• Journal of Information Technology Services
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• v.8 no.4
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• pp.129-140
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• 2009

The accurate estimation of software reliability is important to a successful development in software engineering. Until recent days, the models using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software reliability using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying immune algorithm, changing the number of generations, memory cells, and allele. The proposed IA-SVR model outperforms some recent results reported in the literature.

• Journal of Korean society of Dental Hygiene
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• v.19 no.6
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• pp.1047-1058
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• 2019

Objectives: The aim of this study is to investigate extracurricular program needs according to the learning styles of dental hygiene students, and to develop and organize non-subject programs that strengthen student competencies. Methods: The subjects in this study were dental hygiene students from three colleges located in Chungbuk, Chungnam, and Ulsan, respectively. The survey tools were composed of learning style, a non-subject field, and non-subject teaching and learning methods. Lastly, 313 data points were analyzed. Results: Learning styles of subjects were as follows: assimilators, divergers, convergers, and accommodators, at 44.6%, 33.0%, 16.0%, and 6.4%, respectively. Preference of the non-subject field, according to learning style, showed that accommodators were higher than divergers on startup, and the difference was found to be statistically significant (p<0.05). Preference of non-subject teaching and learning methods, according to learning style, shows that both divergers and convergers prefer special lectures, while assimilators prefer tours, and convergers prefer experience/exercise. The results had achieved statistical significance (p<0.05). Conclusions: This study shows that dental hygiene students had different learning styles, and their learning methods varied depending on learning style. Therefore, a method should be identified to develop and run non-subject programs suitable for each learning style.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of logarithmic hazard learning effects property.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.789-792
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• 2004

In various fields as web mining, bioinformatics, statistical data analysis, and so forth, very diversely missing values are found. These values make training data to be sparse. Largely, the missing values are replaced by predicted values using mean and mode. We can used the advanced missing value imputation methods as conditional mean, tree method, and Markov Chain Monte Carlo algorithm. But general imputation models have the property that their predictive accuracy is decreased according to increase the ratio of missing in training data. Moreover the number of available imputations is limited by increasing missing ratio. To settle this problem, we proposed statistical learning theory to preprocess for missing values. Our statistical learning theory is the support vector regression by Vapnik. The proposed method can be applied to sparsely training data. We verified the performance of our model using the data sets from UCI machine learning repository.

• Industry Promotion Research
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• v.2 no.2
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• pp.31-44
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• 2017

This study is to investigate the relationship between the communication type recognized by members of organization and the learning transfer climate in the organization, and when it comes to the type of communications within organization set as independent variable, four variables such as communication with supervisor, media quality communication, and organizational outlook communication were proposed and regarding learning transfer climate which is a dependent variable, four sub-parameters such as supervisor support, colleague support, transfer opportunity and organizational compensation recognition were selected. 116 copies of the statistical data excluding statistically insignificant surveys were used for 150 participants who participated in the 2015 core competency curriculum for SMEs and 3 months have passed, in order to achieve this study's objective. Meanwhile, the research hypothesis was verified with the collected data through frequency analysis, factor analysis, reliability verification, technical statistical analysis, and simple and multiple regression analysis by using the statistical package program of SPSS 20.0. Results of this study have shown that firstly, communication with supervisor, media quality communication, and organizational outlook communication all showed a positive (+) significant influence on the superior support in the influence relationship between communication type in organization and supervisor support which is learning transfer climate. Secondly, communication type in organization doesn't appear to affect colleague support of learning transfer climate. Thirdly, communication with supervisor, media quality communication, and organizational outlook except for communication with colleagues have shown a positive (+) influence on transfer opportunity in the influence relationship between communication type in organization and transfer opportunity of learning transfer climate. Lastly, communication with supervisor and communication on organizational outlook showed positive(+) influence in the influence relationship between communication type in organization and organizational compensation recognition of learning transfer climate.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.4
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• pp.63-73
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• 2018

Purpose : This study aims to verify the effects of flipped learning on self-directed learning and class satisfaction in a class of college physical therapy students. Methods : The subjects were 97 students in College A who had registered for musculoskeletal examination and assessment and practice at the second semester of 2017. All subjects were measured with the self-directed learning questionnaire for college student proposed by Lee et al., and the class satisfaction questionnaire proposed by Lee et al., before and after intervention. The collected data were processed using a computerized statistical program SPSS Win version 21.0. Mean, standard deviation, paired t-test and Cronbach's alpha coefficient were calculated. Results : The results showed significant differences in goal setting, identify resources for learning, effort attributed to results, self-reflection of self-directed learning and problem solving excellence, class methods and contents attention and understanding(p<.05), class interest of class satisfaction(p<.05). Conclusion : These results suggest that flipped learning improves learning motivation and attitudes. Therefore, follow-up study is necessary to investigate further the application of flipped learning in various students and teaching methods.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.241-248
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• 2022

The current article examines the interactions among students' attitudes to e-learning, their implementation of e-learning in their studies, and learning effectiveness. Significantly, it emphasizes the mediating role of accepting e-learning in training. It applied reliability analyses to test the measurement of items and construct validity, using the research data collected from students at Vietnam National University of Ho Chi Minh. Then, the current article used multiple regressions to inspect the causal relations; and applied procedures to investigate the mediating influence. The empirical results indicate students' attitude to e-learning positively influences their implementation of e-learning in their studies. When students apply e-learning in their studies, they likely achieve the best possible training effectiveness. Statistical evidence on the mediating role of accepting e-learning in training by students on the linkage between their attitude to e-learning and training effectiveness is revealed in this article. The findings of this article make some contributions. For educational administrators, it offers insight into the links among students' attitudes to e-learning, their implementation of e-learning in their studies, and training effectiveness, which likely allows them to establish suitable online training programs. This will be beneficial to both learners and educational institutes.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.137-141
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• 2003

LS-SVM(least squares support vector machine) is a widely applicable and useful machine learning technique for classification and regression analysis. LS-SVM can be a good substitute for statistical method but computational difficulties are still remained to operate the inversion of matrix of huge data set. In modern information society, we can easily get huge data sets by on line or batch mode. For these kind of huge data sets, we suggest an on line pruning regression method by LS-SVM. With relatively small number of pruned support vectors, we can have almost same performance as regression with full data set.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.99-116
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• 2008

This study explores the impacts of e-learning system characteristics on learner committment and satisfaction by surveying the firms utilizing e-learning systems for learning. In the study, we have, first, drawn the key factors and instruments to measure e-learning system characteristics through intensive literature review. Second, we have investigated whether the characteristics contribute to increasing learner's commitment and satisfaction. Finally, we have examined the mediating effect of learner's commitment between the characteristics of e-learning system and learner satisfaction. We have conducted a survey on the employees having experience in using e-learning systems for learning, and collected a total of 93 responses. The results of a statistical analysis show the following: First, expression and interaction affect the learner's commitment. The results indicate that a learner should engage in e-learning and ultimately be more committed on it when there is a coherence in design and organization of learning contents, and when the system offers various multimedia options including audio, sound, image, graphics, etc. Second, leaner's commitment leads to higher learning satisfaction. Finally, our results show that the commitment plays a mediating role between learner characteristics (expression, control, and trust) and learner satisfaction.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.3
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• pp.87-98
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• 2021

Due to the influence of COVID-19, many changes have been made in the education methods in universities. In respomse, this study intendsto present an efficient learning method by identifying the impact of professor images on learning immersion and the learning satisfaction of classes taught with blended learning for university students majoring in beauty at H University in Seoul. For final analysis, 232 of the 234 questionnaires administered from May 17, 2021 to June 2, 2021 were analyzed. For statistical analysis, SPSS 21.0 was utilized; frequency analysis was conducted to identify demographic characteristics, factor analysis was used to verify the research model, and regression analysis was conducted to verify the hypothesis. First, images of professors have been shown to affect learning immersion. Second, the professor image were shown to affect learning satisfaction. Third, education immersion has been shown to affect educational satisfaction. In order to overcome the limitations of online lectures in universities that suddenly began with onset of COVID-19, it is believed that students' satisfaction can be increased by applying blended learning as a way to improve the quality of classes.