• Informatization Policy
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• v.23 no.2
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• pp.73-97
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• 2016

Social changes due to ICT like Big Data, IoT, Cloud and Mobile is progressing rapidly. Now, we get out of the old-fashioned frame was measured at the level of the information society through the introduction of PC, Internet speed and Internet subscribers etc and there is a need for a new type of diagnostic information society framework. This study is the study for the framework established to diagnose and measure post-information society. The framework and indicators were chosen in accordance with the technological society coevolution theory and information society-related indicators presented from authoritative international organizations. Empirical results utilizing the indicators and framework developed in this study were as follows: First, the three sectors, six clusters (items), 25 nodes (indicators) that make up the information society showed that all strongly connected. Second, it was diagnosed as information society development (50.34%), technology-based expansion (25.03%) and ICT effect (24.63%) through a network analysis (ANP) for the measurement of importance of the information society. Third, the result of calculating the relative importance of the cluster and nodes showed us (1)social development potential (26.04%), (2)competitiveness (15.9%), (3)ICT literacy (15.5%) (4) (social)capital (24.3 %), (5)ICT acceptance(9.54%), (6)quality of life(8.7%). Consequently, We should take into account the effect of the economy and quality of life beyond ICT infrastructure-centric when we measure the post-information society. By applying the weighting we should performs a comparison between countries and we should diagnose the level of Korea and provide policy implications for the preparation of post-information society.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2641-2654
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• 2014

In the smart media environment, magazine industry has been experiencing a transition to ecosystem of value network, which includes high complexity and ambiguity. Using case study method, this article conducts research on digital convergence, the model of magazine ecosystem and adaptation strategy of global magazine companies. Research findings have it that the way of contents production of global magazines has been based on collaborative production system within communities, expert communities, creative users, media contents companies and magazine platform. The system shows different patterns and characteristics depending on magazine-driven platform, Platform-driven platform or user-driven platform. Collaboration system has been confirmed in various cases: Huffington Post and Zinio which collaborate with media contents companies, Amazon magazines and Bookish with magazine companies, Huffington Post and Wired with expert communities, and Flipboard with creative users and communities. Foreign magazine contents diverge into (paper, electronic, app and web magazine) as they start the lively trades of their contents on the magazine platform. In the area of contents uses, readers employ smart media technology effectively such as cloud computing, artificial intelligence and module individualization, making it possible for the virtuous cycle to remain in the relationship within communities, expert communities and creative users.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.229-235
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• 2019

As the demand for broadband multimedia including the Internet explosively increases, the advancement of the subscriber network is becoming the biggest issue in the telecommunication industry due to the surge of data traffic caused by the emergence of new services such as smart phone, IPTV, VoIP, VOD and cloud services. In this paper, we have developed WDM(Wavelength Division Multiplexing)-PON(passive optical network) based on the 1-Gigabit Reach Externder (RE) technique to reduce optical core. Particularly, in order to strengthen the market competitiveness, we considered low cost, miniaturization, integration technique, and low power of optical parts. In addition, we have developed a batch system by integrating all techniques for reliability, remote management through the development of transmission distance extension and development of capacity increase of optical line by using RE technology in existing PON network. Based on system interworking with existing commercial 1G PON devices, it can be worthy of achievement of wide nationalization and optical core reduction by using this developed system. Based on these results, we are studying development of 10G PON technology.

• Convergence Security Journal
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• v.18 no.1
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• pp.19-31
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• 2018

As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.421-430
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• 2021

The study was conducted to examine the educational experiences and perceptions of college students in the field of physical education as they were taken remote classes in university due to the effects of the social collective infection caused by COVID-19. To achieve the purpose of the study, an online survey was conducted on 278 university students who major in physical education, and the survey questions include the status of remote classes, remote class recognition (preference, and satisfaction level). As for the analysis method, frequency analysis, response sample t-verification, ANOVA, and word-cradle were performed using SPSS 22.0 and R programs, and all significance levels were set at .05. The results from the above research process are as follows. First, in the types of remote classes in the sports category due to COVID-19, video types were used the most in both theoretical and practical classes, and the following was shown as assignment types. The third type was the voice record lecture type for theoretical classes, and the practical class was the video lecture scene. Second, in the remote class preference for the students, both theory and practical classes, video format were the most prefered, followed by video lecture scene and voice lecture type. Third, the analysis of the differences in satisfaction between theoretical and practical classes of the students showed that there was no difference in satisfaction according to the type of class.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.362-373
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• 2021

This study sought to explore the enhancement of the introduction of teaching and learning methods for Problem Based Learning (PBL) and the evaluation factors to evaluate them effectively through an understanding lecture in Cultural Content Planning. It was intended to incorporate a practical zero-volume education methodology of problem-oriented learning and sufficient leading learning to reflect storytelling in the entire process of completing a cultural content with culture, cultural content, and content planning. To this end, the role of teaching methods should be faithful to ensure that teamwork and cooperation can be done organically according to the educational field, practice and situation. Students who take classes were asked to meet demand, reflect it through surveys, apply real-world problems, and acquire the entire course. Learners had to cooperate with each other until planning cultural content and completing the results through classes, and they evaluated themselves and colleagues in teamwork until the last result was completed from creative ideas. The results were shared together and the students were able to investigate the necessary PBL evaluation factors for themselves, and the prior research and survey on the method of PBL evaluation was conducted to derive the factors of understanding of cultural content planning. The derived assessment elements were able to identify priorities between the assessment elements using basic statistics, word cloud analysis, and AHP analysis. The components of the assessment derived were communication skills, basic knowledge, reasoning process, expertise, and evaluation techniques. Through this article, I was able to lead the understanding of cultural content planning to problem-oriented learning classes and encourage students to be familiar and smooth.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.313-325
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• 2022

The purpose of this study is to examine the changes in the elderly healthcare app market through text mining analysis and to present basic data for activating elderly healthcare apps. Data collection was conducted on Naver, Daum, blog web, and cafe. As for the research method, text mining, TF-IDF(Term frequency-inverse document frequency), emotional analysis, and semantic network analysis were conducted using Textom and Ucinet6, which are big data analysis programs. As a result of this study, a total of six categories were finally derived: resolving the healthcare app information gap, convergence healthcare technology, diffusion media, elderly healthcare app industry, social background, and content. In conclusion, in order for elderly healthcare apps to be accepted and utilized by the elderly, they must have a good diffusion infrastructure, and the effectiveness of healthcare apps must be maximized through the active introduction of convergence technology and content development that can be easily used by the elderly.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.59-65
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• 2021

This is a case study on the use of Albert Camus' La Peste, which has gained its popularity in today's generation of post-COVID as well as the use of big data analysis tools for major and elective classes. First, we asked students majoring in French to compare the use of vocabulary and the number of appearances for characters using big data analysis, for about 400 pages of the original text. As a result, we were able to confirm a similar relationship between Camus' Absurdism and the vocabulary used within La Peste, in addition to noting the heavy frequency of resistant characters. Students in elective classes were asked to read the literature in a Korean-translated version to determine the frequency of vocabulary and characters' appearances. Students were able to strongly relate to La Peste due to its commonality between COVID and the plague in the literature. We also received high levels of class satisfaction regarding the use of big data analysis tools. The students showed a positive response both towards choosing La Peste as the work of literature and using big data, the main tool in the Fourth Industrial Evolution. We were able to identify good results even in a non-contact environment, as long as the literature does not rely on traditional methods but rather lectures to reflect current situations.

• Advanced Industrial SCIence
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• v.1 no.1
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• pp.7-15
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• 2022

To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.