• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.5
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• pp.165-173
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• 2017

In this research, based on the CBAM model, there is a research purpose to measure the degree of interest of the physical education teacher ahead of execution of the revised educational curriculum 2015 and to analyze the difference in degree of interest by teacher's background variation. For this reason, we conducted an an- nental survey of 200 physical education teachers in K-area middle school, high schools and analyzed the results. The conclusion of this research is as follows. Firstly, as a whole, the attention to the revised education curriculum has been very high in view, as a result, the physical education teacher at the middle / high school, 2015 about the influence and the result that the revised curriculum gives to the student in the physical education class Although the interest is very high, a systematic approach will be necessary for training and utilization schemes so that 2015 the revised educational curriculum can be executed appropriately. Secondly, since the interest in the revised educational curriculum by the whole number of classes 2015 is different, we need to develop and give a training program for revised curriculum 2015 customization by class number 2015. Training that departs from the one-way set form of transmission training and distribution method of materials depending on the class number may be different. Thirdly, in order to stabilize the revised educational curriculum 2015, it is necessary to develop a course example program corresponding to the level of interest of the physical education teacher.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.367-377
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• 2016

The purpose of the projects for strengthening the Service Business Competitiveness, which had been sponsored by the Ministry of Trade, Industry and Energy, and managed by the NIPA, is to support for combining the whole business process of the SMEs with the business model considering the scientific aspects of the services, to enhance the productivity of them and to add the values of their activities. 5 organizations are selected in 2014, and 4 in 2015 as leading organizations for these projects. This study analyzed the efficiency of these projects using DEA. Throughout the analysis of the prior researches, this study used the amount of government-sponsored money as the input variable, and the number of new customer business, the sales revenue, and the number of new employment as the output variables. And the result of this analysis showed that the decision making unit 12, 15, and 21 was efficient. And from this study, we found out two more performance indicators such as, the number of new employment and the amount of sales revenue, besides the number of new customer businesses.

• Trans-
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• v.15
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• pp.81-104
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• 2023

This paper analyzes the danmu phenomenon with the concept of participatory culture proposed by Henry Jenkins. Unlike other comments, Danmu is a function that allows users to post anonymously while watching a video, and comments posted at that time are immediately displayed on the screen and can be viewed by other viewers. The service was first launched by Niconico. In this paper, the danmu phenomenon in the Chinese video platform Bilibili is analyzed by focusing on three aspects. First, in terms of creative sharing under collective intelligence, we explore how users create their own creations and share them with other users through danmu. Second, in the collaboration model under public participation, the method and meaning of collective cooperation through users' interaction is dealt with. Third, in terms of financial support of commercial capital, the influence of danmu videos to create commercial profits is analyzed as a case. In addition, the negative aspects and challenges of participatory culture in Bilibili are analyzed. Negative aspects such as participation gap, copyright infringement, excessive use of danmu and problems of anonymity were reviewed, and major challenges to realize the potential of danmu as a participatory culture were suggested. This paper comprehensively analyzes danmu using research methods such as literature review and case studies, and through this, tries to derive insights on how participatory culture and danmu interact and evolve in modern society. Danmu, as a participatory medium, is an important tool that promotes individual and collective creation and interaction, and is pioneering a new boundary between the media industry and its users.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.143-156
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• 2023

To precisely and reliably analyze the contents of the satellite imagery, recognizing the clouds which are the obstacle to gathering the useful information is essential. In recent times, deep learning yielded satisfactory results in various tasks, so many studies using deep neural networks have been conducted to improve the performance of cloud detection. However, existing methods for cloud detection have the limitation on increasing the performance due to the adopting the network models for semantic image segmentation without modification. To tackle this problem, we introduced the multi-branch neural architecture search to find optimal network structure for cloud detection. Additionally, the proposed method adopts the soft intersection over union (IoU) as loss function to mitigate the disagreement between the loss function and the evaluation metric and uses the various data augmentation methods. The experiments are conducted using the cloud detection dataset acquired by Arirang-3/3A satellite imagery. The experimental results showed that the proposed network which are searched network architecture using cloud dataset is 4% higher than the existing network model which are searched network structure using urban street scenes with regard to the IoU. Also, the experimental results showed that the soft IoU exhibits the best performance on cloud detection among the various loss functions. When comparing the proposed method with the state-of-the-art (SOTA) models in the field of semantic segmentation, the proposed method showed better performance than the SOTA models with regard to the mean IoU and overall accuracy.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.349-355
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• 2023

This study attempted to investigate the effect of competitive anxiety on injury psychology according to the athletic career of tennis athletes at Chinese universities. To study the method, 208 athletes enrolled in a four-year university (0 university, 0 university) located in A City, Hanam Province, were surveyed for a total of three weeks from the end of January to the beginning of February 2023. To verify the research model, frequency analysis, exploratory factor analysis, reliability analysis, and correlation analysis were conducted using SPSS Statistics 25. And independent sample t-test and one-way ANOVA were conducted to find out the differences in variables according to general characteristics, and multiple regression analysis was conducted to verify hypotheses through the concept of measurement. As a result of the study, first, it was found that there was a significant difference in the athletic career of tennis athletes at West China University. Second, the non-standardized coefficient of competition anxiety was found to have a positive (+) effect on exercise weaponry. Third, the non-standardized coefficient of competition anxiety was found to have a positive (+) effect on anxiety and anxiety. Therefore, it was found that other competitive anxiety in the exercise career had an effect on injury psychology. Since competition anxiety according to the athletic career of tennis athletes at Chinese universities affects injury psychology, it suggests that a psychological program that can control competition anxiety and injury psychology of athletes should be developed and introduced to athletes.

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.367-390
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• 2008

The primary purpose of this study is to investigate the college students' implicit theory of Korean creativity. This study deals with the degree to which the students exploit the creativity, and the obstacles for them to exploit the creativity. Another purpose of this study is to explore their implicit knowledge of Korean creative environments. The results are as follows. The implicit knowledge of Korean creativity could be characterized by the following key words: 'flexibility', 'application', 'transformation', 'originality', 'perseverance', 'not being stereotyped', 'esthetic flavor' and 'understanding-new-by-exploring-old'. Students thought themselves to be more or less creative. Students in art and physical education, and male students estimated themselves more creative than other discipline and female. They thought that socio-institutional factors such as educational system focused on the college entrance test are the most serious obstacles against creativity. About half of the students thought the creative persons would have been raised in poor family whereas other students thought differently. The home environment of the creative person was thought to be characterized by the words such as democratic, free and encouraging. Creative persons were thought to be maladaptive school life, but good at peer relations. This study will be used as a pioneer research which suggest a model of Korean creativity.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.285-294
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• 2024

This study aims to enhance learners' creative and integrative thinking through the use of a practical music education program, facilitating high-quality artistic activities and the integration of various disciplines. To achieve this, a practical music education program incorporating the PDIE model was designed, and the content validity of the developed program was verified. Through this process, We have researched and described methodologies for multidisciplinary research that can be applied in practical music education. This paper focuses on the fourth session of the study, which deals with the creative and integrative education of practical music and mathematics. The mathematical theory of interest in this research is the Fibonacci sequence, fundamental to the golden ratio in art. The goal is to enable balanced and high-quality creative activities through learning and applying the Fibonacci sequence. Additionally, to verify the validity and effectiveness of the instructional plan, including the one used in the 15-week course, we have detailed the participants involved in the content validation, the procedures of the research, the research tools used, and the methods for collecting and analyzing various data. Through this, We have confirmed the potential of creative and integrative education in higher practical music education and sought to develop educational methodologies for cultivating various creative talents in subsequent research.

• Publications of The Korean Astronomical Society
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• v.34 no.3
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• pp.31-40
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• 2019

We study the internal structure under the artificial mountain of Heumkyeonggak-nu, a Korean water-powered clock in the early Joseon dynasty. All the puppets on the artificial mountain are driven by the rotational force generated by the water wheel at their designated time. We design a model that work with three parts of the artificial mountain. At the upper part of the artificial mountain to the east, west, north and south, there are four puppets called the Four Mystical Animal Divinity and four ladies called the Jade Lady respectively. The former rotates a quarter every double hour and the latter rings the bell every hour. In the middle part of this mountain is the timekeeping platform with four puppets; the Timekeeping Official (Hour Jack), the Bell-, Drum-, and Gong-Warriors. The Hour Jack controls time with three warriors each hitting his own bell, drum, and gong, respectively. In the plain there are 12 Jade Lady puppets (the lower ladies) combined with 12 Oriental Animal Deity puppets. In his own time a lady doll pops out of the hole and her animal doll gets up. Two hours later, the animal deity lies down and his lady hides in the artificial plain. These puppets are regularly moved by the signal such as iron balls, bumps, levers, and so on. We can use balls and bumps to explain the concept of the Jujeon system. Iron balls were used to manipulate puppets of the timekeeping mechanism in Borugak-nu, another Korean water-powered clock in Joseon dynasty, which was developed earlier than Heumgyeonggak-nu. According to the North Korea's previous study (Choi, 1974), it is obvious that bumps were used in the internal structure of Heumgyeonggak-nu. In 1669, The armillary clock made by Song, I-young was also utilized bumps. Finally we presented mock-ups of three timekeeping systems.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.999-1011
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• 2008

To most of the students studying fashion related major, the graduation fashion show is a big challenge. They have to put together all they learn and show what they can do to their future employers. They design, pattern work, and make up garments for the show all by themselves. Unfortunately. while they make up their garments, they usually don't Dow exactly body measurements of the models. So quite often they have to alter their art works up to the last minute of the fashion show opening. Sometimes such unadequate work process ruins their work. The purpose of this study is to suggest block patterns of Korean fashion models measurements for basic items, such as jacket and pants for male models and torso length block pattern, skirt and pants for female models. 20 male and 20 female professional models were measured. The block patterns were based on their measurements. After the first fitting test, patterns were corrected by their body characteristic. For both male and female models, it was found desirable to fix the shoulder width and make an adjustment to the patterns with a deviation of width and girth items. In case of the resultant patterns the satisfaction was made better. Model sizes proposed in this study are considered closer to the size of average models, since they were based on A-grade models who are currently working in Korea. The resultant patterns can be produced by simply making a slight adjustment to the width of the proposed pattern in this study.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.