• Journal of Educational Research in Mathematics
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• v.24 no.2
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• pp.205-225
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• 2014

This study analyzed how two sixth graders recognized, generalized, and represented functional relationships in exploring geometric growing patterns. The results showed that at first the students had a tendency to solve the given problem using the picture in it, but later attempted to generalize the functional relationships in exploring subsequent items. The students also represented the patterns with their own methods, which in turn had an impact on the process of generalizing and applying the patterns to a related context. Given these results, this paper includes issues and implications on how to foster functional thinking ability at the elementary school.

• Journal of Educational Research in Mathematics
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• v.21 no.1
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• pp.67-86
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• 2011

This study aimed to examine first graders' recognition and thinking about mathematical patterns. To attain the goal, this paper analyzed 116 students' response with regard to repeating, growing, and changing patterns represented in both picture and number, and also analyzed four students' thinking process of the patterns through interview. It was found that students showed high recognition in repeating, growing, and changing patterns in order. Whereas there was no significant difference between picture and number representation in both repeating and growing patterns, pictures gained a bit higher scores than numbers in changing patterns. Also, according to the result of examining the thinking process by the patterns, students tended to consider the patterns as a bundle and tried to solve problems with counting strategies. The result of this paper provides an empirical foundation on how first graders recognize and think of various patterns.

• Journal of Educational Research in Mathematics
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• v.17 no.2
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• pp.163-177
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• 2007

Studies on mathematically gifted students have been conducted following Krutetskii. There still exists a necessity for a more detailed research on how these students' mathematical competence is actually displayed during the problem solving process. In this study, it was attempted to analyse the algebraic thinking process in the problem solving a peg puzzle in which 4 mathematically gifted students, who belong to the upper 0.01% group in their grade of elementary school in Korea. They solved and generalized the straight line peg puzzle. Mathematically gifted elementary school students had the tendency to find a general structure using generic examples rather than find inductive rules. They did not have difficulty in expressing their thoughts in letter expressions and in expressing their answers in written language; and though they could estimate general patterns while performing generalization of two factors, it was revealed that not all of them can solve the general formula of two factors. In addition, in the process of discovering a general pattern, it was confirmed that they prefer using diagrams to manipulating concrete objects or using tables. But as to whether or not they verify their generalization results using generalized concrete cases, individual difference was found. From this fact it was confirmed that repeated experiments, on the relationship between a child's generalization ability and his/her behavioral pattern that verifies his/her generalization result through application to a concrete case, are necessary.

• ETRI Journal
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• v.17 no.1
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• pp.11-22
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• 1995

This paper proposes a modified error function to improve the error back-propagation (EBP) algorithm for multi-Layer perceptrons (MLPs) which suffers from slow learning speed. It can also suppress over-specialization for training patterns that occurs in an algorithm based on a cross-entropy cost function which markedly reduces learning time. In the similar way as the cross-entropy function, our new function accelerates the learning speed of the EBP algorithm by allowing the output node of the MLP to generate a strong error signal when the output node is far from the desired value. Moreover, it prevents the overspecialization of learning for training patterns by letting the output node, whose value is close to the desired value, generate a weak error signal. In a simulation study to classify handwritten digits in the CEDAR [1] database, the proposed method attained 100% correct classification for the training patterns after only 50 sweeps of learning, while the original EBP attained only 98.8% after 500 sweeps. Also, our method shows mean-squared error of 0.627 for the test patterns, which is superior to the error 0.667 in the cross-entropy method. These results demonstrate that our new method excels others in learning speed as well as in generalization.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.7
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• pp.70-81
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• 1997

In this paper, we propose HMCNN(hybrid multiple component neural networks) that enhance performance of MCNN by adapting new pattern partitioning algorithm which can cluster many input patterns efficiently. Added neural network performs similar learning procedure that of kohonen network. But it dynamically determine it's number of output neurons using algorithms that decide self-organized number of clusters and patterns in a cluster. The proposed network can effectively be applied to problems of large data as well as huge networks size. As a sresutl, proposed pattern partitioning network can enhance performance results and solve weakness of MCNN like generalization capability. In addition, we can get more fast speed by performing parallel learning than that of other supervised learning networks.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.193-217
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• 2001

Despite of the rich literature in discriminant analysis, this complicated subject remains much to be explored. In this article, we study the theoretical foundation that supports Fisher's linear discriminant analysis (LDA) by setting up the classification problem under the dimension reduction framework as in Li(1991) for introducing sliced inverse regression(SIR). Through the connection between SIR and LDA, our theory helps identify sources of strength and weakness in using CRIMCOORDS(Gnanadesikan 1977) as a graphical tool for displaying group separation patterns. This connection also leads to several ways of generalizing LDA for better exploration and exploitation of nonlinear data patterns.

• Research in Mathematical Education
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• v.26 no.3
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• pp.147-166
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• 2023

Mathematics is a science of pattern. Mathematics is a subject of inquiring which aims at discovering the models hidden behind the world. Pattern is abstraction and generalization of the model. Mathematical pattern is a higher level of mathematical model. Mathematics patterns are often hidden in pattern similarity. Creation of mathematics lies largely in discovering the pattern similarity among the various components of mathematics. Inquiring is the core and soul of mathematics teaching. It is very important for students to study mathematics like mathematicians' exploring and discovering mathematics based on pattern similarity. The author describes an example about how to guide students to carry out mathematics inquiring based on pattern similarity in classroom.

• Education of Primary School Mathematics
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• v.14 no.2
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• pp.117-134
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• 2011

The purpose of this research was to analyze mathematical task types to enhance creativity. Creativity is increasingly important in every field of disciplines and industries. To be excel in the 21st century, students need to have habits to think creatively in mathematics learning. The method of the research was to collect the previous research and papers concerning creativity and mathematics. To search the materials, the researcher used the search engines such as the GIL and the KISTI. The mathematical task types to enhance creativity were categorized 16 different types according to their forms and characteristics. The types of tasks include (1) requiring various strategies, (2) requiring preferences on strategies, (3) making word problems, (4) making parallel problems, (5) requiring transforming problems, (6) finding patterns and making generalization, (7) using open-ended problems, (8) asking intuition for final answers, (9) asking patterns and generalization (10) requiring role plays, (11) using literature, (12) using mathematical puzzles and games, (13) using various materials, (14) breaking patterned thinking, (15) integrating among disciplines, and (16) encouraging to change our lives. To enhance students' creativity in mathematics teaching and learning, the researcher recommended the followings: reshaping perspectives toward teaching and learning, developing and providing creativity-rich tasks, applying every day life, using open-ended tasks, using various types of tasks, having assessment ability, changing assessment system, and showing and doing creative thinking and behaviors of teachers and parents.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.535-538
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• 2001

Since 1990s, many literatures have shown that connectionist models, such as back propagation, recurrent network, and RBF (Radial Basis Function) outperform the traditional models, MA (Moving Average), AR (Auto Regressive), and ARIMA (Auto Regressive Integrated Moving Average) in time series prediction. Neural based approaches to time series prediction require the enough length of historical measurements to generate the enough number of training patterns. The more training patterns, the better the generalization of MLP is. The researches about the schemes of generating artificial training patterns and adding to the original ones have been progressed and gave me the motivation of developing VTG schemes in 1996. Virtual term is an estimated measurement, X(t+0.5) between X(t) and X(t+1), while the given measurements in the series are called actual terms. VTG (Virtual Tern Generation) is the process of estimating of X(t+0.5), and VTG schemes are the techniques for the estimation of virtual terms. In this paper, the alternative VTG schemes to the VTG schemes proposed in 1996 will be proposed and applied to multivariate time series prediction. The VTG schemes proposed in 1996 are called deterministic VTG schemes, while the alternative ones are called stochastic VTG schemes in this paper.

• Journal of the Korean Institute of Educational Facilities
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• v.19 no.3
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• pp.3-12
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• 2012

Owing to generalization of design competitions since 1990s, various design methods was tried in elementary middle high school design competitions. Therefore, to analyze design characteristics of elementary middle high school is very meaningful. In this context, this study is the most important purpose for analyzing layout plans and their trends in prizewinners of elementary middle high school design competitions and for furnishing basic datum for next school design. The result of this study is following : (1) The layout patterns of school buildings are classified into 12 types. (2) Entrance design is divided into 6 types(structure, column and wall, open, half structure, general, and mixed type). (3) Square design is grouped into 7 types. (4) Pedestrian mall is sorted out 6 types(straight lineal, curve, curve and square, straight lineal and curve, and straight lineal and curve and square type). (5) Entrance types of vehicle and pedestrian are classified into 4 types(parallel, ㅡ separation, ㄱ separation, and opposite separation type) Analysis shows that the best applying for layout patterns of school buildings is ㄷ type and ㅌ type, for entrance design is structure type, for square design is ${\square}$ type and ${\bigcirc}$ type, for pedestrian mall is straight lineal and square type, and for entrance types of vehicle and pedestrian is parallel type.