• 한국초등과학교육학회지:초등과학교육
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• 제25권2호
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• pp.167-178
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• 2006

The purpose of this study was to explore characteristics of sixth grade students' opistemological beliefs in science and the relationship to learner's characteristics: learning motivation, learning strategies, and logical thinking. The subjects were 265 sixth graders and data was collected through two types of questionnaires, translated and modified by researchers: opistemological beliefs regarding science, learning motivation & strategies. The results of this study were as follows. The students believed that the goals of science were related to activations such as 'Science is experiment', or 'Science is invention: These beliefs were connected with the emphasis of science classes or the focus of the science curriculum. However, the students' beliefs related to the changeability of science knowledge, the source of science knowledge, and the role of experiments in developing knowledge were oriented to modern opistemological views. Moreover, the beliefs were meaningfully related to students' characteristics: learning motivation, learning strategies, and logical thinking. Among the students' characteristics, logical thinking was especially related to all of the factors of students' beliefs: the changeability of science knowledge, the source of science knowledge, and the role of experiments in developing knowledge. However, the students who believed that scientific knowledge came from scientists, science teachers, or science textbooks had high levels of self-efficacy. Therefore, the belief that scientific knowledge is formed by self-discovery, in order to generate high self-efficacy, needs to be encouraged. From the results, it is possible to check the orientation of current science education based on the students' opistemological beliefs. In addition, the resources can be accumulated for persevering in our efforts to achieve a positive orientation for science education.

• Journal of Information Science Theory and Practice
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• 제6권3호
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• pp.6-15
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• 2018

With the increasing demand for intelligent services, knowledge graph technologies have attracted much attention. Various application-specific knowledge bases have been developed in industry and academia. In particular, open knowledge bases play an important role for constructing a new knowledge base by serving as a reference data source. However, identifying the same entities among heterogeneous knowledge sources is not trivial. This study focuses on extracting and determining exact and precise entities, which is essential for merging and fusing various knowledge sources. To achieve this, several algorithms for extracting the same entities are proposed and then their performance is evaluated using real-world knowledge sources.

• 한국지구과학회지
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• 제27권7호
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• pp.705-714
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• 2006

The purpose of this study was to explore the elementary students' perceptions of Earth systems and environmental issues. A survey was conducted to determine the students' perceptions on the following aveas: (1) the concepts of certainty and tangibility, (2) self-reported knowledge level, (3) perceived danger level of selected eight Earth systems and environmental issues, and (4) their primary information source on these issues. Results indicated that ozone hole, acid rain, El $Ni\widetilde{n}o$, and global warming were identified by the students as uncertain and intangible issues. Perceived certainty and perceived tangibility were highly positively correlated with self-reported knowledge compared to other relationships. The results also showed that learning from school was the most frequent information source for environmental issues. The second most frequently used source of information was television among several mass media sources. It is hoped that this study contributes to understanding the elementary school students' perceptions toward the selected Earth systems and environmental issues.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes the hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.387-394
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• 1995

With respect to the effectiveness of types of knowledge on human diagnostic performance, the results of several experiments claimed that training with diagnostic rules (procedural knowledge) is more effective than training that provides theoretical knowledge (principle knowledge). However, we usually have the idea that understanding the principles of system dynamics is necessary for diagnosis in some situations. In this study, we pointed out some problems in the previous experiments that force to reinterpret their experimental conclusions. Accordingly, we conducted an experiment to reinvestigate the value of theoretical knowledge in two problem situations. A simulator system, which is named DLD, that is to diagnose an electronic device was created for this purpose. It is a context-free digital logic circuit which includes forty-one gates of three basic types. Our experiment investigated the marginal effects of theoretical knowledge over common diagnostic rules. The experimental results showed that the effectiveness of the instruction in theoretical knowledge is dependent on the complexity of diagnostic situations. This adds up an experimental evidence against the presumed ineffectiveness of theoretical knowledge and forward reasoning in fault diagnosis. Furthermore, the result suggests the source of the use of theoretical knowledge.

• 한국경영과학회지
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• 제20권1호
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• pp.159-177
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• 1995

The objective of this paper is to propose a knowledge-based fuzzy post adjustment so that unstructured problems can be solved more realistically by expert systems. Major part of this mechanism forcuses on fuzzily assessing the influence of various external factors and accordingly improving the solutions of unstructured problem being concerned. For this purpose, three kinds of knowledge are used : user knowledge, expert knowledge, and machine knowledge. User knowledge is required for evaluating the external factors as well as operating the expert systems. Machine knowledge is automatically derived from historical instances of a target problem domain by using machine learning techniques, and used as a major knowledge source for inference. Expert knowledge is incorporate dinto fuzzy membership functions for external factors which seem to significantly affect the target problems. We applied this mechanism to a prototyoe expert system whose major objective is to provide expert guidance for stock market timing such as sell, buty, or wait. Experiments showed that our proposed mechanism can improve the solution quality of expert systems operating in turbulent decision-making environments.

• 한국초등과학교육학회지:초등과학교육
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• 제34권4호
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• pp.434-446
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• 2015

The purpose of this study was to investigate elementary school students' conceptions about the knowledge source and the mechanism about the greenhouse effect, and the relationship between the greenhouse effect and the global warming. Participants were 157 sixth graders (boy : n=79, girl : n=78) from six elementary schools located in the same city. The open-ended questionnaire was used to examine the students' spontaneous ideas depicted by their drawings and/or writings. The results of this study are as follows: First, although there is no the content on the greenhouse effect in the elementary school curriculum document, the children in this study indicated that the main source of their knowledge about the greenhouse effect came from 'school class' (31.8%); Second, although the children did not take a class about the greenhouse effect itself, 14.0% of children had a relatively high level of the mental model on the phenomenon; Third, more than 90% of the children did not have the correct understanding about the relation between the greenhouse effect and the global warming.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.221-232
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• 2021

In recent years, with the existence of huge amounts of data stored in huge databases, the need for developing accurate tools for analyzing data and extracting information and knowledge from the huge and multi-source databases have been increased. Hence, new and modern techniques have emerged that will contribute to the development of all other sciences. Knowledge discovery techniques are among these technologies, one popular technique of knowledge discovery techniques is data mining which aims to knowledge discovery from huge amounts of data. Such modern technologies of knowledge discovery will contribute to the development of all other fields. Data mining is important, interesting technique, and has many different and varied algorithms; Therefore, this paper aims to present overview of data mining, and clarify the most important of those algorithms and their uses.

• Journal of Forest and Environmental Science
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• 제27권1호
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• pp.23-31
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• 2011

Ever since the dawn of civilization, the ambient vegetation and the resources constituted major source of human existence for various substantial requirements. Our present knowledge on plant resources emerged from the traditional heritable knowledge descended from generation to generation. However, traditional knowledge pertaining to several aspects remained untapped from various remote localities or populations. Furthermore, with the present trends of excessive exploitation of natural resources and degradation of habitats, conservation and ecological management require coherence of traditional skills and modern approaches. Therefore, the present study is to record traditional plant based knowledge among the inhabitants of Siwalik region of Uttarakhand Himalaya. Extensive field survey was made for the collection of data on the medicinal aspects of plant species in the study area covering the parts of districts Pauri, Dehradun and Haridwar. During the course of study 130 plant species belonging to 65 families are reported, used as traditional medicine by the local inhabitants of this region.