• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.250-257
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• 2018

Today, the integration of the rapid development of ICT and the smart devices moves our lives quickly into an online community environment through not only quick and easy information search but also various social media. Accordingly, individual activities in the smart media environment are pouring out vast quantities of data in many fields, accumulating a tremendous amount of data. The everyday data of individuals is reproducing different values from the previous ones, while suggesting new customized services that utilize them in various fields. Recently, big data utilization has attracted a great attention in the field of healthcare. Especially, development of healthcare service linked with mobile is expected to bring a new paradigm in this field. In this study, creation of a 3D avatar character model as a means to transfer information to individuals more efficiently is proposed in the development of mobile customized service for health promotion and growth prediction of children and adolescents, at the same time, an effective visual expression method to have a sense of immersion and unity is searched.

• Research in Plant Disease
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• v.26 no.3
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• pp.121-133
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• 2020

Climate change, increased extreme weather and climate events, and rapidly changing socio-economic environment threaten agriculture and thus food security of our society. Therefore, it is urgent to shift from conventional farming to smart agriculture using big data and artificial intelligence to secure sustainable growth. In order to efficiently manage plant diseases through smart agriculture, agricultural big data that can be utilized with various advanced technologies must be secured first. In this review, we will first learn about agrometeorological big data consisted of meteorological, environmental, and agricultural data that the plant pathology communities can contribute for smart plant disease management. We will then present each sequential components of the smart plant disease management, which are prediction, monitoring and diagnosis, control, prevention and risk management of plant diseases. This review will give us an appraisal of where we are at the moment, what has been prepared so far, what is lacking, and how to move forward for the preparation of smart plant disease management.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.14-33
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• 2018

The purpose of this study to analyze the informatization trends in Korea through objective newspaper data for the period from 1998 to 2017 for informatization and library in four newspapers including KyoungHyang Newspaper, Kookmin Ilbo, Hankyoreh and Hankookilbo. Based on the analysis results of metadata and related words using BIGKinds, a news big data system, this study presented analysis of simple frequency, classification and classification of the keywords 'information', 'informatization' and 'library'. Based on the results, we compared and analyzed the tendency of informatization in the media through comparison with the 'Information White Paper' which is the publication of government agencies and with research about the research topic of 4 academic journals in the Library and Information Science field. This study tried to interpret the trends of informatization based on the media and it is meaningful that we analyzed the big data of newspaper article which is the long term and time series data. Based on the results of the study, implications of the growth and development of libraries with domestic informatization were suggested. It is expected that we will be able to create a basic framework for developing library informatization policy through the further studies.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.989-1009
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• 2018

Rapid advances in science and technology with exponential development of smart mobile devices, workstations, supercomputers, smart gadgets and network servers has been witnessed over the past few years. The sudden increase in the Internet population and manifold growth in internet speeds has occasioned the generation of an enormous amount of data, now termed 'big data'. Given this scenario, storage of data on local servers or a personal computer is an issue, which can be resolved by utilizing cloud computing. At present, there are several cloud computing service providers available to resolve the big data issues. This paper establishes a framework that builds Hadoop clusters on the new single-board computer (SBC) Mobile Raspberry Pi. Moreover, these clusters offer facilities for storage as well as computing. Besides the fact that the regular data centers require large amounts of energy for operation, they also need cooling equipment and occupy prime real estate. However, this energy consumption scenario and the physical space constraints can be solved by employing a Mobile Raspberry Pi with Hadoop clusters that provides a cost-effective, low-power, high-speed solution along with micro-data center support for big data. Hadoop provides the required modules for the distributed processing of big data by deploying map-reduce programming approaches. In this work, the performance of SBC clusters and a single computer were compared. It can be observed from the experimental data that the SBC clusters exemplify superior performance to a single computer, by around 20%. Furthermore, the cluster processing speed for large volumes of data can be enhanced by escalating the number of SBC nodes. Data storage is accomplished by using a Hadoop Distributed File System (HDFS), which offers more flexibility and greater scalability than a single computer system.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.305-316
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• 2021

The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1357-1366
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• 2017

In the context of domestic consumption environment changes such as expansion of smartphones and increase of single-person households, hypermarket, which was the mainstream of the existing retail market, have recorded negative growth for the last three years due to declining sales. And it is not enough to analyze the influence relationship with other retail channels or investigate the cause of consumption movement. In this study, we analyzed the decline in the growth rate of hypermarket by demographic variables, consumption time, etc. And logistic regression analysis revealed the relationship between the decrease in consumption of hypermarket and the change in the proportion of sales of other retail channels. In addition, we surveyed consumers who have decreased consumption of hypermarket based on actual card consumption data to determine why they choose different retail channels. This is significant in that the result of quantitative analysis of changes in retail channel consumption and the result of qualitative reasoning converged to give a stereoscopic view of consumption.

• Journal of Environmental Science International
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• v.13 no.10
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• pp.883-890
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• 2004

The purpose of this study is to survey and analyze the growth, management and surrounding environment of the big and old trees in Kyoungju-si or the cultural assets alive in our history, and thereby, provide for some data useful to their reasonable protection and use of their surrounding areas. As a result of surveying the growth conditions of the big and old trees, it was found that the height of new grass was 10.5cm on average, the activity scale of the wood was 7.2k$\Omega$, the soil hardness was $16.7kg/cm^2$, the soil acidity was pH 4.8, and the soil moisture was $13.3\%$. Such findings suggest that the soil has been acidified by people's frequent passages, but that the other growth conditions are more or less normal. Hence, it is desirable to secure a sufficient space around the trees or reduce people's stamping pressure with some mechanisms. On the other hand, the visible conditions of the trees were found more or less normal, but many trees remained cut or barked (with some cavities), requiring an optimal treatment or measure. Lastly, as the population has decreased in the suburban traditional villages, the surrounding environment seems to be less vulnerable to people's frequent visits. Nevertheless, in consideration of the fact that there are only a few public space for the villagers, it is deemed necessary to rearrange or maintain some parts of the surrounding environment as public space for villagers or hikers.

• The Journal of Bigdata
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• v.7 no.2
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• pp.153-172
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• 2022

Online shopping has transformed and rapidly grown the entire market at the forefront of wholesale and retail services as an effective solution to issues such as digital transformation and social distancing policy (COVID-19 pandemic). Small business owners, who form the majority at the center of the online shopping industry, are constantly collecting policy changes and market trend information to overcome these problems and use them for marketing and other sales activities in order to overcome these problems and continue to grow. Objective and refined information that is more closely related to the business is also needed. Therefore, in this paper, through the collection and analysis of big data information, which is the core technology of digital transformation, key variables are set in product classification, sales trends, consumer preferences, and review information of online shopping malls, and a method of using them for competitor comparison analysis and business sustainability evaluation has been prepared and we would like to propose it as a service. If small and medium-sized businesses can benchmark competitors or excellent businesses based on big data and identify market trends and consumer tendencies, they will clearly recognize their level and position in business and voluntarily strive to secure higher competitiveness. In addition, if the sustainable growth of the online shopping mall operator can be confirmed as an indicator, more efficient policy establishment and risk management can be expected because it has an improved measurement method.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.87-95
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• 2018

Recently, with the technological development of artificial intelligence, related market is expanding rapidly. In the artificial intelligence technology field, which is still in the early stage but still expanding, it is important to reduce uncertainty about research direction and investment field. Therefore, this study examined technology trends using text mining and topic modeling among big data analysis methods and suggested trends of core technology and future growth potential. We hope that the results of this study will provide researchers with an understanding of artificial intelligence technology trends and new implications for future research directions.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.301-311
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• 2020

With the recent global urban issues such as climate change, urbanization, and energy problems, the smart city was proposed as one of the solutions in urban planning. This study introduces the smart city initiatives of South Korea by examining the recent history of smart city policies and their limitations. This case study reflects the experience of one of the countries which thrived to building smart cities as their national key industries to drive economic growth. It also analyzes the trends of the smart city using big data analysis techniques. Although there are obstacles such as economic recession, failing to differentiate from the U-city, low service level than expected smart functionality, We could recognize the current status of the smart city policies in South Korea such as 1) Korean smart city development projects are actively implemented, 2) public consensus suggests that applying advanced technology and the active role of government need, 3) a comprehensive and strategic approach with the integration and application of advanced technologies is required as well, 4) investment by both private and public sectors need to deliver social improvements. This study suggests future direction of smart city polity in South Korea in the conclusion.