• 한국체육학회지인문사회과학편
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• v.56 no.2
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• pp.303-320
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• 2017

This paper seeks to better understand the focal issues and persons related to Rio Olympic soccer games through social data science and analytics. This study collected its data from online news articles and comments specific to KOR during the Olympic football games. In order to investigate the public interests for each game and target persons, this study performed the co-occurrence words analysis. Then after, the study applied the NodeXL software to perform its visualization of the results. Through this application and process, the study found several major issues during the Rio Olympic men's football game including the following: the match between KOR and PIJ, KOR player Heungmin Son, commentator Young-Pyo Lee, sportscaster Woo-Jong Jo. The study also showed the general public opinion expressed positive words towards the South Korean national football team during the Rio Olympics, though there existed negative words as well. Furthermore the study revealed positive attitude towards the commentators and casters. In conclusion, the way to increase the public's interest in big sporting events can be achieved by providing the following: contents that include various professional sports analysis, a capable domain expert with thorough preparation, a commentator and/or caster with artistic sense as well as well-spoken, explanatory power and so on. Multidisciplinary research combined with sports science, social science, information technology and media can contribute to a wide range of theoretical studies and practical developments within the sports industry.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2873-2881
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• 2018

It is very important to obtain objective and credible information through election polls in order to contribute to the correct voting behavior of the voters or to establish appropriate election strategies for candidates or political parties. Therefore, many related organizations such as political parties, media organizations, and research institutions have been making efforts to improve the accuracy of the results of the polls and the election prediction. Kim et al. (2017) analyzed whether the non-response group responded that there is no support candidate in the election survey to increase the accuracy of the estimation of the vote rate. As a result, it has been confirmed that the accuracy of the estimation of the vote rate can be significantly improved by performing an appropriate classification on the non-response layer. In this study, we propose a method to estimate the turnout by each strata (sex, age group) under the condition that the total turnout rate is given for a specific district (region) and propose a procedure to predict the vote rate by reflecting the turnout. In addition, case studies were conducted using data gathered through telephone interviews for the 20th National Assembly elections in 2016.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.500-507
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• 2021

The virtual reality industry has an opportunity to take another leap forward with the surge in demand for non-face-to-face content and interest in the metaverse after Covid-19. Therefore, in order to popularize virtual reality content along with this trend, high-quality content production and storytelling research suitable for the characteristics of virtual reality should be continuously conducted. In order for content to which virtual reality characteristics are applied to be effectively produced through user feedback, a quantitative index that can evaluate the content is needed. In this study, the process of viewing virtual reality contents was analyzed and head movement was set as a quantitative indicator. Afterwards, the experimenter watched five animations and analyzed the correlation between recorded head movement information and immersion. As a result of the analysis, high immersion was shown when the head movement speed was relatively slow, and it was found that the head movement speed can be used significantly as an index indicating the degree of content immersion. The result derived in this way can be used as a quantitative indicator that can verify the validity of the storytelling method applied after the prototype is produced when the creator creates virtual reality content. This method can improve the quality of content by quickly identifying the problems of the proposed storytelling method and suggesting a better method. This study aims to contribute to the production of high-quality virtual reality content and the popularization of virtual reality content as a basic research to analyze immersion based on the quantitative indicator of head movement speed.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.973-979
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• 2020

This study aims to objectively and quantitatively determine the social emotion of empathy by collecting pupillary response. 52 subjects (26 men and 26 women) voluntarily participated in the experiment. After the measurement of the reference of 30 seconds, the experiment was divided into the task of imitation and spontaneously self-expression. The two subjects were interacted through facial expressions, and the pupil images were recorded. The pupil data was processed through binarization and circular edge detection algorithm, and outlier detection and removal technique was used to reject eye-blinking. The pupil size according to the empathy was confirmed for statistical significance with test of normality and independent sample t-test. Statistical analysis results, the pupil size was significantly different between empathy (M ± SD = 0.050 ± 1.817)) and non-empathy (M ± SD = 1.659 ± 1.514) condition (t(92) = -4.629, p = 0.000). The rule of empathy according to the pupil size was defined through discriminant analysis, and the rule was verified (Estimation accuracy: 75%) new 12 subjects (6 men and 6 women, mean age ± SD = 22.84 ± 1.57 years). The method proposed in this study is non-contact camera technology and is expected to be utilized in various virtual reality with smart glasses.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.681-692
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• 2020

This study analyzed a textbook published for Korean culture education in a trend of communicative teaching methods, and suggested the ways for the integrated diversity of culture education with expression activities. This study set up the final goal of strengthening 'cultural competence' which is the next stage of 'cultural awareness' and 'cultural literacy' in the goal hierarchy for culture education, and analyzed not only the theme distribution but the patterns of expression activities in the textbook. It assumed that one of the most effective ways to achieve the goal is the convergence with expression activities in order to strengthen 'cultural competence' which aims to the creative culture production as well as the simple comparison between learners' mother culture and the target culture. This textbook is characterized by abundant visual materials, focus on the behavior culture and the information culture rather than the achieved culture. and media reading materials in diverse levels for utilization possibly in any proficiency levels. Also, it found out by analyzing the patterns of expression activities that the question forms inducing learners' speech and writing are restricted to a few patterns. Lastly, this study proposed the ways to achieve the goal "cultural competence" as follows: diversity of question forms, extension of expression activities and creative application in integrating the related activities.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.283-295
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• 2021

This paper proposes a method for generating dense depth map using information of color images and depth map generated based on lidar based on self-organizing map. The proposed depth map upsampling method consists of an initial depth prediction step for an area that has not been acquired from LiDAR and an initial depth filtering step. In the initial depth prediction step, stereo matching is performed on two color images to predict an initial depth value. In the depth map filtering step, in order to reduce the error of the predicted initial depth value, a self-organizing map technique is performed on the predicted depth pixel by using the measured depth pixel around the predicted depth pixel. In the process of self-organization map, a weight is determined according to a difference between a distance between a predicted depth pixel and an measured depth pixel and a color value corresponding to each pixel. In this paper, we compared the proposed method with the bilateral filter and k-nearest neighbor widely used as a depth map upsampling method for performance comparison. Compared to the bilateral filter and the k-nearest neighbor, the proposed method reduced by about 6.4% and 8.6% in terms of MAE, and about 10.8% and 14.3% in terms of RMSE.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.50-59
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• 2021

To understand the research trends of English education in Korea for the last 20 years from 2000 to 2019, 12 major academic journals in Korea in the field of English education were selected, and bibliographic information of 7,329 articles published in these journals were collected and analyzed. The total number of articles increased from the 2000s to the first half of the 2010s, but decreased somewhat in the late 2010s and the number of publications by journal has become similar. These results show that the overall influence of English education journals has decreased and then leveled in terms of quantity. Next, 34 topics were extracted by applying latent Dirichlet allocation (LDA) topic modeling using the English abstract of the articles. Teacher, word, culture/media, and grammar appeared as topics that were highly studied. Topics such as word, vocabulary, and testing and evaluation appeared through unique keywords, and various topics related to learner factors emerged, becoming topics of interest in English education research. Then, topics were analyzed to determine which ones were rising or falling in frequency. As a result of this analysis, qualitative research, vocabulary, learner factor, and testing were found to be rising topics, while falling topics included CALL, language, teaching, and grammar. This change in research topics shows that research interests in the field of English education are shifting from static research topics to data-driven and dynamic research topics.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.497-508
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• 2021

After the spread of COVID-19, the OTT market has grown rapidly. Accordingly, competition of OTT platforms has intensified. Among them, TVing provides users distinct characteristics of service, such as media and commerce, to differentiate it from other platforms. It is important to offer appropriate usability when proving combined service in one mobile application. Otherwise, it can adversely affect the user experience. In this regard, this research conducted usability testing of TVing and found out what user experience should be considered when integrating different characteristics of service in one mobile application. Through the usability testing, we measured and analyzed effectiveness, efficiency, and satisfaction based on the ISO usability testing guidelines. As a result, three important considerations of UX design for mobile application of combined services were found; 1) connectivity between services, 2) easy navigation, 3) consistent UI design, and 4) relations between subjects and provided information. This design consideration is expected to be applicable not only to TVing mobile application, but also to the situation where composed services are provided in one application.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.233-244
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• 2022

One of the most noteworthy topics in recent corporate management is ESG(Environmental, Social, Governance). Although there are many companies that have declared ESG management, KT has declared full-fledged ESG management in 2021 and is sharing its sustainable management strategy with stakeholders. In addition, KT is strengthening ESG management by issuing ESG bonds for the first time in the domestic ICT industry. At a time when the information technology industry became more important due to COVID-19, this study attempted to examine KT's ESG management goals and strategies by dividing them into environmental, social, and governance areas. KT was aiming to achieve environmental integrity through 'environmental management', 'green competence', 'energy resources', and 'eco-friendly projects' in the environmental field. In addition, in the social field, genuine creating social value was pursued through 'social contribution', 'co-growth', and 'human rights management'. Finally, in the governance area, it was aiming for a transparent corporate management system to pursue economic reliability through 'ethics and compliance' and 'risk management'. In particular, KT was promoting its own ESG management by promoting strategies to solve environmental and social problems using AI and BigData technologies based on the characteristics of a digital platform company. This study aims to derive implications for ESG strategy establishment and ESG management development direction through KT's ESG management case in relation to ESG management, which has emerged as a hot topic.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.