• Advanced Industrial SCIence
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• v.2 no.1
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• pp.39-44
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• 2023

The purpose of this study is to compare the performance and satisfaction of online classes and non-face-to-face mixed classes at universities during the COVID-19 pandemic. This study was conductedtargeted fourth-grade students taking adult nursing lectures at the Department of Nursing at one university. Class performance and class satisfaction were compared between students who participated in the non-face-to-face class and participated in the non-face-to-face mixed class. class performance, students' average scores out of 100 on the final exams were compared. Class satisfaction compared the average score of questionnaire on class satisfaction Class performance was high in online classes, Class satisfaction was higher in mixed classes than in non-face-to-face classes. In the future, it will be necessary to develop and operate various educational methods for university education in the post-COVID-19 era.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.327-333
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• 2021

Currently development of the Artificial Intelligence technology is rapidly progressing in the era of the Fourth Industrial Revolution. The government is trying to improve the education of Artificial Intelligence and cultivating human resources. However there are very few cases where A.I technology is actually used in public education classes. Therefore we designed a text repository by implementing A.I speech recognition to provide career counseling for elementary school students. In the meantime, there have been many difficulties in giving advance consultations required for students' career counseling. In this study we suggested A.I speech recognition technology which can solve addressed problem and we planned various ways to make the program more educational. To conclude we expect A.I technology implemented in this study provides effective solution to career counseling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1863-1871
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• 2022

In the era of Fourth Industrial Revolution, secure networking technology is playing an essential role in the defense weapon systems. Encryption technology is used for information security. The safety of cryptographic technology, according to Kerchoff's principles, is based on secure key management of cryptographic technology, not on cryptographic algorithms. However, traditional centralized key management is one of the problematic issues in battlefield environments since the frequent movement of the forces and the time-varying quality of tactical networks. Alternatively, the system resources of each node used in the IoBT(Internet of Battlefield Things) environment are limited in size, capacity, and performance, so a lightweight key management system with less computation and complexity is needed than a conventional key management algorithm. This paper proposes a novel key escrow scheme in a lightweight manner for the IoBT environment. The safety and performance of the proposed technique are verified through numerical analysis and simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.214-216
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• 2021

It proposes a plan to strengthen the limitations of existing corporate security systems based on Zero-Trust. With the advent of the era of the Fourth Industrial Revolution, the paradigm of security is also changing. As remote work becomes more active due to cloud computing and COVID-19, security issues arising from the changed IT environment are raised. At the same time, in the current situation where attack techniques are becoming intelligent and advanced, companies should further strengthen their current security systems by utilizing zero trust security. Zero-trust security increases security by monitoring all data communications based on the concept of doubting and trusting everything, and allowing strict authentication and minimal access to access requestors. Therefore, this paper introduces a zero trust security solution that strengthens the existing security system and presents the direction and validity that companies should introduce.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.486-489
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• 2021

The purpose of this study was to investigate whether block-based programming language, which is currently being used in elementary and secondary schools, attracts students' interest and motivates them to learn. In addition, this study was to investigate how block-based programming language can help students improve their computing thinking ability and have a good effect on learning text-based programming to learn in high school. In addition, this study tried to study the direction of education linked with artificial intelligence and programming, which are popular in the era of the Fourth Industrial Revolution. The interest in software education has increased so much that software and information education from elementary school to high school has achieved quantitative and qualitative growth that can not be compared with before. However, in the field of artificial intelligence, discussions have begun, but we can not say that we have yet established ourselves in our education. We will discuss how block-based programming and text-based programming will be combined with artificial intelligence and educated.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.823-830
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• 2022

The risk of project execution increases due to the enlargement and complexity of Engineering, Procurement, and Construction (EPC) plant projects. In the fourth industrial revolution era, there is an increasing need to utilize a large amount of data generated during project execution. The design is a key element for the success of the EPC plant project. Although the design cost is about 5% of the total EPC project cost, it is a critical process that affects the entire subsequent process, such as construction, installation, and operation & maintenance (O&M). This study aims to develop a system using machine-learning (ML) techniques to predict risks and support decision-making based on big data generated in an EPC project's design and construction stages. As a result, three main modules were developed: (M1) the design cost estimation module, (M2) the design error check module, and (M3) the change order forecasting module. M1 estimated design cost based on project data such as contract amount, construction period, total design cost, and man-hour (M/H). M2 and M3 are applications for predicting the severity of schedule delay and cost over-run due to design errors and change orders through unstructured text data extracted from engineering documents. A validation test was performed through a case study to verify the model applied to each module. It is expected to improve the risk response capability of EPC contractors in the design and construction stage through this study.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.707-719
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• 2023

In the Fourth Industrial Revolution era, AI technologies, such as Chat GPT, have moved beyond assisting to actively analyzing data and providing solutions. This research assessed Chat GPT's e-service quality's influence on perceived value, innovativeness, and subsequent learning outcomes. Findings revealed that while ease of use and responsiveness weren't significant, safety and reliability were positively related to perceived value and innovativeness. A negative correlation was found between trustworthiness and perceived value. Users who saw Chat GPT as valuable and innovative experienced enhanced learning. The study emphasizes the need for guidelines in deploying Chat GPT academically. Given Chat GPT's recent introduction, further nuanced research is necessary.

• The Journal of Fisheries Business Administration
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• v.54 no.3
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• pp.45-67
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• 2023

The purpose of this study is to construct a regional-sector-fishery-offshore and inshore fishery competitiveness index, examine the types and changes of competitiveness, and derive implications by processing data of the Survey on the Current Status of Offshore and Inshore Fishery from 2013 to 2020 for this study. The main results of this study can be summarized as follows. First, considering the competitiveness of offshore and inshore fishery by region and year, Jeonnam, Jeju, and Incheon were relatively competitive. Second, considering the competitiveness of inshore fishery by region and year, we found that Jeonnam, Chungnam, Jeonbuk, and Jeju were relatively competitive. Third, looking at the types of competitiveness based on the competitiveness index in the management sector of offshore and inshore fisheries by region and year, Ulsan, Jeonnam, and Gyeongbuk were relatively competitive between 2014 and 2020. Fourth, Jeonnam and Jeju were relatively competitive between 2014 and 2020 based on the competitiveness index in the fishing sector of offshore and inshore fisheries by region and year. Fifth, we found that Jeonnam, Jeju, and Chungnam were relatively strong in the competitiveness of offshore and inshore fishery, combining the offshore and inshore fishery indexes by region and year. The results of this study have some limitation on outlier treatment, grade assignment, and weight for aggregation, so research considering these needs to be done in the future. In conclusion, the results of this study which were derived objectively and scientifically in the era of the 4th industrial revolution, when evidence-based decision-making was becoming critical, are expected to help the central or local governments determine the priority of support projects or investments.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.58-67
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• 2024

In the era of the fourth industrial revolution, data plays a vital role in enhancing the productivity of industries. To advance digitalization in the construction industry, which suffers from a lack of available data, this study proposes a model that classifies construction site photos by work types. Unlike traditional image classification models that solely rely on visual data, the model in this study includes semantic analysis of construction work types. This is achieved by extracting the significance of relationships between objects and work types from the standard construction specification. These relationships are then used to enhance the classification process by correlating them with objects detected in photos. This model improves the interpretability and reliability of classification results, offering convenience to field operators in photo categorization tasks. Additionally, the model's practical utility has been validated through integration into a classification program. As a result, this study is expected to contribute to the digitalization of the construction industry.

• Knowledge Management Research
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• v.24 no.4
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• pp.1-22
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• 2023

Knowledge management can be defined as the valuable storing and creation of new knowledge, as well as the sharing of this knowledge to be applied in all areas of an organization's management activities (Turban et al., 2003). In a knowledge-based society where intangible intellectual assets are the source of competitive advantage rather than tangible assets, knowledge management activities are emphasized in both academia and industry. This study analyzes research on "knowledge management" keyword indexed in the Korean Citation Index (https://kci.go.kr), operated by the National Research Foundation of Korea (NRF), to identify related research trends in Korea and suggest future directions for knowledge management activities. The results show that knowledge management is being researched through the integration of various fields and theories, indicating the potential for expanding research topics and fostering interdisciplinary collaboration. Furthermore, the study of knowledge management often include the keyword 'innovation', emphasizing its significant role in organizational and technological innovations. The analysis of keywords by year also reveals that they reflect the major environmental changes of each period, demonstrating the increasing importance of knowledge management in the era of the Fourth Industrial Revolution.