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1870-1883
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• 1993

In this paper, in order to build up the User Network Interface based on ATM, a study on traffic control techniques which should be performed by main function groups-B 75,5 NT2, LEX-is discussed. The structure of B-NT2 which is the most important function group In the User Network Interface is defined in quite a simple manner in addition, the functional blocks of LEX are defined in a similar manner as those of B NT2. It is possible to distribute total traffic control functions by using the similarities between B-NT2 and LEX and by allocating virtual path identifiers fixedly according to the characteristics of the traffics. For the traffic control techniques of ATM, relations among Connection Admtsslon Control, Usage Parameter Control and Bandwidth Allocation Control are defined and Multi Rule Base structure to realize optimal control functions according to the characteristics of the source traffics is proposed. And the Real-time Variable Window algorithmsimply designed to be suitable for the Multi Rule Base architecture is also proposed. The performances of the proposed algorithm are analyzed through the computer simulation by generating on-off source traffic in a virtual system that has the form of the proposed hardware. The analyzed results show that the distributed control is possible and that the implementation of the proposed architecture and algorithm is possible.