• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.42-48
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• 2003

In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.125-136
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• 2007

The study on query relaxation which provides approximate answers has received attention. In recent years, some arguments have been made that semantic relationships are useful to present the relationships among data values and calculating the semantic distance between two data values can be used as a quantitative measure to express relative distance. The aim of this article is a hierarchical metricized knowledge abstraction (HiMKA) with an emphasis on combining data abstraction hierarchy and distance measure among data values. We propose the operations and the query relaxation algorithm appropriate to the HiMKA. With various experiments and comparison with other method, we show that the HiMKA is very useful for the quantified approximate query answering and our result is to offer a new methodological framework for query relaxation.

• Knowledge Management Research
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• v.10 no.2
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• pp.65-84
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• 2009

The purpose of this study is to develop Meta Evaluation Indicators for Defense R&D Programs in Korea. At first, the four components of this meta evaluation model were designed, which are evaluation context, evaluation input, evaluation process and evaluation outcome. And fifty two indicators for this meta evaluation were developed by experts who performed evaluations for Defense R&D Programs. The reliability of components and items was verified by Cronbach's ${\alpha}$ coefficient. It was over 0.6 in all areas. The validity of components and items was verified by Factor Analysis. Analytic Hierarchy Process method was used in assigning the evaluation weight. The survey of twenty two evaluators participated in Defense R&D Programs showed that the Consistency Ratio was under 0.1 in evaluation components and items. In this study, an objective and reasonable set of Defense R&D Meta Evaluation Indicators was developed to increase the responsibility of Defense R&D Programs and improve the quality of evaluation results.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.233-238
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• 2002

This paper propose the construction of fault diagnosis engine for diesel generator engine and rule inference method to induce rule for fuzzy inference from the monitored data of diesel engine. The proposed fault diagnosis system is constructed the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HME), It is Proposed the rule reduction method of knowledge base for concerning data among the various analog data.

• Education of Primary School Mathematics
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• v.2 no.1
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• pp.65-73
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• 1998

The purpose of this study is to investigate significant differences of structural knowledges among the groups(high, middle, low) when the 6th grade subjects structured the concepts of the plane figures, triangle and quadrangle, by concept maps, and to analyse the features of concept maps according to hierarchy. For this purpose, the following two research contents were investigated： 1. Investigating significant differences of structural knowledge in the concepts of the plane figures using concept maps among the groups(high, middle, low). 2. Analysing the features of concept maps according to hierarchy. The structural knowledges represented on the concept maps of triangle and quadrangle which were drawn by the subjects were analysed by propositions, hierarchies, and cross-links. Subject-self Reports about how to make the concept maps were used to analyse the features of concept maps according to hierarchy. The conclusions drawn from the results were as fellows： First, there were significant differences among the groups in proposition links. Second, there wasn't my significant difference among the groups in hierarchy. Third, there were significant differences among the groups in cross-links, and Fourth, the results of analysing the concept maps by hierarchy showed that there were differences among the individuals in constructing the knowledges.

• Journal of The Korean Association For Science Education
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• v.35 no.5
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• pp.857-870
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• 2015

Concerning elementary school science subject electric circuit units, which are regarded as difficult by teachers and students, this study aims to use the knowledge state analysis method along with interviews to analyze the knowledge state and hierarchy of inquiry abilities. Before and after applying the electric circuit inquiry abilities module, the question items aimed at assessing the basic inquiry abilities and integrative inquiry abilities for electric circuits were presented to students, and their knowledge state was analyzed along with interviews. Through analysis of the knowledge structure and hierarchy of inquiry abilities about electric circuits, the way of thinking of teachers who taught inquiry abilities, and the way of thinking of students were found to be visually different from each other, and this is an important factor that should not be neglected in the process of teaching and learning about inquiry abilities and should be considered. In addition, the presentation of the knowledge state of and hierarchical relations between inquiry abilities factors can offer implications for guidance on students' learning about inquiry abilities.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.137-148
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• 2009

Knowledge management becomes the key point for organizations to survive and maintain competitive advantages in the knowledge economy era. E-learning plays a vital role for the organizational learning. How to share the experience of knowledge and the success of the knowledge management has great connection with the organizational culture. This study focuses on the factors of effective E-learning as well as its relation to the organizational culture. A successful e-learning system should not only aim at different statistical variables but emphasize on : course contents, variety of teaching methods and establishes a stable network environment. A stable E-learning platform and speedy bandwidth is a must to achieve the non-barrier communication and built an interactive learning environment. To achieve success in E-learning, it is not necessary to divide the organizational culture to strengthen the course content multiplication and plans the E-learning supervisory work by the sole responsibility unit. It should establish an ample teaching frequency width and platform and also must establish the appropriate study network frequency width and hardware equipment to achieve the best E-learning effect. The interaction in different organizational culture in adapting E-learning, those Ad-hoc and Marketing Culture, are mostly influence by the external environment and have more interactive content. Those in Clan and Hierarchy Culture are affected by traditional conception and lack of interaction. Meanwhile, under the cost consideration, Clan and Ad-hoc Culture on the dynamic side prefer to spend more cost on E-Learning while the stable side, Hierarchy and Marketing culture are willing to pay more expenses on E-Learning.

• Journal of Platform Technology
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• v.12 no.3
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• pp.3-15
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• 2024

Knowledge mining is a research field that applies various techniques such as data modeling, information extraction, analysis, visualization, and result interpretation to find valuable knowledge from diverse large datasets. It plays a crucial role in transforming raw data into useful knowledge across various domains like business, healthcare, and scientific research etc. In this paper, we propose analytical techniques for performing knowledge discovery and data mining from various data by extending the Formal Concept Analysis method. It defines algorithms for representing diverse formats and structures of the data to be analyzed, including models such as many-valued data table data and triadic data table, as well as algorithms for data processing (dyadic scaling and flattening) and the construction of concept hierarchies and the extraction of association rules. The usefulness of the proposed technique is empirically demonstrated by conducting experiments applying the proposed method to public open data.

• Korean Journal of Child Studies
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• v.33 no.5
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• pp.19-35
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• 2012

The purposes of this study were to investigate how children's categorization differs in object categorical hierarchy and to examine whether these aspects were different according to the children's age of 18 months, 24 months, 30 months. The participants consisted of 120 young children aged 18 months, 24 months, and 30 months from 31 child-care centers located in middle-income regions of Seoul and Kyonggi Province. The major findings were as follows : First, all the children from all three age groups could consistently differentiate the superordinates; however, they could not consistently differentiate basic categories. Second, 24 month appears to be a critical change period in category development. Third, as the children become older, they are able to acquire more knowledge regarding categories. These results suggested that the advent of ordering, in terms of basic categories as well as superordinates which occurred around the age of 24 month, was confirmed in category development.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.354-360
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• 2006

The purpose of this paper is to propose a securely personalized context-aware cooperative query that supports a multi-level data abstraction hierarchy and conceptual distance metric among data values, while considering privacy concerns around user context awareness. The conceptual distance expresses a semantic similarity among data values with a quantitative measure, and thus the conceptual distance enables query results to be ranked. To show the feasibility of the methodology proposed in this paper we have implemented a prototype system in the area of site search in a large-scale shopping mall.