• Journal of Digital Convergence
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• v.19 no.9
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• pp.67-73
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• 2021

This study aims to investigate whether differences in self-directed learning ability according to the personality types of learners occur in after-school programs and the difference in self-directed learning ability according to extroversion and introversion personality types was analyzed for 12 elementary school students in Jeollanam-do who voluntarily participate in after-school programs. As a result of this test, there was no difference in self-directed learning ability in accordance extraversion and introversion. It is judged that when elementary school students are freed from the sense of duty of passive learning participation, introverted students can also pioneer and develop learning methods suitable for them. Based on this, the limitations and implications of the study and next research direction was presented.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.361-371
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• 2021

Communication education research has focused on the effects of instructor characteristics on learning. It is necessary to consider student characteristics as well to develop an effective teaching strategy. The current study tries to classify students into multiple distinct groups depending on their personality traits and communication characteristics and investigates differences in effects of teacher characteristics between those groups. A survey on unversity students was conducted to collect data. A cluster analysis was carried out to identify distint sub-groups of respondents by their personality traits and communication characteristics. The analysis yielded two distinct groups. The two groups were named stable-reticent group', and 'neurotic-talkative group' respectivley. Series of multiple regression were carried out in order to investigate differences in the effects of instructor characteristics. The analyses found different patterns of effects between the two sub-groups. The findings suggest that it is necessary to adopt different communication styles and teaching strategies depending on student types.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.323-337
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• 2021

This study will attempt to analyze media art and discuss its main characteristics by using the concept based on Relational Aesthetics 'Affective Turn' as a basis of the theory. In addition, this study has some theoretical and practical implications, both in terms of the research and analysis of artworks and the structure development of art theories and aesthetics. To conduct the research, I have gone through a literature review on previous studies related to media art and Relational Aesthetics. Then, I have conducted a case study on the media art of TeamLab. This study shows that from the perspective of Relational Aesthetics, media art shows unique characteristics such as borderless and shareability. Moreover, it can allow the audience to actually 'feel' the relationship and integration between various objects. I hopethat this research could be used as a solid basis for future research and helpstrengthen the interaction between modern art and the public.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.387-395
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• 2021

The study looks into the prospect of expanding interdisciplinary education by examining case studies related to the subject activating economy and understanding the nature of cultural potential of different regions around Korea. The objective is to integrate regional societal for co-existence of cultural events with university being the educational entity for development. The study analyzes the internationally recognized craft event known as the Cheongju International Craft Biennale founded in 1999. For twenty years the Cheongju Industry Cultural Promotion Foundation has organized the Cheongju Craft Biennale and the study researches on the collaborative aspect between the foundation and Cheongju University's Department of Craft and Design. The value of the event is predominant and the locality has clearly been shown.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.549-563
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• 2020

Based on Deleuze's body aesthetics and from the perspective of 'deterritoraliazation', this study makes an in-depth discussion on the modern fashion design modeling by four visual characteristics: hysteria, visualization, body segmentation and becoming animals. First, hysteria embodies the strong visual effect brought by the deformation and exaggeration of clothing. Second, visualization in fashion shows the elimination or ambiguity of faces, representing the weakening of identity and the prominence of clothing and body. Third, body segmentation represents the deconstruction and reorganization of clothing, and a new way of thinking, as well. Fourth, becoming-animals are manifested in the physical mutation caused by the heterogeneous connection between humans and animals, which brings about the possibility of rethinking the body.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.259-264
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• 2021

Recently, as the number of used trading sites supporting used trading increases, users want to search for a variety of information in real time. This new change has enabled a new type of C2C (Commerce to Commerce) transaction in the e-commerce base. However, since each used trading site has its own characteristics, it is difficult to standardize the whole. Therefore, in this paper, we studied a system that provides the transaction data used by the user in real time and provides the desired information quickly. In this paper, we researched the crawler system necessary for the development of the integrated trading system for used goods through Internet e-commerce, and made it possible to provide information in the web environment desired by the user through the defined morpheme analyzer. Therefore, in this study, we designed a system that provides information desired by users without accessing various used goods sites.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.233-238
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• 2021

Recently, blockchain technology accumulates and stores all transactions. Therefore, in order to verify the contents of all transactions, the data itself is compressed, but the scalability is limited. In addition, since a separate verification algorithm is used for each type of transaction, the verification burden increases as the size of the transaction increases. Existing blockchain cannot participate in the network because it does not become a block sink by using a server with a low specification. Due to this problem, as the time passes, the data size of the blockchain network becomes larger and it becomes impossible to participate in the network except for users with abundant resources. Therefore, in this paper, we are improved transaction as studied the zero knowledge proof algorithm for general operation verification. In this system, the design of zero-knowledge circuit generator capable of general operation verification and optimization of verifier and prover were also conducted.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.251-258
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• 2021

In this paper, we proposed an encoder-decoder model utilizing residual learning to improve the accuracy of the U-Net-based semantic segmentation method. U-Net is a deep learning-based semantic segmentation method and is mainly used in applications such as autonomous vehicles and medical image analysis. The conventional U-Net occurs loss in feature compression process due to the shallow structure of the encoder. The loss of features causes a lack of context information necessary for classifying objects and has a problem of reducing segmentation accuracy. To improve this, The proposed method efficiently extracted context information through an encoder using residual learning, which is effective in preventing feature loss and gradient vanishing problems in the conventional U-Net. Furthermore, we reduced down-sampling operations in the encoder to reduce the loss of spatial information included in the feature maps. The proposed method showed an improved segmentation result of about 12% compared to the conventional U-Net in the Cityscapes dataset experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.88-95
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• 2021

This study aims to provide implications for establishing support policies for students by empirically analyzing data on university students dropouts. To this end, data of students enrolled in D University after 2017 were sampled and collected. The collected data was analyzed using topic modeling(LDA: Latent Dirichlet Allocation) technique, which is a probabilistic model based on text mining. As a result of the study, it was found that topics that were characteristic of dropout students were found, and the classification performance between groups through topics was also excellent. Based on these results, a specific educational support system was proposed to prevent dropout of university students. This study is meaningful in that it shows the use of text mining techniques in the education field and suggests an education policy based on data analysis.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.415-423
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• 2021

This study is to analyze works of Memphis design in the 1980s, which captured the appearance of a diversified society since the 20th century, and to present practical designs that can communicate with the public through the formulation of indoor lighting. As a research method, the background of the occurrence of Memphis groups, the theoretical background and the formative features of Memphis designs are considered around literature and prior research. The research applied Memphis's formative characteristics, colors and patterns to incorporate newly formulated designs into lighting. Lighting lamps in the forms that have made small changes to basic shapes show not only its functionality and decorability, but also its scalability as a formative language that conveys the emotions contained within humans. In addition, the choice of materials according to the changes in sculpture in the production of the work will suggest the possibility of creating a new formative art.