• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.135-138
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• 2021

본 논문에서는 예비교사를 위한 AI-STEAM 교육 사례로서 봇빌더를 활용한 챗봇 제작 교육을 실시하고 이를 바탕으로 챗봇 제작 AI-STEAM 교육을 위한 시사점을 제시하였다. 최근 관련 정책이 발표되는 등 인공지능 교육이 학교에서 실시되기 위한 기반이 마련되었다. 인공지능 교육이 학교 현장에 제대로 안착되기 위해서는 현직 교사들에 대한 보수교육 뿐 아니라 교육 및 사범대학의 교원양성과정에서도 인공지능 교육이 실시되어야 할 필요가 있다. 본 논문에서는 교사들의 인공지능 교사교육 요구를 바탕으로 AI-STEAM을 제안하고 다양한 전공의 예비교사를 위한 챗봇 제작 AI-STEAM 교양교육 및 학생 작품 사례를 제시하였다.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.471-481
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• 2021

The purpose of this study is to analyze the effectiveness of AI convergence education program. To this end, the "Elementary Science AI Convergence Education Program for Machine Learning" developed in previous research were taught to elementary school students in the fourth to sixth grades in eight times. The quantitative changes of each factor were analyzed by R program, and the effectiveness of education was analyzed by Pearson correlation and paired samples t-test. As a result, there is a deep correlation between "Attitude to AI technology, Scientific preference and STEAM Literacy" and technical average has improved in many factors. Therefore, AI convergence education program is meaningful in terms of education, and if AI education and AI convergence education are implemented into the primary formal education curriculum, they will have a positive effect.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.405-412
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• 2021

To prevent problems such as portrait rights, copyright, and cyber violence, an ethics education STEAM projects using deepfake apps using AI technology were developed and applied. The Deepfake apps were screened, and the contents of the elementary school curriculum were reconstructed. The STEAM project as creative experiential activities was mainly operated by the UCC activities, and applied the info-ethics awareness measurement test based on the planned behavior theory. The social STEAM project as money (financial) education was qualitatively analyzed. It was found that this STEAM classes using AI technology app significantly enhances the ethical awareness of information communication.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.43-48
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• 2023

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.213-221
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• 2021

With the advent of the 4th industrial revolution, the need for artificial intelligence education has increased. The online learning environment caused by COVID-19 made it possible to use variety of artificial intelligence platforms. In this study, an aritificial intelligence class plan was developed and proposed to achieve the goal of artificial intelligence education using an AI platform. The AI platform used is AI for Oceans, With the theme of creating a program for the environment, designed a 6-hour project class using Novel Engineering-based on STEAM model. Students experience AI for Oceans enough time and learn supervised learning by experience. Based on understanding of supervised learning, students design their own programs for the environment using Entry's AI blocks. In this study, for AI convergence education, this lesson was developed and presented with the goal of acquiring the creative problem solving ability and integrated thinking ability by using the principles of artificial intelligence to solve problems.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.48-56
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• 2024

The application of artificial intelligence (AI) is becoming increasingly important to coping with air pollution. AI is effective in coping with it in various ways including air pollution forecasting, monitoring, and control, which is attracting a lot of attention. This attention has created high need for analyzing studies on AI and air pollution. To contribute for satisfying it, this study performed bibliometric analyses on the studies on AI and air pollution from 2012 to 2022 using the Web of Science database. This study analyzed them in various aspects such as the trend in the number of articles, the trend in the number of citations, the top 10 countries of origin, the top 10 research organizations, the top 10 research funding agencies, the top 10 journals, the top 10 articles in terms of total citations, and the distribution by languages. This study not only reports the bibliometric analysis results but also reveals the eight distinct features in the research steam in studies on AI and air pollution, identified from the bibliometric analysis results. They are expected to make a useful contribution for understanding the research stream in AI and air pollution.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.7 no.2
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• pp.73-79
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• 1978

This paper presents the experimental study on the design conditions of pressure between booster ejector and air ejector in the steam-jet water-vapour refrigeration system. In this experiment, the motive steam of booster ejector and ai. ejector was dry saturated from 6 ata to 8 ata and flash chamber pressure were about $10\∼540mmHg$ higher than mixing section in booster ejector. The investigation of air on the pressure of booster ejector was performed by changing the condenser pressure. The experimental results show that flash chamber vacuum and condenser pressure of steam-jet refrigeration cycle increased in accordance with the increase of motive steam Pressure. Among the several nozzle sires tested, No.4 nozzle were best in term of evaporator vacuum under the constant operating conditions of air ejector in condenser.

• Clinical Nutrition Research
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• v.13 no.3
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• pp.156-164
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• 2024

The purpose of this study was to evaluate the nutritional adequacy of senior-friendly foods sold in Korea, focusing on protein and sodium. This study examined the nutritional content of 170 products with nutritional labels that were sold in online stores in Korea and categorized the products into 93 staple foods (cooked rice, porridge, and mousse) and 77 side-dish and snack foods (braized·steam·roast products, broth, sauces, and snacks). Then, the adequacy of the nutritional content of these foods, focusing on protein and sodium, was evaluated according to product type. The 93 staple products and 77 side-dish products had average serving sizes of 163.27 g and 127.92 g, prices of $3.25 and $2.72, and energy contents of 295.25 kcal and 141.95 kcal, respectively. For staple foods, the energy content was significantly greater in cooked rice, but the protein content and index of nutrition quality (INQ) were significantly greater in mousse. There were no significant differences in sodium content or contribution to adequate intake (AI) by product type, but the sodium INQ was significantly greater in the mousse and porridge. For side-dish foods and snack products, the protein content, contribution to the recommended intake, and INQ were all significantly greater for the braized·steam·roast products. Sauces and braized·steam·roast products were significantly higher in sodium content and contribution to the AI, while broth was significantly higher in sodium INQ. These findings can be used to guide proper product selection and nutritional management that considers the health characteristics of health-vulnerable and elderly people.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.417-422
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• 2023

AI blockchain technology, which is attracting attention as a core technology of the 4th Industrial Revolution, is a technology that can be used as an important means of innovation not only in the current gaming industry but also in various industrial fields. This paper extracts the platforms and types of blockchain games currently ranked within the top 100 on the blockchain app (DApp) sites State Of The DApps, DApp.com, and Dapp Rader and introduces the top games on major platforms. As a result of extracting platforms and types, the top games were mainly based on Ethereum, EOS, and Steam. However, the results showed that there are significantly more games based on the Ethereum platform, which are stable, easy to apply, and have a low barrier to entry due to the large number of users and DApps. We plan to improve awareness of blockchain games by studying the characteristics that only blockchain games have.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.