• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.262-264
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• 2018

Many of users play Mobil Social Network Games (M-SNG). M-SNGs are played through social network, and typically features multiplayer and asynchronous gameplay mechanics. It is most often implemented as mobile devices with mobile instant messenger app. Kakaotalk provids mobile game platform. The purpose of this study is to find significant factors that have effects on the commitment of M-SNGs. We also conduct multi-group comparison test to study the difference in factors of models between time t and time t1. Time t is October, 2012 and time t1 is April, 2016. This study is to empirically test the research model using data collected from M-SNGs' users. We survey two different groups of time t and time t1 people with the same model. We use structural equation model analysis with AMOS 18.0 and compare two models of different times. This study is to give academicians and practitioners insight about its effects and implications

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.329-331
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• 2020

Edutech is a compound word of education and technology, and is an educational paradigm in the era of the 4th industrial revolution. This refers to next-generation education using information and communication technology (ICT) such as big data, artificial intelligence (AI), robots, and virtual reality (VR) of the 4th industrial revolution. e-Learning is being used as an online lecture for education in ICT, but edutech is attracting attention along with e-learning as the feeding of non-face-to-face education has rapidly increased due to COVID-19. Therefore, this paper summarizes the reviewed papers on the blockchain-based badge service platform, simulation-based collaborative e-Learning system, video English dictionary, and blockchain-based access control audit system.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.49-56
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• 2019

The purpose of this study is to analyze the characteristics and meanings of Instagram hashtags related to the exhibitions as a online communication platform of museums. At the same time, it focuses on efficiency of hashtags as a reference framework of inferring viewing experiences. We collect and visualize Instagram hashtags of exhibitions held in Korea for the past two years including 'Paper Present (2017)', 'YOUTH (2017)', 'Monet, Draw Light Exhibition (2018)', 'Van Gogh Inside (2016)', 'Drawn by the Wind: Shin yun-bok & Jeong Seon'. To sum up, significant data related to viewing experiences are not derived, and hashtags as a reference framework of inferring viewing experiences are turned out to be inefficient. Meanwhile, we conclude that potential for distributing information about the exhibitions is inherent in hashtags. In terms of informational characteristics, we notice that the influence of hashtags related to regional information is presented more than the response toward the viewing experiences. This result shows that Instagram users in the exhibitions are worthy of place making rather than viewing experiences.

• Journal of Soil and Groundwater Environment
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• v.27 no.2
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• pp.36-40
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• 2022

To respond to rapidly changing water circumstances such as climate change, drought, etc., the korean government (MOE) established four advanced strategies for integrated groundwater management. The first strategy is watershed-based management of groundwater. The second strategy is total quantity management of groundwater including improvement of groundwater preservation area policy and procedure of investigation for groundwater influence area, additional construction of groundwater dam, installation of large-scale public wells, extention of spilled groundwater use. The third strategy is prevention of groundwater contamination including expansion of monitoring wells, introducing declaration of groundwater contamination. The last strategy is advancement of groundwater information management including integrated management of data, setting up a big-data based open platform. The above-mentioned four strategies will be reflected in the 4th National Groundwater Management Plan to secure implementation power, and it is expected to laid the foundation for advanced and rational groundwater management system.

• The Journal of Information Systems
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• v.31 no.4
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• pp.47-73
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• 2022

Purpose The purpose of this study is to select the electronic architecture concept of the powertrain domain of the electronic platform to be applied to electric vehicles after 2025. Previously, the automotive electrical and electronic architecture was determined only by trend analysis, but the purpose was to determine the scenario based on the data and select it with clear evaluation indicators. Design/methodology/approach This study identified the function to be applied to the powertrain domain of next-generation electric vehicle, estimated the controller, defined the function feature list, organized the scenario candidates with the controller list and function feature list, and selected the final architecture scenario. Findings According to the research results, the powertrain domain of electric vehicles was selected as the architectural concept to apply the DCU (Domain Control Unit) and VCU (Vehicle Control Unit) integrated architecture to next-generation electric vehicles. Although it is disadvantageous or equivalent in terms of cost, it was found to be excellent in most indicators such as stability, security, and hardware demand.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.99-111
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• 2024

Purpose - This study aims to quantify the long tail effect in the digital economy. It also investigates the role of digital platform before and after the COVID-19 pandemic. Design/methodology/approach - We take advantage of a granular data set from one of the biggest digital platforms in Korea. Rather than computing the absolute number of products sold or the Gini coefficient, we estimate the slope of the log-linear relationship of the non-parametric sales distribution. Findings - We find that the use of online food order and delivery services is positively associated with individual restaurant's sales growth. We also document that the long tail effect is increasing over time. Long tail effects are clustered in the cross-section where average revenue per order is high or the restaurant belongs to the top 50% of the sales distribution. Research implications or Originality - The findings may indicate that digital platforms are contributing to the development of the digital economy in Korea. Also, we confirm that digital platforms make it possible for small and sole proprietors to go through the difficulties induced by the COVID-19 pandemic.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.705-717
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• 2020

Cities in the world are rushing to develop smart cities to create a sustainable and happy city by solving many problems in cities using information and communication technologies such as big data and IoT. However, in Korea's smart cities and smart city certification systems, the focus is on platform-oriented hardware infrastructure, and the information security aspect is first considered to build and authenticate. It is a situation in which a response system for the risk of leakage of big data containing personal information is needed through policy research on the aspect of personal information protection for smart city operation. This paper analyzes the types of personal information in smart cities, problems associated with the construction and operation of smart cities, and the limitations of the current smart city law and personal information protection management system. As a solution, I would like to present a model of a personal information protection management system in the smart city field and propose a plan to strengthen personal information protection through this. Since the management system model of this paper is applied and operated in the national smart city pilot cities, demonstration cities, and CCTV integrated control centers, it is expected that citizens' personal information can be safely managed.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.1-13
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• 2021

This study was performed to investigate the ecosystem service patterns in relation to climate change acceleration utilizing big data analysis. This study aimed to use big data analysis as one of the network of views to identify convergent thinking in two fields: climate change and ecosystem service. The keywords were analysed to ascertain if there were any differences in the perceiving problems, policy direction, climate change implications, and regional differences. In addition, we examined the research keywords of each continent, the centre of ecosystem service research, and the topics to be referred to in domestic research. The results of the analysis are as follows: First, the keyword centrality of climate change is similar to the detailed indicators of The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) regulations, content, and non-material ecosystem services. Second, the cross-analysis of terms in two journals showed a difference in value-oriented point; the Ecosystem Service Journal identified green infrastructure as having economic value, whereas the Climate Change Journal perceives water, forest, carbon, and biodiversity as management topics. The Climate Change Journal, but not the former, focuses on future predictions. Third, the analysis of the research topics according to continents showed that water and soil are closely related to the economy, and thus, play an important role in policy formulation. This disparity is due to differences in each continent's environmental characteristics, as well as economic and policy issues. This fact can be used to refer to the direction of research on ecosystem services in Korea. Consistent with the recent trend of expanding research regarding the impacts of climate change, it is necessary to study strategies to scientifically predict and respond to the negative effects of climate change.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.9
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• pp.207-212
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• 2020

The amount of data has increased significantly due to advances in technology, and various big data processing platforms are emerging, to handle it. Among them, the most widely used platform is Hadoop developed by the Apache Software Foundation, and Hadoop is also used in the IoT field. However, the existing Hadoop-based IoT sensor data collection and analysis environment has a problem of overloading the name node due to HDFS' Small File, which is Hadoop's core project, and it is impossible to update or delete the imported data. This paper uses Apache Kudu and Impala to design Lambda Architecture. The proposed Architecture classifies IoT sensor data into Cold-Data and Hot-Data, stores it in storage according to each personality, and uses Batch-View created through Batch and Real-time View generated through Apache Kudu and Impala to solve problems in the existing Hadoop-based IoT sensor data collection analysis environment and shorten the time users access to the analyzed data.

• Smart Media Journal
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• v.12 no.5
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• pp.65-72
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• 2023

Smart Farm means creating new value in various fields related to agriculture, including not only agricultural production but also distribution and consumption through the convergence of agriculture and ICT. In Korea, a rental smart farm is created to spread smart agriculture, and a smart farm big data platform is established to promote data collection and utilization. It is pushing for digital transformation of agricultural products distribution from production areas to consumption areas, such as expanding smart APCs, operating online exchanges, and digitizing wholesale market transaction information. As such, although agricultural data is generated according to characteristics from various sources, it is only used as a service using statistics and standardized data. This is because there are limitations due to distributed data collection from agriculture to production, distribution, and consumption, and it is difficult to collect and process various types of data from various sources. Therefore, in this paper, we analyze the current state of domestic agricultural data collection and sharing for digital agriculture and propose a data collection and linkage method for artificial intelligence services. And, using the proposed data, we propose a deep learning-based environmental factor recommendation method.