• Journal of Platform Technology
• /
• v.8 no.4
• /
• pp.38-46
• /
• 2020

This study describes how to build a security control system using an open source big data solution so that private companies can build an overall security control infrastructure. In particular, the infrastructure was built using the Elastic Stack, one of the free open source big data analysis solutions, as a way to shorten the cost and development time when building a security control system. A comparative experiment was conducted. In addition, as a result of comparing and analyzing the functions, convenience, service and technical support of the two solution, it was found that the Elastic Stack has advantages in the security control of Big Data in terms of community and open solution. Using the Elastic Stack, security logs were collected, analyzed, and visualized step by step to create a dashboard, input large logs, and measure the search speed. Through this, we discovered the possibility of the Elastic Stack as a big data analysis solution that could replace Splunk.

• Journal of The Korean Association of Information Education
• /
• v.24 no.5
• /
• pp.463-471
• /
• 2020

Humanity faces the fourth industrial revolution, a time of technological revolution by the collaboration of various industries including the fields of artificial intelligence(AI) and big data. Many countries are focused on fostering AI talent to prevail in the coming technological revolution. While Korea also provides some strategies to enhance the cultivation of AI talent, it is still difficult for Korean undergraduate students to get involved in AI studies. Through on the implementation of 'Big data analysis based AI education', which allows an easier approach to AI education, this paper examined the changes in the attitudes of undergraduate students regarding general AI education. 'Big data analysis based AI education' was provided at undergraduate level for 5.5 weeks (15 hours). The attitudes of undergraduate students were analyzed by pre-postmortem. The results showed there was a significant improvement in confidence and self-directed in regard to receiving AI education. With these results, further active research to develop basic AI education that also increases confidence and self-initiative can be expected.

• Korea Trade Review
• /
• v.46 no.5
• /
• pp.65-81
• /
• 2021

The technological development in the era of the 4th industrial revolution is changing the paradigm of various industries. Various technologies such as big data, cloud, artificial intelligence, virtual reality, and the Internet of Things are used, creating synergy effects with existing industries, creating radical development and value creation. Among them, the logistics sector has been greatly influenced by quantitative data from the past and has been continuously accumulating and managing data, so it is highly likely to be linked with big data analysis and has a high utilization effect. The modern advanced technology has developed together with the data mining technology to discover hidden patterns and new correlations in such big data, and through this, meaningful results are being derived. Therefore, data mining occupies an important part in big data analysis, and this study tried to analyze data mining techniques that can contribute to the logistics field and common logistics using these data mining technologies. Therefore, by using the AHP technique, it was attempted to derive priorities for each type of efficient data mining for logisticalization, and R program and R Studio were used as tools to analyze this. Criteria of AHP method set association analysis, cluster analysis, decision tree method, artificial neural network method, web mining, and opinion mining. For the alternatives, common transport and delivery, common logistics center, common logistics information system, and common logistics partnership were set as factors.

• Journal of KIISE
• /
• v.42 no.4
• /
• pp.459-467
• /
• 2015

The analysis platform of remote-sensing big data is a system that downloads data from satellites, transforms it to a data type of L3, and then analyzes it and produces its analysis results. The objective of this paper is to develop ISO/IEC 9126-1 software quality model-based assessment criteria, in order to evaluate the quality of remote-sensing big data analysis platform. Its detailed research contents are as follows. First, the ISO/IEC 9216 standards and previous software evaluation models will be reviewed. Second, this paper will define evaluation areas, evaluation elements, and evaluation items for measuring the quality of big data analysis platform. Third, the validity of the assessment criteria will be verified by statistical experiments through content validity, reliability validity, and construct validity, by using SPSS 20.0 and Amos 20.0 software. The construct validity will also be conducted by performing the confirmatory factor analysis and path analysis. Lastly, it is significant that our research result demonstrates the first evaluation criteria in measuring the quality of big data analysis platform. It is also expected that our assessment criteria could be used as the basis information for evaluation criteria in the platforms that will be developed in the future.

• Convergence Security Journal
• /
• v.19 no.5
• /
• pp.63-73
• /
• 2019

In the 4th Industrial Revolution, information is collected and analyzed from people and objects through the rapid development of ICT. It is possible to create value. However, there are many legal and institutional restrictions on the collection of information aimed at people.Therefore, in-depth research on the protection and use of personal information in the rapidly changing cyber security environment is needed. The purpose of this study is to protect and utilize personal information for the operation of AI (Artificial Intelligence) and big data during the 4th Industrial Revolution. It is to seek a paradigm shift. The organization of the research for this is: Chapter 1 examines the meaning of personal information during the 4th Industrial Revolution, Chapter 2 presents the framework for the review and analysis of prior research. In Chapter 3, after analyzing policies for the protection and utilization of personal information in major countries, Chapter 4 looks at the paradigm shift in personal information protection during the 4th Industrial Revolution and how to respond. Chapter 5 made some policy suggestions for the protection and utilization of personal information.

• Journal of Korean Elementary Science Education
• /
• v.33 no.4
• /
• pp.646-654
• /
• 2014

The aim of this study was to investigate the patterns of the elementary school students' interests to animals and plants based on affinity toward animals and plants, and curiosity about animals and plants by using a cluster analysis. In addition, the differences of the big five personality traits by the identified clusters was examined. A total number of 411 elementary school students participated in the study. The students were clustered into four distinct interest groups with respect to the level of interests to animals and plants. Cluster 1 'Developed Interest to Organisms group' showed high levels in the interest to both animals and plants. Cluster 2 'Developed Interest to Animals group' showed high interest to animals and relatively low interest to plants whereas cluster 3 'Developed Interest to Plants group' showed high interest to plants and relatively low interest to animals. Lastly, cluster 4 were identified as 'Lack of Interest to Organisms group' by showing low levels of interest to both animals and plants. The four identified groups also showed different distributions of students according to gender and school year. These results support gender difference in the interest to animals and plants and suggest the decreased and specialized interest with school year. The Big Five personality traits excluding neuroticism were positively related with the interest to organisms and the identified groups showed significant differences in the traits. These findings indicate that agreeableness, conscientiousness, extraversion, and openness can be significant predictors of the interests to animals and plants.

• Journal of Korean Society for Quality Management
• /
• v.49 no.4
• /
• pp.551-567
• /
• 2021

Purpose: The purpose of this paper is to present implications by analyzing research trends on smart factories by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on smart factories. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "SMART FACTORY" and "Smart Factory" as search terms, and the titles and Korean abstracts were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, 739 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; Smart factory research slowed down from 2005 to 2014, but until 2019, research increased rapidly. According to the analysis by fields, smart factories were studied in the order of engineering, social science, and complex science. There were many 'engineering' fields in the early stages of smart factories, and research was expanded to 'social science'. In particular, since 2015, it has been studied in various disciplines such as 'complex studies'. Overall, in keyword analysis, the keywords such as 'technology', 'data', and 'analysis' are most likely to appear, and it was analyzed that there were some differences by fields and years. Conclusion: Government support and expert support for smart factories should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to smart factories. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.

• Journal of Korean Society for Quality Management
• /
• v.50 no.4
• /
• pp.751-776
• /
• 2022

Purpose: The purpose of this paper is to present implications by analyzing research trends on CSR, CSV and ESG by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on CSR, CSV and ESG. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "CSR", "CSV" and "ESG" as search terms, and the Korean abstracts and keyword were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, CSR 2,847 papers, CSV 395 papers, ESG 555 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; CSR, CSV, and ESG studies showed that research slowed down somewhat before 2010, but research increased rapidly until recently in 2019. Research have been found to be heavily researched in the fields of social science, art and physical education, and engineering. As a result of the study, there were many keyword of 'corporate', 'social', and 'responsibility', which were similar in the word cloud analysis. Looking at the frequent keyword and word cloud analysis by field and year, overall keyword were derived similar to all keyword by year. However, some differences appeared in each field. Conclusion: Government support and expert support for CSR, CSV and ESG should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to them. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.25 no.4
• /
• pp.77-92
• /
• 2023

The purpose of this study is to investigate the public perception of Gorpcore through Big Aata analytics. The study was conducted based on the collection of Big Data on the word 'Gorpcore' through Textom from July 24, 2017 to March 31, 2023. As a result, 63,386 words were collected from a total of 18,879 posts, and the top 50 words were determined based on frequency of appearance. Based on the collected words, centrality measures and CONCOR algorithm were performed in Ucinet 6. The research results are as follows. 1) The frequency of appearance was high in the order of 'Gorpcore look', 'fashion', 'coordination', 'clothes', 'outdoor', 'Musinsa', 'look', 'trend', 'brand' and 'ahjussi (middle-aged old man in Korean)'. These words had high TF-IDF scores, which leads to the conclusion that these are key words that are recognized as important. 2) Network centrality shows that 'Gorpcore look', 'fashion', 'outdoor', 'coordination', 'clothes', 'trend', 'look' and 'style' have a high correlation with other words. Through this, it was found that the public thinks it is important to create a variety of fashions by styling high-performance outdoor wear and casual wear, and that they are highly interested in clothes and in brands leading the Gorpcore trend. 3) As a result of the CONCOR algorithm, four significant groups were formed. The words that appear in each group are as follows. Group 1 - 'outdoor', 'Gorp', 'Normcore', 'hiking', 'functionality', 'new', 'sports', 'casual wear', 'activity', 'generation', 'collaboration'. Group 2 - 'fashion', 'trend', 'look', 'brand', 'style', 'shoes', 'ugly', 'item', 'trend', 'product', 'Salomon', 'padded jacket', 'stylishness', 'utilization', 'Winter', 'street', 'design', 'retro', 'popular', 'styling'. Group 3 - 'Gorpcore look', 'coordination', 'Musinsa', 'windbreaker', 'recommendation', 'Arcteryx', 'pants', 'man'. Group 4 - 'clothes' 'ahjussi', 'jacket', 'launching', 'spring', 'The North Face', 'collection', 'utility', 'jumper'. As a result, it can be seen that the Gorpcore is also regarded as a part of outdoor, fashion, coordination, and casual wear.

• Korean Journal of Plant Resources
• /
• v.16 no.2
• /
• pp.99-108
• /
• 2003

This study was carried out to make a standard criteria for protection and maintenance of the big and old trees in Ansung city, Kyonggi Prvince. There have been found 6 vegetative species cultivated in this area, which are Zelkova serrata, Gingko biloba, Kalopanax pictus, Pyrus ussuriensis var. macrostipes, Pyrus ussuriensis var. acidula, Pinus densiflora, etc. The Zelkova serrata tree is the major species among them and about 73.5％ in the population of the big and old trees in this area. The DBH (diameter at brest height) of them is 1.5-1.9m in 29.4% of whole population and the tree height is 10-l4m in 47.1%. The estimate age of 7 trees is more than 500 years old and they were 20.6％ of the whole population. Interesting point is that about 64.7％ of these trees in this area have own succeed story in terms of folk religion, object of worship, taboo, legend or secret. This study has also revealed that many fowls, small animals and epiphyte inhabited with the big and old trees have been found. However, 97.1％ of them are in danger from the plant disease and noxious insects or cutting damage of branches, but no management has been taken. More over, 85.3％ of the whole investigated big and old trees have been in the poor condition for percolation or aeration because the area around them has been payed with asphalt or concrete.