• Journal of Korean Elementary Science Education
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• v.26 no.4
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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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• v.17 no.4
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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.

• Journal of Korean Elementary Science Education
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• v.27 no.3
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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.

• Communications of the Korean Mathematical Society
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• v.32 no.3
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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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• 2005.06a
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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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• v.21 no.6
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• pp.1225-1235
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• 2010

The coarse classifying procedure in credit scoring splits the values of a continuous characteristic into bands and the values of a discrete characteristic into groups of values. Also, the scorecard degrades over time and thus we should adjust the cut-off score being used. However, the coarse classifying and the adjustment of cut-off score in credit scoring are very complicate and troublesome procedure. Thus, in this paper, we develop a software for the coarse classifying and the model evaluation by using Visual Basic Language. By using the developed software, we can find the best split in the coarse classifying and the optimal cut-off score in the model evaluation.

• Fashion & Textile Research Journal
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• v.9 no.5
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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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• v.31 no.4
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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.

• Bulletin of the Korean Mathematical Society
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• v.42 no.3
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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.

• Journal of the Korean Ceramic Society
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• v.27 no.6
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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.