• Journal of Digital Convergence
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• v.13 no.11
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• pp.25-33
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• 2015

In Korea, despite the increase in demand for Bigdata manpower, institutions and universities to educate and train Bigdata manpower are not yet much. Therefore, this study investigated the status regarding the recognition on Bigdata of universities students and presented a direction for educating Bigdata manpower at the university. In order to accomplish this purpose, this study surveyed and analyzed the students' understanding of Bigdata, the awareness of the students about the social impact of Bigdata, the learning intention of the students on Bigdata and presented Implications for Bigdata workforce development. As a result, despite of the somewhat difference in understanding for the Bigdata, it was found that their awareness about the impact of Bigdata is very positive. And this study showed the need of universities' and government' political effort for Bigdata workforce development, because it was investigated that students' intentions of learning for Bigdata is proportional to students' understanding levels and learning experience for Bigdata.

• The Journal of Bigdata
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• v.2 no.2
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• pp.67-74
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• 2017

The use of Bigdata plays an important role in all areas of society. Especially in the health care field, the role of Bigdata is very considerable because it deals with people's life and health. However, the interest and awareness of quality control of medical data is markedly low. Because the low-quality medical Bigdata leads to national loss and public health impairment, quality control of medical Bigdata is needed. The purpose of this research is to present the direction of medical Bigdata quality management by examining literature and cases of domestic and foreign medical Bigdata quality management practices. In addition, as a case of medical Bigdata quality control in the Y medical institution in Korea, activities of a Bigdata quality management TFT and results of a survey conducted for major data users in the hospital were presented.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.29-29
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• 2022

• Journal of Digital Convergence
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• v.13 no.10
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• pp.305-312
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• 2015

In Korea, institutions and universities to educate and train Bigdata manpower are not yet much. There are various causes, but major cause among them is lack of understanding and perception on Bigdata. Therefore, this study investigated the situation regarding the recognition on Bigdata of universities' faculties and presented a direction for educating Bigdata manpower at the university. As a result, it was investigated that their awareness about the impact of Bigdata is not so great, despite of the somewhat understanding for the Bigdata. In particular, it was investigated that their intentions of research and education for Bigdata are not high. So, for a while, it was identified that Bigdata specialist training will not be easy. In conclusion, this study suggested that the government should pay its attention more on policy for Bigdata manpower training policy of the universities according to direction of the government 3.0 policy that considers the Bigdata to the axis of the major policy.

• The Journal of Bigdata
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• v.2 no.1
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• pp.1-3
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• 2017

• The Journal of Bigdata
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• v.7 no.2
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• pp.75-90
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• 2022

Recently, complex and sophisticated analysis of transportation is required due to changes in the socioeconomic environment and the development of bigdata technology. Especially, the revision of 3 laws including PERSONAL INFORMATION PROTECTION ACT makes it possible to combine various types of mobility data. But strengthen personal information protection makes inefficiency in utilizing mobility bigdata. In this paper, we proposed the "Virtual fusion methdology via mobility bigdata" which is a methodology for indirect data fusion for various mobility bigdata such as mobile data and transportation card data, in order to resolve legal restrictions and enable various transportation analysis. And we also analyzed regional bus passenger in Seoul capital area and Cheongju city with aforementioned methodology for verification. This methdology could analyze behavioral pattern of passenger with the MCGM(Mobility Comprehensive Genetic Map), graph with position and time, making with mobile data. Consquently, using MCGM, which is a result for indirect data fusion, makes it possible to analyze various transportation problems.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.107-108
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• 2018

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.109-110
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• 2018

• Journal of Information Technology Services
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• v.15 no.1
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• pp.97-111
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• 2016

In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.7
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• pp.791-797
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• 2014

In order to create an environment for Apache Hadoop for parallel distributed processing system of Bigdata, by connecting a plurality of computers, or to configure the node, using the configuration of the virtual nodes on a single computer it is necessary to build a cloud fading environment. However, be constructed in practice for education in these systems, there are many constraints in terms of cost and complex system configuration. Therefore, it is possible to be used as training for educational institutions and beginners in the field of Bigdata processing, development of learning systems and inexpensive practical is urgent. Based on the Raspberry Pi board, training and analysis of Big data processing, such as Hadoop and NoSQL is now the design and implementation of a learning system of parallel distributed processing of possible Bigdata in this study. It is expected that Bigdata parallel distributed processing system that has been implemented, and be a useful system for beginners who want to start a Bigdata and education.