• Smart Media Journal
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• v.9 no.3
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• pp.107-115
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• 2020

Recently, BIM has become mandatory in the construction field, research on various use cases is increasing. In particular, when virtual reality technology, one of the core technologies of the 4th industrial revolution, and BIM are combined, it can be used in various fields such as preliminary design review and construction simulation. Until now, however, virtual reality grafting technology is only used as a simple prototype or as a model house. Also, it is difficult to activate virtual construction because it is expensive to produce high-quality virtual reality contents. Therefore, in this paper, in order to increase the utilization and quality of the virtual construction field, a study was conducted to shorten the material mapping time, which takes a lot of time when producing virtual reality contents using BIM. To this end, object properties were assigned to enable material mapping in the BIM model, and materials most used in the construction field were configured, and automated material function development and final tests were conducted that automatically map properties and materials. For the test, 10 models were used and the test was repeated three times, and the productivity improvement of about 50.16% was finally achieved. In the future, we plan to conduct research on physical data weight reduction based on the advanced material mapping automation function and the large-capacity BIM model.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.327-332
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• 2021

Materials used for education include SM20C, Al6061, and acrylic. SM20C materials are used a lot in certification tests and functional competitions as carbon steel, but they are also used in industrial sites. Al6061 is said to be a material that produces a lot of tools because it has lower hardness than carbon steel and is highly flexible. When practical guidance is given to students using acrylic materials, it is a material that causes vibration and tool damage due to excessive cutting. In this process, we examine how impact on the 5-axis equipment 2NC head can affect precision control. The weakest part of a five-axis equipment is the head that controls the AC axis. In the event of precision and cumulative tolerances in this area, the precision of all products is reduced. Thus, a key part of the 2NC head, the spindle housing was carried out using Al7075 T6 (U.S. Alcoasa) material and the entire body using FCD450 (spherical graphite cast iron). In the vibration and cutting process acting on these two materials, the analysis was carried out to determine the value of applying the force as a finite element analysis under extreme conditions. We hope that using these analytical data will help students see and understand the structure of 5-axis machining rather than 5-axis cutting.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.295-309
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• 2021

Maker education has recently been actively practiced under strong governmental support as a nation-wide policy for innovative education, which now had to confront the unexpected challenge and crisis of 'contactless educational environments' due to COVID-19 pandemic. In this context, this study aimed to develop a checklist needed for developing 'contactless maker education program' which still continues to maintain 'maker mindsets' as the goal and direction of maker education, since maker education has been regarded as an alternative educational environment suitable for the 4th industrial revolution age. For this purpose, this study first conducted literature review related to maker education and contactless (i.e. online) education environments, from which several characteristics of the contactless maker education have been extracted. And then, 5 maker education instructors currently conducting the contactless maker education programs in various settings provided feedback on the developed checklist draft, which actually became the final version of the checklist. Considering the current COVID-19 pandemic situation, the checklist for the contactless Maker education might be helpful in preventing to diminish or reduce the educational values and active application of maker education.

• Korean small business review
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• v.42 no.3
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• pp.245-274
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• 2020

The 4th Industrial Revolution is rapidly changing the business environment and enterprises are required to accelerate various innovative activities for sustainable competitiveness. Recently corporate entrepreneurship is widely spread to organization for establishing innovative corporate culture and stimulating corporate ventures. However, many enterprises are not successful and productive due to lack of readiness of corporate entrepreneruship. Therefore, finding the factors influencing corporate entreprensurship, innovative activities and business performance is a very important research issues. A research model and hypothesis are developed by through literature review to analyze positive effects of corporate entrepreneurship to corporate performance and influential effects of factors such as innovation-based efforts at the organizational level, vision and organizational strategies and innovative operating system to corporate entrepreneurship and business performance. The result of Entrepreneurship Survey with Corporates conducted by Korea Entrepreneurship Foundation in 2017 is used for the research sample. Hypothesis test used 1,326 samples and the structural equation modeling is applied. The results show that corporate entrepreneurship improves innovative idea activity performance and business performance. And, establishing innovative vision and strategies and innovative organizational culture enhances corporate entrepreneurship. In addition, it was confirmed that the innovative operational system has a moderating effect that strengthens the positive influence relationship between corporate entrepreneurship and innovative idea performance. The results of this study have implications for previous research on corporate entrepreneurship in Korea by presenting the relationship between corporate entrepreneurship and business performance and the multilateral relationships between innovative organizational structure and corporate entrepreneurship.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.675-683
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• 2022

Blockchain, which is the basis of virtual assets such as cryptocurrency, is receiving great attention as one of the cornerstone technologies of the 4th industrial revolution. Blockchain is a technology that can fundamentally change our lives not only in finance, but also in politics, logistics, and culture. However, it shows lower-than-expected usability because it is complicated to learn and is continuously being developed. In this study, we tried to investigate whether the Technology Acceptance Model(TAM) of virtual assets can be changed through education on the underlying technology, blockchain. A video-based online experiment was conducted with a total of 103 participants and examined how the type of training(positive, negative) and measurement timing(before, after) affect perceived usefulness, perceived ease of use, acceptance, which are TAM variables, and trust and security, which are related to blockchain characteristics. As a result of the experiment, interactions were found in all dependent variables according to the type of education and measurement timing. Specifically, groups that received negative education had no difference in all variables before and after, but it was found that groups that received positive education showed an increase afterwards. Through this, it can be seen that the effect of education based on the anchoring effect is also shown in the intention to use virtual assets using block chain technology, suggesting that the intention to use blockchain related technology can be increased through positive education.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.276-279
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• 2022

The 4th industrial revolution refers to the transition to a knowledge society in which the production speed of knowledge is fast and the proportion of the knowledge industry is greatly increased. The reorganization of the industrial structure and the change of occupations and jobs due to new technologies are bringing about changes in education, and the development of digital technology has made education that is borderless, individual and dynamic, becoming the new standard of education. With these changes, interest in nano-degrees on new technologies or micro-degrees focused on core courses rather than regular course degrees is increasing. As a representative example, Udacity in the United States has opened and operated online nanodegree courses related to jobs, and collaborates with major companies to develop and educate core training courses necessary for companies, thereby efficiently supporting companies in securing talent. With the revitalization of online vocational and job training, an environment has been prepared in which individuals can set goals for vocational competency development and continue their portfolio-based sustainable learning. However, for effective vocational education, automated and personalized educational content design should be preceded. To this end, in this paper, we propose a personalized career and course map recommendation system in the era of online learning

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.164-169
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• 2019

Defense R&D investment is expanding. This shows that major countries are preparing for future warfare by securing high-tech technologies and developing new concept weapons systems. In particular, it is expected to accelerate the development of the technology of the 4th Industrial Revolution in the future, and Korea needs its own ability to develop advanced weapons and medium- and long-term investment strategies to prepare for future warfare. The defense science and technology strategy will be established every five years. The strategy-dependent R&D drive has limitations in replacing the rapidly changing security environment and changes in science and technology. This study proposes an investment efficiency process to proactive incorporate information into R&D strategies with a focus on implementing policies and changing security threats, while maintaining continuity in which strategic and focused areas are linked to core technology development. The process can quickly reflect the needs of technological change, the security environment and defense policy. The process can be used to efficiently allocate defense R&D budgets and establish strategic investment directions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.537-543
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• 2020

In order to cultivate the talents needed in the 4th industrial revolution era, it is necessary to select gifted students and train them systematically. The affective characteristics of the gifted are self-concept, personality, sociality, motivation, morality, attitude and interest, and these are important factors that affect science achievement. In particular, computer scientific attitude is an important variable affecting computer science achievement. This study developed a computer scientific attitude test based on TOSRA developed by Fraser to measure the affective characteristics of information-gifted students. The computer scientific attitude test is composed of 7 areas: social implications of computer science, attitude to computer scientific inquiry, adoption of computer scientific attitudes, adoption of computer scientific attitudes, leisure interest in computer science, career interest in computer science, and normality of computer scientists. The relationship between computer scientific attitude and academic achievement of gifted students was analyzed using the developed test. To determine find out whether computer scientific attitude significantly predicts academic achievement, the results of a regression analysis showed that t = 2.543 and p = 0.025, indicating that the average of computer science attitude significantly predicted academic achievement.

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.