• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.218-223
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• 2021

Pervasive enhancement and required enforcement of the Internet of Things (IoTs) in a distributed massively multiplayer online architecture have effected in massive growth of Big-Data in terms of server over-load. There have been some previous works to overcome the overloading of server works. However, there are lack of considered methods, which is commonly applicable. Therefore, we propose a combing Sparse Auto-Encoder and Load-Balancing, which is ProGReGA for Big-Data of server loads. In the process of Sparse Auto-Encoder, when it comes to selection of the feature-pattern, the less relevant feature-pattern could be eliminated from Big-Data. In relation to Load-Balancing, the alleviated degradation of ProGReGA can take advantage of the less redundant feature-pattern. That means the most relevant of Big-Data representation can work. In the performance evaluation, we can find that the proposed method have become more approachable and stable.

• The Korean Journal of Food & Health Convergence
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• v.10 no.1
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• pp.1-6
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• 2024

Purpose: The research aims to address the intricacies of AI and Big Data application within the food industry. This study explores the strategic implementation of AI and Big Data in the food industry. The study seeks to understand how these technologies can be employed to bolster consumer engagement and contribute to market expansion, while considering ethical implications. Research Method: This research employs a comprehensive approach, analyzing current trends, case studies, and existing academic literature. It focuses on the application of AI and Big Data in areas such as supply chain management, consumer behavior analysis, and personalized marketing strategies. Results: The study finds that AI and Big Data significantly enhance market analytics, consumer personalization, and market trend prediction. It highlights the potential of these technologies in creating more efficient supply chains, improving consumer satisfaction through personalization, and providing valuable market insights. Conclusion and Implications: The paper offers actionable insights and recommendations for the effective implementation of AI and Big Data strategies in the food industry. It emphasizes the need for ethical considerations, particularly in data privacy and the transparency of AI algorithms. The study also explores future trends, suggesting that AI and Big Data will continue to revolutionize the industry, emphasizing sustainability, efficiency, and consumer-centric practices.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.106-111
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• 2020

In the era of the fourth industrial revolution, the application of big data analysis technology is crucial in various industries. In this regard, considerable research is necessary to improve aquafarming productivity, particularly in fish culture, which is one of the primary industries in the world. In this study, a sample experiment using a flop was conducted to improve oyster productivity in fish farms, and a flush was installed in an environment similar to aquaculture farms. Thereafter, the temperature data of the water environment where the formation of burrows considerably improved were collected; the growth rate of burrow seeds was also measured. The gathered experimental data were examined by time series data analysis. Finally, a system that visualizes the analysis results based on big data is proposed. In accord with the results of this study, it is expected that more advanced research on the productivity improvement of oyster aquafarming will be performed.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.59-66
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• 2021

Recently, conceptual information model is changing fast, and these changes are coming about as a result of individual tendency, social cultural, new circumstances and societal shifts within big data environment. Despite the data is growing more and more, now is the time to commit ourselves to the development of renewable, invaluable information of social/live commerce. Because we have problems with various insoluble data, we propose about deep learning prediction model-based object classification in social commerce of big data environment. Accordingly, it is an increased need of social commerce platform capable of handling high volumes of multiple items by users. Consequently, responding to rapid changes in users is a very significant by deep learning. Namely, promptly meet the needs of the times, and a widespread growth in big data environment with the goal of realizing in this paper.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.5
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• pp.103-112
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• 2011

Old big tree transcends the simple meaning of trees as they are the natural monuments that embody the people's history and culture of this land. The Cultural Heritage Administration of Korea(CHA) defines and protects old big tree based not only on the size of the tree but also on its definitive cultural and natural factors such as value, implications, and originality. This research aims to identify and analyze the growth conditions, soil conditions and location character of 20 old big tree in Gyeongsangnamdo korea. The research examined the soundness of the arboreal form, the degree of damage on the bark, as well as the quantity of leafs levels to evaluate the overall condition of growth and development. Also, 9 elements such as soil texture, nitrogen and organic matter content, soil pH, phosphoric acid and EC were further analyzed The research analyzed in correlation of Growth condition and soil. Tree health related positivity that total nitrogen and organic matter. The result which analyzes location character, With natural monument old big trees raising a hand the area where is contiguous appeared with the fact that the farming village style where the rice field and the arable land of field etc. This research aimed at generating some foundational reference data for the analysis of the habitation and management conditions of natural monument old big tree within the Gyeongsangnamdo korea.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.103-103
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• 2019

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.547-552
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• 2019

Recently, the massive growth in the scale of data has been observed as a major issue in the Big Data. Furthermore, the Big Data should be preprocessed for normalization to get a high performance of the Machine learning since the Big Data is also an input of Machine Learning. The performance varies by many factors such as the scope of the columns in a Big Data or the methods of normalization preprocessing. In this paper, the various types of normalization preprocessing methods and the scopes of the Big Data columns will be applied to the SVM(: Support Vector Machine) as a Machine Learning method to get the efficient environment for the normalization preprocessing. The Machine Learning experiment has been programmed in Python and the Jupyter Notebook.

• Smart Media Journal
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• v.9 no.2
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• pp.99-109
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• 2020

This paper proposes a platform construction plan for the use of spectrum big data, collects and analyzes the big data in the radio wave field, establishes a linkage plan, and presents a support system scheme for linking and using the spectrum and public sector big data. It presented a plan to build a big data platform in connection with the spectrum public sector. In a situation where there is a lack of a support system for systematic analysis and utilization of big data in the field of radio waves, by establishing a platform construction plan for the use of big data by radio-related industries, the preemptive response to realize the 4th Industrial Revolution and the status and state of the domestic radio field. The company intends to contribute to enhancing the convenience of users of the big data platform in the public sector by securing the innovation growth engine of the company and contributing to the fair competition of the radio wave industry and the improvement of service quality. In addition, it intends to contribute to raising the social awareness of the value of spectrum management data utilization and establishing a collaboration system that uses spectrum big data through joint use of the platform.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.428-436
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• 2014

The convergence technology of ICT(Information & Communication Technology) in agriculture is the main key of the future agricultural industry. Recently, many that by using big data it can improve crop growth-circumstance and agricultural Industry. However, the data of crop growth-circumstance has been not shared and operated separately by individual farm. Therefore, it is necessary to build the LOK(Linked Open Knowledge) system for Quality of Farming & Farm product. We research previous studies for big data and development of the corp growth-circumstance using big data system case. Also, we suggest to build LOK system for improving the domestic agricultural industry.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.51-61
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• 2024

This study analyzes and compares the roles and significance of large firms in economic growth by differentiating developmental stages. The focus is on both the role of big businesses on the road from middle- to high-income countries and the performance in their economies. By classifying the top 30 nonfinancial firms into their origin countries, we have constructed a country-level data basis covering 33 countries ranging from middle- to high-income economies for the 2001 to 2017 period. We conduct fixed effect estimation. Empirical results show that capital-intensive big businesses would be more predominant in developed economies. In terms of policy implications, the results suggest that if policymakers want to optimize the role of big businesses in economic growth, policymakers need to distinguish the income level. Policymakers also need to adjust the size distribution of firms moderately ahead of time to create the size distribution of firms needed to take the economy to the next level.