• Journal of The Korean Association For Science Education
• /
• v.37 no.5
• /
• pp.835-846
• /
• 2017

The purpose of this study is to investigate the perceptions of scientifically gifted middle school students about their engineering design process according to gender and talent division. The instrument in surveying their perceptions about the engineering design process consists of 24 items (Likert 5 point type) five domains: problem definition, information collection and utilization, idea generation, inquiry performance, and teamwork (communication, cooperation, leadership). A total of 102 scientifically gifted students participated in the survey, according to gender (69 males and 33 females) and talent divisions (physics, biological sciences, software, mathematics, space-geological sciences, and chemistry). They had a high level of awareness of their engineering design ability. It is necessary to develop a customized gifted-education program so that their talent in their field of interest can be fully displayed according to the gender and talent division. In addition, the teaching and learning methods and strategies of the engineering design program for the scientifically gifted middle school students should be established to fully reflect the practical needs of the talented.

• The Journal of the Korea Contents Association
• /
• v.9 no.9
• /
• pp.151-162
• /
• 2009

As the aging population has increased, the silver generation is getting to account for the considerable percent of economic activities and becomes the main body of production and consumption. Although the economic activity of silver generation is increased, the development of silver contents for the leisure activities is still not revitalized. The serious silver contents and the easy-to-use interface are very important because the silver generation is relatively weaker than young people in perception, studying, and exercise, and is fragile in mobility and vitality. This paper suggests methods to develop sensory bicycle, gate ball, and mole game contents haying lower body exercise effects for the silver generation to utilize leisure and maintain health. Along with fun as games, functional design factors suitable to the cognitive ability and bodily activity ability of the silver generation were considered and through sensory intefaces that are easy for the silver generation to use and customized progressing methods complying with individual characteristics, it was attempted to induce continued interests and lower body exercise effects.

• Journal of Convergence for Information Technology
• /
• v.9 no.8
• /
• pp.248-253
• /
• 2019

Early diagnosis of mild cognitive impairment (MCI) can reduce the incidence of dementia. This study developed the MCI prediction model for the elderly in Korea. The subjects of this study were 3,240 elderly (1,502 men, 1,738 women) aged 65 and over who participated in the Korean Longitudinal Survey of Aging (KLoSA) in 2012. Outcome variables were defined as MCI prevalence. Explanatory variables were age, marital status, education level, income level, smoking, drinking, regular exercise more than once a week, average participation time of social activities, subjective health, hypertension, diabetes Respectively. The prediction model was developed using Restricted Boltzmann Machine (RBM) neural network. As a result, age, sex, final education, subjective health, marital status, income level, smoking, drinking, regular exercise were significant predictors of MCI prediction model of rural elderly people in Korea using RBM neural network. Based on these results, it is required to develop a customized dementia prevention program considering the characteristics of high risk group of MCI.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.5
• /
• pp.655-661
• /
• 2020

This study examined community-centered informatization education support measures for empowerment of women with disabilities based on gender perspective.First, the 'Digital Information Gap Survey' conducted by the Ministry of Science and ICT used the 2018 'Digital Information Gap Survey' to find out the current status of the digital information gap between male and female handicapped people. The law on information education support for women with disabilities is presented.Lastly, based on the current status of informatization education support available to women with disabilities, centered on local communities, such as establishing a comprehensive women's disability support center, visiting education considering disability types, developing and supporting customized informatization education considering learning ability, and discovering community resources related to informatization. In this paper, we propose a plan to support informatization education for women with disabilities based on capacity building.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.3
• /
• pp.571-576
• /
• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• Journal of Broadcast Engineering
• /
• v.27 no.5
• /
• pp.738-750
• /
• 2022

In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.

• Journal of Internet Computing and Services
• /
• v.24 no.2
• /
• pp.57-66
• /
• 2023

Currently, a new energy system is emerging that implements consumption reduction by improving energy efficiency. Accordingly, as smart grids spread, the rate system by timing is expanding. The rate system by timing is a rate system that applies different rates by season/hour to pay according to usage. In this study, external factors such as temperature/day/time/season are considered and the time series prediction model, LSTM, is used to predict energy power usage data. Based on this energy usage prediction model, energy usage charges are reduced by analyzing usage patterns for each device and transferring power energy from the maximum load time to the light load time. In order to analyze the usage pattern for each device, a clustering technique is used to learn and classify the usage pattern of the device by time. In summary, this study predicts usage and usage fees based on the user's power data usage, analyzes usage patterns by device, and provides customized demand transfer services based on analysis, resulting in cost reduction for users.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.193-198
• /
• 2023

We study a learner-customized lecture recommendation project using deep learning. Recommendation systems can be easily found on the web and apps, and examples using this feature include recommending feature videos by clicking users and advertising items in areas of interest to users on SNS. In this study, the sentence similarity Word2Vec was mainly used to filter twice, and the course was recommended through the Surprise library. With this system, it provides users with the desired classification of course data conveniently and conveniently. Surprise Library is a Python scikit-learn-based library that is conveniently used in recommendation systems. By analyzing the data, the system is implemented at a high speed, and deeper learning is used to implement more precise results through course steps. When a user enters a keyword of interest, similarity between the keyword and the course title is executed, and similarity with the extracted video data and voice text is executed, and the highest ranking video data is recommended through the Surprise Library.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.51-57
• /
• 2021

Quite a few elementary school teachers began to utilize AI technology in order to provide students with customized, intelligent information services in recent years. However, learning principles of AI may be as important as utilizing AI in everyday life because understanding principles of AI can empower them to buildup adaptability to changes in highly technological world. In the paper, 'Linear Regression Algorithm' is selected for teaching AI-based prediction system to solve real world problems suitable for elementary students. A simulation program written in Scratch was developed so that students can find a solution of linear regression model using the program. The paper shows that students have learned analyzing data as well as comparing the accuracy of the prediction model. Also, they have shown the ability to solve real world problems by finding suitable prediction models.

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