• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.337-339
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• 2021

본 연구는 최근 펜데믹 위기에서 교육의 변화하는 모습을 점검하고 미래의 학습에 대한 모습들을 예측하기 위해 이러닝과 학습분석에 대한 신흥기술의 동향을 살펴보고자 한다. 연구방법으로 신흥기술의 '하이프 사이클'과 '이러닝 예측 하이프 커버'를 기반으로 하여 각 단계별 기술들을 점검하고 펜데믹 위기에서 더 공고히 된 이러닝과 학습 관련 기술들이 무엇인지 살펴본다. 또한 하이프 사이클의 5단계인 기술촉발 단계, 부풀려진 기대의 정점 단계, 환멸 단계, 계몽 단계, 생산성 안정 단계인 각 단계별 학습과 관련된 기술들은 어떤 것이 있으며, 그 기술들이 이러닝과 학습분석에 어떠한 영향을 미칠 것인지 예측해 본다. 향후 연구로는 본 연구를 기반으로 인공지능이 이러닝과 학습분석에서의 역할을 알아보고자 한다.

• Convergence Security Journal
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• v.24 no.2
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• pp.47-53
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• 2024

The traditional personal information life cycle model, primarily tailored to conventional systems, is inherently unsuitable for comprehending the nuances of personal information flow within artificial intelligence frameworks and for formulating effective protective measures. Therefore, this study endeavors to introduce a personal information life cycle model specifically designed for artificial intelligence (AI). This paper presents a personal information life cycle model suitable for artificial intelligence, which includes the stages of collection, retention, learning, use, and destruction/suspension, along with the re-learning process for destruction/suspension. Subsequently, we compare the performance of these existing models (such aspersonal information impact assessment and the ISMS-P model) with the newly proposed model. This underscores the superiority of our proposed model in comprehensively understanding the personal information flow in AI and establishing robust protective measures.

• Journal of Korea Foundry Society
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• v.41 no.6
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• pp.521-527
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• 2021

This study presents a process management method for the detection of casting defects during in high-pressure die casting based on machine learning. The model predicts the defects of the next cycle by extracting the features appearing over the previous cycles. For design of the gearbox, the proposed model detects shrinkage defects with data from three cycles in advance with 98.9% accuracy and 96.8% recall rates.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.527-529
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• 2021

This paper focuses on the implementation of machine learning model for Recycling bot, which is a platform service of recycling education. The recycling bot applied with a AI model using collected image set. The experiment confirms that classified by the model result are accurate.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.265-273
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• 2019

This research aims at developing human resources who will serve as flexible mediators in the future national or cultural conflict situations. The primary learning contents approach the class by selecting the upcycling design activities, in which the students recognize the problem of waste that is for all and study representative characteristics and backgrounds of each culture. The classes were held centering around the student members of GunpoYMCA, and the culturally characteristic materials were made through upcycling design. The activities included making giraffes in Africa with plastic bottles, Mongolian tents with wooden posts, snow globes with sauce pots, patchworks and rugs with shirts and textiles, and garlands with banners, which helped students learn the new term upcycling as well as get interested in the environmental problems. Also, they could understand other cultures by creating materials that represent each culture and studying their origins and historical backgrounds. In conclusion, this research offers value by developing abilities to cope with not only conflicts between cultures but confrontations between nations in the larger scope.

• Journal of Korean Home Economics Education Association
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• v.35 no.2
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• pp.133-144
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• 2023

The goal of this study was to improve environmental awareness by systematically developing a hands-on online lesson for adults on making drink bags by upcycling discarded umbrella cloth. The lesson was developed using an ADDIE model. During the analysis stage, the instructional design direction was established based on the findings of previous studies. In the design stage, the operation of practical classes in the online environment was specifically planned. The contents of education and the training time were also determined. The materials developed during the development stage included a kit and theoretical information containing images to raise awareness of environmental pollution and the significance of upcycling, as well as videos and photos. During the implementation stage, two sessions were held three months apart. A total of 36 adults participated, with 18 participants in each session. In the evaluation stage, the first session participants provided feedback on class satisfaction, which led to improvements. Positive feedbacks were received from the second session participants, who expressed satisfaction with the smooth communication and easy approaches to the learning materials. In both instances, the surveys on environmental consciousness and attitudes yielded an overall average score of 4.27, indicating a generally positive evaluation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8753-8759
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• 2015

Establishment of analysis procedures and validated performance measurements for generator output is required to maintain stable management of generator output in turbine power generation cycle. We developed turbine expansion model and measurement validation model for the performance calculation of generator using turbine output based on ASME (American Society of Mechanical Engineers) PTC (Performance Test Code). We also developed verification model for uncertain measurement data related to the turbine and generator output. Although the model in previous researches was developed using artificial neural network and kernel regression, the verification model in this paper was based on algorithms through Support Vector Machine (SVM) model to overcome the problems of unmeasured data. The selection procedures of related variables and data window for verification learning was also developed. The model reveals suitability in the estimation procss as the learning error was in the range of about 1%. The learning model can provide validated estimations for corrective performance analysis of turbine cycle output using the predictions of measurement data loss.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.663-670
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• 2019

Corrective thermal performance analysis is required for power plants' turbine cycles to determine the performance status of the cycle and improve the economic operation of the power plant. We developed a sectional classification method for the main feed-water flow to make precise corrections for the performance analysis based on the Performance Test Code (PTC) of the American Society of Mechanical Engineers (ASME). The method was developed for the estimation of the turbine cycle performance in a classified section. The classification is based on feature identification of the correlation status of the main feed-water flow measurements. We also developed predictive algorithms for the corrected main feed-water through a Kernel Regression (KR) model for each classified feature area. The method was compared with estimation using an Artificial Neural Network (ANN). The feature classification and predictive model provided more practical and reliable methods for the corrective thermal performance analysis of a turbine cycle.

• Communications of Mathematical Education
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• v.27 no.4
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• pp.473-486
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• 2013

This study examines the learning styles of freshmen enrolled in a college of science and engineering, and analyses the relationship between learning styles and academic achievement in mathematics to provide basic data for the teaching-learning methods, which are more suitable to learning styles of students. For the purpose of this research, a reliability analysis of Kolb's LSI is applied to 282 freshmen enrolled in a college of science and engineering of the medium-sized university. The outcomes of this survey are followings. Firstly, students hold higher positions in the order of converger, assimilator, accommodator, diverger among 4 learning styles. Secondly, while there is a positive corelation between abstract conceptualization[AC] and academic achievement, there is a negative corelation between concrete experience[CE] and academic achievement. Thirdly, as for academic achievement in mathematics, converger is superior to assimilator and accommodator. Finally, the correlation between learning styles and academic achievement is different by demographic characteristics. Based on these results, this study suggests the necessity for various teaching-learning strategies, which are adjusted to both academic characteristics of mathematics and learning styles. Also, the need for teaching methods, which help students to develop effectively four learning cycles, is proposed.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.35-57
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• 2022

This study developed an 'Eco-friendly Clothing Life Cycle' class applying gamification. And the effect of and learners' satisfaction on the class were examined after implementation. The developed class was applied to 40 sophomore students from "A" high school in Gyeonggi-do from February 3, 2022, to February 10, 2022, in a total of 4 sessions. The class was conducted in the stages of production-distribution-consumption-disposal, and was conducted in a way that a mission is solved after learning in Gather Town. It is designed so that learners continuously repeat learning until they accomplish the mission. The learners completed pre-class and post-class questionnaires. And a focus group interview was conducted with a randomly selected group of three learners. According to the pre-/post-class test comparison, the gamification class on the theme of "Eco-friendly Clothing Life Cycle" was found not to have a significant effect on learners' immersion or self-directed learning attitudes. However, in the case of the learners with high levels of non-immersion tendency, the level of immersion in the class increased, and the satisfaction level was positively associated with the level of immersion and self-directed attitude. Learners expressed 'concern' and 'expectation' about the gamification class, and said that although the developed class was using a 'new teaching method', 'appropriate use' was necessary. And learners were evaluated this class as a 'student-centered class' and acknowledged that it allowed 'self-directed learning'. The teacher who implemented the class said that this class was more effective in attracting students' expectations and interests compared to the conventional classes, and that the class in the meta-verse environment was perceived as a new type of class in the non-face-to-face era. The teacher also mentioned that when applied to the actual educational field, a detailed design is needed that allows the learners to proceed smoothly, and the role of the teacher in the class was more important. And the teacher also mentioned that the class should be properly designed so that the expectations given by the 'game' do not obscure the essence of the class.