• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.323-332
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• 2022

As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.1-13
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• 2019

This study examined the effect of digital technologies on adolescent mental health; attention deficit, aggression, depression. Furthermore, we investigated the role of parenting style and peer attachment as they might have effects on digital technologies. Using two-wave longitudinal data, we conducted longitudinal analysis from the Korean Children and Youth Panel Survey done in 2015 and 2016. Results showed that computer and internet usage for learning purpose has a positive effect on mental health, while computer games and social media have negative effects. Also, the positive effects of learning on depression indicated stronger in adolescents who felt less affection from their parents. On the other hand, the negative effects of computer games and social media could be moderated by both parenting style and peer attachment. Implications of these results and directions for future research are discussed.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.147-155
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• 2024

Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.37-44
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• 2021

A study was conducted on the effects of improving concentration by obscuring the peripheral vision using a blindfold that only covers the left and right sides of the field of view. The blindfold was trapezoidal in shape (5 × 4.8 cm in length and width) and was fixed to the left and right sides of the glasses with fixing clips. The material was a black-colored polypropylene (PP) and weighed 2.3 g including the clip. Qualitative and quantitative evaluations were performed on 50 healthy college students during the 15 days of using a blindfold. The qualitative analysis was performed utilizing a questionnaire regarding the improvement of concentration and the structure of the blindfold. EEG was measured while watching a learning video that required attention for quantitative analysis, and signal power and ERD/S analyses were performed for the mid β band (15-20 Hz) at the F4 position, which was the frontal lobe. The results showed that 40 of the 50 people reported improved concentration when they wore a vision shield, and 80% of the total subjects found it to be effective. From the quantitative evaluation, the ERS peak (p = 0.023) and the ERD + ERS peak value showed a significant difference (p = 0.017). In conclusion, concentration still improved even if only the left and right visual fields were used. Thus, it is expected that blindfolding could be used in various environments that require concentration.

• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.279-293
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• 2019

This study investigated the effects of national science leading school programs on students' positive experiences about science (PES) and teachers' perceptions of curriculum implementation factors affecting students' PES. For this study, Test for Indicators of Positive Experiences about Science (TIPES) was administered to a total of 11,488 students from 117 national science leading schools and 1,315 students from 50 normal counterpart schools. In addition, a total of 105 teachers were given a survey asking their curriculum implementation levels and perceptions on importance and performance levels of each identified factor that was known to influence students' PES. Students' total PES scores and scores in five sub-components of PES were widely varied across science leading school program types. In general, participating teachers reported common curriculum implementation factors that most positively affected students' PES including 'science-related activities out of school,' 'student-centered research projects,' 'ICT-related materials' and 'performance assessment.' Based on these results, implications for science education were discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.285-296
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• 2014

This study was to develop a introduction program contents for first year nursing students and to verify the effectiveness of the program contents. The effects of introduction program contents for first year nursing students is to identify a career attitude maturity and self-efficacy. The study used a One Group Pre-post Test Design and the surveys were carried out form 5, March to 26, March, 2012. The participants were 129 students of nursing in K university. The data were obtained via questionnaires survey before and after taking the course. The collected data were analyzed by paired t-test using SPSS 15. As a result in analyzing the effect of introduction program contents on career attitude maturity and self-efficacy for first year nursing students, introduction program contents was appeared to influence the self-efficacy. The scores of self-efficacy(t=2.36, p=.002) showed statistically significant improvement after the education. Also there was significant increase in career attitude maturity(t=2.92, p=.004) after the education. The results of this study were the positive effects of introduction program contents on first nursing students' career attitude maturity and self-efficacy. These findings suggest that introduction program contents as a subject would be an efficient way for self-efficacy and career attitude maturity of first year nursing students. and I recommend that various professor teaching method and nursing education contents development with utilizing ICT.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.607-619
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• 2019

As software education was introduced through the 2015 revised curriculum, various research activities have been carried out to improve the computational thinking of learners beyond the existing ICT literacy and software utilization education. With this change, the purpose of this study is to examine the research trends of various research activities related to computational thinking which is emphasized in software education. To this end, we extracted the key words from 190 papers related to computational thinking subject published from January 2014 to September 2019, and conducted frequency analysis, word cloud, connection centrality, and topic modeling analysis on the words. As a result of the topical modeling analysis, we found that the main studies so far have included studies on 'computational thinking education program', 'computational thinking education for pre-service teacher education', 'robot utilization education for computational thinking', 'assessment of computational thinking', and 'computational thinking connected education'. Through this research method, it was possible to grasp the research trend related to computational thinking that has been conducted mainly up to now, and it is possible to know which part of computational thinking education is more important to researchers.

• Journal of Platform Technology
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• v.10 no.4
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• pp.47-55
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• 2022

Recently, diverse devices using different wireless technologies are gradually increasing in the IoT environment. In particular, it is essential to design an efficient feature extraction approach and detect the exact types of radio signals in order to accurately identify various radio signal modulation techniques. However, it is difficult to gather labeled wireless signal in a real environment due to the complexity of the process. In addition, various learning techniques based on deep learning have been proposed for wireless signal classification. In the case of deep learning, if the training dataset is not enough, it frequently meets the overfitting problem, which causes performance degradation of wireless signal classification techniques using deep learning models. In this paper, we propose a generative adversarial network(GAN) based on data augmentation techniques to improve classification performance when various wireless signals exist. When there are various types of wireless signals to be classified, if the amount of data representing a specific radio signal is small or unbalanced, the proposed solution is used to increase the amount of data related to the required wireless signal. In order to verify the validity of the proposed data augmentation algorithm, we generated the additional data for the specific wireless signal and implemented a CNN and LSTM-based wireless signal classifier based on the result of balancing. The experimental results show that the classification accuracy of the proposed solution is higher than when the data is unbalanced.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.81-91
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• 2014

STEAM education has been introduced to resolve the existing problems of science education since 2011. However, as ICT develops rapidly, the future of the schools with various educational technologies is demanding for a new type of STEAM education. Therefore, the current research suggests CT-STEAM (Computational Thinking & STEAM) education, the new approach to provide integrated thinking based education with all sorts of computing devices. Firstly, the instruction model was developed as a fundamental step to introduce CT-STEAM in the real education scene. Then, lesson plan was developed as a implementation strategy, and it was tested for validity by computer education experts. It is hoped that the results of this study can enhance the understanding of CT and STEAM Education, also to provide baseline information to develop various teaching methods for integrated CT education.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.263-269
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• 2024

Amidst the global challenges of climate crisis, warfare, and escalating inequality, the pursuit of achieving the United Nations Sustainable Development Goals (SDGs) has become increasingly imperative. Consequently, research into effective pedagogical methodologies from the student perspective continues to gain momentum. Particularly, with the advancement of generative AI technologies, the potential for leveraging such tools in providing global citizenship education to the youth is garnering attention. This study implemented and emphatically analyzed an artificial intelligence educational program focused on the creation of sustainable urban spaces under the UN Academic Impact(UNAI). The findings indicated a high level of literacy pertaining to global citizen AI education, evidenced by increased interest, satisfaction, and recommendation intention. Furthermore, the study observed an enhancement in digital interactions through the processes of posting, viewing, and real-time discussions of the created works with Generative AI such as the ChatGPT, Midjourney, and Stable Diffusion. Through these instances, the study proposes the development of HTHT curricula that enhance creative thinking, collaborative growth, and analytical capabilities.