• The Journal of Industrial Distribution & Business
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• v.13 no.9
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• pp.27-36
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• 2022

Purpose: The coronavirus pandemic has affected the tourism industry in a big way. The travel industry suffered intense damage from the pandemic and procedures acquainted to containing its spread because the pandemic outbreak has led to a decline in the number of tourists and a change in their behavior. At this point, this research is to investigate adequate solutions for tourism industry to overcome the crisis in a post-Covid 19 era. Research design, data and methodology: The current author gathered data from each included study to analyze and summarize the evidence when conducting a literature analysis. This stage involves gathering and reviewing intricate texts databases for the meta-analysis. Results: The current author found total five solutions from numerous literature contents, suggesting how to overcome the crisis in a post-Covid era for tourism industry. Solutions as follows, (1) Drawing beginning illustrations, (2) Introducing Government Backing Programs, (3) Increasing Promotion of Tourism Destinations, (4) Enhancing Safety and Security Measures, and (5) Improving Infrastructure and Facilities. Conclusions: This research suggests that although the global economic recession leads to reduced demand and intense competition from other sectors, the tourism industry will be well positioned to weather these challenges if practitioners of tourism organizations follow five solutions of this research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.427-435
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• 2023

Cardinality estimation is used in wide range of applications and a fundamental problem processing a large range of data. While the internet moves into the era of big data, the function addressing cardinality estimation use only on-chip cache memory. To use memory efficiently, there have been various methods proposed. However, because of the noises between estimator, which is data structure per flow, loss of accuracy occurs in these algorithms. In this paper, we focus on minimizing noises. We propose multiple data structure that each estimator has the number of estimated value as many as the number of structures and choose the minimum value, which is one with minimum noises, We discover that the proposed algorithm achieves better performance than the best existing work using the same tight memory, such as 1 bit per flow, through experiment.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.225-231
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• 2022

Transcendence of space and time, virtual reality, augmented reality, etc. are being realized through the latest technologies in the era of the 4th industrial revolution. In a situation where they are currently experiencing artificial intelligence, augmented reality, big data, etc., the degree of interest in the latest technologies of the 4th industrial revolution for radiology students, the necessary competencies in the 4th industrial revolution era, and the prospect of the radiation field employment environment in the 4th industrial revolution era The purpose of this study was to find out the level of awareness of From February 7th to February 18th, 2022, surveys on awareness were analyzed using questionnaires for 2nd and 3rd year students in the Department of Radiology at S University in Daegu. As a result of the study, the level of interest in 3D modeling was shown to be the highest with an average of 3.34 ± 1.09 points, and interest in big data and artificial intelligence was also shown with an average of 3.27 ± 1.17 and 3.33 ± 1.07 points. In addition, the correlation between the awareness of the necessary competencies in the 4th industrial revolution era and the awareness of the prospects for employment in the radiation field in the 4th industrial revolution era was the highest (r=0.778, p<0.01), and the interest in the latest technologies in the 4th industrial revolution and the 4th industrial revolution It was found that there was also a correlation between the perceptions of the necessary capabilities of the times (r=0.694, p<0.01). In the era of the 4th industrial revolution, it is judged that it is necessary to strengthen professional education that can handle the latest technologies such as 3D printing, artificial intelligence, and big data, and to strengthen employment capabilities related to the latest technologies in the field of radiation medical technology.

• 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.

• The Journal of Information Systems
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• v.31 no.1
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• pp.175-195
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• 2022

Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

• The Korean Journal of Archival Studies
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• no.67
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• pp.99-138
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• 2021

In the era of big data, analyzing not only structured data but also unstructured data is emerging as an important task. Official documents produced by government agencies are also subject to big data analysis as large text-based unstructured data. From the perspective of internal work efficiency, knowledge management, records management, etc, it is necessary to analyze big data of public documents to derive useful implications. However, since many of the public documents currently held by public institutions are not in open format, a pre-processing process of extracting text from a bitstream is required for big data analysis. In addition, since contextual metadata is not sufficiently stored in the document file, separate efforts to secure metadata are required for high-quality analysis. In conclusion, the current official documents have a low level of machine readability, so big data analysis becomes expensive.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.1
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• pp.109-121
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• 2022

Purpose - This study attempted to analyze news big data in order to examine the trend of change in housework due to technological innovation and family changes. Research design, data, and methodology - News big data was collected from Bigkinds for the purpose of trend analysis. A total of 8,270 articles containing 'housework' were extracted from news articles between January 1, 1990 and December 31, 2021. 11 general daily newspapers and 8 business newspapers were selected and were analyzed by dividing them into five-year units. Result - The change of trends in housework that appeared through news big data analysis can be summarized as below. First, the tendency to regard housework as work of women or housewives is gradually weakening. Instead, the centrality of connection with double income is increasing. Second, there is a tendency to strengthen the institutional approach to evaluation of the productivity of housework. Third, the possibility of market substitution for housework is expanding. Conclusion - In the era of the 4th industrial revolution, examining the impact of technological innovation and family change on housework not only enables the prospect of an industry, but also provides implications for policies related to housework. In addition, this study is differentiated in that it contributed to expand the field of housework research previously limited to analyzing survey data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.4038-4056
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• 2018

Recently, the most frequently studied topics related to the fourth industrial revolution (FIR) are Big data, AI, Cloud Computing and Internet of Things- these four components are collectively known as the main components of the FIR (henceforth MCs). The MCs have a wide range of effects on workers' performance. As such it is imperative that these components are properly understood. This understanding will lead to a proper recognition of the attitudes that workers need to adopt to the MCs. Specifically, the attitudes of workers to several variables need to be examined, including importance, intention to use, belief in improvement, efficacy to use, and negative cognition. Each of these variables plays a role in determining how worker's performance in the FIR era will change. The performance-related variables such as self-efficacy, expectations, and acceptance of change are also crucial. These variables are related to creation of new opportunities, and can greatly influence performance in the FIR era. This study explains how specific attitudes to MCs improve performance-related factors for FIR. The adoption of these attitudes will ultimately lead to more successful adaption to the FIR era.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1399-1410
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• 2015

Gartner is requiring companies to considerably change their survival paradigms insisting that companies need to understand and provide again the upcoming era of data competition. With the revealing of successful business cases through statistic algorithm-based predictive analytics, also, the conversion into preemptive countermeasure through predictive analysis from follow-up action through data analysis in the past is becoming a necessity of leading enterprises. This trend is influencing security analysis and log analysis and in reality, the cases regarding the application of the big data analysis framework to large-scale log analysis and intelligent and long-term security analysis are being reported file by file. But all the functions and techniques required for a big data log analysis system cannot be accommodated in a Hadoop-based big data platform, so independent platform-based big data log analysis products are still being provided to the market. This paper aims to suggest a framework, which is equipped with a real-time and non-real-time predictive analysis engine for these independent big data log analysis systems and can cope with cyber attack preemptively.

• Smart Media Journal
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• v.8 no.1
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• pp.9-18
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• 2019

In the era of the 4th industrial revolution, the big data industry is gathering attention for new business models in the public and private sectors by utilizing various information collected through the internet and mobile. However, although the big data integration and analysis are performed with de-identification techniques, there is still a risk that personal privacy can be exposed. Recently, there are many studies to invent effective methods to maintain the value of data without disclosing personal information. In this paper, a personal information protection system is investigated to boost big data utilization in industrial sectors, such as healthcare and agriculture. The criteria for evaluating the de-identification adequacy of personal information and the protection scope of personal information should be differently applied for each industry. In the field of personal sensitive information-oriented healthcare sector, the minimum value of k-anonymity should be set to 5 or more, which is the average value of other industrial sectors. In agricultural sector, it suggests the inclusion of companion dogs or farmland information as sensitive information. Also, it is desirable to apply the demonstration steps to each region-specific industry.