• Smart Structures and Systems
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• v.30 no.6
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• pp.601-612
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• 2022

The prediction of structural mechanical behaviors is vital important to early perceive the abnormal conditions and avoid the occurrence of disasters. Especially for underground engineering, complex geological conditions make the structure more prone to disasters. Aiming at solving the problems existing in previous studies, such as incomplete consideration factors and can only predict the continuous performance, the deep attention fused temporal convolution network (DATCN) is proposed in this paper to predict the spatial mechanical behaviors of structure, which integrates both the temporal effect and spatial effect and realize the cross-time prediction. The temporal convolution network (TCN) and self-attention mechanism are employed to learn the temporal correlation of each monitoring point and the spatial correlation among different points, respectively. Then, the predicted result obtained from DATCN is compared with that obtained from some classical baselines, including SVR, LR, MLP, and RNNs. Also, the parameters involved in DATCN are discussed to optimize the prediction ability. The prediction result demonstrates that the proposed DATCN model outperforms the state-of-the-art baselines. The prediction accuracy of DATCN model after 24 hours reaches 90 percent. Also, the performance in last 14 hours plays a domain role to predict the short-term behaviors of the structure. As a study case, the proposed model is applied in an underwater shield tunnel to predict the stress variation of concrete segments in space.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.181-188
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• 2022

This study analyzed the effectiveness of sharing activities through software creative sharing classes. The purpose is to find a way for related activities to be carried out continuously. For this study, pre and post were test on changes in self-esteem, responsibility, and sense of community targeting 25 university students in Chungnam. The collected data were analyzed with SPSS 24. The results derived from this study are as follows. First, the self-esteem was significantly higher after the software creative sharing class than before. Second, the responsibility was significantly higher after the software creative sharing class compared to the prior. Third, the sense of community was found to be significantly higher after the software creative sharing class than before. Therefore, it was found that the software creative sharing class had a positive effect on self-esteem responsibility and sense of community. Based on these data, a method to expand continuous participation in talent sharing was suggested.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.375-384
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• 2022

As artificial intelligence(AI) education becomes essential in elementary schools with the revised 2022 curriculum, it is necessary to develop an AI curriculum for elementary school students. In this study, I developed the AI content framework to cultivate AI literacy of elementary school students. AI education areas were largely divided into AI understanding and AI development, and detailed areas were divided into eight categories: using of AI, impact of AI, AI ethics, recognition of AI, data expression, data exploring, learning of AI, and prediction of AI. In addition, twice expert Delphi surveys were conducted to verify the validity of the subject elements and achievement standards for each area. The final draft was finalized after reflecting expert opinions on the AI education content framework. In order for AI education to be expanded in elementary schools in the future, continuous research is needed, such as developing textbooks and teaching tools according based on the AI framework proposed in this study, securing the lesson hours to apply them to schools, and correcting and supplementing the problems of them.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.321-327
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• 2023

With the development of artificial intelligence, the prediction system has become one of the essential technologies in our lives. Despite the growth of these technologies, traffic congestion at intersections in the 21st century has continued to be a problem. This paper proposes a system that predicts intersection traffic jams using a Convolutional LSTM (Conv-LSTM) algorithm. The proposed system models data obtained by learning traffic information by time zone at the intersection where traffic congestion occurs. Traffic congestion is predicted with traffic volume data recorded over time. Based on the predicted result, the intersection traffic signal is controlled and maintained at a constant traffic volume. Road congestion data was defined using VDS sensors, and each intersection was configured with a Conv-LSTM algorithm-based network system to facilitate traffic.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.889-899
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• 2017

Various efforts and technical development for integrating the ICT technologies to the area of special needs education have been continuing. In this paper we have studied and implemented various ICT-based disability evaluation websites and mobile applications for special needs education and also verified their usefulness from the field test at disability schools. The valuer can access the websites and mobile applications for autistic behavior or learning disability evaluation at the any places and by any devices such as laptop, PC, smartphone and tablet PC. And all the evalation results are stored into and managed at the server database and shared with websites and mobile applications to integrate together easily. From the study about disability evaluation and implementation results we have a confidence that they will be useful to support the seamless evaluation and the continuous monitoring services for the disabled at the special needs education fields.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.321-331
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• 2023

This study aimed to develop an engineering design-based science education program for high school students and to investigate its effects on students' science-related attitudes and engineering design abilities. "Creating healthy shoes for maintaining proper posture program" was developed as an activity to come up with creative solutions using the methodology of an engineering design process to solve problems in daily life. The creating healthy shoes for maintaining proper posture program consisted of the following five stages: "defining the problem," "ingathering information related to the problem," "generating the solution," "implementing the best solution," and "evaluating the solution & reflecting." As a result of applying this engineering design-based science education program, it improved the high school students' science-related attitudes and engineering design abilities. Therefore, the program developed in this study has a positive effect on enhancing high school students' science-related attitudes and engineering design abilities. These findings imply that the continuous operation and expansion of activities incorporating an engineering design process in science education are necessary as a teaching and learning strategy for cultivating future science talents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.284-286
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• 2021

With the continuous development of the Internet and digital, platforms are emerging to store large amounts of media data and provide customized services to individuals through online. Companies that provide these services recommend movies that suit their personal tastes to promote media consumption. Each company is doing a lot of research on various algorithms to recommend media that users prefer. Movies are divided into genres such as action, melodrama, horror, and drama, and the film's audio (music, sound effect, voice) is an important production element that makes up the film. In this research, based on movie trailers, we extract audio for each genre, check the commonalities of audio for each genre, distinguish movie genres through supervised learning of artificial intelligence, and propose a utilization method for generating metadata in the future.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.3
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• pp.163-169
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• 2009

The concept of library is newly interpreted and designed under the environment of U-City. The basic notion of the library should not changed its kernel nevertheless, the new technologies like ubiquitous computing services are applied to the library, which functions in terms of information services, continuous learning programs and communities of practice(CoP). The library is fit for any technologies or environments as organism. Actually the library has been shown in terms of new information technologies with the changes of the times. It leads to comprehend the library as its appearance not as it is. The libraries including even cities have evolved toward ubiquitous(computing) environment. On the other words, the libraries have sought ubiquitous at the past, now they are still chasing it.

• Journal of Digital Policy
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• v.2 no.4
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• pp.33-39
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• 2023

With a continuous occurrence of right-turn traffic accidents at intersections, there is an increasing demand for measures to address these incidents. In response, a technology has been developed to detect the presence of pedestrians through object detection in CCTV footage at right-turn areas and display warning messages on the screen to alert drivers. The YOLO (You Only Look Once) model, a type of object detection model, was employed to assess the performance of object detection. An algorithm was also devised to address misidentification issues and generate warning messages when pedestrians are detected. The accuracy of recognizing pedestrians or objects and outputting warning messages was measured at approximately 82%, suggesting a potential contribution to preventing right-turn accidents

• Applied Chemistry for Engineering
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• v.35 no.2
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• pp.85-95
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• 2024

Direct air capture (DAC) technology plays a crucial role in mitigating climate change. Reports from the International Energy Agency and climate change emphasize its significance, aiming to limit global warming to 1.5 ℃ despite continuous carbon emissions. Despite initial costs, DAC technology demonstrates potential for cost reductions through research and development, operational learning, and economies of scale. Recent advancements in high-permeance polymer membranes indicate the potential of membrane-based DAC technology. However, effective separation of CO₂ from ambient air requires membranes with high selectivity and permeability to CO₂. Current research is focusing on membrane optimization to enhance CO₂ capture efficiency. This study underscores the importance of direct air capture, evolving cost trends, and the pivotal role of membrane development in climate change mitigation efforts. Additionally, this research delved into the theoretical background, conditions, composition, advantages, and disadvantages of permeance and selectivity in membrane-based DAC.