• Fisheries and Aquatic Sciences
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• v.17 no.3
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• pp.377-380
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• 2014

RNA interference (RNAi)-mediated transcriptional knock-down of Crassostrea gigas big defensin 1 and 2 genes (Cg-BigDef1 and Cg-BigDef2) was investigated. The cDNA sequences of Cg-BigDef1 and Cg-BigDef2 were identical, excluding an additional fragment of 20 nucleotides in Cg-BigDef1; thus, a long double-stranded RNA (dsRNA) targeting the mRNA of Cg-BigDef2 effectively downregulated both Cg-BigDef2 and Cg-BigDef1. In addition, long dsRNA targeting green fluorescent protein (GFP) did not affect transcription of the two big defensin genes. These results suggest that the transcriptional downregulation of Cg-BigDef1 and Cg-BigDef2 was mediated by sequence-specific RNA interference (RNAi). Despite injection of long dsRNA targeting Cg-BigDef2 into only the adductor muscle, knock-down of Cg-BigDef1 and Cg-BigDef2 was observed in the adductor muscle, hemocytes, mantle, and gills, suggestive of systemic spread of RNAi in C. gigas. Furthermore, the inhibitory effect of dsRNA persisted until 72 h post-injection, indicative of a long-lasting RNAi-mediated knock-down of target genes.

• Journal of Information Technology Applications and Management
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• v.21 no.1
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• pp.53-67
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• 2014

In recent years, more data is being generated for the activation of the SNS, the spread of Smartphones and the development of IT technology. Therefore, it is to collect large amounts of data, analyze and ensure meaningful information has become important. The use of these data are formed on the global trend. Big data so-called, has attracted attention as a source of new business. Big Data can then give us the opportunity to be able to create a new customer and diversify the business. So, many companies have investment and effort for big data utilization. However, technology, infrastructure, human resources is different for each of the companies. Therefore, it is necessary to diagnose the level of big data utilization companies. In this study, through a literature review of existing, we derived the success factors for the big data utilization. And developed a diagnostic indicator that allows success factors derived, can be used to determine levels of big data utilization of the company. In addition, as a development of diagnostic indicators, were carried out case studies to diagnose company. Through this study, it will be an opportunity to be able to be reflected in the strategy of big data utilization company.

• Smart Media Journal
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• v.4 no.3
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• pp.56-61
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• 2015

Although many successful cases regarding big data have been reported, building information systems of big data is still difficult. From the perspective of technology the builders need to understand the whole process of systems development ranging from collecting, storing, processing, and analyzing data to presenting and using information. Whereas, from the perspective of business, the builders need to understand the values of the proposed big data project and explain to top managers who have to make a decision of the risky investment. This study proposes a framework of 5W 1H that can help the builder understand things related to the development of big data information systems. In addition, big data cases from the real world have been illustrated by applying to the framework. It is expected to help builders understand and manage big data projects and lead managers to make better decisions of the investment to the development of information systems.

• Journal of Korean Society of Archives and Records Management
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• v.15 no.1
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• pp.127-155
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• 2015

This study proposes the formation of education service models using presidential archives based on ubiquitous technology. To accomplish these, this study analyzed various education programs of presidential archives in Korea and other countries. The reason behind the use of ubiquitous technology is to allow interinstitution cooperation and create synergy effects. With this, this technology is grafted onto the modified BIG6 Model, which is developed for information literacy. This study can be useful and valuable in the aspects of education, contents development, and service development.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.301-314
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• 2013

The existing computer environment, numerous mobile environments and the internet environment make human life easier through the development of IT technology. With the emergence of the mobile and internet environment, data is getting bigger rapidly. From this environment, we can take advantage of using those data as economic assets for organizations which make dreams come true for the emerging Big Data environment and Big Data security services. Nowadays, Big Data services are increasing. However, these Big Data services about Big Data security is insufficient at present. In terms of Big Data security the number of security by Big Data studies are increasing which creates value for Security by Big Data not Security for Big Data. Accordingly in this paper our research will show how security for Big Data can vitalize Big Data service for organizations. In details, this paper derives the priorities of the components of Big Data Information Security Service by AHP.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.721-728
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• 2013

Big data is one of the most spotlighted technological trends in these days, enabling new methods to handle huge volume of complicated data for a broad range of applications. Real-time network traffic analysis essentially deals with big data, which is comprised of different types of log data from various sensors. To tackle this problem, in this paper, we devise a big data based platform, RENTAP, to detect and analyse malicious network traffic. Focused on military network environment such as closed network for C4I systems, leading big data based solutions are evaluated to verify which combination of the solutions is the best design for network traffic analysis platform. Based on the selected solutions, we provide detailed functional design of the suggested platform.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.184-195
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• 2004

Current companies 집중 on how to operate and select projects to achieve the best result. 6sigma projects are chosen in the best suitable concept, which are solved by the 6Sigma experts according to the priority. And every project has to be launched not the view of individual management factors but the total factors, Big Y. Therefore, a process needs to be treated to connect the vital few factors in various processes to improve the yield, which is the main performance criteria in a manufacturing industry This report is to make the total optimization through the Vital-Few mapping between quality characteristics and process factors in a manufacturing line. Accordingly, it means to secure lower variance by making the CTP(Critical To Process) optimization and finally to improve the yield.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.1-9
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• 2014

This research describes strategies to promote the growth of the Big Data industry and the companies within the ecosystem. In doing so, we identify the roles and responsibilities of various objects of this ecosystem and Big Data concepts. We describe the five components of the Big Data ecosystem: governance, data holders, service users, service providers and infrastructure providers. Related to the Big Data industry, the paper discusses 13 business strategies between the five components in the ecosystem. These strategies directly respond to areas of research by the Big Data industry leading experts on its early development. These strategies focus on how companies can gain competitive advantages in a growing new business environment of Big Data. The strategy topics are as follows: 1) the government's long term policy, 2) building Big Data support centers, 3) policy support and improving the legal system, 4) improving the Privacy Act, 5) increasing the understanding of Big Data, 6) Big Data support excavation projects, 7) professional manpower education, 8) infrastructure system support, 9) data distribution and leverage support, 10) data quality management, 11) business support services development, 12) technology research and excavation, 13) strengthening the foundation of Big Data technology. Of the proposed strategies, establishing supportive government policies is essential to the successful growth of thee Big Data industry. This study fosters a better understanding of the Big Data ecosystem and its potential to increases the competitive advantage of companies.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.95-106
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• 2016

The major thrust of this research focuses on the development of phased big data distribution model based on the big data ecosystem. This model consists of 3 phases. In phase 1, data intermediaries are participated in this model and transaction functions are provided. This system consists of general control systems, registrations, and transaction management systems. In phase 2, trading support systems with data storage, analysis, supply, and customer relation management functions are designed. In phase 3, transaction support systems and linked big data distribution portal systems are developed. Recently, emerging new data distribution models and systems are evolving and substituting for past data management system using new technology and the processes in data science. The proposed model may be referred as criteria for industrial standard establishment for big data distribution and transaction models in the future.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.109-118
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• 2016

Big data, thanks to the development of data sciences, has been key words for economic development and governmental policies. This study reviewed how big data has been used with entertainment contents since the uses of big data in the fields have been more popular and the cases making successful business have been reported. To do ends, the changes in production, distribution, and consumption of entertainment contents have been characterized and prime cases have been introduced. Furthermore, Korean production companies of entertainment contents, Bloter and NEOTOUCHPOINT, were selected to investigate how big data has been utilized. It was found that the companies used big data to analyze consumers' behaviors and gain insights of content creation, such as identifying specific elements of enjoyments and conditions to share the contents with others. The domestic entertainment companies are preparing a full-scale of use of big data but, in order to take advantage of big data, collaboration between developers and experts in the field and specific goal-setting and model building are recommended.