• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.354-360
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• 2021

People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.267-275
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• 2020

Even ordinary-looking plays can have a profound meaning. Based on this assumption, Eugene Pink (1960) has established an analytical model of play with five elements, namely "delight", "meaning", "community", "rules" and "tools." It was an effort to reflect on the true meaning of play beyond the cortical entertaining nature of play. In this study, it was carried out that all the texts containing images and performance from the EBS character "Pengsu" were selected, since he emerged as a new star in 2019. And also his play structure was analyzed by applying the Pink's model. As a result, Pengsu's play structure was confirmed to be systematic and complete as a play prototype because it was well-organized with five elements of play. It was regarded as a successful character that skillfully attracts participants to the play world. Among the components of the play, "fun" was found to be his funny appearance, sudden and unconventional behavior, "meaning" was the elimination of authoritarianism, self-esteeming and energizing, "community" was a multi-platform media user who crossed off-on-line, analog-digital-line, "rules" was to set his concept fixed as a young stranger with an ego to unreveal his identity, and "tools" was shown as his character itself and continual discourse. It shows that until now, Pengsu has a social net function of quite spreading the positive meaning of encouragement and comfort, advice and guide, consideration and forgiveness, introspection and nirvana to all members of our society, including the youth who are struggling with uncertainty and anxiety by showing rather exaggerated and stimulating performance that precisely combines these play elements.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.175-187
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• 2020

The purpose of this study is to discuss the elements and meanings of the performative scenography which has been revealed through the new directorial interpretation and deconstruction process of the musical 『All Shook Up』. The performative scenography characteristics after postmodernism aim to create individual active perceptions and various social meanings through audience's voluntary and particular emergence. To this end, the theoretical foundation of scenography was examined by periods in advance. Based on this, I attempted to establish performative scenography for synthesized scenic and media design through the reconstruction process for the 『All Shook Up Travelers』. As a result, I set up visual narrative based world of 『All Shook Up Travelers』 which was produced by text-based intense images for a direct medium in order to expand actors' inner narrative and established unique performative scenography of its own: 1. enhancing the adapted one's narratives for the actors' and audience's co-existence and detachment, 2. delivering its own independent meanings which have double meanings, 3. encouraging audience's critical and active perception experiences through collage and montage of media.

• Journal of Korean Elementary Science Education
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• v.41 no.2
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• pp.307-324
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• 2022

This study examined the content diversity of seven authorized science textbooks by comparing the characteristics of the science concept description and the contents of inquiry activities in the "weight of objects" unit. For each textbook, the flow of concept description content and the uniqueness of the concept description process were analyzed, and the number of nodes and links and words with high connections were determined using language network analysis. In addition, for the inquiry activities described in each textbook, the inquiry subject, inquiry type, science process skill, and uniqueness were investigated. Results showed that the authorized textbooks displayed no more diversity than expected in their scientific concept description method or their inquiry activity composition. The learning elements, inclusion of subconcepts, and central words were similar for each textbook. The comparison of inquiry activities showed similarities in their contents, inquiry types, and scientific process skills. Specifically, these textbooks did not introduce any research topics or experimental methods that were absent in previous textbooks. However, despite the fact that the authorized textbook system was developed based on the same curriculum, some efforts were made to make use of its strengths. Since the sequence of subconcepts to explain the core contents differed across textbooks, this explanation process was divided into several types, and although the contents of inquiry activities were the same, the materials for inquiry activities were shown differently for each textbook to improve and overcome the difficulties in the existing experiments. These findings necessitate the continuation of efforts to utilize the strengths of certified textbooks.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.325-330
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• 2022

This paper conducts the collection and experiment of datasets for deep learning research on sign language such as sign language recognition, sign language translation, and sign language segmentation for Korean sign language. There exist difficulties for deep learning research of sign language. First, it is difficult to recognize sign languages since they contain multiple modalities including hand movements, hand directions, and facial expressions. Second, it is the absence of training data to conduct deep learning research. Currently, KETI dataset is the only known dataset for Korean sign language for deep learning. Sign language datasets for deep learning research are classified into two categories: Isolated sign language and Continuous sign language. Although several foreign sign language datasets have been collected over time. they are also insufficient for deep learning research of sign language. Therefore, we attempted to collect a large-scale Korean sign language dataset and evaluate it using a baseline model named TSPNet which has the performance of SOTA in the field of sign language translation. The collected dataset consists of a total of 11,402 image and text. Our experimental result with the baseline model using the dataset shows BLEU-4 score 3.63, which would be used as a basic performance of a baseline model for Korean sign language dataset. We hope that our experience of collecting Korean sign language dataset helps facilitate further research directions on Korean sign language.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.297-318
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• 2023

The purpose of this study is to propose criteria for selecting picture books as various reading education materials for middle school students and to check whether it can be applied to book selection. First, identified the educational value of picture books as reading materials and the criteria for selecting picture books by academic field through previous studies. After integrating the commonalities of various picture book selection criteria presented in previous studies by categorizing them into illustrations, text, and other categories. And it devised selection criteria that can be applied after selecting middle school students as readers. Based on the unified picture book selection criteria, a survey was conducted to ask in-service librarians about the main criteria to consider when selecting picture books for middle school students, and intensive interviews were conducted with experts who have experience in picture book education. As a result, the picture book selection criteria from previous studies were revised and supplemented with two criteria related to text, four criteria related to pictures, and five other criteria, and presented as picture book selection criteria for middle school students. To verify the practicality of the picture book selection criteria, it checked the applicability of each category of criteria to picture books recommended by the Children's Book Research Society (ages 13 and older). Out of 22 picture books for middle school students, 15 books could be applied to all categories of the selection criteria, showing significant practicality.

• Journal of Life Science
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• v.33 no.8
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• pp.663-679
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• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.93-106
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• 2019

Persona is an actor's external ego constructed by playing various roles, and his/her another self-portrait in the eyes of the audience. This study was conducted to analyze persona identity containing core persona(CP) and to gain implications for the growth strategy of the actress Son Ye-jin called "melo queen" by verifying consistency between the CP and audience responses to her starring works of the past. According to the related theories and models, the persona was firstly set as image, visuality, personality and consistency, and it was used to extract and sort descriptive texts about Son related news articles in the last 5 years of the six major Korean newspapers using the content analysis method. After that, we analyzed the number of viewers of her movies and the audience share of her dramas by genre. As a result, Son's persona components were found to have a proportion for 54.2% images (34.0% for melo and romance images, 20.2% for non-melo and romance images), 25.6% for visibility, 13.8% for consistency, and 6.4% for personality. Her CP was derived from a melo and romance image. Comparing this with the audience reaction, the melo romance genre dominated and showed consistency in the drama, but in the case of the film, the non-melo romance was dominant and did not match each other. The results were attributed to a wide gap between dramas and movies in terms of key viewers, box office factors, degree of genre hybridity and experimentality. Therefore, Son should actively use her CP in the drama and challenge the various roles in order to expand her persona spectrum in the film.

• The Journal of Bigdata
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• v.6 no.2
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• pp.151-159
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• 2021

Construction of a blockchain network needs a cumbersome and time consuming activity. To overcome these limitations, global IT companies such as Microsoft are providing cloud-based blockchain services. In this paper, we propose a blockchain-based construction and management tool that enables blockchain developers, blockchain operators, and enterprises to deploy blockchain more comfortably in their infrastructure. This tool is implemented using Hyperledger Fabric, one of the famous private blockchain platforms, and Ansible, an open-source IT automation engine that supports network-wide deployment. Instead of complex and repetitive text commands, the tool provides a user-friendly web dashboard interface that allows users to seamlessly set up, deploy and interact with a blockchain network. With this proposed solution, blockchain developers, operators, and blockchain researchers can more easily build blockchain infrastructure, saving time and cost. To verify the usefulness and convenience of the proposed tool, a blockchain network that conducts electronic voting was built and tested. The construction of a blockchain network, which consists of writing more than 10 setting files and executing commands over hundreds of lines, can be replaced with simple input and click operations in the graphical user interface, saving user convenience and time. The proposed blockchain tool will be used to build trust data infrastructure in various fields such as food safety supply chain construction in the future.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.109-118
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• 2023

Cardiac arrest is a critical medical emergency where immediate response is essential for patient survival. This is especially true for Out-of-Hospital Cardiac Arrest (OHCA), for which the actions of emergency medical services in the early stages significantly impact outcomes. However, in Korea, a challenge arises due to a shortage of dispatcher who handle a large volume of emergency calls. In such situations, the implementation of a machine learning-based OHCA detection program can assist responders and improve patient survival rates. In this study, we address this challenge by developing a machine learning-based OHCA detection program. This program analyzes transcripts of conversations between responders and callers to identify instances of cardiac arrest. The proposed model includes an automatic transcription module for these conversations, a text-based cardiac arrest detection model, and the necessary server and client components for program deployment. Importantly, The experimental results demonstrate the model's effectiveness, achieving a performance score of 79.49% based on the F1 metric and reducing the time needed for cardiac arrest detection by 15 seconds compared to dispatcher. Despite working with a limited dataset, this research highlights the potential of a cardiac arrest detection program as a valuable tool for responders, ultimately enhancing cardiac arrest survival rates.