• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.15-21
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• 2021

This paper conducted a feasibility study by applying an Internet of Things and Artificial intelligence-based management system for the elderly living alone in an aging society. The number of single-person families over the age of 50 is expected to increase, and problems such as health, safety, and loneliness may occur due to aging. Therefore, by establishing an IoT-based care system for the elderly living alone, a stable service was developed through securing a rapid response system for the elderly living alone and automatically reporting 119. The participants of the demonstration test were subjects under the jurisdiction of the "Seongnam Senior Complex," and the data collection rate between the IoT sensor and the emergency safety gateway was high. During the demonstration period, as a result of evaluating the satisfaction of the IoT-based care system for the elderly living alone, 90 points were achieved. We are currently in the COVID-19 situation. Therefore, the number of elderly living alone is continuously increasing, and the number of people who cannot benefit from care services will continue to occur. Also, even if the COVID-19 situation is over, the epidemic will happen again. So the care system is essential. The elderly care system developed in this way will provide safety management services based on artificial intelligence-based activity pattern analysis, improving the quality of in-house safety services.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.4
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• pp.297-304
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• 2022

This study compares the performance of artificial intelligence (AI)-based maximum power point tracking (MPPT) methods under partial shading conditions in a photovoltaic generation system. Although many studies on AI-based MPPT have been conducted, few studies comparing the tracking performance of various AI-based global MPPT methods seem to exist in the literature. Therefore, this study compares four representative AI-based global MPPT methods including fuzzy logic control (FLC), particle swarm optimization (PSO), grey wolf optimization (GWO), and genetic algorithm (GA). Each method is theoretically analyzed in detail and compared through simulation studies with MATLAB/Simulink under the same conditions. Based on the results of performance comparison, PSO, GWO, and GA successfully tracked the global maximum power point. In particular, the tracking speed of GA was the fastest among the investigated methods under the given conditions.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.777-786
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• 2023

Generative AI systems are expected to be more widely utilized. However, relatively little attention has been paid to understanding how users perceive and accept generative AI results. To identify strategies for increasing the future use of generative AI and prepare for potential issues, we organized design workshop for the general user group and the designer group. They created artwork utilizing Novel AI and semi-structured interview was followed to evaluate their attitudes toward generative AI and its copyright. Results indicate that the general public views generative AI positively, while the design-related group views it quite negatively. The participants expressed concerns as to the misuse the system, specifically related to copyright issues. People who are likely to utilize generative AI outcomes have insisted more strongly that copyrights should be their own. Those working in the design field highly evaluated the possibility of using generative AI in their work. Copyright perceptions were not significantly influenced by users' satisfaction or their level of involvement in the creation process. We discuss design implications for interfaces using generative AI based on the findings.

• The Journal of Korean Association of Computer Education
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• v.23 no.2
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• pp.21-29
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• 2020

The purpose of this study is to develop the educational programs for cultivating balanced view of technical understanding and social impact on Artificial Intelligence (AI). To this end, an educational program based on a constructivist approach was developed. Through an experimental class for middle school students we analyzed the concept and perception of AI and the satisfaction of the class. The main results are as follows. First, students' understanding of the concept and the cases of AI in their daily lives has improved. Second, the recognition of the impact of AI on society has emerged and concern about social impact have been lowered. Third, in terms of program satisfaction, all the factors such as understanding of AI, interest in class, interest in AI were high. With these results, we discussed the implications for AI education in elementary and secondary school.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.76-87
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• 2008

As hardware performance rises, game users demand higher computer graphic, more convenient UI(User Interface), faster network, and smarter AI(Artificial Intelligence). At this time, however, AI development is accomplished by a co-development team or only one developer. For that reason, it's hard to verify that AI performance and basic game AI technology is lacking for developing high-level AI. Searching the merits and demerits of existing game AI platforms, we investigate main points to consider when designing game AI platforms in this paper. From this we suggest Darwin, a game platform, based on agent that developers embody AI easily and capable of proposing AI test with module that makes them find strategic position. And then evaluate achievement results through making agent used strategic module that Darwin offers.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.227-236
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• 2021

This study aims to develop an AI education program for secondary school students to help understand AI and to provide an experience of solving real-life problems by using AI, and to analyze the effectiveness of education. The education program based on the AI education system for K-12 developed in the previous study was composed of a total of 12 lessons by selecting the self-driving cars, which is emerging as a recent issue among real life problems, as the main topic. Classes were conducted for secondary school students who had experience in software education, and the effectiveness of education and class satisfaction were analyzed. As a result of the analysis, it was confirmed that the understanding of AI and the sense of AI efficacy were improved, and the class satisfaction was high in all items such as educational content, fun in class, difficulty of class, and interest in AI. Based on these results, implications for AI education for secondary students were proposed.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.157-162
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• 2022

In a society full of knowledge and information, digital literacy and artificial intelligence (AI) education that can utilize AI technology is needed to solve numerous everyday problems based on computational thinking. In this study, data-centered AI education was conducted while teaching computer programming to non-computer programming students at universities, and the correlation between major factors related to academic performance was analyzed in addition to student satisfaction surveys. The results indicated that there was a strong correlation between grades and problem-solving ability-based tasks, and learning satisfaction. Multiple regression analysis also showed a significant effect on grades (F=225.859, p<0.001), and student satisfaction was high. The non-computer programming students were also able to understand the importance of data and the concept of AI models, focusing on specific examples of project types, and confirmed that they could use AI smoothly in their fields of interest. If further cases of AI education are explored and students' AI education is activated, it will be possible to suggest its direction that can collaborate with experts through interest in AI technology.

• The Journal of Bigdata
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• v.7 no.2
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• pp.91-102
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• 2022

As artificial intelligence develops, AI chatbot systems are actively taking place. For example, in public institutions, the use of chatbots is expanding to work assistance and professional knowledge services in civil complaints and administration, and private companies are using chatbots for interactive customer response services. In this study, we propose a scenario-based AI voice chatbot system to reduce museum operating costs and provide interactive guidance services to visitors. The implemented voice chatbot system consists of a watcher object that detects the user's voice by monitoring a specific directory in real-time, and an event handler object that outputs AI's response voice by performing inference by model sequentially when a voice file is created. And Including a function to prevent duplication using thread and a deque, GPU operations are not duplicated during inference in a single GPU environment.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.303-313
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• 2023

This study aimed to investigate the relevance of cardiovascular disease risk factors AI and AIP, divided into three groups, among 300 individuals who underwent health checkups at the hospital. Various variables such as Age, Sex, BMI, WC, TC, TG, HDL-C, LDL-C, FBS, HbA1C, SBP, DBP, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were analyzed using statistical methods including frequency analysis, cross-tabulation, one-way ANOVA, Pearson's correlation analysis, and multiple linear regression analysis. The cross-analysis based on cardiovascular disease risk criteria revealed that men and individuals in their 50s had higher cardiovascular disease risk based on AI and AIP. Significant differences were observed in TG, TC, HDL-C, LDL-C, SBP, DBP, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) according to AI criteria. For the AIP criteria, TG, TC, HDL-C, FBS, HbA1C, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were identified as cardiovascular disease risk factors. FBS and HbA1c showed the highest positive correlation In the correlation analysis, followed by TC and LDL-C. The lowest positive correlation was observed between LDL-C and DBP. In terms of negative correlation, HDL-C and AI had the highest negative correlation, while LDL-C and TG showed the lowest negative correlation. Multiple regression analysis indicated that the AI and AIP risk criteria had explanatory powers of 73.6% and 72.5%, respectively. HDL-C had the greatest negative effect on the AI risk criterion, while TG had the most significant influence on the AIP risk criterion. In conclusion, while other serological variables are important, managing HDL-C and TG levels may help reduce the risk of cardiovascular disease.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.397-402
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• 2024

Speech recognition and motion recognition technologies are applied and used in various smart devices, but they are composed of simple command recognition forms and are used as simple functions. Apart from simple functions for recognition data, professional command execution capabilities are required based on data learned in various fields. Research is being conducted on a system platform that provides optimal data to users using Generative AI, which is currently competing around the world, and can interact through voice recognition and motion recognition. The main technical processes designed for this study were designed using technologies such as voice and motion recognition functions, application of AI technology, and two-way communication. In this paper, two-way communication between a device and a user can be achieved by various input methods through voice recognition and motion recognition technology applied with AI technology.