• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.173-190
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• 2015

The purpose of this study is to improve bankruptcy prediction models by using a novel hybrid under-sampling approach. Most prior studies have tried to enhance the accuracy of bankruptcy prediction models by improving the classification methods involved. In contrast, we focus on appropriate data preprocessing as a means of enhancing accuracy. In particular, we aim to develop an effective sampling approach for bankruptcy prediction, since most prediction models suffer from class imbalance problems. The approach proposed in this study is a hybrid under-sampling method that combines the k-Reverse Nearest Neighbor (k-RNN) and one-class support vector machine (OCSVM) approaches. k-RNN can effectively eliminate outliers, while OCSVM contributes to the selection of informative training samples from majority class data. To validate our proposed approach, we have applied it to data from H Bank's non-external auditing companies in Korea, and compared the performances of the classifiers with the proposed under-sampling and random sampling data. The empirical results show that the proposed under-sampling approach generally improves the accuracy of classifiers, such as logistic regression, discriminant analysis, decision tree, and support vector machines. They also show that the proposed under-sampling approach reduces the risk of false negative errors, which lead to higher misclassification costs.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.1
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• pp.33-47
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• 2021

This study developed a big data-based STEAM (Science, Technology, Engineering, Art & Mathematics) program using WWT (World Wide Telescope), focusing on content elements of 'solar system', 'star and universe' in the 2015 revised science curriculum, and in order to find out the effectiveness of the STEAM program, analyzed creative problem solving, STEAM attitude, and STEAM satisfaction by applying it to one middle school 176 students simple random sampled. The results of this study are as follows. First, we developed a program to encourage students to actively and voluntarily participating, utilizing the astronomical data platform WWT. Second, in the paired t-test based on the difference between the pre- and post-scores of the creative problem solving measurement test, significant statistical test results were shown in 'idea adaptation', 'imaging', 'analogy', 'idea production' and 'elaboration' sub-factors except 'attention task' sub-factor (p < .05). Third, in the paired t-test based on the difference between the pre- and post-scores of the STEAM attitude test, significant statistical test results were shown in 'interest', 'communication', 'self-concept', 'self-efficacy' and 'science and engineering career choice' sub-factors except 'consideration' and 'usefulness / value recognition' sub-factors (p < .05). Fourth, in the STEAM satisfaction test conducted after class application, the average values of sub-factors were 3.16~3.90. The results indicated that students' understanding and interest in the science subject improved significantly through the big data-based STEAM program using the WWT.

• Journal of Distribution Research
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• v.11 no.1
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• pp.69-97
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• 2006

This research aimed to establish and test a empirical model for antecedents and consequences of manufacturer's degree of channel concentration in multiple channels from strategic perspective. For this purpose, I suggested new concept of channel concentration based on related literature review and developed the measurement index of channel concentration. Second, I examined and applied the transaction cost theory and market power theory to provide broad understanding of multiple channel structure and to explain it. Finally, I present the theoretical and managerial implications to the firms that build up channel strategy under multiple channel contexts on this research results. For the purpose of these goals, eight hypotheses were drawn from the previous researches. To verify these hypotheses, 248 data were collected as samples, and the data were tested by reliability test, factor analysis, and covariance structure analysis. Empirical findings strongly support that strategic management of distribution channel especially are important in multiple channels. The overall implications to researchers and practitioners are presented, and limits and further study direction were discussed as a final.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.595-607
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• 2010

This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.139-144
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• 2008

Generally, real system that is the object of decision-making is very variable and sometimes it lies situations with uncertainty. To solve these problem, it has used statistical methods as significance level, certainty factor, sensitivity analysis and so on. In this paper, we propose a method for fuzzy decision-making based on MFAC(Multiple Fuzzy Alpha Cut) to improve the definiteness of classification results with similarity evaluation. In the proposed method, MFAC is used for extracting multiple a ${\alpha}$-level with proximity degree at proximity relation between relative Hamming distance and max-min method and for minimizing the number of data which are associated with the partition intervals extracted by MFAC. To determine final alternative of decision-making, we compute the weighted value between extracted data by MFAC From the experimental results, we can see the fact that the proposed method is simpler and more definite than classification performance of the conventional methods and determines an alternative efficiently for decision-maker by testing significance of sample data through statistical method.

• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.6
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• pp.464-476
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• 1998

Determination of location, shape and size of a flaw from its eddy current testing signal is one of the fundamental issues in eddy current nondestructive evaluation of steam generator tubes. Here, we propose an approach to this problem; an inversion of eddy current flaw signal using neural networks trained by finite element model-based synthetic signatures. Total 216 eddy current signals from four different types of axisymmetric flaws in tubes are generated by finite element models of which the accuracy is experimentally validated. From each simulated signature, total 24 eddy current features are extracted and among them 13 features are finally selected for flaw characterization. Based on these features, probabilistic neural networks discriminate flaws into four different types according to the location and the shape, and successively back propagation neural networks determine the size parameters of the discriminated flaw.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.491-505
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• 2021

We consider linear regression models in high-dimensional settings (p ≫ n) and compare various classes of priors. The spike and slab prior is one of the most widely used priors for Bayesian regression models, but its model space is vast, resulting in a bad performance in finite samples. As an alternative, various continuous shrinkage priors, including the horseshoe prior and its variants, have been proposed. Although each of the above priors has been investigated separately, exhaustive comparative studies of their performance have been conducted very rarely. In this study, we compare the spike and slab prior, the horseshoe prior and its variants in various simulation settings. The performance of each method is demonstrated in terms of the regression coefficient estimation and variable selection. Finally, some remarks and suggestions are given based on comprehensive simulation studies.

• Journal of Science Education
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• v.41 no.3
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• pp.334-350
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• 2017

The purposes of this study are to develop scientific-inquiry based on STEAM education program and to investigate the effects of the program on middle-school students' interests, self-efficacy, and career choice about science, technology/engineering, and mathematics. In order to develop this program, the literature investigation and previous studies were conducted, so that finally the developmental direction was based on scientific inquiry and the developmental theme and model were selected. A total 92 first-graders in G middle-school of Daegu city were participated in this study. A single group pre-post test paired t-test was conducted to figure out changes of students' interest, self-efficacy, and career choices before or after applying this program. In addition, in-depth interviews were conducted with 14 students to find their specific responses. The results of this study were as follows. First, STEAM education program on the theme of 'RC Airplane' was developed on the basis of the 'ADBA' model. Second, the developed STEAM educational program not only results a decisive difference statistically but also has significant effects on middle-school students' interests, self-efficacy, and career choice in science, technology/engineering, and mathematics, who are involved in the free-semester program, across the overall affective domain. In conclusion, the STEAM educational program in this study could affect significant meanings to middle-school students during the free-semester. It could contribute to facilitate middle-school students' education for happiness and to grow the creative STEAM talents.

• Korean Journal of Environment and Ecology
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• v.26 no.3
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• pp.463-471
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• 2012

Objective of this study is to provide basic information for developing more differentiated and targeted forest healing policy and Korean medical healing programs grounded on consumer preference for forest based Korean medical healing tourism products. The internet survey(CAWI) by percentage quota sampling with 400 Seoulite ages over 30 by the age, area, and gender was conducted, and 317 samples were used for a final analysis. 61.5% of the Seoulite associated 'forest bath/walking in the woods/tree' with an image of a forest based Korean medical healing tourism product, and preference for the product and the intention to use were positive at the percentages of 72.9% and 67.5%, respectively. Preferred areas were Seoul/Gyeonggi-do(53.5%) and Gangwon-do(38.8%). 'Stress solving and refreshment', 'taking a forest bath and a walk', and 'maintaining and promoting health' were the main purposes of the use. As for a therapy, 'walking therapy' was most preferred, and 'ergotherapy' was the next. First priority as for a use facility was 'healing trail', and 'professional medical facility' ranked second. Although important decision attributes were ' cost of use', 'food', and 'friendliness of medical staff', all the other sets of attributes related to use convenience, quality of medical service and tourism activities also recorded high, which forecasts higher consumer expectation for the product. As the result showing differences in consumer preference by the demographic segmentation, differentiated and segmented consumer needs should be considered when planing and managing a product. The scope of the study is limited to a demographic segmentation which is a basic stage of understanding consumer preference, therefore more detailed future researches on complicated and multi-dimensional consumer needs are required.

• Journal of Korean Society of Forest Science
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• v.96 no.1
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• pp.7-13
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• 2007

This study was done to develop PDA based application system for forest geographic information with GPS. The major results obtained in this study were as follows. A PDA based application program was developed to work on $Microsoft^{TM}$ PocketPC 2002 and 2003 operating system. The screen of PDA displays a 1:25,000 digital topographical map adopted DXF format converted from PC, and the map data with 1:2,500 to 1:30,000 on PDA can be zoomed in or out to five levels. Current position and navigating path received from GPS can be displayed on the screen and be saved in PDA. Information selected among layers of digital topographic map in DXF format can be converted into binary files which can be used on forest geographic information software. This can compress DXF files to 90% in size, and the processing speed of PDA was improved. The forest geographic information management system can be used to manage sample plots on which forest inventory is done, with the help of the sub-menus and grid index values with position information received from GPS. Forest workers can in quire forest geographic information such as forest type, location, forest roads, soil erosion control dams using forest geographic information management system in the field. The forest geographic information management system can provide current position and mobile path information to people who enjoy forest related activities like mountain-climbing, sightseeing, and visiting to historic spots.