• Journal of The Korean Association of Information Education
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• v.7 no.2
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• pp.199-206
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• 2003

XML is becoming a new developing tool of web technology because of its ability of data management and flexibility in data presentation. So it's well researched that the reusability and integration with learning objects such as text, image, sound, video and plug-in programs of web contents in computer education. But the research for storing, extracting and integrating metadata about learning object was needed prior to implementing online learning system to integrate and manage it. Therefore this study propose a new method of using web service of DBMS for extracting learning object's metadata in database server which located in 3-tier system. To evaluate the efficiency of proposed method, The test server and two DBMSs(MS SQL Server 2000 and Oracle 9i) which have 30 metadata was implemented and the response time of it was measured. The response time of it was short, but in order to using this method the additional programming with SAX/DOM was necessary.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4543-4549
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Burr distribution applied to distribution was based on finite failure NHPP. 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. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.293-302
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• 2008

Multiculuralism becomes the presentive term of Korea. And school is interested in multicutural education very much. The reason for this is connected to the fact of increasing intermarriages, immigrant laborers, and their children. So, the academic world is producing various research papers and public institution is proposing and practicing several policies. Particularly multicultural education is recognized as the very important intervening strategy on multicutral society and studied. The purpose of this paper is to suggest the ideas of teaching-learning experience selection for multicutural education in Korea. So the study contents of this paper are as follows ; First, it is to analyze the concepts of multicultural education and its' research trends. Second, it is to review the prior models of theorizing multicultural education and the models of curriculum development and teaching design. Finally, it is to inquiry the model of teaching-learning experience selection for multicutural education. Above all, we think that it is necessary to develop the model of multicutural teaching-learning experience selection classified by objects involved in multicutural education.

• Journal of the Korean Chemical Society
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• v.46 no.4
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• pp.377-384
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• 2002

In this study, the effect of cooperative computer-assisted instruction upon students' conceptual under-standing,application ability, and learning motivation were investigated by a previous achievement level. The treatment and the control groups (2 classes) were selected from a middle school in Seoul, and taught about the motion of molecule for 5 class periods. Prior to the instructions, a learning motivation test was administered and used as covariate. The scores of a previous achievement test were also used as covariate. The scores of the mid-term science examination were used as blocking variable. After the instructions, the conceptions test, the application test, and the learning motivation test were administered. Two-way ANCOVA results revealed that there were no significant differences in the scores of the con-ceptions test and the application test. However, the scores of the treatment group were found to be significantly higher than those of the control group in the learning motivation test.

• Convergence Security Journal
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• v.13 no.1
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• pp.71-78
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• 2013

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The doubly bounded power law distribution model makeup Weibull distribution applied to distribution was based on finite failure NHPP. 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. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• Convergence Security Journal
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• v.11 no.1
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• pp.25-32
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Weibull distribution applied to distribution was based on finite failure NHPP. 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. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R_{sq}$.

• Convergence Security Journal
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• v.12 no.3
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• pp.19-26
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• 2012

In this study, software products developed in the course of testing, software managers in the process of testing software and tools for effective learning effects perspective has been studied using the NHPP software. The log type hazard function applied to distribution was based on finite failure NHPP. 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. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$(coefficient of determination).

• Journal of Korean Medical Science
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• v.33 no.43
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• pp.239.1-239.12
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• 2018

Background: We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system. Methods: A 5-step retinal fundus image reading tool was developed that rates image quality, presence of abnormality, findings with location information, diagnoses, and clinical significance. Each image was evaluated by 3 different graders. Agreements among graders for each decision were evaluated. Results: The 234,242 readings of 79,458 images were collected from 55 licensed ophthalmologists during 6 months. The 34,364 images were graded as abnormal by at-least one rater. Of these, all three raters agreed in 46.6% in abnormality, while 69.9% of the images were rated as abnormal by two or more raters. Agreement rate of at-least two raters on a certain finding was 26.7%-65.2%, and complete agreement rate of all-three raters was 5.7%-43.3%. As for diagnoses, agreement of at-least two raters was 35.6%-65.6%, and complete agreement rate was 11.0%-40.0%. Agreement of findings and diagnoses were higher when restricted to images with prior complete agreement on abnormality. Retinal/glaucoma specialists showed higher agreements on findings and diagnoses of their corresponding subspecialties. Conclusion: This novel reading tool for retinal fundus images generated a large-scale dataset with high level of information, which can be utilized in future development of machine learning-based algorithms for automated identification of abnormal conditions and clinical decision supporting system. These results emphasize the importance of addressing grader variability in algorithm developments.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.115-120
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• 2019

This study aims to prove the value of convergence-based mobile English curriculum for English education prior to its practical use. This is deferent from the existing studies in developing and studying a curriculum using an English program loaded in mobile to make an effective English learning. In order to find out how well teachers are aware of this curriculum, we performed qualitative researches. Some English teachers asked for feedback about the curriculum gave us positive feedback in most areas such as learning authentic English, repetition effects, cooperative learning, self-efficacy experience, and so on. As a negative feedback, they were afraid of students' easy and free attitudes because of the new learning environments. This problem can be solved by the very close communications between teacher and student through on and off line. Next time applying this curriculum to the field and analyzing will be expected.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1615-1622
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• 2022

In order to overcome the limitations of the instructor-centered lecture-style teaching method, recently, flipped learning, a learner-centered teaching method, has been widely introduced. However, despite the many advantages of flipped learning, there is a problem that students cannot solve questions that arise during prior learning in real time. Therefore, in order to solve this problem, we developed DBbot, an assistant chatbot for database design course managed in the flipped learning method. The DBBot is composed of a chatbot app for learners and a chatbot management app for instructors. Also, it's implemented so that questions that instructors can anticipate in advance, such as questions related to class operation and every semester repeated questions related to learning content, can be answered using Google's DialogFlow. It's implemented so that questions that the instructor cannot predict in advance, such as questions related to team projects, can be answered using the question/answer DB and the BM25 algorithm, which is a similarity comparison algorithm.