• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.131-145
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• 2020

The numbers of SNS (Social Network Service) users and usage amounts are increasing every year. The influence of SNS is increasing also. SNS has a wide range of influences from daily decision-making to corporate management activities. Therefore, proper analysis of SNS can be a very meaningful work, and many studies are making a lot of effort to look into various activities and relationships in SNS. In this study, we analyze the SNS following relationships using Twitter, one of the representative SNS services. In other words, unlike the existing SNS analysis, our intention is to analyze the interests of the accounts by extracting and visualizing the accounts that two accounts follow in common. For this, a common following account was extracted using Microsoft Excel macros, and the relationship between the extracted accounts was defined using an adjacency matrix. In addition, to facilitate the analysis of the following relationships, a direction graph was used for visualization, and R programming was used for such visualization.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.1-22
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• 2016

News contents has been collected, selected, edited and sometimes distorted by the news recommendation mechanisms of online portals in nowadays. Prior studies had not confirmed the consensus of newsworthiness, and they had not tried to empirically validate the impacts of newsworthiness on audience reactions. This study challenged to summarize the concepts of newsworthiness and validate the impact of representativeness of both editor's and audience's perspective on audience reactions as perceived news quality, trust on news portal, perceived usefulness, service satisfaction, loyalty, continuous usage intention, and word-of-mouth intention by adopting the representativeness heuristics method and information adoption model. 357 valid data had been collected using a scenario survey method. Subjects in each groups are exposed by 3 news recommendation mechanisms: 1) the time-priority news exposure mechanism (control group), 2) the reference-score-based news recommendation mechanism (a single treatment group), and 3) the major-news-priority exposure mechanism sorting by the reference scores made by peer audiences (the mixed treatment group). Data had been analyzed by the MANOVA and PLS method. MANOVA results indicate that only mixed method of both editor and audience recommendation mechanisms impacts on perceived news quality and trust. PLS results indicate that perceived news quality and trust could significantly affect on the perceived usefulness, service satisfaction, loyalty, continuance usage, and word-of-mouth intention. This study would contributions to empathize the role of information technology in media industry, to conceptualize the news value in the balanced views of both editors and audiences, and to empirically validate the benefits of news recommendation mechanisms in academy. For practice, the results of this study suggest that online news portals would be better to make mixed news recommendation mechanisms to attract audiences.

• The Journal of Society for e-Business Studies
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• v.18 no.1
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• pp.191-211
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• 2013

The deployment of social network service(SNS) makes the social network game(SNG) as the new value added service of SNS be popular. But, a few study had identified the reason of this popularity and the elements of SNG. Based on the social presence theory and media richness theory, we had tried to identify three community artifacts (i.e. persistent labeling, self presentation and deep profiling) and two media characteristics(i.e. vividness and interactivity) as the SNG elements in this research. Then we had empirically validated the effect of these elements on the SNGexperience (i.e. social presence, perceived enjoyment) and behavioral intentions (i.e. Continuous usage intention, willingness to pay and loyalty) of the users. We conducted a survey to the actual SNG users. 243 data were collected and analyzed by PLS algorism. The results indicated that the community artifacts mediated by the social presence and media characteristics could significantly affect on the experiences and behavioral intentions. These findings could contribute to identify what element could be the reason of social network game popularity and could also contribute to design more attractive social network game in practice.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.212-218
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• 2005

These days, mobile technology is developing very fast. It has increased the usage of the Internet by mobile phones. Nowadays the avatar and game contents services are most popular in mobile phones using the Internet. In this paper, we propose a Client/Server system to combine the animation avatar and e-mail services on SK-VM which are different from simple avatar services. The server which consists of DB (database) module and mail management module is designed in order to manage the information about avatar and the user. The client is designed so as to show the email contents and avatar animation on the mobile phone. This model is intended to reduce the performance overhead on the client as much as possible. We expect that this module would be useful in the mobile phones with limited resources, although the technology is being developed very rapidly.

• Journal of Service Research and Studies
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• v.12 no.4
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• pp.94-105
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• 2022

Urban Air Transportation (UAM) is a three-dimensional transport within the city using eVTOL as an alternative to the saturation of land transportation due to overcrowding in major cities around the world. Design has played its roles in various fields in the development of transport, but research on the design application of UAM, which will be commercialized soon, is insufficient. Accordingly, there is a growing need for prior research on the forecasting the future environment and the design application through phenomenon analysis. The purpose of this study is to derive mega trends through STEP analysis for UAM and present ways to apply design in the UAM field based on this. The research method was conducted in the following order. First, the theoretical background of UAM was established by analyzing prior art documents on UAM. Second, five trends in the future environment centered on UAM were derived through STEP analysis. Finally, in order to derive a design application, five experts in each design area (product, visual, video, environment, service) discussed the design application focusing on the results of STEP analysis and derived a design application plan for each design area in the UAM field. Through this study, it was found that the most frequent design area in the STEEP analysis is product design and service design, and therefore related design development is important. After analyzing UAM's information provision plan, display method, and usage process suggested in this study, it is expected that it will lead to various prior design studies related to UAM, such as customized service design, to establish an infrastructure environment for commercialization of UAM.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.183-193
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• 2017

Digital accredited certificates issued under the Digital Signature Act provide essential functionalities for online service, so certificates are used for various services such as online banking, e-government. However, certificates can be stolen by hackers and users need to install separate software to use certificates. Recently FIDO, which aims to solve the problems of password-based authentication and the lack of interoperability between authentication methods, is used for biometric authentication and TrustZone, hardware-based secure environment, is used for safe smartphone usage. In this paper, the new service method is suggested which uses FIDO-based biometric authentication and stores certificates in TrustZone. This method can not only improve security and convenience but also be easily applied to the service because it uses built-in functionalities of new smartphones such as biometric sensors and TrustZone. It is expected that people can use certificates in a safe and convenient way with this method.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.183-198
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• 2002

The purpose of this research is mainly to make an analysis and comparison of the purchasing behaviors of consumers in Mainland China and Taiwan. We precede this research with a questionnaire survey. In Mainland China, we targeted consumers of 10 department stores of the Parkson Plaza Co., Ltd. that are located in 10 different cities. In Taiwan, we selected 3 department stores of the Far Eastern Department Stores in 3 cities. The results of this analysis indicate the importance of quality attributes to the consumers for both Mainland China and Taiwan, albeit with some differentiations. The consumers in China are more focused on the merchandise for example as well as imitation, quality and price. Contrarily, the consumers in Taiwan are more attentive to service quality and parking Issues. On the level of evaluation of satisfaction, the differences are not so obvious for both sides. For example, the quality attributes of “No imitation products” and “Friendly servers” are ranked as the most satisfactory items for both sides. Generally speaking, the service quality of Taiwan's department stores is very outstanding. There are also some differences in the areas of lesser satisfaction between consumers of China and Taiwan. The consumers in China identified the quality attribute “the designs of merchandising, display and the usage of each floor” as the most dissatisfactory item, while the performance on this quality attribute is well accepted by the consumers of Taiwan's department stores. Another contradiction is that Taiwan's consumers are more concerned about “Parking”; this quality attribute obtained much less attention from the consumers in Mainland China. From the analysis of determinants that will have impacts on the willingness of customers to buy again, we found that the viewpoints of consumers from both sides are quite similar. The two main factors are “quality of merchandise” and “service quality”. However, the consumers in Mainland China care more about “the price of merchandise”; this is less important to the consumers in Taiwan. We may conclude from the importance and satisfaction level of the quality attributes and determinants for return customers that differences are caused mainly by the different management of the department stores and the different living circumstances of people across the straights.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.319-328
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• 2021

With popularization of services for massive content, the fundamental limitations of TCP/IP networking were discussed and a new paradigm called Information-centric networking (ICN) was presented. In ICN, content is addressed by the content identifier (content name) instead of the location identifier such as IP address, and network nodes can use the cache to store content in transit to directly service subsequent user requests. As the user request can be serviced from nearby network caches rather than from far-located content servers, advantages such as reduced service latency, efficient usage of network bandwidth, and service scalability have been introduced. However, these advantages are determined by how actively content stored in the cache can be utilized. In this paper, we 1) introduce content access schemes in Named-data networking, one of the representative ICN architectures; 2) in particular, review the schemes that allow access to cached content away from routing paths; 3) conduct comparative study on the performance of the schemes using the ndnSIM simulator.

• Journal of Information Management
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• v.43 no.1
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• pp.63-87
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• 2012

This study aims to analyse the actual condition of the ebook services and propose the improvements of ebook services for children in the Korean public library. For this purpose, the current condition of the ebook services in the public libraries were analyzed and categorized by three criteria. Secondly, the ebook use analysis was conducted using PCs and mobile devices in terms of access to ebook library site, searching method, contents type and viewer, lending process, and user help. As a result of the analysis, several issues such as the difficulty in access to ebook site, the complexity of setting and usage depending on the file format, the insufficient user guide, the relatively lower quality service than the commercial's, and the lack of retrieval functions specialized for the ebook were presented. The improvement plan for the ebook services, especially for children in the public library was suggested.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.