• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.300-306
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• 2021

Due to the development of IT technology, hardware technologies applied to IoT equipment have recently been developed, so smart systems using low-cost, high-performance RF and computing devices are being developed. However, in the infrastructure environment where a large amount of IoT devices are installed, big data collection causes a load on the collection server due to a bottleneck between the transmitted data. As a result, data transmitted to the data collection server causes packet loss and reduced data throughput. Therefore, there is a need for an efficient big data collection technique in an infrastructure environment where a large amount of IoT devices are installed. Therefore, in this paper, we propose an efficient big data collection technique in an infrastructure environment where a vast amount of IoT devices are installed. As a result of the performance evaluation, the packet loss and data throughput of the proposed technique are completed without loss of the transmitted file. In the future, the system needs to be implemented based on this design.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.495-500
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• 2021

This paper is to identify the recent growing crisis from coronavirus infections-19, using domestic news big data. This paper analyzed media articles related to the crisis caused by COVID-19 using the Korea Press Foundation's news big data analysis system 'BIGKinds'. In this paper, a total of 54 media articles were extracted around the keywords 'Corona' and 'Crisis', after a period of about 10 months. We want to understand the correlation coefficient between the two keywords "Corona" and "Crisis" and to understand what kind of crisis the COVID-19 is facing for each representative category of economy, society, international and cultural. As the COVID-19 crisis is taking a heavy toll on the economy, society and any other categories, this research using big data is expected to be used as a basic data to overcome the crisis of COVID-19.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.10-17
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• 2022

Recently, with the issue of the 4th Industrial Revolution, many services using big data have been developed. Accordingly, studies have been conducting to utilize public data, which is considered as the most valuable data among big data. In this paper, we design and implement a food price information analysis system based on public big data. The proposed system analyzes the collected food price-related data in various forms from various sources and classifies them according to characteristics. In addition, the proposed system analyzes the factors affecting the price of food through big data analysis techniques and uses them as data to predict the price of food in the near future. Finally, the proposed system provides the user with the analyzed results through data visualization.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.815-821
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• 2021

The advantage of big data is to collect a large amount of data on the Internet and refine and use valuable data. That is, the unstructured data is processed so that the user can analyze and utilize it from a necessary point of view. This paper is a relatively small project and is based on unstructured data that can be closely applied to real life and used for marketing. The subjects of the experiment were modeled on lodging companies in the Seoul metropolitan area an hour away from Seoul, and analyzed for the increase in lodging rates before and after marketing using big data. As an experiment that shows the effects of increasing sales, reducing costs, and increasing returns by users, we propose a system to determine and filter whether data input in the process of analyzing big data such as social networks can be used as accommodation-related information.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.269-275
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• 2023

In 2021, the 150th anniversary of Proust's birth, and in 2022, the 100th anniversary of his death, the interest in À la recherche du temps perdu increased. We took advantage of a digital humanities approach to make these seven novels known as difficult easily accessible to French literature major korean students. We let the students analyze using the analyzing tools for the big data and find some clues to understand the works through the visualized data. We picked out the main characters and places that appear in his works with Wordcloud, and checked the awareness of Proust in domestic and foreign through the various sites to analyze the big data, such as Big Kinds and Textom. Through the methodology of digital humanities, the students commented that they have gradually enlarged their understanding breadth for Proust's 『In Search of Lost Time』 rather than giving up it as difficult. This study confirmed that applying the big data analysis and digital humanities is an appropriate teaching method in finding ways for the students to broaden the understanding of French literature.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.551-571
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• 2023

Purpose: The purpose of this study is to propose useful suggestions by analyzing the causal effect relationship between the failure rate of quality and the process variables in the C5ISR domain of the defense industry. Methods: The collected data through the in house Systems were analyzed using Big data analysis. Data analysis between quality data and A/S history data was conducted using the CRISP-DM(Cross-Industry Standard Process for Data Mining) analysis process. Results: The results of this study are as follows: After evaluating the performance of candidate models for the influence of inspection data and A/S history data, logistic regression was selected as the final model because it performed relatively well compared to the decision tree with an accuracy of 82%/67% and an AUC of 0.66/0.57. Based on this model, we estimated the coefficients using 'R', a data analysis tool, and found that a specific variable(continuous maximum discharge current time) had a statistically significant effect on the A/S quality failure rate and it was analysed that 82% of the failure rate could be predicted. Conclusion: As the first case of applying big data analysis to quality issues in the defense industry, this study confirms that it is possible to improve the market failure rates of defense products by focusing on the measured values of the main causes of failures derived through the big data analysis process, and identifies improvements, such as the number of data samples and data collection limitations, to be addressed in subsequent studies for a more reliable analysis model.

• Korean Journal of Construction Engineering and Management
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• v.19 no.3
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• pp.89-96
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• 2018

This study derived big issues in overseas construction through big data analysis. To derive big issues in overseas construction, candidate groups of big issues were identified through big data analysis targeting 53,759 issues including 39,436 issues from major portal sites, 10,387 issues from daily newspapers, and 336 issues in construction magazines from Oct. 1, 2016 to Sep. 30, 2017. The main results are as follows: First, the main issues of overseas construction for the past one year showed that markets were concentrated in Middle East Asia and most of them were low-price order plant projects, which revealed the limitations. Although orders of overseas construction were slightly upward in the first half of 2017 compared to previous year, overseas construction orders are still unstable due to uncertainties in the international affairs and drops in oil prices. Second, the interest topics based on the 8th core keywords of overseas construction among the overseas construction issues for the past one year showed that region (29.9%), corporation environment (22.0%), profitability (17.0%), organizations (15.1%), projects (5.2%), market environment (3.6%), policy and system (3.6%), and education (3.5%) in the order of interest. Third, 10 core issues that have expandability and persistence of discourse were extracted out of 30 issue candidates with regard to eight keywords. Based on the extracted issues, detailed analysis on each of the core issues in overseas construction and correlation analysis between 10 core issues were conducted.

• The Korean Journal of Pain
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• v.29 no.4
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• pp.215-216
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• 2016

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.1036-1042
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• 2023

• Industry Promotion Research
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• v.5 no.4
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• pp.1-13
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• 2020

Since the 4th industrial revolution was thrown into the world at the Davos World Economic Forum in January 2016, the world has been undergoing major social and economic changes. In this study, the direction of quality management in the 4th industrial revolution era was examined. First, in all the major countries the industrial structural changes and smart business models were confirmed due to the convergence of new ICT such as IoT, robotics, 3D printing, big data, and AI with the existing technologies and industries. Second, we found that although the core technology level of the 4th industrial revolution in Korea is not as good as that of advanced countries, we have been working on expanding smart production methods and creating new industries by utilizing new ICT. Finally, it was confirmed that quality management is a real-time implementation of new ICT that reflects the needs of the market in real time based on big data from the planning and design stage of products or services.