• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.51-59
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• 2018

The purpose of this study is to analyze genre differentiation in digital games and examine the changing characteristics of core genre elements. Especially this study focuses on the aspect that how players recognize genre differentiation based on the conceptual blending theory. The evolution of the genre does not end with decline or extinction. The genre keeps being divided into sub-genres through partial use of genre elements. The differentiation of the genre results from the principle of frame confrontation or expansion with a parent genre. Rogue-like games are differentiated from Role-playing games by frame conflict, while Metroidvania games are differentiated from Platform adventure games by frame expansion. In the former case, the core genre elements are independent and easily combined with other genres. For example, the core mechanism of Rogue-like genre like 'perma-death' or 'procedural generation' has a decisive effect on the differentiation of the game experience become an independent genre element. In the latter case of Metroidvania, the core genre elements strongly reveals context dependency and are difficult to use outside the genre convention. The core mechanism of Metroidvania is 'backtracking' in the labyrinth style map, but it could be effective genre element within the specific context like side-scrolling action-platformer.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.267-291
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• 2021

Due to the global pandemic caused by COVID-19 in 2020, there have been major changes in the education sites. Universities have fully introduced remote learning, which was considered as an auxiliary education, and non-face-to-face classes have become commonplace, and professors and students are making great efforts to adapt to the new educational environment. In order to improve the quality of non-face-to-face lectures amid these changes, it is necessary to study the factors affecting lecture satisfaction. Therefore, This paper presents a new methodology using big data to identify the factors affecting university lecture satisfaction changed before and after COVID-19. We use Topic Modeling method to analyze lecture reviews before and after COVID-19, and identify factors affecting lecture satisfaction. Through this, we suggest the direction for university education to move forward. In addition, we can identify the factors of satisfaction and dissatisfaction of lectures from multiangle by establishing a topic classification model with an F1-score of 0.84 based on KoBERT, a deep learning language model, and further contribute to continuous qualitative improvement of lecture satisfaction.

• Journal of Korean Elementary Science Education
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• v.40 no.3
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• pp.326-342
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• 2021

In this study, experimental guide materials for teachers were developed so that algorithm expression, the core of computational thinking, can be applied to experimental activities. The experimental manuals presented in text was converted into an algorithmic form with a linear, branched, and repetitive structure according to the information visualization process using flowchart symbols. As an example, an experiment guide materials was developed by applying an algorithm expression to an experiment to find out the properties of a magnet. The developed experiment guide materials is different from the existing experiment guide materials expressed only sequentially in that it has an algorithmic structure of branching and repetition in which the suitability and judgment of information are expressed, and that the experiment process is visualized and expressed. It is expected that the experimental guide materials developed in this study will help teachers to understand algorithmic thinking and to implement experiments using it.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.53-63
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• 2019

To provide a hand gesture interface through deep learning in mobile environments, research on the light-weighting of networks is essential for high recognition rates while at the same time preventing degradation of execution speed. This paper proposes a method of real-time recognition of written characters in the air using a finger on mobile devices through the light-weighting of deep-learning model. Based on the SSD (Single Shot Detector), which is an object detection model that utilizes MobileNet as a feature extractor, it detects index finger and generates a result text image by following fingertip path. Then, the image is sent to the server to recognize the characters based on the learned OCR model. To verify our method, 12 users tested 1,000 words using a GALAXY S10+ and recognized their finger with an average accuracy of 88.6%, indicating that recognized text was printed within 124 ms and could be used in real-time. Results of this research can be used to send simple text messages, memos, and air signatures using a finger in mobile environments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.114-128
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• 2019

Recently, the interest in the safety of autonomous vehicles has globally been increasing. Also, there is controversy over the reliability and safety about autonomous vehicle. In Korea, the K-City which is a test-bed for testing autonomous vehicles has been constructing. There is a need for test scenarios for autonomous vehicle test in terms of safety. The purpose of this study is to develop the evaluation scenario for autonomous vehicle at community roads in K-City by using crash data collected by the Korea National Police Agency and a text-mining technique. As a result, 24 scenarios were developed in order to test autonomous vehicle in community roads. Finally, the logical and concrete scenario forms were derived based on the Pegasus 5-layer format.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.757-763
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• 2019

Youtube has become so popular that it is called the age of YouTube. As the number of users and contents increase, the choice of information increases. However, it is difficult to select information that meets the needs of users. YouTube provides recommendations based on their watch list. Therefore, in this study, we want to analyze the channel of user's subject in various angles and provide the proposed scheme based on the crawled channels, measurement of the perception of channels and channel videos through quantitative data and hidden qualitative data analysis. Based on the above two data analysis, it is possible to know the recognition of the channel and the recognition of the channel video, thereby providing a ranking of the channels that deal with the topic. Finally, as a case study, we recommend English learning channels to users based on numerical data statistics and emotional analysis results to maximize flipped learning effect regardless of time and space.

• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.255-273
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• 2019

Recently, the table of contents (TOC) has been becoming increasingly accessible and utilized. The study conducted descriptive statistics and comparative analysis of the table of contents in terms of parts of speech and subject in text. For this purpose, this study chose the books of the social sciences field from acquisition lists of an academic library, obtained Dewey class numbers of target books from KERIS union catalog, and extracted TOC data from online bookstore. Morphological analysis was performed on each book titles and TOCs, and descriptive statistics and frequency analysis were carried out. As a result, nouns made up roughly half of the morphemes of titles or the TOCs. TOCs had about 50 times more nouns than titles. The percentage of unique nouns that appeared only in the table of contents is estimated to be 95.2% of the TOC's total nouns. The table of contents also showed a differences in its lengths depending on the field of social science.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.9-23
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• 2019

The artificial intelligence speaker market is in a new age of mounting displays. This study aimed to analyze the difference of experience using artificial intelligent speakers in terms of usage context, according to the presence or absence of displays. This was achieved by using semantic network analysis to determine how the online review texts of Amazon Echo Show and Echo Plus consisted of different UX issues with structural differences. Based on the physical context and the social context of the user experience, the ego network was constructed to draw out major issues. Results of the analysis show that users' expectation gap is generated according to the display presence, which can lead to negative experiences. Also, it was confirmed that the Multimodal interface is more utilized in the kitchen than in the bedroom, and can contribute to the activation of communication among family members. Based on these findings, we propose a user experience strategy to be considered in display type speakers to be launched in Korea in the future.

• The Korean Journal of Archival Studies
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• no.52
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• pp.59-117
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• 2017

This study aims to logically investigate the changing interpretation and implementation of the principle of provenance by using an argument model for discourse analysis. First, it divides the history of discourses on the principle from the Dutch Manual publication of 1989 up to the present into four areas, which includes establishing, diffusing, transforming, and expanding or deconstructing, and articulates the core discourses of each. Second, it designs the argument model for analyzing the discourses on the principle by applying Toulmin's argument model and Dunn's policy argument model. Third, it selects the articles and books that cover the core discourses of the principle, and analyzes their contents in consideration of the argument model. Fourth and finally, it presents four argument models corresponding to each area of the discourses.

• Knowledge Management Research
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• v.20 no.1
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• pp.45-75
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• 2019

Recently, the growth of beauty industry such as plastic surgery and beauty is continued every year in Korea. With the increased interest in appearance based on the improvement of life standard and the development of media, people's perception of cosmetic plastic surgery is changing. Now, as the service for consumer satisfaction based on their desire, the perception of plastic surgery medical service is changed to the high value-added industry with the high growth potential. Thus, this study aims to suggest the strategies for providing the medical service that could satisfy customers, by drawing the factors cognized as important when customers aim to get the cosmetic plastic surgery, and then additionally analyzing the relationships of those factors. On top of performing the topic modeling based on customers' comments data of social commerce related to cosmetic plastic surgery, this study also conducted the network analysis for visualizing the relations of each keywords. The drawn main factors were divided by applying the sub-categories of the SERVQUAL theory, and the additional characteristics of plastic surgery were shown by referring the relevant previous researches. Moreover, the interview with the cosmetic plastic surgery specialists (plastic surgeons) and customers who actually received the plastic surgery, helped the understanding of the interpretation of each factor and the actual relevant phenomenons. The significance of this study is to draw and discuss the main factors that should be observed by Korean cosmetic plastic surgery medical institutes, by mining and analyzing the opinions of customers interested in the cosmetic plastic surgery and procedure with the use of topic modeling. In other words, the quality of medical service of cosmetic plastic surgery could be improved by presenting the key factors that could be considered by the cosmetic plastic surgery medical service suppliers and also the actual strategies.