• Journal of Information Science Theory and Practice
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• v.2 no.3
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• pp.29-39
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• 2014

In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.117-120
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• 2005

퍼지 규칙 기반 시스템에서 분류 및 경계를 결정하기 위한 방법으로 퍼지 규칙을 학습하는 다양한 방법들이 제안되고 있다. 그리고 추론 규칙간의 상관성을 고려하여 불필요한 속성을 제거함으로써 좀 더 효율적인 추론 결과를 얻을 수 있다. 따라서 본 논문에서는 퍼지 규칙 기반 시스템에서 각 규칙에 따른 결정 테이블를 작성하고 러프집합을 이용하여 불필요한 속성을 제거하였으며 규칙의 확신도에 퍼지 네이브 베이스 이론을 적용한 추론 방법을 제안한다.

• Journal of Korean Elementary Science Education
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• v.32 no.2
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• pp.139-158
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• 2013

This study investigated elementary students' (grade 4~6) learning progressions for water cycling drawn from iterative assessments using ordered multiple-choice (OMC) items. An assessment system, which consisted of construct map, item design, outcome space, and measurement model, was employed in this study to examine children's learning progressions. At the first stage of the assessment system, a construct map was designed on which children's conceptual understandings from naive to most sophisticated were represented. At the item design stage, 8 OMC items were drawn from the construct map. Each item option of the OMC items was scored from 0 to 3 according to its level of understanding at the stage of outcome space. As a measurement model, Rasch model, a branch of item response theory, was applied to interpreting the outcomes of the OMC items. This cycle of assessment system was furtherly implemented iteratively in order to elaborate on the first version of water cycling learning progression. In conclusion, children's understanding of water cycling could be described in two aspects: water distribution and water movement. We identified children's conjectural developmental pathways about water cycling existed from superficial and naive accounts to more complex and abstract accounts.

• Journal of Astronomy and Space Sciences
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• v.22 no.3
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• pp.311-328
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• 2005

This study was to understand the components that influence preservice elementary teachers' mental models about 'astronomical phenomena' such as the Seasons of the year, and the Lunar Phases of the month. We selected university of education students among whom 23 were in the second you. The data collected from the paper-pencil test and individual interview with students. The results of this study show that the students had apparent synthetic Mental models, and that the distance theory, and occultation theory had most important effects on their Mental Models. It can be said that preservice elementary teachers' initial mental models of the' astronomical phenomenon' have their origin in their belief sets (specific theory) related to 'astronomical phenomenon', on the basis of which they can interpret their observations and cultural information with the constraints of a naive framework of physics. The structures and possible sources of their mental models for overcoming these synthetic mental models were also discussed.

• Journal of The Korean Association For Science Education
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• v.26 no.1
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• pp.68-87
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• 2006

The aim of this study was to understand the components that influence the mental models of preservice elementary teachers on the astronomical phenomena of seasons of the year and lunar phases of the month. For this, participants were selected from a university of education. Data was collected from a paper-pencil test and individual interviews with the participants. The results of this study showed that the preservice teachers had apparent synthetic mental models, and that the 'Distance Theory' and 'Occlusion Theory' had the greatest effect on their mental models. Furthermore, it was found that preservice elementary teachers' initial mental models of 'astronomical phenomenon' had their origin in personal belief sets (specific theory) related to 'astronomical phenomenon'. It was on these belief sets that they interpreted their observations and cultural information with the constraints of a naive framework of physics. The structures and possible sources for overcoming these synthetic mental models were also discussed in this paper. Lastly, implications for preservice elementary teacher education were presented.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.485-490
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• 2004

In data representation, the clustering performs a grouping process which combines given data into some similar clusters. The various similarity measures have been used in many researches. But, the validity of clustering results is subjective and ambiguous, because of difficulty and shortage about objective criterion of clustering. The fuzzy clustering provides a good method for subjective clustering problems. It performs clustering through the similarity matrix which has fuzzy membership value for assigning each object. In this paper, for objective fuzzy clustering, the clustering algorithm which joins principal components analysis as a dimension reduction model with bayesian learning as a statistical learning theory. For performance evaluation of proposed algorithm, Iris and Glass identification data from UCI Machine Learning repository are used. The experimental results shows a happy outcome of proposed model.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.372-377
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• 2008

Multiclass cancer classification has been actively investigated based on gene expression profiles, where it determines the type of cancer by analyzing the large amount of gene expression data collected by the DNA microarray technology. Since gene expression data include many genes not related to a target cancer, it is required to select informative genes in order to obtain highly accurate classification. Conventional rank-based gene selection methods often use ideal marker genes basically devised for binary classification, so it is difficult to directly apply them to multiclass classification. In this paper, we propose a novel method for multiclass gene selection, which does not use ideal marker genes but directly analyzes the distribution of gene expression. It measures the class-discriminability by discretizing gene expression levels into several regions and analyzing the frequency of training samples for each region, and then classifies samples by using the naive Bayes classifier. We have demonstrated the usefulness of the proposed method for various representative benchmark datasets of multiclass cancer classification.

• Journal of Astronomy and Space Sciences
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• v.22 no.1
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• pp.69-88
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• 2005

This study was to understand the components that influence preservice secondary teachers' conceptions about 'seasonal changes' We selected 74 university science education students among whom 23 were in the second, 23 in the third, and 28 in the fourth year. The data collected from the paper-pencil test and individual interview with students. The results of this study show that the students had considerable apparent alternative conceptions, and that the 'distance theory' had most important effects on their alternative conceptions. It can be said that preservice secondary teachers' initial models of the seasonal change have their origin in their belief sets (specific theory) related to 'seasonal change', on the basis of which they can interpret their observations and cultural information with the constraints of a naive frame-work of physics. The structures and possible sources of their alternative conceptions for overcoming these alternative conceptions were also discussed. Implications for preservice science teacher education related to the results were discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.888-894
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• 2010

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase and more efficient and accurate methods have been studied. This paper proposes a bayesian algorithm for wireless fingerprinting and indoor location determination using fuzzy clustering with bayesian learning as a statistical learning theory.

• Communications of the Korean Mathematical Society
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• v.34 no.3
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• pp.855-861
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• 2019

The geodesics on the round 2-sphere $S^2$ are all simple closed curves of equal length. In 1903 Otto Zoll introduced other Riemannian surfaces with the same property. After that, his name is attached to the Riemannian manifolds whose geodesics are all simple closed curves of the same length. The question that "whether or not the set of Zoll metrics on 2-sphere $S^2$ is connected?" is still an outstanding open problem in the theory of Zoll manifolds. In the present paper, continuing the work of D. Jane for the case of the Ricci flow, we show that a naive application of some famous geometric flows does not work to answer this problem. In fact, we identify an attribute of Zoll manifolds and prove that along the geometric flows this quantity no longer reflects a Zoll metric. At the end, we will establish an alternative proof of this fact.