• Journal of Engineering Education Research
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• v.20 no.5
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• pp.43-49
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• 2017

This paper deals with inter-relationship change of women's university students on the process of SW development project using social collaboration tool. Inter-relationship is one of the basic vocational competency in NCS(National Competency Standards) of Korea. We redesigned the curriculum of "Software Engineering" subject for this study and composed the project teams of students to develop software. The details of inter-relationship are satisfaction, communication, faith, friendliness, sensitivity, openness and consideration. From the result of this study, faith, openness and consideration have positive effect but satisfaction, communication, friendliness and sensitivity have no meaningful effect. The surveys were conducted in the beginning of semester and the same surveys were conducted again in the end of semester. The results were verified by paired t-test with SPSS 18.0. It is significant that the using of social collaboration tool for team project has positive effect on inter-relationship change, especially faith of women's university students. This study has some limitations for generalization but has meaning as new trial to enlarge the basic vocational competency of students in major subject, "Software Engineering". We expect new study for inter-relationship change of students to evaluate generality based on the proposed method in this paper.

• Journal of Korea Water Resources Association
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• v.37 no.11
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• pp.889-896
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• 2004

The fractal advection-diffusion equation (ADE) is a generalization of the classical AdE in which the second-order derivative is replaced with a fractal order derivative. While the fractal ADE have been analyzed with a stochastic process In the Fourier and Laplace space so far, in this study a fractal ADE for describing solute transport in rivers is derived with a finite difference scheme in the real space. This derivation with a finite difference scheme gives the hint how the fractal derivative order and fractal diffusion coefficient can be estimated physically In contrast to the classical ADE, the fractal ADE is expected to be able to provide solutions that resemble the highly skewed and heavy-tailed time-concentration distribution curves of contaminant plumes observed in rivers.

• Journal of Elementary Mathematics Education in Korea
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• v.14 no.1
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• pp.65-80
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• 2010

The aims of our study are to investigate the nature of mathematical reasoning and the teaching of mathematical reasoning in school mathematics. We analysed the process of shaping deduction in ancient Greek based on Netz's study, and discussed on the comparison between his study and Freudenthal's local organization. The result of our analysis shows that mathematical reasoning in elementary school has to be based on children's natural language and their intuitions, and then the mathematical necessity has to be formed. And we discussed on the sequences and implications of teaching of the sum of interior angles of polygon composed the discovery by induction, justification by intuition and logical reasoning, and generalization toward polygons.

• 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 The Korean Association For Science Education
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• v.11 no.1
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• pp.83-96
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• 1991

The purpose of this study is to construct the evaluative objectives of science inquiry skills specificationaly. Specification of evaluative objectives will be able to serve as evaluative criterion for development of a test of the integrated science process skills. The results in this study are as follows ; (l) The selections of science inquiry skills from the previous developed taxonomies are observation, measurement, formulating hypothesis, designing an experiment and controlling variables, inference, predicting(including intrapolation and extrapolation), organizing data and interpreting, defining operationally, formulating a generalization or model, drawing a conclusion. (2) The definitions of the selected science inquiry skills are made operationally. (3) Evaluative objectives relating to the selected science inquiry skills are specified with the previous developed items. Based on the above results, total 9 science inquiry skills are selected and 72 evaluative objectives are specified.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.59-68
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• 2016

Purpose: Increase in suicide rate for senior citizens which has become widespread in our society today. It is not a normal social phenomenon and is beyond the danger level. The contents of this study include Korean senior citizens' suicide related risk factors and warning signs, and the development of a simple Geriatric Suicide Risk Scale. Methods: This study is Methodological Research to verify reliability and validity of the Geriatric Suicide Risk Scale according to the tool development process suggested by Devellis (2012). Results: For predictive validity assessment, high suicide screening accuracy was showed with an Area under the ROC curve (AUC) of .93. For the optimal cutoff point of 11, sensitivity was 93.9%, and specificity, 75.7% which are excellence levels. Cross validity for assessment of generalization possibility showed the Area under the ROC curve (AUC) as .82 and in case of a cutoff point of 11, sensitivity was 73.7%, and specificity, 65.9%. Conclusion: When it comes to practical nursing, it is significant that the Korean Geriatric Suicide Risk Scale has high reliability and validity through adequate tool development and the tool assessment step to select degree of suicide risk of senior citizens. Also, it can be easily applied and does not take a long time to administer. Further, it can be used by health care personnel or the general public.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.64-75
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• 2003

Medical image segmentation is the process by which an original image is partitioned into some homogeneous regions like bones, soft tissues, etc. This study demonstrates an automatic medical image segmentation technique based on independent component analysis. Independent component analysis is a generalization of principal component analysis which encodes the higher-order dependencies in the input in addition to the correlations. It extracts statistically independent components from input data. Use of automatic medical image segmentation technique using independent component analysis under the assumption that medical image consists of some statistically independent parts leads to a method that allows for more accurate segmentation of bones from CT data. The result of automatic segmentation using independent component analysis with square test data was evaluated using probability of error(PE) and ultimate measurement accuracy(UMA) value. It was also compared to a general segmentation method using threshold based on sensitivity(True Positive Rate), specificity(False Positive Rate) and mislabelling rate. The evaluation result was done statistical Paired-t test. Most of the results show that the automatic segmentation using independent component analysis has better result than general segmentation using threshold.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.675-677
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• 1998

In this paper, we propose the fuzzy inference algorithm with multi-layer structure. MFIS(Multi-layer Fuzzy Inference System) uses PNN(Polynomial Neural networks) structure and the fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Hendling), and uses several types of polynomials such as linear, quadratic and cubic, as well as the biquadratic polynomial used in the GMDH. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here, the regression polynomial inference is based on consequence of fuzzy rules with the polynomial equations such as linear, quadratic and cubic equation. Each node of the MFIS is defined as fuzzy rules and its structure is a kind of neuro-fuzzy structure. We use the training and testing data set to obtain a balance between the approximation and the generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.254-259
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• 1998

A new design methology is proposed to identify the structure and parameters of fuzzy model using PNN and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and cubic besides the biquadratic polynomial used in the GMDH. The FPNN(Fuzzy Polynomial Neural Networks) algorithm uses PNN(Polynomial Neural networks) structure and a fuzzy inference method. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here a regression polynomial inference is based on consequence of fuzzy rules with a polynomial equations such as linear, quadratic and cubic equation. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture. In this paper, we will consider a model that combines the advantage of both FPNN and PNN. Also we use the training and testing data set to obtain a balance between the approximation and generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.468-474
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• 2005

Brain-machine interface (BMI) based on neuronal spike trains is regarded as one of the most promising means to restore basic body functions of severely paralyzed patients. The spike train decoding algorithm, which extracts underlying information of neuronal signals, is essential for the BMI. Previous studies report that a linear filter is effective for this purpose and there is no noteworthy gain from the use of nonlinear mapping algorithms, in spite of the fact that neuronal encoding process is obviously nonlinear. We designed several decoding algorithms based on the linear filter, and two nonlinear mapping algorithms using multilayer perceptron (MLP) and support vector machine regression (SVR), and show that the nonlinear algorithms are superior in general. The MLP often showed unsatisfactory performance especially when it is carelessly trained. The nonlinear SVR showed the highest performance. This may be due to the superiority of the SVR in training and generalization. The advantage of using nonlinear algorithms were more profound for the cases when there are false-positive/negative errors in spike trains.