• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3529-3550
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• 2016

In heterogeneous networks (HetNets), energy saving is vital for a sustainable network development. Many techniques, such as spectrum allocation, network planning, etc., are used to improve the network energy efficiency (EE). In this paper, micro BSs utilizing cell range expansion (CRE) and spectrum allocation are considered in multi-channel heterogeneous networks to improve EE. Hotspot region is assumed to be covered by micro BSs which can ensure that the hotspot capacity is greater than the average demand of hotspot users. The expressions of network energy efficiency are derived under shared, orthogonal and hybrid subchannel allocation schemes, respectively. Particle swarm optimization (PSO) algorithm is used to solve the optimal ratio of subchannel allocation in orthogonal and hybrid schemes. Based on the results of the optimal analysis, we propose three service control strategies on the basis of large-scale user behaviors, i.e., adjust micro cell rang expansion (AmCRE), adjust micro BSs density (AmBD) and adjust micro BSs transmit power (AmBTP). Both theoretical and simulation results show that using shared subchannel allocation scheme in AmBD strategies can obtain maximal EE with a very small area ratio. Using orthogonal subchannel allocation scheme in AmCRE strategies can obtain maximal EE when area ratio is larger. Using hybrid subchannel allocation scheme in AmCRE strategies can obtain maximal EE when area ratio is large enough. No matter which service control strategy is used, orthogonal spectrum scheme can obtain the maximal hotspot user rates.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.627-636
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• 2022

The purpose of this study is to maximize the development and utilization of digital innovation. First, analyzed the status of industrial development and digital innovation. Second, examined emotion and experience, looked into their types and properties. Third, attempted to develop a more creative and innovative user experience. The results of this study were presented as a theoretical basis, specification of research direction and research scope, and design analysis direction. It is expected to be used as a basic data that can help how to approach and interpret human emotions and behaviors in order to provide differentiated experiences by he essential concepts of emotions, experiences in various fields in the future.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.169-180
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• 2022

As people spend more time indoors due to the COVID-19 pandemic situation, content consumption is increasing, leading to the rapid demand for Over The Top(OTT) services. Thus, this study attempted to verify impacts of OTT traits on the value, satisfaction, and continuous use intention perceived by users. Through the survey, 437 responses were collected, and analysis was conducted using AMOS 26.0. Results found that the traits of OTT service had a positive effect on perceived value that had a positive effect on user satisfaction and continuous use intention. User satisfaction was also found to have a positive effect on the intention to continue using OTT services. Moreover, hedonic innovation moderated the relationships between OTT traits and perceived value with exception of ubiquity. The findings provide valuable information for OTT service providers in understading users' behaviors.

• Journal of the Ergonomics Society of Korea
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• v.33 no.4
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• pp.267-279
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• 2014

Objective: The objective of this study was to define the Dynamic Sitting (DS) through trend analysis and research on the Dynamic Chair (DC) and applied technologies. Background: The effects of changing posture on the human body have been studied to find out healthy sitting postures. It is believed that changing posture is effective in reducing disc pressure on spinal cord and preventing back pain and musculoskeletal disease. But, the definition of DS and trends of DC have not been researched yet. Therefore, trend analysis of DC and its applied technologies are required to define dynamic sitting posture. Method: We researched the type of occupant postures from previous studies. And then, sitting behaviors were classified into three types; (1) sitting and standing, (2) working and studying, (3) taking a rest. Results: Variety shapes of DC and applied technologies were found out. From the result, the trend of DC and applied technology were summarized from three perspectives. ; (1) changing the chair functions according to user's intention, (2) conversion of dynamic chair technologies to office chair mechanism, (3) enables the user to change their sitting posture without operating control device. Conclusion: From this study, we defined dynamic sitting posture and analyzed the trend of DC and its applied technologies. This result might be used to develop an office chair for healthy sitting. But further investigation is required to figure out the technologies and functions for development of healthy chair. Application: The results of the publishing trend analysis might help to determine design concept of office chair.

• Journal of Korean Library and Information Science Society
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• v.40 no.4
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• pp.139-158
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• 2009

This paper used the network analysis method to analyse a variety of attributes of searcher's search behaviors which was appeared on search access log data. The results of this research are as follows. First, the structure of network represented depending on the similarity of the query that user had inputed. Second, we can find out the particular searchers who occupied in the central position in the network. Third, it showed that some query were shared with ego-searcher and alter searchers. Fourth, the total number of searchers can be divided into some sub-groups through the clustering analysis. The study reveals a new recommendation algorithm of associated searchers and search query through the social network analysis, and it will be capable of utilization.

• Journal of the Korean Society for information Management
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• v.17 no.3
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• pp.193-212
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• 2000

This study was to analyze the media-contacting motivation and the optional seeking behavior for the informations, namely, what kinds of media the information users contact and what types of informations they select for the purpose of meeting their needs of the informations. For this purpose, the questionaires answered by 277 of the employees including the professors, reseatchers, teachers, officials and collegians were analyzed by properties. The Result of this analysis is that the new hints or ideas by the professors and the researchers appeared in the highest at the academic meetings or the reseatching activities and those at the other employees appeared at the internet sites. It was shown that there is a very close correlation between the information-seeking behaviors and the user properties as the types of their seeking informations and their information-seeking morivations are considerably different from each other.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.1-21
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• 2018

This study aims to investigate the usage patterns of users in Social Network Services (SNS) where is an upsurge. Specifically, the paper considers the reason why young people more and more prefer online (or mobile) SNS activities rather than offline face-to-face social relationship. Furthermore, the drivers which affect SNS usages are considered from users' personal characteristics and social influences. User's personal characteristics include their personalities (extraversion and introversion), narcissism, and life satisfaction. Social influences involve subjective norm, visibility, and image. Affected by personal and social factors in SNS, users intend to show positive self-presentation, which refers to a behavior to selectively expose his/her goodness to others. As one of the most influential drivers affecting SNS usage, the positive self-representation has an effect on the level of SNS usage. Thus, this paper suggests the hypothesized research model focusing on positive self-representation in the relationship among personal characteristics, social influence, and user's behavior in SNS. Empirical data analysis with 100 questionnaires suggests that all hypotheses were adopted except for the effect of visibility among social influence factors on positive self-representation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.491-500
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• 2013

With the advent of big data and increased costs of SSD(HDD), domestic and foreign Internet cafes and organizations have adopted NDS(No Disk System) solution recently. NDS is a storage virtualization solution based on a kind of cloud computing. It manages Operating System and applications in the central server, which were originally managed by individual computers. This research will illustrate the way to analyze user's behaviors under NDS circumstance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.6-8
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• 2022

Web log analysis is one of the essential procedures for service improvement. ScienceON is a representative information service that provides various S&T literature and information, and we analyze its logs for continuous improvement. This study aims to analyze ScienceON web logs recorded in May 2020 and May 2021, dividing them into humans and web crawlers and performing an in-depth analysis. First, only web logs corresponding to S (search), V (detail view), and D (download) types are extracted and normalized to 658,407 and 8,727,042 records for each period. Second, using the Python 'user_agents' library, the logs are classified into humans and web crawlers, and third, the session size was set to 60 seconds, and each session is analyzed. We found that web crawlers, unlike humans, show relatively long for the average behavior pattern per session, and the behavior patterns are mainly for V patterns. As the future, the service will be improved to quickly detect and respond to web crawlers and respond to the behavioral patterns of human users.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.1
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• pp.29-37
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• 2020

This paper implements a method of extracting an object about a dog through real-time image analysis and classifying dog behaviors from the extracted images. The Darknet YOLO was used to detect dog objects, and the Teachable Machine provided by Google was used to classify behavior patterns from the extracted images. The trained Teachable Machine is saved in Google Drive and can be used by ml5.js implemented on a node.js server. By implementing an interactive web server using a socket.io module on the node.js server, the classified results are transmitted to the user's smart phone or PC in real time so that it can be checked anytime, anywhere.