• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1942-1950
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• 2013

This paper suggests a new method of detecting attacks of network traffic by visualizing original traffic data and applying multi-class SVM (support vector machine). The proposed method first generates 2D images from IP and ports of transmitters and receivers, and extracts linear patterns and high intensity values from the images, representing traffic attacks. It then obtains variance of ports of transmitters and receivers and extracts the number of clusters and entropy features using ISODATA algorithm. Finally, it determines through multi-class SVM if the traffic data contain DDoS, DoS, Internet worm, or port scans. Experimental results show that the suggested multi-class SVM-based algorithm can more effectively detect network traffic attacks.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.661-670
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• 2018

This study aims to develop a methodology of convolutional neural networks (CNNs) to produce thematic maps from remote sensing data. Optimizing the image size for CNNs was studied, since the size of the image affects to accuracy, working as hyper-parameter. The selected study area is Mt. Ung, located in Dangjin-si, Chungcheongnam-do, South Korea, consisting of both coniferous forest and deciduous forest. Spatial structure analysis and the classification of forest type using CNNs was carried in the study area at a diverse range of scales. As a result of the spatial structure analysis, it was found that the local variance (LV) was high, in the range of 7.65 m to 18.87 m, meaning that the size of objects in the image is likely to be with in this range. As a result of the classification, the image measuring 15.81 m, belonging to the range with highest LV values, had the highest classification accuracy of 85.09%. Also, there was a positive correlation between LV and the accuracy in the range under 15.81 m, which was judged to be the optimal image size. Therefore, the trial and error selection of the optimum image size could be minimized by choosing the result of the spatial structure analysis as the starting point. This study estimated the optimal image size for CNNs using spatial structure analysis and found that this can be used to promote the application of deep-learning in remote sensing.

• Korean Journal of Child Studies
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• v.6 no.2
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• pp.21-33
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• 1985

This study was conducted to ascertain whether a didactic mode of instruction, favored students who indicated a preference for left hemispheric information processing. The subjects were 50 fifth grade students whose California Achievement Test score percentile ranks were between 50 - 80. They were randomly selected from one elementary school in Chapel Hill, NC, USA. All Ss completed the Form CC of "Your Style of Learning and Thinking" (Torrance and McCarthy, 1980) which is a paper/pencil inventory designed to categorize the subjects according to their hemispheric preference for processing information; right hemisphere, left hemisphere, and integrated. Then all Ss received a didactic mode of instruction, a verbal question/answer followed by teacher's reading of a fictional animal story, "The Chinese Bee-eater". After completion of instruction, the Ss were asked to respond to eighteen open-ended questions about the animal. Eight of the 50 subjects were found to fall into the right hemisphere style of information processing group; fourteen into left; and fourteen into integrated. The remaining fourteen could not be assigned to either of these three categories and were not included in the analysis of the results. the mean scores of the comprehensive test among hemispheric groups and among sex groups. A two way analysis of variance also presented no significant differences among the hemispheric preference combined by sex groups. These results failed to prove the research hypothesis that students who indicate a preference for left hemispheric information processing will have higher scores on a comprehensive test after receiving a didactic mode of instruction, the so-called left style of instruction. Some limits in research process and conceptual confusion about hemisphericity were discussed. Finally, it was suggested that educators need to be more careful in drawing educational implications from neurological hemispheric research.

• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.351-359
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• 2005

The aims of this research are to analyze elementary preservice teacher's conception and causes of their misconceptions on biological reproduction and inheritance. In future, it would be also to provide useful data for the effective teaching-teaming method in the elementary school as well as opportunities to correct their misconceptions, which help elementary preservice teachers have the appropriate scientific conceptions. Thirty kinds of test questions were designed in science curriculum for elementary students and biology textbook for university students in order to develop reproduction and inheritance's concepts. The questionnaire was given to 166 junior students of university of education in a local city. All statistical analysis was performed using SPSS version 10.0 program. The major results are as follows: Among 30 test questions, 2 questions in plants, 5 questions in animals and 2 questions in gene were appeared as misconceptions over $50\%$. The major reason to hold the misconceptions was influenced by 'learning up to now' category. The selection reasons of response were significantly different between scientific conceptions and misconceptions in 10 questions by analysis of variance. The gender also showed statistically significant differences between scientific conception and misconception in 3 questions by $\chi^2$ test. The selection reasons according to gender were significantly different between male and female students in 5 questions. For the reasons in forming misconceptions, they may cause by stereotype, conscious priority, differences of experiences, interest or attention, lack of professional Knowledge, and so on. Therefore, it was concluded that this research may help elementary preservice teachers to reconsider their conception for reproduction and inheritance and to be successful in science instructions fur elementary students.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.49-54
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• 2003

In this paper, we propose a controller with the self-organizing neural network compensator for compensating PID controller's response. PID controller has simple design method but needs a lot of trials and errors to determine coefficients. A neural network control method does not have optimal structure as the parameters are pre-specified by designers. In this paper, to solve this problem, we use a self-organizing neural network which has Back Propagation Network algorithm using a Gaussian Potential Function as an activation function of hidden layer nodes for compensating PID controller's output. Self-Organizing Neural Network's learning is proceeded by Gaussian Function's Mean, Variance and number which are automatically adjusted. As the results of simulation through the second order plant, we confirmed that the proposed controller get a good response compare with a PID controller. And we implemented the of controller performance hydraulic servo motor system using the DSP processor. Then we observed an experimental results.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.108-116
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• 2019

This study is a descriptive survey study intended to analyze the relationship between multicultural acceptability, empathy, and global citizenship of nursing students and identify the factors influencing global citizenship. The data was collected targeting 187 nursing students at universities located in the cities of B, U, and S. The collected data was analyzed using t-test, ANOVA, Pearson correlation coefficients, and stepwise multiple regression analysis. The results were as follows: global citizenship of nursing students was positively correlated with multicultural acceptability and empathy. Factors influencing the level of global citizenship were empathy, multicultural acceptability, which together explained 40.0% of the total variance in global citizenship. Consequently, this study raises the need for the development and application of steady practical programs and various learning methods for the enhancement of global citizenship, which is required in the fields of nursing education where global competence is considered to be important.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.4
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• pp.39-47
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• 2020

Purpose : The purpose of this study was to investigate a comparative study on the effects of maximum voluntary ventilation (MVV) and thickness of the abdominal muscles through two Kegel exercise postures. Methods : Twenty eight (male= 7, female= 21) subjects participated in this experiment. They performed Kegel exercise in sitting and hooklying. The order of exercise was conducted in the order chosen by the subjects to exclude the learning effect. The MVV was measured using a spirometer. The thickness of the abdominal muscles were measured by ultrasound. The MVV and thickness of the abdominal muscles were measured according to the manual in a sitting and hooklying position before the experiment. After each exercise, the MVV and thickness of the abdominal muscles were also measured in the same way. A one way repeated measures analysis of variance (ANOVA) was used to compare the MVV and thickness of the abdominal muscles according to two postures and post hoc analysis, Bonferroni was used. Results : As a result of this study, significant differences in the MVV were observed after exercise than before exercise (p<.05). However, as a result of post hoc analysis, there was no difference in the MVV according to the postures (p>.05). Significant differences in thickness of the abdominal muscles were observed after exercise than before exercise (p<.05). However, as a result of post hoc analysis, there was no difference in thickness of the abdominal muscles according to the postures (p>.05). Conclusion : Based on the results of this study, the MVV and the thickness of the abdominal muscles were confirmed in the sitting and hooklying posture after Kegel exercise. However, further studies on vital capacity and abdominal muscles according to Kegel exercise postures should be conducted.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.4
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• pp.436-446
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• 2021

Purpose: The purpose of this study was to identify the influences of nursing students perfectionism tendencies and their perception of instructor caring on incivility experienced by nursing students during clinical practice. Methods: A descriptive correlational study was conducted. The participants were 244 nursing students from five universities in B city. Data were analyzed using an independent t-test, ANOVA, Pearson's correlation coefficient, Scheffé test and a stepwise regression analysis. Results: The mean score for incivility in nursing students was 2.61 out of 5 points. The explanatory power of the model for incivility was in nursing students 52.8% of the variance in training in student's university hospital (𝛽=-.15, p=.002), total period of clinical practice (𝛽=.17, p<.001), confidence through caring (𝛽=-.23, p<.001), respectful sharing (𝛽=-.15, p=.005), supportive learning climate (𝛽=-.15, p=.005), self-oriented perfectionism (𝛽=.14, p=.004), and socially prescribed perfectionism (𝛽=.18, p<.001). Conclusion: The research results suggest that instructor caring is an important factor in regard to the incivility of nursing students. Organizational efforts and institutional devices will be needed to improve the incivility in clinical environments. By communicating with students and showing them respect, clinical nurses will help nursing students cope with incivility and recognize the clinical practice education environment positively.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.1
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• pp.109-114
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• 2010

In this paper, we developed the web content of statistical analysis using statistical package and Active Server Page (ASP). A statistical package is very difficult to learn and use for non-statisticians, however, non-statisticians want to do analyze the data without learning statistical packages such as SAS, S-plus, and R. Therefore, we developed the web based statistical analysis contents using S-plus which is the popular statistical package and ASP. In real application, we developed the web content for various statistical analyses such as exploratory data analysis, analysis of variance, and time series on the web using water quality data. The developed statistical analysis web content is very useful for non-statisticians such as public service person and researcher. Consequently, combining a web based contents with a statistical package, the users can access the site quickly and analyze data easily.