• Journal of Dental Rehabilitation and Applied Science
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• v.33 no.2
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• pp.88-96
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• 2017

Purpose: The purpose of this study is to assess the relationship between the time spent designing custom abutments and repeated learning using dental implant computer aided design (CAD) software. Materials and Methods: The design of customized abutments was performed four stages using the 3DS CAD software and the EXO CAD software, and measured repeatedly three times by each stage. Learning effect by repetition was presented with the learning curve, and the significance of the reduction in the total time and the time at each stage spent on designing was evaluated using the Friedman test and the Wilcoxon signed rank test. The difference in the design time between groups was analyzed using the repeated measure two-way ANOVA. Statistical analysis was performed using the SPSS statistics software (P < 0.05). Results: Repeated learning of the customized abutment design displayed a significant difference according to the number of repetition and the stage (P < 0.001). The difference in the time spent designing was found to be significant (P < 0.001), and that between the CAD software programs was also significant (P = 0.006). Conclusion: Repeated learning of CAD software shortened the time spent designing. While less design time on average was spent with the 3DS CAD than with the EXO CAD, the EXO CAD showed better results in terms of learning rate according to learning effect.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.689-699
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• 2018

The purpose of this study was to investigate the prediction of self-regulated learning, GRIT and parents support on computational thinking and learning satisfaction in online software education. The participants were 71 elementary students who attended to an online software education which K university offered in Spring 2018. The 63 of cases were used to analyze by SPSS. The key findings were as follows: First, self-regulated learning and GRIT significantly predicted computational thinking. Second, self-regulated learning and GRIT significantly predicted learning satisfaction. This research suggested the implications for computational thinking and learning satisfaction in online software education.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.635-642
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• 2018

In the Era of the Fourth Industrial Revolution, we live in huge amounts of software. However, as software increases, software vulnerabilities are also increasing. Therefore, it is important to detect and remove software vulnerabilities. Currently, many researches have been studied to predict and detect software security problems, but it takes a long time to detect and does not have high prediction accuracy. Therefore, in this paper, we describe a method for efficiently predicting software vulnerabilities using machine learning algorithms. In addition, various machine learning algorithms are compared through experiments. Experimental results show that the k-nearest neighbors prediction model has the highest prediction rate.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.161-168
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• 2017

In this paper, we propose a Software Education Program for the Education Welfare Priority Support students. Elementary school students of education welfare priority support programs has low school satisfaction level and course maturity. Also, they have various problem such as relatively large digital divide when compared to general student. To solve such problem, we designed, developed, and applied a software education program on education welfare priority support program's elementary school students to analyze its effect on their learning motivation, self-efficacy, and goal orientation. Software education program followed the main stages of ADDIE model and was designed into experience Sharing, Requirements analysis, Sharing, Grouping, and Organizing. 20 of 6th graders in education welfare priority support programs were chosen as subject for software education program. The effectiveness has been analyzed through pre, and pro test. As a result of the analysis, we found that the developed software education program has meaningful effect on Learning Motivation, Self-efficacy, and Goal Orientation of education welfare priority support program's elementary students.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.9-17
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• 2005

In this paper we developed e-Leaning system based on open source software. We selected the Moodle that after compared the open source learning management systems. Moodle is LAMP(Linux, Apache, MySQL, PHP) based course management system (CMS), a software package designed to help educators create quality online courses. One of the main advantages of Moodle over other systems is a strong grounding in social constructionist pedagogy. Also we integrated Moodle and legacy systems such as streaming service, webhard service, and short message service. The system operated during one semester at college using blended learning model. We had obtained showed that the students had almost all scored quite highly as preferred learning environment through COLLES(Constructivist On-Line Learning Environment Survey) and ATTLS(Attitudes to Thinking and Learning Survey). Therefore this research showed that open source based e-Loaming system is stable and possible.

• KSCI Review
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• v.14 no.1
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• pp.185-196
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• 2006

IIn this paper, we developed e-Leaning system based on open source software. We selected the Moodle that after compared the open source learning management systems. Moodle is APM(Apache, PHP, MySQL) based learning management system(LMS) support SCORM(Sharable Content Object Reference Model), a software package designed to help educators create quality online courses. One of the main advantages of Moodle over other systems is a strong grounding in social constructionist pedagogy. Also we integrated Moodle and legacy systems such as streaming service, webhard service, and short message service. Therefore this research showed that open source based e-Learning system include learning management system is stable and possible.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.7
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• pp.353-360
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• 2017

In this study, a software education program based on blended learning using scratch was designed for pre-service elementary teachers' software education. Software education program was applied to experimental group and control group within the university of education using Scratch programming for 12 weeks. Blended learning using online lectures was applied to experimental group. The pre-service teachers' recognition about software education and self-evaluation of computational thinking were performed. Then, we analyzed the effect of the developed education program on the recognition of software education and computational thinking. As a result, the level of post-recognition of software education in the experimental group was significantly higher than that of the pre-recognition. In the self-evaluation of computational thinking, the experimental group was significantly higher than the control group. Therefore, it can be seen that the software education program based on blended learning can help improve the learner's computational thinking.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1357-1363
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• 2018

In addition to advances in information technology, machine learning approach is applied to a variety of applications, and is expanding to a variety of areas. In this paper, we propose a software analysis method that applies linear regression to analyse software similarity from the code distribution of the software. The characteristics of software can be expressed by instructions contained within the program, so the distribution information of instructions is used as learning data. In addition, a learning procedure with the learning data generates a linear regression model for software similarity analysis. The proposed method is evaluated with real world Java applications. The proposed method is expected to be used as a basic technique to determine similarity of software. It is also expected to be applied to various software analysis techniques through machine learning approaches.

• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.3-12
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• 2014

Quick and accurate learning of diverse electronic products has become an important daily task. In particular, software occupies core status in the control and operation of the products. This research tested the effects of learning method, schedule, and task difficulty in the learning of software. Using 2 (learning method: experiential vs. verbal) ${\times}$ 2 (learning schedule: spaced vs. massed) ${\times}$ 2 (difficulty: easy vs. difficult) between-subjects design, Experiment 1 tested participants' learning of file control using Windows Movie Maker. There was no effect of learning schedule on task completion time, but participants in experiential learning were faster in the completion of evaluation task compared with those in verbal learning condition. Importantly, as task difficulty increases participants in verbal condition showed markedly lower performance than those in experiential condition, which suggests that experiential learning is more effective with more difficult learning task. That is, in case of learning simple operation of software verbal learning using linguistic manual or instruction could be sufficient; on the other hand in case of learning complex operation learning from experience or tutorial mode would be more effective. Additional studies which manipulated task difficulty (Expt. 2) and inter-trial learning interval (Expt. 3) did not produce meaningful results.