• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.61-73
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• 2021

This study aimed to identify the landscape perception and landscape characteristics of users by utilizing SNS data generated by their experiences. Therefore, how to recognize the main places and scenery appearing on the island, and what are the characteristics of the main scenery were analyzed using online text data and photo data. Text data are text mining and network structural analysis, while photographic data are landscape identification models and color analysis. As a result of the study, First, as a result of frequency analysis of Bakji·Banwol-do topics, we were able to derive keywords for local landscapes such as 'Purple Bridge', 'Doori Village', and location, behavior, and landscape images by analyzing them simultaneously. Second, the network structure analysis showed that the connection between key and undrawn keywords could be more specifically analyzed, indicating that creating landscapes using colors is affecting regional activation. Third, after analyzing the landscape identification model, it was found that artificial elements would be excluded to create preferred landscapes using the main targets of "Purple Bridge" and "Doori Village", and that it would be effective to set a view point of the sea and sky. Fourth, Bakji·Banwol-do were the first islands to be created under the theme of color, and the colors used in artificial facilities were similar to the surrounding environment, and were harmonized with contrasting lighting and saturation values. This study used online data uploaded directly by visitors in the landscape field to identify users' perceptions and objects of the landscape. Furthermore, the use of both text and photographic data to identify landscape recognition and characteristics is significant in that they can specifically identify which landscape and resources they prefer and perceive. In addition, the use of quantitative big data analysis and qualitative landscape identification models in identifying visitors' perceptions of local landscapes will help them understand the landscape more specifically through discussions based on results.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.167-183
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• 2023

Gases originated from the final SNF (spent nuclear fuel) disposal site are very mobile in the barrier and they may also affect the migration of radioactive nuclides generated from the SNF. Mechanisms of gas-nuclide migration in the multi-barrier and their influences on the safety of the disposal site should be understood before the construction of the final SNF disposal site. However, researches related to gas-nuclide coupled movement in the multi-barrier medium have been very little both at home and abroad. In this study, properties of gas generation and migration in the SNF disposal environment were reviewed through previous researches and their main mechanisms were summarized on the hydrogeological evolution stage of the SNF disposal site. Gas generation in the SNF disposal site was categorized into five origins such as the continuous nuclear fission of the SNS, the Cu-canister corrosion, the oxidation-reduction reaction, the microbial activity, and the inflow from the natural barriers. Migration scenarios of gas in porous medium of the multi-barrier in the SNF repository site were investigated through reviews for previous studies and several gas migration types including ① the free gas phase flow including visco-capillary two-phase flow, ② the advection and diffusion of dissolved gas in pore water, ③ dilatant two-phase flow, and ④ tensile fracture flow, were presented. Reviewed results in this study can support information to design the further research for the gas-nuclide migration in the repository site and to evaluate the safety of the Korean SNF disposal site in view points of gas migration in the multi-barrier.

• Journal of the Korea Convergence Society
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• v.9 no.4
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• pp.15-22
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• 2018

The purpose of this study is to investigate the consumer perception of packaging using big data analysis. This study use text mining to extract meaningful words from text and semantic network analysis to analyze connectivity and propagation trends. Data were collected by dividing the 'packaging(Korean)' and 'packaging(English)'. This study visualized the word network structure of the two key words and classified them into four groups with similar meaning through CONCOR analysis. The group name was specified based on the words constituting the classified group. These groups are a major category of consumers' perception of packaging. Especially cosmetics and design have high frequency of words and high centrality. Therefore it can be expected that the packaging design is perceived as important in the cosmetics industry. This study predicts consumers' perception of packaging so it can be a basis for future research and industry development.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.623-637
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• 2016

This study examined the importance of social capital in facilitating older adults' learning and adaptation of information technology as well as alleviating depressive symptoms. At two senior community centers in South Korea, 144 adults aged 60 and older were recruited to participate in 12 week-long technology classes to learn computers, smart phone, and internet skills. At the baseline interviews were conducted to assess their health status, depression, and online social relationships. Online and offline social capital (bonding vs. bridging) was assessed (Williams, 2006). Four-step Hierarchical Linear Regression analysis was conducted to examine the effects of online social relationship on depression. Findings suggested that depressive symptoms were associated with being widowed, being unemployed, and perceiving poor health status. Adding social capital variables in the final step, older adults who perceived less stressors, greater level of subjective health and high online bonding capitals had less depressive symptoms. Only online social bonding was significant in alleviating depression. This final model explained 48% of the variance. Computer/Internet training for older adults need to consider the significant role bonding social capital can play. The findings of this pilot study provided a preliminary base of knowledge about acceptable community-based interventions for older adults.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.123-146
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• 2017

The information that consumers share in the SNS (Social Networking Service) has a great influence on the purchase of consumers. Therefore, it is necessary to pay attention to new research methodology and advertising strategy using Social Big Data. In this context, the purpose of this study is to quantitatively analyze customer value through Social Big Data. In this study, we analyzed the value structure of consumers for the three smartphone brands through text mining and positive/negative image analysis. Analysis result, it was possible to distinguish the emotional aspects (sensitivity) and rational aspects (rationality) for customer value per brand. In the case of the Galaxy S7 and iPhone 6S, emotional aspects were important before the launch, but the rational aspects was important after release date. On the other hand, in the case of the LG G5, emotional aspects were important before and after launch. We can propose two core advertising strategies based on analyzed consumer value. When developing advertising strategy in the case of the Galaxy S7, there is a need to emphasize the rational aspects of product attributes and differentiated functions. In the case of the LG G5, it is necessary to consider the emotional aspects of happiness, excitement, pleasure, and fun that are felt by using products in advertising strategy. As a result, this study will provide a good standard for actual advertising strategy through consumer value analysis. Advertising strategies are primarily driven by intuition or experience. Therefore, it is important to develop advertising strategies by analyzing consumer value through social big data analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.47-62
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• 2012

To propagate clinical disease management service, there should be built a ecosystem where service developers, service providers, device suppliers closely cooperate for u-Health platform. However, most u-Health platform is difficult to build an effective ecosystem due to the lack of secure and effective PHR(Personal Health Record) management, the lack of personalized and intelligent service, difficulties of N-screen service. To solve these problems we suggest the CDMP(Chronic Disease Management Platform) architecture. The CDMP is a software platform that provides the core functions to develop the chronic disease management services and performs a hub function for the link and integration rbetween various services and systems. CDMP is SOA based platform that enables a provision of reusability, expansibility and it provides open API where everybody can share information, contents and services easily. CDMP supports the multi platform system foN-screen service and the self management functions via SNS. In this paper, we design and implement the CDMP including PHR service based on hybrid data model for privacy preservation. Experiment results prove the effectiveness of hybrid model-based PHR service.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.95-110
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• 2014

The purpose of this research is to further investigate the influence of partnership between with the mediator effect of the social business on the outcome of SCM. IT technology fusion electronic tags, mobile phone, such as cloud computing is also activated in supply chain management of recently, business is faster, if social business is applied here that are smarter, customers or suppliers, there may be communication directly and to further improve the relationship partnership. 150 questionnaires were sent to companies that have introduced SCM to their systems and are operating it. Among 150 questionnaires, 127 collected data were analyzed excluding incomplete 23 data. Statistical methods used in this study were frequency analysis, factor analysis, reliability analysis, t-test, ANOVA, path analysis, Scheffe test and Sobel test with Amos 18.0. and SPSS 21.0. The analytical results are as follows. First, the more the reliability, information share, continuous transaction, effects on the social business are getting higher, the interdependence has little impact on it. Second, the impact on the outcome of SCM, partnerships between companies, showed a significant influence the reliability, the share of information, the continuous transaction, but the interdependence was analysed as an uninfluential factor. Third, the social business is analyses to have a mediator effect in relationship between the partnership and the outcome of SCM.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.154-159
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• 2015

Over the past few years, user needs in the smartphone application market have been shifted from diversity toward intelligence. Here, we propose a novel cognitive agent that plans the daily routines of users using the lifelog data collected by the smart phones of individuals. The proposed method first employs DPGMM (Dirichlet Process Gaussian Mixture Model) to automatically extract the users' POI (Point of Interest) from the lifelog data. After extraction, the POI and other meaningful features such as GPS, the user's activity label extracted from the log data is then used to learn the patterns of the user's daily routine by POMDP (Partially Observable Markov Decision Process). To determine the significant patterns within the user's time dependent patterns, collaboration was made with the SNS application Foursquare to record the locations visited by the user and the activities that the user had performed. The method was evaluated by predicting the daily routine of seven users with 3300 feedback data. Experimental results showed that daily routine scheduling can be established after seven days of lifelogged data and feedback data have been collected, demonstrating the potential of the new method of place-time-activity coupled daily routine planning systems in the intelligence application market.

• Journal of KIISE
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• v.42 no.4
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• pp.504-511
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• 2015

Recently, the amount of data is rapidly increasing with the popularity of the SNS and the development of mobile technology. So, it has been actively studied for the effective data analysis schemes of the large amounts of data. One of the typical schemes is a Voronoi diagram based on kNN join algorithm (VkNN-join) using MapReduce. For two datasets R and S, VkNN-join can reduce the time of the join query processing involving big data because it selects the corresponding subset Sj for each Ri and processes the query with them. However, VkNN-join requires a high computational cost for constructing the Voronoi diagram. Moreover, the computational overhead of the VkNN-join is high because the number of the candidate cells increases as the value of the k increases. In order to solve these problems, we propose a MapReduce-based kNN-join query processing algorithm for analyzing the large amounts of data. Using the seed-based dynamic partitioning, our algorithm can reduce the overhead for constructing the index structure. Also, it can reduce the computational overhead to find the candidate partitions by selecting corresponding partitions with the average distance between two seeds. We show that our algorithm has better performance than the existing scheme in terms of the query processing time.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.83-90
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• 2015

This paper examines the rising value of social networked journalism and analyzes the case of a social news site based on the theory of networked journalism. Social networked journalism allows the public to be involved in every aspect of journalism production through crowd-sourcing and interactivity. The networking effect with the public is driving journalism to transform into a more open, more networked and more responsive venue. "wikitree" is a social networking news service on which anybody can write news and disseminate it via Facebook and Twitter. It is operated as an open sourced program which incorporates "Google Translate" to automatically convert all its content, enabling any global citizen with an Internet access to contribute news production and share either their own creative contents or generated contents from other sources. Since its inception, "wikitree global" site has been expanding its coverage rapidly with access points arising from 160 countries. Analyzing its international coverage by country and by news category as well as by the unique visit numbers via SNS, the results of the case study imply that networking with the global public can enhance news traffic to the social news site as well as to specific news items. The results also suggest that the utilization of Twitter and Facebook in social networked journalism can break the boundary between local and global public by extending news-gathering ability while growing audience's interest in the site, and engender a feasible business model for a local online journalism.