• 한국초등과학교육학회지:초등과학교육
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• 제26권4호
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• pp.407-417
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• 2007

The purpose of this research is to develop standards with which we can design an instrument to assess classifying inquiry skills by observing students' behavior and reported outcome which is not the paper and pencil test. This research is focused on developing a standard for analysis of classifying ability among research functions. To identify classifying inquiry skills, standards from classifying behaviors were comparing ways with other cards and using information included in the cards; Standards selected from the final reports were the appropriateness, inconsistency and hierarchy of the classification outcome. The standards were initially selected during the class with picture cards printed various birds appearances on the front side and their traits on the back which was specially designed among sixth graders. The picture cards prepared with plant leaves and stems had designed to identify whether standards was effective to assess student's classifying ability. The standards was an effective tool to assess student's classifying inquiry skills.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1085-1090
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• 2006

In general, the coarse classifying procedure splits the values of a continuous characteristic into bands and the values of a discrete characteristic into groups of values. Coarse classifying improves the robustness of the credit scoring system but it is complicate and troublesome procedure. Thus, in this paper, we develop a software for coarse classifying by using Visual Basic Language. By using the developed software, we can find the best split easily. Also, this software will help learners to study credit scoring.

• 한국초등과학교육학회지:초등과학교육
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• 제27권3호
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• pp.287-295
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• 2008

Elementary students' behaviors classifying leaves have been analyzed according to the material types provided for the classification class. 199 sixth grade students were participated in the task classifying the leaves of various plants for the research. The three types of materials provided to them for the class were real leaves, photos of the leaves and explanation cards including the photos of leaves. One of the research findings was that the only material made students handle in the observed behaviors was the real leave of the material types given as classifying. Three were differences between groups in the time required and the number of using criteria for the class. The numbers of criteria had been applied to analyzing their behaviors as classifying the real leaves which were less than those with photo materials. The amount of taken time to classify the real leaves and photo materials were less than those of another material. Finally, the contents of criteria did not differ between groups except appearing properties presented to the task with photo and explanation materials. It is expected that the research can be contributed for elementary school teachers and for curriculum developers to choose appropriate instructional materials as constructing curriculum contents for elementary science to make elementary school students acquire classifying skill in science classes.

• 대한수학회논문집
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• 제32권3호
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• pp.745-763
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• 2017

The Borel-Serre partial compactification gives cofinite models for the proper classifying space for arithmetic lattices. Non-arithmetic lattices arise only in semisimple Lie groups of ${\mathbb{R}}$-rank one. The author generalizes the Borel-Serre partial compactification to construct cofinite models for the proper classifying space for lattices in semisimple Lie groups of ${\mathbb{R}}$-rank one by using the reduction theory of Garland and Raghunathan.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.838-841
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• 2005

DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

• Journal of the Korean Data and Information Science Society
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• 제21권6호
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• pp.1225-1235
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• 2010

개인신용평점에서 항목그룹화의 과정은 연속형 특성변수를 밴드로 분할하고 이산형 특성변수는 그룹으로 분할하는 것이다. 또한 평점표는 시간이 지나감에 따라 성능이 떨어지게 되고, 따라서 사용되고 있는 승인점을 조정하여야 한다. 그러나 개인신용평점에서 항목그룹화와 승인점의 조정은 매우 복잡하고 번거로운 과정이라고 할 수 있다. 따라서 본 논문에서는 비주얼베이직을 사용하여 개인신용평점에서 항목그룹화와 모형평가를 위한 소프트웨어를 개발하였다. 개발된 소프트웨어를 활용하면 항목그룹화에서 최적의 분할과 모형평가에서 최적의 승인점을 쉽게 찾을 수 있다.

• 한국의류산업학회지
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• 제9권5호
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• pp.516-527
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• 2007

This study was designed to make a proposal of a classifying model of Korean fashion brands as the first step in a long-term research plan developing a globalization roadmap for Korean fashion industry. On the basis of ownership advantages of a brand which included firm level attributes and brand level characteristics, fashion brands were classified into eight types. The proposed model was expected to provide an efficient and meaningful framework in developing global strategies both for academic and practical purposes. The model proposed four major categories of fashion brands including manufacturer brands, designer brands, retailer brands, and non-brands. Manufacturer brands were further classified into three groups of conglomerate fashion brands, fashion brands, and sports-specialized brands. Non-brands included small/very small-sized manufacturer non-brands, small/very small-sized non-brands, and OEM/ODM exporters. The classifying dimensions, brand type characteristics, and the globalization approach were discussed. Methods to test the reliability and validity of classifying were also discussed in the text.

• Geomechanics and Engineering
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• 제31권4호
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• pp.353-364
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• 2022

This study presents a hybrid algorithm for classifying the rock joints, where the improved artificial bee colony (IABC) and the fuzzy C-means (FCM) clustering algorithms are incorporated to take advantage of the artificial bee colony (ABC) algorithm by tuning the FCM clustering algorithm to obtain the more reasonable and stable result. A coefficient is proposed to reduce the amount of blind random searches and speed up convergence, thus achieving the goals of optimizing and improving the ABC algorithm. The results from the IABC algorithm are used as initial parameters in FCM to avoid falling to the local optimum in the local search, thus obtaining stable classifying results. Two validity indices are adopted to verify the rationality and practicability of the IABC-FCM algorithm in classifying the rock joints, and the optimal amount of joint sets is obtained based on the two validity indices. Two illustrative examples, i.e., the simulated rock joints data and the field-survey rock joints data, are used in the verification to check the feasibility and practicability in rock engineering for the proposed algorithm. The results show that the IABC-FCM algorithm could be applicable in classifying the rock joint sets.

• 대한수학회보
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• 제42권3호
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• pp.521-525
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• 2005

We give a necessary and sufficient condition of a rationally elliptic space X such that the Dold-Lashof classifying space Baut1X for fibrations with the fiber X is rank one. It is only when X has the rational homotopy type of a sphere or the total space of a spherical fibration over a product of spheres.

• 한국세라믹학회지
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• 제27권6호
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• pp.769-776
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• 1990

This study deals with the refinement of Hwasun flint clay by grinding, classifying, magnetic separation and acid treatment in sequence. Results are as follows ; 1. Fine kaolinite particles of median size in the range of 4.8 and 1.7$\mu\textrm{m}$ was collected, with the yield of 87.4% by dry grinding and classifying process. 2. It is proven that the iron bearing are of Hwasun flint clay is mainly consisted of chloritoid and iron rich muscovite. 3. As the results of the high gradient magnetic separation, the bleaching and iron removal degree of the dry grinding and classifying sample was 4-58% and 5-62% respectively. 4. As the results of the acid treatment, bleaching and weight loss degree of the dry grinding and classifying sample was reduced to 16-82% and 6-29% respectively.