• Journal of Digital Convergence
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• v.17 no.11
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• pp.483-492
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• 2019

The culture and education are very active with the active policy and support to form the government's Maker Movement. The purpose of this study is to grasp the current status of the education sector of the domestic maker movement, which is increasing recently, and to propose a plan for activating maker education for the development of a positive direction. To this end, first, the current status and problems of domestic maker training are derived through in-depth interviews with existing maker training operators and participants. Second, based on the contents of the interview script, keyword analysis and its characteristics through the qualitative survey analysis program (NVIVO) are identified. Third, based on the analysis results, we propose a plan and development direction for domestic maker education. Based on the educators who performed maker training and the students involved, professional maker teachers were required for the professionalism of education, and the expansion of maker channels and professional networking of participating students was required. In addition, there was a need for specialized programs and appropriate policy support that reflected the characteristics of maker training. This study aims at contributing to the activation of maker education, which is a major field of maker movement, by helping to improve concrete support methods, training related educators, and educational environment for maker education.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.140-153
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• 2019

Cloase-range image information from drones and ground-based camera has been frequently used in the field of disaster mitigation with 3D modeling and mapping. In addition, the utilization of virtual reality(VR) is being increased by implementing realistic 3D models with the VR technology simulating disaster circumstances in large scale. In this paper, we created a VR training program by extracting realistic 3D models from close-range images from unmanned aircraft and digital camera on hand and observed several issues occurring during the implementation and the effectiveness in the case of a VR application in training for disaster mitigation. First of all, we built up a scenario of disaster and created 3D models after image processing with the close-range imagery. The 3D models were imported into Unity, a software for creation of augmented/virtual reality, as a background for android-based mobile phones and VR environment was created with C#-based script language. The generated virtual reality includes a scenario in which the trainer moves to a safe place along the evacuation route in the event of a disaster, and it was considered that the successful training can be obtained with virtual reality. In addition, the training through the virtual reality has advantages relative to actual evacuation training in terms of cost, space and time efficiencies.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.