• Journal of The Korean Association For Science Education
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• v.31 no.2
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• pp.239-255
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• 2011

As a case study on the use of coteaching in science instruction for science-gifted elementary students, this paper analyzed the characteristics of coteaching science instruction for science-gifted elementary students by plan, performance, and reflection-evaluation stages of the classes. To do this, we observed two teachers' coteaching science instruction for science-gifted elementary students during twelve classes and analyzed the taped videos, their journals, and the transcripts for in-depth interviews with them. The results indicated that the characteristics of the coteaching science instruction, in the planning stage of the classes, showed improvement in the quality of the sciencegifted education programs, the reduction of the psychological burdens of developing the programs, and some efficiency loss due to the joint preparation of the classes. The characteristics in the performance stage of the classes include the seamless progression of the classes through the division of roles, the increase of the students' opportunity to explore, the supplement of the teachers' inadequate descriptions and the overlooked contents, the increase of the interaction between teachers and students and/or the interaction among students, the reduction of the risk of accidents in experiments, and the reduction of the responsibility for teaching. Finally, the characteristics in the reflectionevaluation stage of the classes could be attributed to the diversity of the evaluation viewpoints, the increase of the learning opportunities to develop the teaching professionalism, and the increase of the fear for assessing my own classes.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.53-63
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• 2015

Singing voice synthesis is the generation of a song using a computer given its lyrics and musical notes. Hidden Markov models (HMM) have been proved to be the models of choice for text to speech synthesis. HMMs have also been used for singing voice synthesis research, however, a huge database is needed for the training of HMMs for singing voice synthesis. And commercially available singing voice synthesis systems which use the piano roll music notation, needs to adopt the easy to read standard music notation which make it suitable for singing learning applications. To overcome this problem, we use a speech database for training context dependent HMMs, to be used for singing voice synthesis. Pitch and duration control methods have been devised to modify the parameters of the HMMs trained on speech, to be used as the synthesis units for the singing voice. This work describes a singing voice synthesis system which uses a MusicXML based music score editor as the front-end interface for entry of the notes and lyrics to be synthesized and a hidden Markov model based text to speech synthesis system as the back-end synthesizer. A perceptual test shows the feasibility of our proposed system.

• Journal of the Korean School Mathematics Society
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• v.10 no.2
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• pp.149-171
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• 2007

This study is aimed at development of pedagogical content knowledge on fraction in the elementary school mathematics. Elementary students regard fraction as the difficult topic in school mathematics. Furthermore, fraction is the fundamentally important concept in studying mathematics. So it is important to develop the pedagogical content knowledge on fraction. The reason of attention to the pedagogical content knowledge is that improving the quality of teaching is the central focus of a high quality mathematics education. Shulman suggested that various knowledges are required for teacher to improve their classes. Of course, pedagogical content knowledge is the most valuable in teaching mathematics. Pedagogical content knowledge is related to the promotion of students' understanding about the learning. Pedagogical content knowledges are categorized by five factors in this study. These are understanding about curriculum, understanding about students and students' knowledge, understanding about teachers and teachers' knowledge, understanding about the methods, contents, and management of class, and understanding about methods of assessments. I develop the pedagogical content knowledge on fraction according to the these categories. I concentrate on the two types of pedagogical content knowledges in developing. That is, I present knowledges which teachers have to know for teaching fraction effectively and materials which teachers can use during the teaching fraction. Pedagogical content knowledges guarantee teachers as the professionalists. Teachers should not teach only content knowledges but teach various knowledges including the meta-knowledges which have relation to fraction.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.355-362
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• 2018

This study aims to examine the relationship between physical education class activity of youth, smartphone dependence and school life adaptation. The data set of Korean Children and Youth Panel Survey(KCYPS) by National Youth Policy Institute was reanalyzed for this study. The subjects of this study were 2,351 second grade middle school students from 2011. The data were coded with the use of the statistics program on Windows, SPSS 23.0. To analyse the data, descriptive analysis, reliability analysis, one-way ANOVA and regression analysis were employed. The findings of this research are as follows. First, the difference between the activity hours of youth physical education classes and the reliance on smartphones is less dependent on smartphones as they participate enthusiastically in physical education classes. Second, the difference of physical education class activity time and school life adaptation among adolescents was more positive for school life adaptation as learning activity, peer relationship and teacher relationship were more active. third, the dependence of youth on smartphones has a positive effect on learning activities and school rules as the reliance on smartphones is low.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.159-173
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• 2017

In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.

• Journal of the Korean Society of Radiology
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• v.3 no.1
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• pp.29-39
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• 2009

In this paper has proposed to the recognition of the disease on medical images using neural network. The neural network is constructed as three-layers of the input-layer, the hidden-layer and the output-layer. The training method applied for the recognition of disease region is adaptive error back-propagation. The low-frequency region analyzed by DWT are expressed by matrix. The coefficient-values of the characteristic polynomial applied are n+1. The normalized maximum value +1 and minimum value -1 in the range of tangent-sigmoid transfer function are applied to be use as the input vector of the neural network. To prove the validity of the proposed methods used in the experiment with a simulation experiment, the input medical image recognition rate the evaluation of areas of disease. As a result of the experiment, the characteristic polynomial coefficient of low-frequency area matrix, conversed to 4 level DWT, was proved to be optimum to be applied to the feature parameter. As for the number of training, it was marked fewest in 0.01 of learning coefficient and 0.95 of momentum, when the adaptive error back-propagation was learned by inputting standardized feature parameter into organized neural network. As to the training result when the learning coefficient was 0.01, and momentum was 0.95, it was 100% recognized in fifty-five times of the stomach image, fifty-five times of the chest image, forty-six times of the CT image, fifty-five times of ultrasonogram, and one hundred fifty-seven times of angiogram.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.893-914
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• 2016

This paper describes the development of an inquiry-based fieldwork program based on Yangdong village where students explore the ways that it can develop in a sustainable way. Important considerations in an inquiry-based fieldwork design include what the key inquiry questions should be, the geographical issues of fieldwork location, the potential roles of mobile technologies, design of learning activities and a final product, and the roles of a teacher. Student fieldwork activities, including mapping land-use changes at the building level, detecting what should be changed or remain the same, and conducting interview with residents to examine their perceptions of overall tourism impacts, are supported by mobile technologies (i.e., the Collector for ArcGIS and the Google Forms). Twenty one high school students participated in a field test of the program in February 2016, which allowed authors to evaluate the program. Students' pre-, in-, and post-fieldwork activities were observed and the data and final products which they gathered and producted were analyzed. The post-program survey indicated that the students deepened and expanded their understanding of Yangdong village and expressed their satisfaction with the program in general. Incorporating mobile technologies into inquiry-based geographical fieldwork can help students involved in collaborative problem solving and creative activities in real world settings and create a shareable multimodal product combining maps, photo, and text.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.664-673
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• 2008

Recently, the ubiquitous is handled by maximum topic. New knowledge information and ubiquitous computing evolution have promoted new paradigm transfer and grand change. Also, need technology as powerful engineering approached fairly system and educational guidance side examination necessarily to overcome u-Learning base situation and studying obstacle situations. This treatise embodied handiness examination about attention shortage and excess obstacle (Attention Deficit Hyperactivity Disorder, low ADHD) who must solve so as to be square and level being increase trend in primary school using USB (Universal Serial Bus) terminal system that allow fetters to OSGi (Open Service Gateway Initiative). That OSGi base USB terminal system is easy preservation of information, safety of network, cost-cutting and maintenance by various ubiquitous system that server that load many USB terminals and OSGi uses an USB bus of high speed and construct network, there is advantage of concentration elevation and so on of week and ADHD handled in this treatise because early diagnosis and treatment are serious. The confirmed system application that can supplement paper and pens examination's shortcoming and could solve examination's problem which use computer, and help in student guidance through ADHD simpleexamination who utilize OSGi base USB terminal system. Is available by game system that system for human nature examination or intelligence test and general exam explaining and level studying, order style question investigation program, studying system for disabled person, majority that enforce in public in school this study finding does together.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.741-750
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• 2021

School violence has long been recognized as a social problem, and various efforts have been made to prevent it. In this study, we propose a system that can prevent school violence by analyzing data on the frequency of conversations between students, friendship and preference to be in the same group. This data was quantified using a Likert scale questionnaire, and also grouped into the appropriate number of clusters using the K-means algorithm. Additionally, the homeroom teacher observed the frequency and nature of conversations between students, and targeted specific individuals or groups for counseling and intervention, with the aim of reducing school violence. Data analysis revealed that the teachers' qualitative observations were consistent with the quantified data based on student questionnaires, and therefore applicable as quantitative data towards the identification and understanding of student relationships within the classroom. The study has potential limitations. The data used is subjective and based on peer evaluations which can be inconsistent as the students may use different criteria to evaluate one another. It is expected that this study will help homeroom teachers in their efforts to prevent school violence by understanding the relationships between students within the classroom.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.53-59
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• 2021

In this paper, we propose a BERGPT-chatbot, a domestic AI chatbot that can alleviate negative emotions based on text input such as 'Replika'. We made BERGPT-chatbot into a chatbot capable of mitigating negative emotions by pipelined two models, KR-BERT and KoGPT2-chatbot. We applied a creative method of giving emotions to unrefined everyday datasets through KR-BERT, and learning additional datasets through KoGPT2-chatbot. The development background of BERGPT-chatbot is as follows. Currently, the number of people with depression is increasing all over the world. This phenomenon is emerging as a more serious problem due to COVID-19, which causes people to increase long-term indoor living or limit interpersonal relationships. Overseas artificial intelligence chatbots aimed at relieving negative emotions or taking care of mental health care, have increased in use due to the pandemic. In Korea, Psychological diagnosis chatbots similar to those of overseas cases are being operated. However, as the domestic chatbot is a system that outputs a button-based answer rather than a text input-based answer, when compared to overseas chatbots, domestic chatbots remain at a low level of diagnosing human psychology. Therefore, we proposed a chatbot that helps mitigating negative emotions through BERGPT-chatbot. Finally, we compared BERGPT-chatbot and KoGPT2-chatbot through 'Perplexity', an internal evaluation metric for evaluating language models, and showed the superity of BERGPT-chatbot.