• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.102-110
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• 1996

A new design scheme of a binary decision tree is proposed. In this scheme a binary decision tree is constructed by using genetic algorithm and FCM algorithm. At each node optimal or near-optimal feature subset is selected which optimizes fitness function in genetic algorithm. The fitness function is inversely proportional to classification error, balance between cluster, number of feature used. The binary strings in genetic algorithm determine the feature subset and classification results - error, balance - form fuzzy partition matrix affect reproduction of next genratin. The proposed design scheme is applied to the tire tread patterns and handwriteen alphabetic characters. Experimental results show the usefulness of the proposed scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.58-65
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• 2007

Behavioral sequences of the medaka (Oryzias latipes) were continuously investigated through an automatic image recognition system in response to medaka treated with the insecticide and medaka not treated with the insecticide, diazinon (0.1 mg/l) during a 1 hour period. The observation of behavior through the movement tracking program showed many patterns of the medaka. After much observation, behavioral patterns were divided into four basic patterns: active-smooth, active-shaking, inactive-smooth, and inactive-shaking. The "smooth" and "shaking" patterns were shown as normal movement behavior. However, the "shaking" pattern was more frequently observed than the "smooth" pattern in medaka specimens that were treated with insecticide. Each pattern was classified using classification methods after the feature choice. It provides a natural way to incorporate prior knowledge from human experts in fish behavior and contains the information in a logical expression tree. The main focus of this study was. to determine whether the decision tree could be useful for interpreting and classifying behavior patterns of the medaka.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.133-142
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• 2010

As the ubiquitous technology has penetrated into almost every aspect of modern life, the research of the security technology to solve the weakness of security in the ubiquitous environment is received much attention. Because, however, today's security systems are usually based on the fixed rules, many security systems can not handle diverse situations in the ubiquitous environment appropriately. Although many existing researches on context aware security service are based on ACL (Access Control List) or RBAC (Role Based Access Control), they have an overhead in the management of security policy and can not manipulate unexpected situations. Therefore, in this paper, we propose a context-aware security service providing multiple authentications and authorization from a security level which is decided dynamically in a context-aware environment using FCM (Fuzzy C-Means) clustering algorithm and Fuzzy Decision Tree. We show proposed model can solve typical conflict problems of RBAC system due to the fixed rules and improve overhead problem in the security policy management. We expect to apply the proposed model to the various applications using contextual information of the user such as healthcare system, rescue systems, and so on.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.19-22
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• 2019

상완동맥은 어깨에서부터 팔꿈치까지 내려오는 상완골의 내측부에 존재하며 혈압을 측정할 때 사용되는 혈관이다. 이 혈관은 골절로 인해 찢어지거나, 또는 혈액순환에 문제가 생겨 혈관이 막히는 경우가 발생한다. 이러한 경우 혈관의 상태를 확인하기 위하여 색조 도플러 초음파 검사를 사용하지만, 사용자에 따라 영상을 통한 판단 기준이 다르다는 문제점이 발생한다. 따라서 본 논문에서는 FCM과 Fuzzy Decision Tree를 이용한 영상 처리를 통해 일관성 있는 판단기준을 세우기 위한 혈류의 속도를 제안한다. 색조 도플러 초음파 영상에서의 상완 동맥을 추출하여 기울기를 이용한 FCM 알고리즘을 통해 소속도를 추출한 뒤 퍼지 룰에 적용하여 의사 결정 트리로 등급을 분류하고 결과적으로 혈류 속도를 추출한다. 색조 도플러 초음파 영상에서 환자의 개인 정보를 보호하기 위해 개인 정보 영역을 제거하여 ROI 영역을 추출하고 ROI 영역을 이진화를 통하여 상완동맥이 있는 영역을 추출한다. 이진화 된 ROI 영역에서 혈관 영상의 혈류 방향으로의 무게중심을 설정하고 각각의 픽셀과 무게중심 선과의 거리를 이용하여 소속도를 추출한 후 FCM을 사용하여 최적의 기울기를 선정한다. FCM을 통해 추출한 최종 소속도를 이용하여 퍼지 룰에 적용한 뒤 계산된 T-norm과 소속도의 분산을 이용하여 의사 결정 트리를 형성 트리의 단말 노드들은 각 픽셀을 분류한다. 분류되어진 데이터들의 노드별 소속도 평균을 구한 뒤 디퍼지화를 통해 COG(Center of Gravity)를 계산한다. 마지막으로 그 값을 이용하여 혈류 속도에 영향을 미치는 정도를 계산한 뒤 최종 혈류의 속도를 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.273-278
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• 2010

A few small and medium enterprise administer its organization systematically, but most of them is affected by ability and level of a CEO rather than organization system. In this viewpoint, it can be said the study on ability and level of CEO in small and medium enterprise are so meaningful. Thus, in this paper, the core competency of CEO is obtained from the CEO through questionnaire and it is suggested the evaluation model of the CEO core competency. Also patterns were analyzed by ID3 and fuzzy ID3 from data on expert appraise for CEO core competency and level. The 'if-then' fuzzy rules and decision tree created by results of pattern analysis showed their usefulness for evaluation of CEO core competency in small and medium enterprise.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.1-7
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• 2011

Most of expert systems use the text-oriented knowledge bases. However, knowledge management using the knowledge bases is considered as a huge burden to the knowledge workers because it includes some troublesome works. It includes chasing and/or checking activities on Consistency, Redundancy, Circulation, and Refinement of the knowledge. In those cases, we consider that they could reduce the burdens by using relational database management systems-based knowledge management infrastructure and convert the knowledge into one of easy forms human can understand. Furthermore they could concentrate on the knowledge itself with the support of the systems. To meet the expectations, in this study, we have tried to develop a general-purposed knowledge conversion tool for expert systems. Especially, this study is focused on the knowledge conversions among text-oriented knowledge base, relational database knowledge base, and decision tree.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.165-169
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• 2010

This study seeks to find the factors associated with social workers' turnover intention and show us how to manage turnovers by looking for some rules affecting turnover intentions. Our investigation surveying 331 social workers reveals that social workers' turnover intentions are affected by organizational commitment, job satisfaction, and burnout. Our pattern analyses using fuzzy ID3 show that the higher their commitment, the higher their job satisfaction stemming from promotion opportunities, rewards, and personal relations with peers and bosses. In addition, turnover intentions decreases (even if burnouts--the job-related stress--are very serious) when organizational commitment increases. We come to understand that organizational commitment could be a more important variable than job satisfaction and burnouts. Such results suggest that it would be necessary to consider how to improve social workers' organization-wide commitment rather than satisfaction and burnout related to jobs and environments.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.578-580
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• 1998

The paper presents an approach to the structure identification based on the CART (Classification And Regression Tree) algorithm and to the parameter identification by hybrid learning method in neuro-fuzzy system. By using the CART algorithm, the proposed method can roughly estimate the numbers of membership function and fuzzy rule using the centers of decision regions. Then the parameter identification is carried out by the hybrid learning scheme using BP (Back-propagation) and RLSE (Recursive Least Square Estimation) from the numerical data. Finally, we will show it's usefulness for fuzzy modeling to truck backer upper control.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.53-59
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• 2008

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.