• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.609-620
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• 2017

This study set out to examine the effects of usage characteristics of web novels, which have recently gained popularity in the Internet and mobile platforms, on the satisfaction and continued usage intention of users. For that purpose, the investigator conducted a survey with 333 web novel users. The survey results show that web novel users recorded a high level of flow when they had a challenging spirit and proficiency in the process of using the content. Their high level of flow in web novels had positive impacts on their satisfaction and continued usage intention for web novels. When they were highly satisfied with web novels, they intended to use the content continuously. Those findings indicate that web novel users should be encouraged to have a challenging spirit and proficiency in the content consumption process so that they can develop flow in the content. In addition, it is suggested that there should be efforts to increase their flow and satisfaction to promote their continued usage of web novels.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.231-239
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• 2018

This study will analyze the meaning and the characteristic of advertising system in Facebook, one of the leading social platforms. This study focuses on finding the trend of mobile advertisement and observing Facebook users behavior. During 30seconds, the researcher observed the behaviors of 50 male and female university students which they access and use their own Facebook individually. After the observation, the researcher did an in-depth analysis based on offline discussion with tested participants. As a result, it can be classified in positive causes and negative causes of the advertisement. There are 3 positive causes; native advertisement effect, acquaintance effect, and big data effect and they help people watch the advertisement positively. 1.5-3 times per second high speed scroll behavior (Finger effect) is the main negative cause and it help users escape from the advertisement easily. These positive and negative causes have an interactive synergy which reduces user stress and makes people enjoy ad more than other media. Finally, both of them cause making Facebook a better environment for the advertisement.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.592-600
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• 2004

A recommendation system, which is an application area of e-CRM in e-commerce environment, provides individualized goods recommendation service that meets the demand of individual users. In general, existing recommendation systems require extensive historic user information in application domains. However, the method of recommendation based on static historic user information needs to respond flexibly to users'demand that changes rapidly and sensitively over time and in domains including a variety of users. In addition, it is difficult to recommend for new users who are not fall into any of existing domains. To overcome such limitations and provide flexible recommendation service, this study designed and implemented CPAR (Customer Preference Analysis Recommender) system that supports customer preference analysis and filter management. The filtering management capacity of the present system eases the necessity of extensive information about new users. In addition, CPAR system was implemented in XML-based wireless Internet environment for recommendation service independent from platforms and not limited by time and place.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.107-113
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• 2016

In this paper, we suggest a design method of a wide-band Butler matrix working at 5.9 GHz for V2X communication antennas. Since V2X communication needs beam-forming and beam-steering antennas to make transportation systems, mobile comm platforms, saturated frequency-resources, and signal TX-and-RX smart, multi-functional, resolved, and efficient utmost, respectively, the proper Butler matrix and its radiating elements as a low-profile geometry are realized. The constitutive components of the basic Butler matrix of a narrow band are designed first. And then, it is extended to a wide-band version to make its frequency-shift less affected by the event of the antenna system being mounted on a car body. The beam-forming and beam-steering performance is presented as the common feature tagged along with the different bandwidths of the frequency responses as the comparison between the narrow- and wide-band cases.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.143-150
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• 2020

Recently, many companies are interested in smart factory services. Because various smart factory services are provided by the combination of mobile devices, cloud computing, and IoT services. However, many workers turn away from these systems because most of them are not implemented from the worker's point of view. To solve this, we implemented a development tool that allows field workers to produce their own services so that workers can easily create smart factory services. Manufacturing data is collected in real time from sensors which are connected to manufacturing facilities and stored within smart factory platforms. Implemented development tools can produce services such as monitoring, processing, analysis, and control of manufacturing data in drag-and-drop. The implemented system is effective for small manufacturing companies because of their environment: making various services quickly according to the company's purpose. In addition, it is assumed that this also will help workers' improve operation skills on running smart factories and fostering smart factory capable personnel.

• Korean journal of communication and information
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• v.51
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• pp.65-86
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• 2010

This paper reviews the problems and opportunities of Japanese newspaper industry. In the focus are particularly issues related to causes of the crisis and reacting strategies overcoming the crisis. To answer the questions, we conducted in-depth interviews with top-level managers of major newspaper companies in Japan. Secondary data were gathered to complement the interview. Top managers mainly perceived the causes of the crisis as young readers' alienation from newspaper due to the change of media environment and structural factors such as increasing production/distribution costs and diminishing appeals for advertisers. They are implementing several strategies to overcome this crisis - developing newspaper content for young readers; packaging customized on-off line advertisement; extending news distribution via online and mobile platforms; diversifying business into diverse sectors such as real-estate; enhancing brand equity of newspaper; and collaborating with rival newspaper companies in operating news site and joint printing/distribution. Lessons from the case of Japanese newspaper industry may be useful starting points for the Korean newspaper companies agonizing for diminishing circulation and advertising revenues.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.636-643
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• 2013

The current media and content situation is increasingly more competitive and under the radical environment changes, the social & financial position of regional broadcasting companies has been threatened. The internet & mobile based platforms and smart media, however, bring a new opportunity of content distribution. This study analyzes the current status of MBCNET which is the superstation of regional MBC stations and specialists interviews to develop the content distribution strategies of regional broadcasting companies. According to the following: finance, ratings, and new media distribution analysis, the MBCNET outcome is deemed successful based on the content library and regional power. MBCNET utilized opportunity to develop strong content resources and distribution power. In order to maintain its competitive edge, MBCNET needs to adopt the following strategies: content and platform marketing power, research & development of competitive content based on user behavior analysis, and reorganization that is able to counteract N-screen circumstances.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.15-20
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• 2020

In this paper, an error tracking platform is designed for enhanced-reliable IOT system. The platform is designed to enhance reliability of IOT system by analysing additional informations(OS, Browser, Device) and by notifying error detection to developers. Especially, in the case of an error in the service which it is difficult for developers to recognize it, The platform also supports notification services through various communication media(Email, Slack, SMS). The common interface is designed to accommodate many languages(typescript, Swift, and Android) in the development process, and the interface allows users to analyze errors that occur on various platforms, including mobile/web/desktop applications. By presenting each error in groups through issues, developers can easily identify issues in the service. The visualizing function is included to recognize various error type by dashboard.

• Journal of KIISE
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• v.44 no.11
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• pp.1219-1230
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• 2017

Real-time streaming services over the Internet have increased with the explosive growth of the various mobile platforms, with a focus on smart phones, and the demand for them is growing. In addition, the bandwidth occupied by the streaming services over the Internet had already surpassed 50% in 2010. Because of the shortage of network bandwidth for multimedia services traffic, restrictions on quality and capacity will become more and more serious. CCN is a future Internet architecture that improves how existing host-based Internet architecture handles content-oriented structure, but it is designed for the transmission of general contents and is not suitable for transmitting real-time streaming contents. In this paper, we focus on the inefficient aspects of CCN and propose a hierarchical grade-based scheme for real-time service for a more efficient environment in real-time streaming services. Experiments have shown better performance in terms of bandwidth, network load, and reliability.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.