• Journal of the Korean earth science society
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• v.43 no.5
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• pp.647-658
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• 2022

The purpose of this study is to analyze students' learning characteristics regarding spatial ability, orienteering ability and earth science content learning ability and their relationship through development and application of earth science activities using orienteering. The programme aims to improve students' spatial ability using orienteering activity which requires spatial ability. Topics in the programme included map, compass, contour, movement of celestial, and constellation application. Students were to orienteer in the field using the method they learned in class. This programme was applied to five 7th graders. The results are, first, students who have positive attitude toward science and do well at school tended to perceive their orienteering ability high. Second, all parts of spatial ability, spatial visualization, spatial orientation, spatial relation were used during orienteering, especially spatial visualization and spatial orientation. The relationship between spatial ability, orienteering ability, and earth science content learning abilities was not clear. However, orienteering ability and earth science content learning ability were in similar tendency.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.358-368
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• 2022

Social media is a window for everyone, individuals, communities, and companies to spread ideas and promote trends and products. With these opportunities, challenges and problems related to security, privacy and rights arose. Also, the data accumulated from social media has become a fertile source for many analytics, inference, and experimentation with new technologies in the field of data science. In this chapter, emphasis will be given to methods of trend analysis, especially ensemble learning methods. Ensemble learning methods embrace the concept of cooperation between different learning methods rather than competition between them. Therefore, in this chapter, we will discuss the most important trends in ensemble learning and their applications in analysing social media data and anticipating the most important future trends.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.448-449
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• 2022

In the image upscaling field, the method using deep learning is showing better results than using the interpolation method. And for hologram upscaling, using deep learning is showing better results than general interpolation. In this paper, the network structure and learning results are analyzed. The learning results are compared by adjusting the depth of the network and the number of channels at the same weight.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.286-294
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• 2023

We studied learners' perceptions and learning styles of project research activities in the chemical field conducted by 54 science high school students. In a survey of students' perceptions of task research, positive responses were found in "internal motivation," "cooperation," "task solving," and "tenacity and immersion," and statistically significant differences were found in "self-directedness," "cooperation," and "tenacity and immersion" by year. The 'lower' group responded most positively in the 'cooperation' category, and the 'higher' group responded most positively in the 'task solving' category. As a result of investigating the learning styles of the students who conducted the task research, it was found in the order of assimilator, converger, accommodator, and diverger. The assimilators showed the characteristic of systematically and scientifically approaching the problem. Convergers were found to have excellent problem-solving and decision-making ability, are practical, and have experimental-based thinking characteristics. In this study, the characteristics of science high school students showed well in the results of the learning style performed.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.67-76
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• 2024

Diabetic retinopathy is a threatening complication of diabetes, caused by damaged blood vessels of light sensitive areas of retina. DR leads to total or partial blindness if left untreated. DR does not give any symptoms at early stages so earlier detection of DR is a big challenge for proper treatment of diseases. With advancement of technology various computer-aided diagnostic programs using image processing and machine learning approaches are designed for early detection of DR so that proper treatment can be provided to the patients for preventing its harmful effects. Now a day machine learning techniques are widely applied for image processing. These techniques also provide amazing result in this field also. In this paper we discuss various machine learning and deep learning based techniques developed for automatic detection of Diabetic Retinopathy.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.57-64
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• 2024

In the industrial field, robots are used to increase productivity by replacing labors with dangerous, difficult, and hard tasks. However, failures of individual industrial robots in the entire production process may cause product defects or malfunctions, and may cause dangerous disasters in the case of manufacturing parts used in automobiles and aircrafts. Although requirements for early diagnosis of industrial robot failures are steadily increasing, there are many limitations in early detection. This paper introduces methods for diagnosing robot failures using sound-based data and deep learning. This paper also analyzes, compares, and evaluates the performance of failure diagnosis using various deep learning technologies. Furthermore, in order to improve the performance of the fault diagnosis system using deep learning technology, we propose a method to increase the accuracy of fault diagnosis based on an inference window. When adopting the inference window of deep learning, the accuracy of the failure diagnosis was increased up to 94%.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.6-11
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• 2020

In today's world, the design industry is becoming more complex, with the development of networks such as the internet and revolutionary changes in information and telecommunications. As the demand for designers to cope with various situations occurring in these industrial sites or solve problems in practice promptly is required, a capstone design program was developed in collaboration with the industry. Capstone design classes have positive effects on creative problem solving ability, academic achievement and learning satisfaction by allowing students to think and experience the practical problems of the industrial field. It is also effective in improving communication, creative thinking and critical thinking. The purpose of this study is to search for talent training methods needed in the fashion industry and to develop effective programs through capstone design class studies conducted in the fourth grade of fashion design majors from 2017 to 2019 (6 semesters). Through these studies, the aim is to search for talent training methods needed in the fashion industry and to develop effective programs. If the capstone design learning method is used as a method of solving problems through close communication between the company and the educational field as an industry-academia cooperation system, it is expected to be positioned as a field-type human resource education method that is required in the industrial field.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.513-524
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• 2011

Digital Technology actively utilized in all spheres by rapid changes in information and knowledge demands transformations not only in the sociocultural and educational spheres but also specifically in the field of arts education. Digital Technology becomes a challenging factor for the field of arts education. In this study purposed a new teaching-learning approach method in arts education, called "Music Technology-Based Learning"(hereafter, MTBL), which is to, first, take interdisciplinary approaches combining various subjects in the field of arts education. In the case study was conducted to examine the educational effects of the MTBL approach to the liberal arts course in university: mind maps derived from 2 sessions (pre-class and post-class), evaluation sheets regarding self-directed learning and in-depth interviews with ten voluntary learners after the class were used as methods for data collection. The result of case study shows positive changes in the terms of the degrees of emotional sensibilities of the learners. Moreover, the research confirmed the potential of MTBL as a new teaching and learning methodology in art education.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.69-76
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• 2021

This study was analyzed in a phenomenological way to identify the depth of the experience from the perspective of students who participated in field trips and to understand in-depth the practical knowledge and meaning of the process. The subjects of the study were nine people with experience in field training for beauty college students, and they were in-depth stories from October to December 2020. The collected data were analyzed by Colaizzi method. The results of this study showed four essential topic vowels: "Expectation on Field Practice," "Necessity of Practical Education," "Difficulties Experienced in Field Practice," and "The Endurance of Field Practice." Based on the results of this study, the importance of being designed more systematically to enhance the effectiveness of learning experiences so that the effectiveness of learning experiences can be improved with confidence to cope with field practice.

• International Journal of Contents
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• v.12 no.4
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• pp.31-44
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• 2016

Knowledge creation and management are regarded as critical success factors for an organization's survival in the knowledge era. As a process of knowledge acquisition and sharing, organizational learning mechanisms (OLMs) guide the learning function of organizations represented by its different learning activities. We examined a variety of learning processes that constitute OLMs. In this study, we aimed to capture the process and framework of OLMs and knowledge sharing and acquisition. Factors facilitating OLMs were investigated at three levels: individual, group, and organizational. The concept of an OLM has received some attention in the field of organizational learning, however, the relationship among the factors generating OLMs has not been empirically tested. As part of the ongoing discussion, we attempted a systemic approach for OLMs. OLMs can be represented by factors that are inherent to the organization's system; therefore, prior to empirically testing the OLM generating factor(s), evaluation of its organizational integration is required to determine effective treatment of each factor. Thus, we developed a framework to manage knowledge and proposed a method to numerically evaluate factors influencing the OLMs. Specifically, composite importance (CI) of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was applied to explore the interaction effect of these factors based on systemic approach. The augmented matrix thus generated is expected to serve as a stochastic matrix of an absorbing Markov chain.