• The Research Journal of the Costume Culture
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• v.27 no.3
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• pp.193-205
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• 2019

A trend analysis of research articles in a field of knowledge is significant because it can help in finding out the structural characteristics of the field and the future direction of research through observing change in a time series. We identified the structural characteristics and trends in text data (keywords) gathered from research articles which in itself is an important task in various research areas. The titles and keywords were crawled from research articles published from 2016 to 2018 in the Research Journal of the Costume Culture (RJCC), one of the representative Korean journal in the field of clothing and textile. After we extracted data comprising English titles and keywords from 195 published articles, we transformed it into a 1-mode matrix. We used measures from network analysis (i.e., link, strength, and degree centrality) for evaluating meaningful patterns and trends in the research on clothing and textile. NodeXL was used for visualizing the semantic network. This study observed change in the clothing and textile research trend. In addition to covering the core areas of the field, the subjects of research have been diversifying with every passing year and have evolved onto a developmental direction. The most studied area in articles published by the RJCC was fashion retailing/consumer psychology while aesthetic/historic and fashion industry/policy studies were covered to a more limited extent. We observed that most of the studies reflecting the identity of RJCC share subject keywords to a significant extent.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.1-12
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• 2019

A dialog system becomes a new way of communication between human and computer. The dialog system takes human voice as an input, and gives a proper response in voice or perform an action. Although there are several well-known products of dialog system (e.g., Amazon Echo, Naver Wave), they commonly suffer from a problem of out-of-domain utterances. If it poorly detects out-of-domain utterances, then it will significantly harm the user satisfactory. There have been some studies aimed at solving this problem, but it is still necessary to study about this intensively. In this paper, we give an overview of the previous studies of out-of-domain detection in terms of three point of view: dataset, feature, and method. As there were relatively smaller studies of this topic due to the lack of datasets, we believe that the most important next research step is to construct and share a large dataset for dialog system, and thereafter try state-of-the-art techniques upon the dataset.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.2
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• pp.77-107
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• 2019

This study aims to analyze the current state of the operation of the information disclosure system in the judiciary of Korea to identify problems and suggest ways to provide more effective and substantive requests for information disclosure in the future. To this end, we reviewed the court's information disclosure claims process from 2007 to 2017 using the data published in the judicial yearbook and the data charged to the court information disclosure system of Korea. Results showed the different processes according to the person in charge, the high withdrawal rate, the complaint response rate, and the trend of the information nonexistence as the common problems. To solve these issues, we proposed to improve the various claims system, strengthen the education of the information disclosure claimant, publish the manual, and expand the provision and original text of information in advance.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.24-32
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• 2018

System Complexity one of the most common cause failure of the projects, it leads to a lack of understanding about the functions of the system. Hence, the model is developed for communication and furthermore modeling help analysis, design, and understanding of the system. On the other hand, the text-based specification is useful and easy to develop but is difficult to visualize the physical composition, structure, and behaviour or data exchange of the system. Therefore, it is necessary to transform system description into a diagram which clearly depicts the behaviour of the system as well as the interaction between components. According to the International Atomic Energy Agency (IAEA) Safety Glossary, The safety system is a system important to safety, provided to ensure the safe shutdown of the reactor or the residual heat removal from the reactor core, or to limit the consequences of anticipated operational occurrences and design basis accidents. Core Protection Calculator System (CPCS) in Advanced Power Reactor 1400 (APR 1400) Nuclear Power Plant is a safety critical system. CPCS was developed using systems engineering method focusing on Departure from Nuclear Boiling Ratio (DNBR) calculation. Due to the complexity of the system, many diagrams are needed to minimize the risk of ambiguities and lack of understanding. Using Model-Based Systems Engineering (MBSE) software for modeling the DNBR algorithm were used. These diagrams then serve as the baseline of the reverse engineering process and speeding up the development process. In addition, the use of MBSE ensures that any additional information obtained from auxiliary sources can then be input into the system model, ensuring data consistency.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.353-362
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• 2020

This was a single group pretest-protest pre-experimental study designed to find out whether writing using media enhances creative convergence capacity. Data were collected from 30 C university students in C city, from March 1st to July 15th, 2020. Analysis was done using IBM SPSS 25.0 for frequency, percentage, average, standard deviation, and paired t-test. Creative problem solving ability was enhanced by an average of 0,63 points (p<.001), critical thinking tendency by 1.06 points (p<.001), self-leadership by 0,53 points (p<.001), and self-control by an average of 0.51 points, so was statistically significant (p=.001). Writing using media had the effect of improving creativity and integration capabilities. The results of this study are expected to be used as basic data for the development of educational programs for creativity and integration enhancement at university-level. Also, follow-up studies on the effectiveness of writing education by utilizing web media as text and tools simultaneously and customized university-level writing education utilizing media are required.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.91-100
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• 2011

The Triple Data Encryption Algorithm (Triple DES) is an international standard of block cipher, which composed of two encryption processes and one decryption process of DES to increase security level. In this paper, we proposed a Differential Fault Analysis (DFA) attack to retrieve secret keys using reduction of last round execution for each DES process in the Triple DES by fault injections. From the simulation result for the proposed attack method, we could extract three 56-bit secret keys using exhaustive search attack for $2^{24}$ candidate keys which are refined from about 9 faulty-correct cipher text pairs. Using laser fault injection experiment, we also verified that the proposed DFA attack could be applied to a pure microprocessor ATmega 128 chip in which the Triple DES algorithm was implemented.

• Journal of Platform Technology
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• v.8 no.3
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• pp.22-29
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• 2020

The 4th industrial revolution is progressing by country as a mega trend that leads various technological convergence directions in the social and economic fields from the initial simple manufacturing innovation. The epidemic of infectious diseases such as COVID-19 is shifting digital-centered non-face-to-face business from economic operation, and the use of AI and big data technology for personalized services is essential to spread online. In this paper, we analyze cases focusing on the application of artificial intelligence technology, which is a key technology for the effective implementation of the digital new deal promoted by the government, as well as the major technological characteristics of the 4th industrial revolution and describe the use cases in the field of disaster response. As a disaster response use case, AI assistants suggest appropriate countermeasures according to the status of the reporter in an emergency call. To this end, AI assistants provide speech recognition data-based analysis and disaster classification of converted text for adaptive response.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.41-45
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• 2021

This paper proposes a video content delivery scheme for vehicles. Today, we spend a lot of time commuting to work in vehicles such as trains and cars. In addition, the number of users who enjoy video content such as YouTube and Netflix in order to appease the boredom in the vehicle is increasing rapidly. Video content requires a larger amount of data usage than text-based content. Hence, the user's mobile communication data usage increases rapidly along with the cost. The proposed video content delivery scheme downloads a lot of video content in advance when the vehicle is in a free Wi-Fi area. In this way, it is possible to play video content in a vehicle at a low cost. It is expected that the proposed scheme can be applied to the Internet of Things(IoT) for moving objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.1-7
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• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.347-354
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• 2021

As interest in artificial intelligence education for elementary school students has recently increased, it is necessary to analyze the existing elementary information education research from a macroscopic point of view to understand the current situation and to provide implications for subsequent research. This study analyzed Journal of The Korean Association of Information Education for the purpose of looking at the research trend of elementary information education in Korea. For the data of the study, all papers published until 2020 in the first issue of the journal were selected, and 11 research topics were derived by modeling topics. As a result of the study, topic T1, the highest proportion, was analyzed to account for about 38%, and keywords such as education, research, analysis, elementary school, and information were derived according to the order of contribution to topic T1. As a result of regression analysis according to the year of the topic, it was found that the research trend is changing to computing thinking, software education, and artificial intelligence education. The significance of this study is that text data related to elementary information education is objectively clustered.