• Smart Media Journal
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• v.8 no.4
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• pp.17-24
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• 2019

As IoT technology is widely used in industrial environments, its environmental security issues are becoming more important. In such a context, studies utilizing hardware security functions are being actively carried out. However, previous studies did not consider the performance degradation that occurs when using hardware security functions in IoT environment. Gateway devices that are mainly used in IoT environments are often resource-limited. Utilizing hardware security in such an environment can cause serious performance degradation as the number of IoT devices connected to the gateway increases. Therefore, in this paper, we propose a data classification scheme to efficiently utilize hardware security functions in resource limited environment. We implement a platform with the proposed technique using ARM Trustzone. Performance degradation due to the hardware security functions is measured through experiments on the implemented platform and compared with the performance as of when the proposed technique is applied.

• Smart Media Journal
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• v.10 no.1
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• pp.39-46
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• 2021

This study is about a method of extracting a summary from a news article in consideration of the importance of each sentence constituting the article. We propose a method of calculating sentence importance by extracting the probabilities of topic sentence, similarity with article title and other sentences, and sentence position as characteristics that affect sentence importance. At this time, a hypothesis is established that the Topic Sentence will have a characteristic distinct from the general sentence, and a deep learning-based classification model is trained to obtain a topic sentence probability value for the input sentence. Also, using the pre-learned ELMo language model, the similarity between sentences is calculated based on the sentence vector value reflecting the context information and extracted as sentence characteristics. The topic sentence classification performance of the LSTM and BERT models was 93% accurate, 96.22% recall, and 89.5% precision, resulting in high analysis results. As a result of calculating the importance of each sentence by combining the extracted sentence characteristics, it was confirmed that the performance of extracting the topic sentence was improved by about 10% compared to the existing TextRank algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.333-338
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• 2021

Development of 5th generation mobile telecommunication technology is visualizing ideal hyper-connected social information and communication technology (ICT). In particular, virtual reality (VR) technology is at the starting point for new expansion and leaps. This work defines virtual reality as media in this context and collects and analyzes discourse on its scalability around space and communication theory. We first elaborated the concept, starting with the early discussions of the virtual reality concept in 1990, and discussed the relationship between the physical world and digital information, expression and interaction immersion as a medium, simulation, art creation theory, and finally evolutionary development. In conclusion, beyond the discourse on the technology of virtual reality, academic subjects were required to have theoretical frameworks on cognitive science, neuroscience, social science, and humanities issues (ethics, personality, etc.) for the development and evolution of virtual reality. In other words, it is time for the evolution of virtual reality to be discussed, which can be moved beyond.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.222-228
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• 2022

In today's era of digital technologies, the problem of religious communication in the cyberspace is being actualized, since the globality and accessibility of the WWW makes it one of the most effective and promising channels for transmitting various kinds of messages, including those of a religious nature. Today, religious organizations and movements pay the closest attention to the virtual media space, not only using it to attract new followers, but also for religious PR, image-making and branding, informing the world about themselves through news from the life of the organization and its followers. An equally important form of electronic communication in the online sphere is currently the interaction of various religious movements and religious cultures in general, or the dialogue of confessions in particular. Research in the digital space makes it possible to identify important trends in religious spheres based on the analysis of the flow of information on the Internet, to demonstrate the specifics of individual media outlets and the consequences of their activities for interreligious dialogue, to study the role of the Internet in changing religious beliefs, the possibility of changing religious identity, retrospective development of religious enlightenment at the turn of the century, to determine the vectors of possible interreligious interaction and discuss the role of digital technologies in the work of religious structures, to state the need to continue an active dialogue between representatives of religious movements, to hold expert seminars on interreligious dialogue on a regular basis, and to record the risks generated by the digital space. Thus, the coronavirus pandemic served as a background and context, a litmus test and a catalyst for accelerating and intensifying interreligious, interfaith dialogue and dialogue between religious organizations and society.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.39-47
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• 2023

The purpose of this study is to examine the progress of negotiations between the two countries regarding the implementation of AFKN's satellite broadcasting on October 4, 1983, as well as the opposition of domestic public opinion, which emerged as an important variable in the negotiation process. Through this, it was intended to lay the foundation for the historical facts necessary to interpret the negotiation process between the two countries over the implementation of AFKN's satellite broadcasting in the context of world history of cultural globalization. As a research method, the historical literature research method was used, focusing on archive documents stored in diplomatic archives. The study revealed that public opinion's movement toward cultural imperialism under domestic political conditions, which had authoritarian control over the media, served as an accidental factor to help carry out the regime's interests of regime protection. Through these findings, this paper interpreted that AFKN-TV's satellite broadcasting, which was implemented under the U.S. Department of Defense plan without the prior consent of the Korean government, clearly shows that Korea has been "semi-forced" into the U.S.-led cultural globalization order.

• Asia Marketing Journal
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• v.17 no.4
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• pp.63-88
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• 2016

K-Pop is hugely promoted offline/online in East Asia, while efforts to promote it elsewhere are kept to a minimum. Whilst addressing the role of digital marketing in the promotion of K-Pop in the Brazilian music industry this study aims to demonstrate that K-pop will provide its audience with a unique and engaging experience if it thinks globally and acts locally in its marketing and communication strategies. A survey of K-Pop's world fan base was carried out online with 1,074 fans to determine the validity of the hypothesis. The results have demonstrated the need to adapt global and intercultural strategies to local markets with increasing brand awareness through utilizing digital marketing. For example, to increase K-Pop's popularity and market share in Brazil, it is not required to sing in Brazilian Portuguese, contrary to what might be perceived but fully singing in English would help breaking into the market dominated by domestic music as songs would have a higher probability to be included in the international soundtrack of a Brazilian telenovela and promote the K-Pop artist not only across Brazil but also give the artist exposure in all the markets the Brazilian telenovela is exported to, opening an entry door to those markets. K-Pop audience segmentation and psychographic profiling is crucial to the understanding of each market's consumer's preferences, likes, dislikes and their buying habits as it was proven through Brazil's digital media, social media, digital music market and K-Pop market analysis within the global context of the study. It should be also considered that brand extensions are not standard everywhere and that there are cultures where different product categories are not directly associated with its main corporate owner which requires extensive local market knowledge to succeed. The primary and secondary data research that we conducted for this study intended to demonstrate that K-Pop can be successful in Brazil and in Latin America and increase their local and regional market share if digital marketing and communication strategies are tailored to each individual market.

• Smart Media Journal
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• v.11 no.9
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• pp.81-93
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• 2022

In an era where non-face-to-face meetings become common, eXtended Reality(XR) is rapidly developing and filling areas that are not satisfied in online meetings based on existing photos/video method. In particular, general users are also able to easily access and use HMD-type mixed reality devices. However, the basic operations applied in HMD-type in Mixed Reality(MR) with hands as the main input tool do not have a standardized system, and each manufacturer operates in a separate response to each other's hand movements. Therefore, this study considered that a systematic hand motion matching system considering the usability and efficiency of operations performed in mixed reality was necessary, and conducted a study to clarify this. First, the basic operation performed in the MR environment and its attributes were investigated, and at the same time, the structure of the hand and the attributes of the possible hand movements were identified. Based on the identified properties, it is intended to present a system that can intuitively and efficiently match basic operation properties in the MR environment with subtle operation properties according to the structure/context of the hand.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.129-153
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• 2023

This study was conducted in the context of the Covid-19 pandemic by analyzing a large amount of press report frames regarding the Covid-19 vaccine which is of great public interest, in order to explore the role and direction of trusted media as core elements of crisis communication. The study period lasted for eight months beginning in November 2020 when the development of the Covid-19 vaccine was in progress until June 2021. Set-up as research subjects were the Chosun Ilbo, Joongang Ilbo, Dong-A Ilbo and Hankyoreh according to their public confidence rankings and number of readers.The analysis method used structured topic Modeling (STM) and semantic network analysis. As a result, based on a clear cluster of word structures and a central analysis value, a total of 64 relevant frames, 16 for each news company, were gathered. In the third phase a comparative analysis of the four news companies was carried out to verify the organizational degree of the frames and substantial differences.

• Knowledge Management Research
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• v.24 no.4
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• pp.63-85
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• 2023

This study aims to identify the primary user group in the growing metaverse space based on the increased interest during the COVID-19 era. It also aims to explore the predictive factors for metaverse adoption. To predict online activities, the study examined user purposes, motivations, and relevant demographic factors as predictive variables through model analysis. The data from the Korean Media Panel Survey were used, and a two-stage analysis with the Heckman two-stage sample selection model was conducted to predict metaverse users. The analysis revealed that the key factors influencing metaverse adoption were offline activities, openness, OTT usage, and purchasing of paid content. Moreover, in the second stage model, openness, gender, and paid content purchases were identified as significant variables for increasing metaverse usage time. These results indicate that understanding metaverse users is essential in the context of the rising interest in online activities during the COVID-19 era and can provide valuable insights for metaverse platform-related companies and developers.