• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1563-1570
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• 1999

In this paper, we proposed the FPA(Fixed Partition Averaging) algorithm in order to improve the storage requirement and classification time of Memory Based Reasoning method. The proposed method enables us to use the storage more efficiently by extracting representatives out of training patterns. After partitioning the pattern space into a fixed number of equally-sized hyperrectangles, it averages patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.21-26
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the user's access pattern to web site and their following purchasable items and improves their web page on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning, it employs Apriori algorithm, which is a method that searches the association rule. It reasons the web pages by considering the user's access pattern and time by using the web log and reasons the user's purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of user's web pages and displays the inferred goods on user's web pages.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.29-32
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the users' access pattern to web site and their following purchasable items and improves their web pare on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning it employs Rough Set, which is a method that searches the association rule and offers most suitable cases by reduces cases. It reasons the web pages by considering the users' access pattern and time by using the web log and reasons the users' purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of users' web pages and displays the inferred goods on users' web pages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1551-1556
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• 2010

In this paper, we propose a new inspection method that applies fuzzy reasoning method considering the difference of brightness and intensity of illumination by bend together. In the preprocessing phase, we compensate the degree of semiconductor images with bilinear interpolation and moment-rotation. Then we use fuzzy reasoning method with the difference of brightness from error region by pattern matching and the difference of intensity of illumination from bends. Then the result is difuzzified and applied to the final inspection process. In experiment which uses 30 real world semiconductors with strait shots and side shots, the proposed method successfully discard the false positive identified by conventional brightness comparison only method without any loss of misidentification.

• Journal of Educational Research in Mathematics
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• v.11 no.2
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• pp.239-256
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• 2001

The notion of metaphor has been increasingly popular in research of mathematics education. In particular, metaphor becomes a useful unit for analysis to provide a profound insight into mathematical reasoning and problem solving. In this context, this paper takes metaphor as an analytic unit to examine the relationship between objectivity and subjectivity in mathematical reasoning. Specifically, the discourse analysis focuses on the code switching between literal language and metaphor in mathematical discourse. It is shown that the linguistic code switching is parallel with the switching between two different kinds of mathematical knowledge, that is, factual knowledge and mathematical imagination, which constitute objectivity and subjectivity in mathematical reasoning. Furthermore, the pattern of the linguistic code switching reveals the dialectical relationship between the two poles of mathematical reasoning. Based on the understanding of the dialectical relationship, this paper provides some educational implications. First, the code-switching highlights diverse aspects of mathematics learning. Learning mathematics is concerned with developing not only technicality but also mathematical creativity. Second, the dialectical relationship between objectivity and subjectivity suggests that teaching and teaming mathematics is socioculturally constructed. Indeed, it is shown that not all metaphors are mathematically appropriated. They should be consistent with the cultural model of a mathematical concept under discussion. In general, this sociocultural perspective on mathematical metaphor highlights the sociocultural organization of teaching and loaming mathematics and provides a theoretical viewpoint to understand epistemological diversities in mathematics classroom.

• Journal of The Korean Association For Science Education
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• v.18 no.4
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• pp.503-516
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• 1998

The purpose of the present study was to evaluate some variables, such as learner's cognitive characteristics and a training-program emphasized proportional logic, in proportional reasoning development. Seven hundred and ninety students in junior high schools were enrolled as subjects for the study which investigated learner's cognitive characteristics in proportional reasoning development and asked to perform tests of logical thinking, card sorting, planning, mental capacity, cognitive style, brain lateralization, information processing pattern and scientific reasoning. In addition, one hundred and thirty-three students who failed to solve proportional thinking items were administered a training program which has been applied to improve the subjects' proportional reasoning skills. The results showed a significant higher correlation between subjects' performance score on proportional thinking test, and their age and scores on scientific reasoning test, mental capacity, information processing test and perseveration errors on card sorting test. Also, the training program applied in this study showed an effective result in developing subjects' proportional reasoning skills. Further, this study may serve as a suggestion in the efforts to investigate factors of proportional thinking development and a contribution for the future research in other logical thinking development.

• Child Health Nursing Research
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• v.7 no.1
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• pp.118-140
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• 2001

The purpose of this study was to measure the effect of safety education program in preschool children for accident prevention and improve their health through more systematic method. Data were collected from 584 preschoolers(247 preschooler are assigned to experimental group and 337 preschoolers are assinged to control group) from 4 to 6 years old using APP paper test which consists of questions and drawings. To experimental group, safety education were done 4 times within the time of 30 minutes per 1 time using education books, drawings, OHP. The findings of this study are as follows: 1. There were significant difference in movement(χ²=18.732, p=.0000), behavioral character(χ²=27.785, p=.000), synthetic judgement(χ²=12.02, p=0.002). So, safety education program have effect on preschooler. 2. In the accident proneness on preschooler between experimental group and control group according to general characteristics, it proved significant difference in the case of accident prevention education were done, reasoning power(χ²=10.48, p=.005), movement speed(χ²=7.341, p=.025) and behavioral character(χ²=18.86, p=.000), in the case of housing pattern is private house(individual house, yard?), reasoning power(χ²=6.683, p=.035), movement speed(χ²=12.76, p= .002) and behavioral character(χ²=12.24, p=.002), in the case of housing pattern is mixed-type, movement speed(χ²=6.935, p= .031) and behavioral character(χ²=10.816, p=.004), in the case of housing pattern is over six stories, movement speed(χ²=7.543, p=.023), in the case of subjects' age is 4 years old, movement speed(χ²=16.5, p= .000) and behavioral character(χ²=12.18, p=.002), in the case of subjects' age is 5 years old, movement speed(χ²=7.519, p= .023), watchfulness(χ²=6.372, p=.041), behavioral character(χ²=14.74, p=0.001) and synthetic judgement(χ²=14.5, p=.001), in the case of subjects' sex is male, life safety(χ²=6.406, p=.041), movement speed(χ²=22.86, p= .000), behavioral character(χ²=13.72, p= .001) and synthetic judgement(χ²=13.82, p=.001), in the case of subjects' sex is female, reasoning power(χ²=12.57, p=.002) and behavioral character(χ²=13.16, p= .001), in the case of childrens have past accidental experience, traffic safety(χ²= 6.683, p=.035), in the case of childrens have no past accidental experience, reasoning power(χ²=8.384, p=.015), movement speed(χ²=20.6, p=.000), behavioral character(χ²=25.1, p=.000) and synthetic judgement(χ² =10.79, p=.005), in the case of children's order is first, reasoning power(χ²=11.15, p=.004), movement speed(χ²=11.92, p= .003) and behavioral character(χ²=7.003, p=.030), in the case of children's order is second, movement speed(χ²=6.694, p= .035), behavioral character(χ²=26.9, p= .000) and synthetic judgement(χ²=14.3, p= .001), in the case of nuclear family, reasoning power(χ²=8.777, p=.012), movement speed(χ²=19.0, p=.000), behavioral character (χ²=26.4, p=0.000) and synthetic judgement (χ²=9.999, p=.007), in the case of mothers' school career is under high school graduate, life safety(χ²=8.023, p=.018), movement speed(χ²=10.99, p=.004) and behavioral character(χ²=6.777, p=.034), in the case of mothers' school career is beyond college graduate, reasoning power(χ²=6.717, p= .035), movement speed(χ²=8.963, p=.011), behavioral character(χ²=25.03, p=.000) and synthetic judgement(χ²=15.19, p=.001), in the case of mothers' age ranged 31-34, movement speed(χ²=12.29, p=.002) and behavioral character(χ²=14.17, p=.001), in the case of mothers' age ranged 35-39, movement speed(χ²=9.859, p=.007), behavioral character(χ²=9.095, p=.011) and synthetic judgement(χ²=7.810, p=.020), in the case of mothers' age is over 40, life safety(χ² =5.593, p=.025), in the case of mothers' job is full-time, traffic safety(χ²=6.032, p=.049) and reasoning power(χ²=8.502, p= .014), in the case of mothers' job is part- time., movement speed(χ²=10.99, p=.004) and behavioral character(χ²=7.895, p= .019), in the case of mothers have no job, movement speed(χ²=6.410, p=.041), movement stability(χ²=6.879, p=.032), behavioral character(χ²=27.72, p=.000) and synthetic judgement(χ²=18.11, p=.000). The difference of accident proneness between experimental group and control group according to general characterists, it also showed that there were significant difference in behavioral character compared to other area.. From this findings, we can guess that safety education program change and guide preschoolers' behavioral character to desirable direction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.875-885
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• 2010

CBR (Case-Based Reasoning) is a technique to infer the relationships between existing data and case data, and the method to calculate similarity and Euclidean distance is mostly frequently being used. However, since those methods compare all the existing and case data, it also has a demerit that it takes much time for data search and filtering. Therefore, to solve this problem, various researches have been conducted. This paper suggests the method of SE(Speed Euclidean-distance) calculation that utilizes the patterns discovered in the existing process of computing similarity and Euclidean distance. Because SE calculation applies the patterns and weight found during inputting new cases and enables fast data extraction and short operation time, it can enhance computing speed for temporal or spatial restrictions and eliminate unnecessary computing operation. Through this experiment, it has been found that the proposed method improves performance in various computer environments or processing rate more efficiently than the existing method that extracts data using similarity or Euclidean method does.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.3
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• pp.141-149
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• 2008

Most functional programming languages allows programmers to write ambiguous rules, under the strategy that pattern-matching will be performed in a direction of 'from top to bottom' way. While providing programmers with convenience and intuitive understanding of defining default rules, such ambiguous rules may make the semantics of functional languages unclear. More specifically, it may fail to apply the equational reasoning, one of most significant advantage of functional programming, and may cause to obscure finding a formal way of translating functional languages into the ${\lambda}$-calculus; as a result, we only get an ad hoc translation. In this paper, we associate with separability of term rewriting systems, holding purely-declarative property, pattern-matching semantics of lazy functional languages. Separability can serve a formalism for translating lazy functional languages into the ${\lambda}$-calculus.

• Journal of IKEEE
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• v.12 no.1
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• pp.65-74
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• 2008

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it is notorious for memory usage and can't learn additional information from new data. In order to overcome this problem, we propose an incremental learning algorithm (iMPA). iMPA divides the entire pattern space into fixed number partitions, and generates representatives from each partition. Also, due to the fact that it can not learn additional information from new data, we present iMPA which can learn additional information from new data and not require access to the original data, used to train. Proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory using benchmark data sets from UCI Machine Learning Repository.