• The Mathematical Education
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• v.63 no.2
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• pp.209-231
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• 2024

The education sector is undergoing significant changes due to the Fourth Industrial Revolution and the advancement of artificial intelligence. Particularly, the importance of education based on artificial intelligence is being emphasized. Accordingly, the purpose of this study is to develop a statistics education program using deep learning prediction in high school mathematics and to examine the impact of such statistically problem-solvingcentered statistics education programs on high school students' statistical literacy and computational thinking. To achieve this goal, a statistics education program using deep learning prediction applicable to high school mathematics was developed. The analysis revealed that students' understanding of context improved through experiencing how data was generated and collected. Additionally, they enhanced their comprehension of data variability while exploring and analyzing various datasets. Moreover, they demonstrated the ability to critically analyze data during the process of validating its reliability. In order to analyze the impact of the statistics education program on high school students' computational thinking, a paired sample t-test was conducted, confirming a statistically significant difference in computational thinking between before and after classes (t=-11.657, p<0.001).

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.93-100
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• 2024

With the advent of the Fourth Industrial Revolution, cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing are driving innovation across industries. These technologies are generating massive amounts of data that many companies are leveraging. However, there is a notable reluctance among users to share sensitive information due to the privacy risks associated with collecting personal data. This is particularly evident in the healthcare sector, where the collection of sensitive information such as patients' medical conditions poses significant challenges, with privacy concerns hindering data collection and analysis. This research presents a novel technique for collecting and analyzing medical data that not only preserves privacy, but also effectively extracts statistical information. This method goes beyond basic data collection by incorporating a strategy to efficiently mine statistical data while maintaining privacy. Performance evaluations using real-world data have shown that the propose technique outperforms existing methods in extracting meaningful statistical insights.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.559-564
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• 2024

Since the era of industrial revolution, the waste volume has continued to grow; waste management has thus become one of the major global environmental challenges facing humanities today. Waste treatment and management issues trigger NIMBY movements, and disputes among states, governments, and social actors over the issues have been accelrating. At the level of states and sub-states, various measures including institutions, laws, regulations, market-oriented methods, consensus and collaborative governance have been introduced to address various problems associated with waste. More recently, science and technology has been applied to the waste treatment and management under the notion of circular economy. However, societal support for addressing waste problems still remains inadequate, calling for new approaches and alternative pathways. In this context, this study examines two cases of urban incineration plants designed by Hudertwasser, Austria-born artist and architect: Spittelau, Austria, and Osaka, Japan. Through these case studies, I demonstrate how creative and innovative culture-technology convergence can shed new light on challenging environmental issues such as an urban waste problem.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.2
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• pp.10-16
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• 2023

This study establishes the operation concept of the 4th industrial revolution defense technology and communication facility-based 5G MUM-T system, and diagnoses our current situation, focusing on the case of US government technology policy, which is a leading country in 5G MUM-T system and operation. And to advance the operation of the 5G MUM-T system, reflect combat robots and drones in the detailed classification of weapon systems, early introduction of low-orbit 5G satellite communication, expansion of the use of 5G specialized networks and wholesale provision for demonstration and verification, establishment of a defense AI governance system, Suggests the necessity of a 3-class method for radiological weapon systems. For future research, it is important to respond to the technological evolution of 6G MUM-T and 6G NTN and compare and analyze each country's policy cases, such as China, Germany, the United Kingdom, and Japan.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.1-7
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• 2024

Traditional security model design presents two primary issues. First, these models have been developed and implemented with a technology-centered approach rather than considering human factors. Such structures can be undermined by cognitive vulnerabilities like psychological resistance within organizations and user errors. Second, these models are typically designed based on network perimeter security. This design is unsuitable for the boundary-less remote work environments rapidly becoming prevalent due to the Fourth Industrial Revolution and the COVID-19 pandemic. This paper proposes an approach to address these limitations by integrating human-centered threats within the Zero Trust security model, a state-of-the-art boundary-less security framework. By doing so, we suggest a robust security model design that can protect against both technical and human-centered threats.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.21-28
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• 2024

Nowadays, based on the 4th Industrial Revolution, by using the CHATGPT function and 3D virtual reality technology, anyone can easily open a virtual environment WEB-based, smart tourism OPEN source and travel destination without having to directly visit the travel location in the real world. Using the API function, it provides the convenience of virtual tourism. However, this function does not work if the travel transportation system is suddenly changed due to sudden bad weather, travel operation information cannot be checked in real time, and due to a lack of flight cancellation information and passenger ship operation information, it cannot be used until the plane or ferry departs normally. A very inconvenient problem arises where you have to wait a long time in the waiting room. Therefore, in this paper, in order to solve this problem, automatic duty-free product information and automatic product payment functions were added even when passenger ship cancellations and operation information suddenly occur due to bad weather and multiple products are purchased during the trip. In addition, the computer simulation experiment was conducted on a WEB basis so that anyone can conveniently travel smartly.

• Journal of the Korea Fashion and Costume Design Association
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• v.26 no.3
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• pp.1-12
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• 2024

3D printing technology is a key technology of the Fourth Industrial Revolution and has been gaining attention in various fields, having been selected as one of the top 10 core manufacturing technologies by the U.S. government. In the apparel industry as well, there have been various attempts to develop products using 3D printers. However, compared to other industries and research fields, utilization remains insufficient. This is mainly due to the high price of large 3D printers and a limited varieties of filaments, making it difficult to implement traditional textiles and produce full-size garments. In this study, to develop 3D printed textiles, textile structures that can be 3D printed were categorized. Applying various types of filaments and layering methods allowed for the printing and evaluation of structures, ultimately leading to the selection of three types of 3D printed textile structures suitable for use as clothing materials. Subsequently, types of filaments were selected that match the chosen textile structures and suitabel designs were applied to develop 3D printed clothing designs. As a result of this study, an ideal form for 3D printing textiles was proposed and mehods were presented for clothing construction using practical (versatile) 3D printing technology. This study plays a significant role in contributing to the expansion of research areas related to 3D printing technology in the fashion field and suggesting effective research directions.

• Information Systems Review
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• v.26 no.1
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• pp.355-365
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• 2024

The necessity of informatization triggered by the Fourth Industrial Revolution has led to significant educational investments and social expenditures in related technologies over the past decade. However, despite this, the levels of literacy in the field of informatization among adults and adolescents in Korea are below the OECD average. This is due to a bias towards education in analysis tools such as Python, rather than a comprehensive competency related to data literacy. This study aims to overcome these limitations and propose directions for data-related education. To this end, we present the necessary conditions (criteria) for data literacy education based on excellent overseas cases and derive suggestions for educational directions by analyzing the case of the CO-DATA Station data literacy hackathon competition organized by the Korea Foundation for the Advancement of Science and Creativity (Convergence and Open Sharing System) project.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.279-285
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• 2024

The Fourth Industrial Revolution is driving transformative changes across society, leading to a surge in demand for professionals skilled in computer technologies. However, traditional education systems face challenges in adapting to rapidly evolving technologies, with long learning durations and high costs. In response, microdegrees have emerged as a solution, offering focused, short-term learning in specific fields, thereby enhancing flexibility and accessibility in education. This study explores how microdegrees provide new opportunities within existing educational frameworks, examines their roles and impacts across various domains, and identifies key elements to consider when designing microdegree programs. Ultimately, microdegrees will play a crucial role in rapidly adapting to technological trends and cultivating the workforce needed for the future. This research aims to contribute to foundational studies on microdegrees, driving educational innovation and proposing a new educational paradigm.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.391-398
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• 2024

Under the influence of pervasive digital revolution, the world is overwhelmed with data with an increasing speed of data generation. The accessibility and analysis of 'big data' can provide useful insight and help various industry sectors revolute. Although the concept of 'big data' has gained popularity in the construction industry in recent years, the construction industry remains at a nascent stage in the adoption of big data technologies and lags behind other sectors. To the best of our knowledge, few empirical studies have been done to examine the status quo of big data adoption in the construction sector and its influencing factors. This paper fills the gaps and examines the current status of big data adoption in companies with different sizes and roles and projects with different types, and the drivers and challenges in adopting big data technologies. After an extensive literature review, a questionnaire survey and post-interviews were conducted. The results of the analysis show that the big data adoption in the construction sector is affected by the size of companies and the work experience of employees. Technology advancement, competitiveness, government plan, and policy initiatives are the main drivers of the big data adoption, while design appropriate system, difficulty in data collection and the lack of knowledge and experience were found to be the major challenges for the big data adoption in the construction sector. Finally, the identified top three strategies to overcome challenges and promote big data adoption are 'clear organization structure', 'government incentives' and 'the training of IT personnel'. The findings of this study guide construction practitioners in different companies and projects put domain specific strategies in place to enhance the big data adoption.