• Journal of Appropriate Technology
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• v.6 no.2
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• pp.126-135
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• 2020

Recently, with the development of the 4th Industrial Revolution era and the popularization of technologies the maker movement is spreading worldwide in various ways for education, entrepreneurship, and solving social problems. This paper introduces a case of establishing and operating a maker space in Tanzania, East Africa, one of the developing countries. iTEC Tech-shop was established in the first half of 2018 at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania by Innovative Technology and Energy Center (iTEC), and has been operating for nearly two years. With the allocation of empty warehouse space from NM-AIST, physical facilities were established through the purchase and installation of equipment and hand tools. Based on the advice from Idea Factory of Seoul National University and Fab-Lab Seoul, iTEC Tech-shop operational system were established. Through a total of 7 technical workshops, iTEC Tech-shop provided training courses for about 180 local personnel. In addition, the smart Techshop test-bed project was promoted in order to improve the operation level along with securing sustainability of the Techshop. The case of the iTEC Tech-shop could be a useful case for institutions or organizations promoting the maker movement to developing countries.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.85-95
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• 2021

Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.57-58
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• 2023

The working time for loading and transporting containers in the container terminal is one of the factors directly related to port productivity, and minimizing working time for these operations can maximize port productivity. Among working time for container operations, the working time of yard tractors(Y/T) responsible for the transportation of containers between berth and yard is a significant portion. However, it is difficult to estimate the working time of yard tractors quantitatively, although it is possible to estimate it based on the practical experience of terminal operators. Recently, a technology based on IoT(Internet of Things), one of the core technologies of the 4th industrial revolution, is being studied to monitoring and tracking logistics resources within the port in real-time and calculate working time, but it is challenging to commercialize this technology at the actual port site. Therefore, this study aims to develop yard tractor working time prediction model to enhance the operational efficiency of the container terminal. To develop the prediction model, we analyze actual port operation data to identify factors that affect the yard tractor's works and predict its working time accordingly.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.57-68
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• 2023

With the technological development in the era of the 4th Industrial Revolution, technologies using HMD are being applied in various fields. HMD is especially useful in virtual reality fields such as AR/VR, and is very effective in receiving vivid impressions from users located in remote locations. According to these characteristics, the frequency of using HMD is increasing in the field related to collaboration. However, when HMD is applied to collaboration, communication between experts located in remote locations and workers located in the field is not smooth, causing various problems in terms of usability. In this paper, remote experts and workers in the field use HMD to solve various problems arising from collaboration, design/propose new types of HMD structures and functions that enable more efficient collaboration, and verify their usability using SUS evaluation techniques. As a result of the SUS evaluation, the new type of HMD structure and function proposed in this paper was 86.75points, which is believed to have greatly resolved the restrictions on collaboration and inconvenience in use of the existing HMD structure. In the future, when the HMD structure and design proposed in this paper are actually applied, it is expected that the application technology using HMD will expand rapidly.

• 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.

• 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.

• 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.