• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1129-1137
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• 2013

Cloud storage system that cloud computing providers provides large amounts of data storage and processing of cloud computing is a key component. Large vendors (such as Facebook, YouTube, Google) in the mass sending of data through the network quickly and easily share photos, videos, documents, etc. from heterogeneous devices, such as tablets, smartphones, and the data that is stored in the cloud storage using was approached. At time, growth and development of the globally data, the cloud storage business model emerging is getting. Analysis new network storage cloud storage services concepts and technologies, including data manipulation, storage virtualization, data replication and duplication, security, cloud computing core.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.11
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• pp.1289-1301
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• 2004

Direct numerical simulation (DNS) of strongly-heated air flows moving upward in a vertical tube has been conducted to investigate the effect of gas property variations on turbulence modification. Three heating conditions(q$_1$$^{+}$=0.0045, 0.0035 and 0.0018) are selected to reflect the experiment of Shehata and McEligot (1998) at the inlet bulk Reynolds numbers of 4300 and 6000. At these conditions, the flow inside the heated tube remains turbululent or undergoes a transition to subturbulent or laminarizing flow. Consequently, a significant impairment of heat transfer occurs due to the reduction of flow turbulence. The predictions of integral parameters and mean profiles such as velocity and temperature distributions are in excellent agreement with the experiment. The computed turbulence data indicate that a reduction of flow turbulence occurs mainly due to strong flow acceleration effects for strongly-heated internal gas flows. Thus, buoyancy influences are secondary but not negligible especially for turbulent flow at low heating condition. Digital flow visualization also shows that vortical structures rapidly decay as the heating increases.s.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.66-71
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• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

• Journal of Information Technology Applications and Management
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• v.29 no.1
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• pp.59-70
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• 2022

Recently, in platforms such as YouTube and Instagram, virtual characters resembling human life become the main characters, produce various contents, breathe with the public, and create the era of virtual humans. For example, existing game characters appear as virtual characters with unique AUs, or AI characters created by reflecting the public's preferences are actively communicating with the public through advertisements and SNS activities. As the consumption of video content through smart devices increases significantly in the post-corona era, virtual influencers are being used as all-round entertainers because there is little risk of personality controversy or production cost. there is a trend In this study, we investigated the characteristics of the case of being active as an influencer among the activities of a virtual character, and how the interactive aspect of the influencer appears by identifying the current situation through major cases. Combining this, based on the analysis of the influence of virtual influencers, the parts that producers should recognize are derived, and the differentiated characteristics of interactive virtual influencers are summarized. In addition, the difficulties of virtual influencers were investigated and problems were identified, and for the development of the content industry, a more favorable method for interaction was presented and suggestions were made to secure inner sincerity.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.111-118
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• 2023

Cyber attacks are increasing worldwide, and attacks on personal privacy such as CCTV and IP camera hacking are also increasing. If you search for IP camera hacking methods in spaces such as YouTube, SNS, and the dark web, you can easily get data and hacking programs are also on sale. If you use an IP camera that has vulnerabilities used by hacking programs, you easily get hacked even if you change your password regularly or use a complex password including special characters, uppercase and lowercase letters, and numbers. Although news and media have raised concerns about the security of IP cameras and suggested measures to prevent damage, hacking incidents continue to occur. In order to prevent such hacking damage, it is necessary to identify the cause of the hacking incident and take concrete measures. First, we analyzed weak account settings and web server vulnerabilities of IP cameras, which are the causes of IP camera hacking, and suggested solutions. In addition, as a specific countermeasure against hacking, it is proposed to add a function to receive a notification when an IP camera is connected and a function to save the connection history. If there is such a function, the fact of damage can be recognized immediately, and important data can be left in arresting criminals. Therefore, in this paper, we propose a method to increase the safety from hacking by using the connection notification function and logging function of the IP camera.

• Journal of Distribution Science
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• v.13 no.8
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• pp.97-104
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• 2015

Purpose - This study examines the positive impact of the social distance between producers and users of online content, investigating and analyzing the most popular Web content. In addition, it tries to elicit the matching effect that appears when the individuals'cultural background is consistent with social distance. Research design, data, and methodology - We collected and analyzed actual data about 4,981 videos clips on YouTube, looking at six countries in order to verify the content of this study. Based on the results of the data analysis, the study conducted behavioral measurements on popularity, social distance, culture, and user engagement. The unit of analysis was the content and we collected information about the content producers and the content records. We controlled the views, comments, likes, calendar dates, and ages in the empirical models. The data was collected in 2011, with the records coming from South Korea, Japan, China, U.S., German, and France. A total of 4,980 elements were analyzed in the model. The empirical model estimated is the bivariate negative binomial distribution (NBD) model. Results - It turns out that there is a possibility that the matching effect can be diminished by variables that reflect the psychological involvement of user engagement. This study proposes academic and practical implications based on these research results. This research shows the positive effect of social distance between users and producers on the increased performance of the online content. We find the effect of social distance to be a stronger tendency in collectivism. The collectivists follow their sense of friendship and intimacy in their culture and, the social congruence effect can be found there as well. The effect, however, could erode in a social case where users are motivated by strong intrinsic and psychological factors. In addition, user engagement complicates the process of user decision making regarding the information. Conclusions - This study examines how the differential effects of social distance caused by culture could disappear through user commitment as a complicated user motivation. Some potential implications are as follows. First, a firm in the collectivism culture has to communicate based on the social distance. In fact, most online channels do not have a function that indicates the social distance as measured by favorites or subscribers. This function could help increase the performance of the content in online channels, but this increasing effect can only be found in a collectivist culture. Based on this, the firms have to communicate and announce to users the actual social distance between users and producers. Second, firms should develop a system that discovers the social distance and culture and shows these measures to users and producers, since the congruence effect between social distance and culture is found only for low user engagement. The firms can take the advantage of the congruence effect only for the development of the social distance and culture visualized system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.111-120
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• 2016

Prior knowledge about the SNS (Social Network Services) datasets is often required to conduct valuable analysis using social media data. Understanding the characteristics of the information extracted from SNS datasets leaves much to be desired in many ways. This paper purposes on analyzing the detail of the target social network services, Twitter, Instagram, and YouTube to establish the spatial informatization process to integrate social media information with existing spatial datasets. In this study, valuable information in SNS datasets have been selected and total 12,938 data have been collected in Seoul via Open API. The dataset has been geo-coded and turned into the point form. We also removed the overlapped values of the dataset to conduct spatial integration with the existing building layers. The resultant of this spatial integration process will be utilized in various industries and become a fundamental resource to further studies related to geospatial integration using social media datasets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2334-2347
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• 2023

Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.1-8
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• 2023

Cross-domain recommendation is a method that shares related user information data and item data in different domains. It is mainly used in online shopping malls with many users or multimedia service contents, such as YouTube or Netflix. Through K-means clustering, embeddings are created by performing clustering based on user data and ratings. After learning the result through a transformer network, user satisfaction is predicted. Then, items suitable for the user are recommended using a transformer-based recommendation model. Through this study, it was shown through experiments that recommendations can predict cold-start problems at a lesser time cost and increase user satisfaction.

• Steel and Composite Structures
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• v.9 no.1
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• pp.19-38
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• 2009

The present paper provides test data to evaluate the seismic performance of recycled aggregate concrete (RAC) filled steel square hollow section (SHS) beam-columns. Fifteen specimens, including 12 RAC filled steel tubular (RACFST) columns and 3 reference conventional concrete filled steel tubular (CFST) columns, were tested under reversed cyclic flexural loading while subjected to constant axially compressive load. The test parameters include: (1) axial load level (n), from 0.05 to 0.47; and (2) recycled coarse aggregate replacement ratio (r), from 0 to 50%. It was found that, generally, the seismic performance of RACFST columns was similar to that of the reference conventional CFST columns, and RACFST columns exhibited high levels of bearing capacity and ductility. Comparisons are made with predicted RACFST beam-column bearing capacities and flexural stiffness using current design codes. A theoretical model for conventional CFST beam-columns is employed in this paper for square RACFST beam-columns. The predicted load versus deformation hysteretic curves are found to exhibit satisfactory agreement with test results.