• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.1249-1250
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• 2012

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.81-86
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• 2002

In current CBR(Case-Based Reasoning) systems, the case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck similar to those found in traditional expert system design. In this thesis, 1 present a model for learning method of case adaptation knowledge using case base. The feature difference of each pair of cases are noted and become the antecedent part of an adaptation rule, the differences between the solutions in the compared cases become the consequent part of the rule. However, the number of rules that can possibly be discovered using a learning algorithm is enormous. The first method for finding cases to compare uses a syntactic measure of the distance between cases. The threshold fur identification of candidates for comparison is fixed th the maximum number of differences between the target and retrived case from all retrievals. The second method is to use similarity metric since the threshold method may not be an accurate measure. I suggest the elimination method of duplicate rules. In the elimination process, a confidence value is assigned to each rule based on its frequency. The learned adaptation rules is applied in riven target Problem. The basic. process involves search for all rules that handle at least one difference followed by a combination process in which complete solutions are built.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.9
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• pp.414-421
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• 2001

If a machine has some faults, we can detect them using vibration or noise signals. However some maintenance engineers who don\`t have export knowledge, need the help of vibration experts for diagnosing the machine. In this paper a case based reasoning (CBR) system is developed which is able to manipulate the past experiences of vibration diagnosis experts. In the CBR system, the maintenance engineers can retrieve the information form previous cases which are most similar to new problem s that they can solve new problem using solutions form the previous cases. In this paper, a new case retrieval method of CBR system using Petri net is proposed and also applied to diagnosis for electric motors as a practical problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.561-564
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• 2009

In this paper, we present an environment configuration of UML CASE tool for internet based collaboration work. We define a method of model sharing in distributed location and construct shared repository. Also we design for model history among work processes and to give responsibility using user authentication. Its result will contribute development of CASE tool supporting collaboration work.

• Journal of The Korean Association For Science Education
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• v.14 no.2
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• pp.123-132
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• 1994

The experimental evidence evaluation of the 11th grade students(N:91) was investigated. Specially, the influence of students' ideas about optical phenomena and presented evidence types on their evidence evaluation, and the influence of students' ideas on their causal inference modes were investigated. After eliciting the students' ideas about shadow phenomena and conformity of their idea, the experimental results with a binary outcome were presented as the evidence. Then the students were asked to evaluate the evidence. Again students' ideas were elicited. Most of students had causal ideas such that the shape of object(96%) and the inclination of screen(75%) were causes of shadow shape, not the shape(70%) and color(92%) of light source. In the case of the shape of object and the color of light source, most students(70%) believed strongly their ideas. Most responses(80%) in the evidence were evidence-based, and 12% of them were theory-based. There was no significant difference of reponses types between students with causal ideas(81%) and students with non-causal ideas(78%), between covariable and non-covariable evidence. But in the case of non-causal ideas, covariable evidence was more likely to yield evidence-based reponses than non-covariable evidence. If students had preconcepts inconsistent(84%) with the evidence, they were more likely to make evidence-based responses than the students with consistent ideas (75%) with the evidence. Especially in the case perceptually biased evidence, this tendency was marked. In the case of covariable evidence, many students made inclusion inferences(40%) rather than uncertainty inferences(32%). In the case of uncertainty inferences(94%), students more likely to make evidence-based reponses than inclusion inferences(83%) and exclusion infernces(88%). In the case of inclusion inferences and exclusion infernces, students tended to make idea-based responses and distort the evidences. In conclusion, when the students evaluate the experimental evidences, their ideas influence the causal inference modes. Especially, according to the conformity of the preconcepts and logical relation of evidences, the inference modes are more strongly depended upon the preconcepts rather than evidences.

• Archives of Plastic Surgery
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• v.36 no.6
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• pp.720-726
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• 2009

Purpose: Fasciocutaneous flap with random pattern flap has limitation in mobility and length - width ratio. This characteristic is more pronounced in lower extremity which has relatively poor vascularity. Perforator based flap in lower extremity reconstruction has various advantages as a axial flap, allowing abundant blood supply and widening of mobility range. So if it is not a case of wide defect, free flap can be replaced by perforator based flap. Methods: From April 2007 to March 2009, 18 cases of perforator flap were performed. 8 had defect in upper 1/3 of calf, 6 in middle 1/3, and 4 in lower 1/3. In 10 cases island flap were used, 3 case had transposition flap, 2 cases used advancement flap, 2 case had propeller flap and 1 case had rotation flap. Results: 17 cases survived without flap necrosis. Partial flap necrosis occurred in 1 case, so secondary split thickness skin graft was done. Chronic wound with pseudomonas infection occurred in 1 case, but it was completely cured with conservative treatment. Conclusion: Perforator based flap is useful in lower extremity reconstruction because of relative freedom in changing the size and thickness of the flap depending on the recipient site, good mobility, and abundant vascularity. And donor site morbidity can be minimized. Lower extremity reconstruction using perforator based flap is a good method because it can minimize the complication and obtain effective result.

• Research in Community and Public Health Nursing
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• v.13 no.3
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• pp.444-455
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• 2002

Purpose: This study was performed to develop the case management program that can provide the qualitative health care service to satisfy the increasing needs for health care elderly and prevent the increase in medical cost cased by prolonged and repetitive hospitalization. Method: The survey was completed as follows. First, 290 elderly patients who would be soon discharged in 4 hospitals are participated in the survey on needs of nursing care and case management programs. Second, 70 professionals working at 5 hospitals including doctors, nurses, social workers and so on are participated in the survey on the case management team operation. Result: Level of needs to Nursing care and case management programs showed so high. Professionals suggested on the case management team operation. Finally, based on the survey and literature review, the case management program was developed. Conclusion: In this study, the specific models for the five case management services were suggested. It is thought that the service provision by the case management team based on the multi-disciplinary case management program model suggested in this study would be suggested as a constituent of the effective health care delivery system for the hospitalized elderly patients.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.77-92
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• 2004

When humans make decisions, they differentiate classifications of individual attribute variables that affect the decisions according to the importance and pattern of each attribute variables. The present study examines the practicality of the proposed Code Arrangement-Based Reasoning(CABR), which resembles the human's way of reasoning. To this end, we developed a CABR technique that classifies each attribute variable affecting significant impacts on the target variable into a cluster and assigns a code to the cluster. For verifying the proposed technique, both case-based reasoning and CABR were used for the customer continuance judgment problem of an automobile insurance company. Results indicated that the performance of CABR is close to the one of the case-based reasoning. The CABR also shows the possibility of using bio-informatics techniques for organizational data analysis in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.27-44
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• 2008

Owl-based ontology is useful to realize the context-aware services which are composed of the distributed and self-configuring modules. Many ontology-based inference engines are developed to infer useful information from ontology. Since these engines show the uniqueness in terms of speed and information richness, it's difficult to ensure stable operation in providing dynamic context-aware services, especially when they should deal with the complex and big-size ontology. To provide a best inference service, the purpose of this paper is to propose a novel methodology of context-aware engine selection in a contextually prompt manner Case-based reasoning is applied to identify the causality between context and inference engined to be selected. Finally, a series of experiments is performed with a novel evaluation methodology to what extent the methodology works better than competitive methods on an actual context-aware service.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.