• Journal of information and communication convergence engineering
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• v.3 no.4
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• pp.209-212
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• 2005

This study proposes hybrid case-based reasoning and genetic algorithms model for customer classification. In this study, vertical and horizontal dimensions of the research data are reduced through integrated feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed model may improve the classification accuracy and outperform various optimization models of typical CBR system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.988-991
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• 1996

The purpose of this thesis is to develop methods of designing robust LQR/LQG controllers for time-varying systems with real parametric uncertainties. Controller design that meet desired performance and robust specifications is one of the most important unsolved problems in control engineering. We propose a new framework to solve these problems using Linear Matrix Inequalities (LMls) which have gained much attention in recent years, for their computational tractability and usefulness in control engineering. In Robust LQR case, the formulation of LMI based problem is straightforward and we can say that the obtained solution is the global optimum because the transformed problem is convex. In Robust LQG case, the formulation is difficult because the objective function and constraint are all nonlinear, therefore these are not treatable directly by LMI. We propose a sequential solving method which consist of a block-diagonal approach and a full-block approach. Block-diagonal approach gives a conservative solution and it is used as a initial guess for a full-block approach. In full-block approach two LMIs are solved sequentially in iterative manner. Because this algorithm must be solved iteratively, the obtained solution may not be globally optimal.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.71-84
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• 2006

Case-based reasoning (CBR) is a reasoning technique that reuses past cases to find a solution to the new problem. It often shows significant promise for improving effectiveness of complex and unstructured decision making. It has been applied to various problem-solving areas including manufacturing, finance and marketing for the reason. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still a challenging issue. Most of the previous studies on CBR have focused on the similarity function or optimization of case features and their weights. According to some of the prior research, however, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. In spite of the fact, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the novel approach to Korean stock market. Experimental results show that the GA-optimized k-NN approach outperforms other AI techniques for stock market prediction.

• Journal of Families and Better Life
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• v.24 no.1 s.79
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• pp.237-251
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• 2006

The present study was to investigate the teacher's and the mother's beliefs about literacy acquisition and to analyse differences between them The subjects for this study were 134 teachers and 174 mothers of the kindergarten and daycare centers. The 25-item questionnaire constructed by Westwood, Knight and Redden(1997) was used in this study with a slight modification. Collected data were analyzed by one-way ANOVA to verify the differences of the teacher's beliefs according to an academic background and a career, and mother's according to an academic background and an occupation, and compared by t-test to verify the differences of the teacher's and mother's beliefs. The major findings were the most teachers and mothers showed balanced approach: more skill-based about reading than writing. The university graduated teachers took more meaning-based, child-centered approach than finisher of caregiver training center. According to career, more the experienced kept more skilled-based approach. In case of the mother, the university and graduated school graduates took more meaning-based, child-centered approach than finisher of college and High school. According to occupation, more the professional kept more meaning-based approach. Finally there were no meaningful difference in an income and mothers' age. And teachers took more meaning-based, child-centered approach than mothers. Especially about writing, teachers kept much more meaning-based approach than mothers.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.93-100
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• 2016

This paper shows what kind of influence the learning motivation factors have on the effectiveness of Flipped Learning Model through the case of operating a JAVA programming subject. The Flipped Learning Approach consisting of Before Class, Before or At Start of Class, and In Class provides the students with learning motivation as well as satisfies Keller's ARCS(Attention, Relevance, Confidence, Satisfaction) to keep them studying steadily. This research conducts the operation of Flipped Learning and gets Exploratory Factor Analysis and Reliability Analysis from the result of the course experience questionnaire at the end of the class. Given this survey result, Flipped Learning approach improves the learners' satisfaction in class and the effectiveness in the fields of understanding learning context more than does the previous lecture-based learning approach by pacing learning procedure and conducting self-directed learning.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.91-109
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• 2004

This study investigates the effectiveness of a hybrid approach using fuzzy sets that describe approximate phenomena of the real world. Compared to the other existing techniques, the approach handles inexact knowledge in common linguistic terms as human reasoning does it. Integration of fuzzy sets with case-based reasoning (CBR) is important in that it helps to develop a successful system far dealing with vague and incomplete knowledge which statistically uses membership value of fuzzy sets in CBR. The preliminary results show that the accuracy of the integrated fuzzy-CBR approach proposed for this study is higher that of conventional techniques. Our proposed approach is applied to corporate bond rating of Korean companies.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.255-262
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• 2014

Our previous research[1] suggested object extraction and modeling method based on Fillmore's case grammar. This approach had not considered of use case extraction and method. To solve this problem, we adopt Fillmore's semantic method as linguistic approach into requirement engineering, which refine fillmore's case grammar for extracting and modeling use cases from customer requirements. This Refined mechanism includes the definition of a structured procedure and the representation of visual notations for 'case' modeling. This paper also proposes the use case decision matrix to identify use case size from extracted use cases based on goal oriented requirement engineering(GoRE), which related with the complexity of use case, and also prioritizes the use cases with this matrix. It demonstrates our proposal with the bank ATM system.

• Journal of the Korean Society of Physical Medicine
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• v.4 no.3
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• pp.193-200
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• 2009

Purpose：In this study is to verify the effects postural control training based on Bobath approach for body schema and visual perception on Middle Cerebral Artery(MCA) Infarcts. Methods：The subject was a 46 years old man with MCA infaction, lives in B city. An AB design for a single-subject research was used for this study. The procedures consisted of 1 time of baseline phase(A), 20 times of treatment phase(B). We applied the Bobath approach at the subject. Treatments included to facilitate trunk alignment and stability, and to train weight bearing and shifting, to facilitate pelvis movement, and to train walk especially stance phase and assist up-down stairs locomotion in environment similar to actual daily life. Results：With this treatment, the majority of body schema and visual perception and postural control was improved in treatment phase compared with in baseline phase. Therefore, this study supported the effectiveness of postural control training based on Bobath approach for body sechma and visual perception of hemiplegia. Conculusion：This study is integrated postural control training with Bobath approach that are widespread for hemiplegia and measured outcomes based on individualized therapy goals. Consequently the study is suggested the meaning of quality effectiveness of Bobath approach.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1015-1018
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• 2013

최근 임베디드 펌웨어를 객체 지향 어플리케이션과 함께 개발하는 경우가 증가하고 있다. 하지만 기존의 펌웨어는 절차적 설계를 기반으로 하기 때문에 어플리케이션과 다른 설계 기법이 필요하여 개발 비용과 테스트 비용이 증가한다. 그렇지만 아두이노를 사용하면 펌웨어를 객체 지향 설계가 가능하다. 본 논문은 객체지향 적용 펌웨어를 설계에 초점을 두고, Gary E.Mogyorodi의 Test Case 생성 방법을 적용하여, 실제 펌웨어를 시험을 하고자 한다. 이 방법이 가능하면 일반적인 펌웨어와 어플리케이션을 같은 방법으로 설계 및 테스트가 가능하다. 적용사례로써, 한백전자 HBE-SmartCAR의 펌웨어를 아두이노 기반으로 설계 및 추출된 Test Case 실행을 통해, 설계와 구현이 동일함을 검증이 가능하다.