• CELLMED
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• v.13 no.10
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• pp.9.1-9.6
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• 2023

This study aims to explore the potential of Korean language learning as a means of psychological healing and improving the quality of life for Japanese middle-aged and older learners. Results showed that Korean language learning could help alleviate various psychological issues experienced by middle-aged learners and contribute to enhancing their quality of life. Learning a foreign language is not just about acquiring information but also about meeting people who use the language and understanding and experiencing their culture. In particular, for Japanese middle-aged learners, Korean language learning can be advantageous as it can lead to the discovery or development of new hobbies or interests. Results also showed that Korean language learning increased learners' opportunities for interaction with others and enjoyment of learning new cultural customs. These positive outcomes suggest the need for discussion of teaching strategies that focus on psychological healing in foreign language education. Further clinical trials with participants who learn foreign languages for healing purposes may provide more conclusive evidence on the diverse effects of language learning on stress, anxiety, depression, self-development, social connections, and cognitive ability.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.2
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• pp.29-50
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• 2010

The purpose of this study presents a model of the integrated online library service with LMS (Learning Management System). The new library service is called 'Library on Blackboard' which was developed and implemented by Murray State University Libraries in Murray, Kentucky, USA. This user-centered service with applied information technology has the potential to enhance the quality of the library performance in university libraries. The introduction of the Learning Management System in South Korea has a potential to enhance the education environment and promote new library services. With the emergence of new information technologies and growing popularity in online classes and distance education programs, the importance and usage of Learning Management Systems in higher education has increased.

• Computers and Concrete
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• v.33 no.2
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• pp.175-193
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• 2024

Researchers have embarked on an active investigation into the feasibility of adopting alternative materials as a solution to the mounting environmental and economic challenges associated with traditional concrete-based construction materials, such as reinforced concrete. The examination of concrete's mechanical properties using laboratory methods is a complex, time-consuming, and costly endeavor. Consequently, the need for models that can overcome these drawbacks is urgent. Fortunately, the ever-increasing availability of data has paved the way for the utilization of machine learning methods, which can provide powerful, efficient, and cost-effective models. This study aims to explore the potential of twelve machine learning algorithms in predicting the tensile strength of geopolymer concrete (GPC) under various curing conditions. To fulfill this objective, 221 datasets, comprising tensile strength test results of GPC with diverse mix ratios and curing conditions, were employed. Additionally, a number of unseen datasets were used to assess the overall performance of the machine learning models. Through a comprehensive analysis of statistical indices and a comparison of the models' behavior with laboratory tests, it was determined that nearly all the models exhibited satisfactory potential in estimating the tensile strength of GPC. Nevertheless, the artificial neural networks and support vector regression models demonstrated the highest robustness. Both the laboratory tests and machine learning outcomes revealed that GPC composed of 30% fly ash and 70% ground granulated blast slag, mixed with 14 mol of NaOH, and cured in an oven at 300°F for 28 days exhibited superior tensile strength.

• Journal of The Korean Association For Science Education
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• v.31 no.7
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• pp.1025-1039
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• 2011

Even though many researchers have reported that everyday contexts can arouse students' interests and improve their science learning, the connection between everyday context and physics learning is not yet clearly discussed. In our study, at first, we assumed five guidelines for helping the development of teaching materials for physics learning in everyday context. Based on these guidelines, we developed teaching materials for understanding basic optics and applied these materials to ninth grade students. From the positive responses of students and science teachers about the developed materials, we could confirm that the guidelines were reflected well in the materials. And also, it was found that students and teachers wanted to learn or teach context-based physics in future classroom learning. However, all students do not receive benefits from learning physics in everyday context. By analyzing students' actual learning processes and interviews with them, we found five potential impeding factors which could hinder students' successful learning of physics in everyday context. As a result, we suggested five recommendations for overcoming these impeding factors.

• Investigative Magnetic Resonance Imaging
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• v.23 no.2
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• pp.81-99
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• 2019

Recently, deep learning methods have shown great potential in various tasks that involve handling large amounts of digital data. In the field of MR imaging research, deep learning methods are also rapidly being applied in a wide range of areas to complement or replace traditional model-based methods. Deep learning methods have shown remarkable improvements in several MR image processing areas such as image reconstruction, image quality improvement, parameter mapping, image contrast conversion, and image segmentation. With the current rapid development of deep learning technologies, the importance of the role of deep learning in MR imaging research appears to be growing. In this article, we introduce the basic concepts of deep learning and review recent studies on various MR image processing applications.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.29-34
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• 2023

The flow from developing a machine learning model to deploying it in a production environment suffers challenges. Efficient and reliable deployment is critical for realizing the true value of machine learning models. Bridging this gap between development and publication has become a pivotal concern in the machine learning community. FastAPI, a modern and fast web framework for building APIs with Python, has gained substantial popularity for its speed, ease of use, and asynchronous capabilities. This paper focused on leveraging FastAPI for deploying machine learning models, addressing the potentials associated with integration, scalability, and performance in a production setting. In this work, we explored the seamless integration of machine learning models into FastAPI applications, enabling real-time predictions and showing a possibility of scaling up for a more diverse range of use cases. We discussed the intricacies of integrating popular machine learning frameworks with FastAPI, ensuring smooth interactions between data processing, model inference, and API responses. This study focused on elucidating the integration of machine learning models into production environments using FastAPI, exploring its capabilities, features, and best practices. We delved into the potential of FastAPI in providing a robust and efficient solution for deploying machine learning systems, handling real-time predictions, managing input/output data, and ensuring optimal performance and reliability.

• Asia pacific journal of information systems
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• v.31 no.1
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• pp.102-120
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• 2021

E-learning is a planned effort towards providing interactive and experiential learning having flexibility in terms of time, place, pace, participation and accessibility. Globalization has set the stage for a social transformation of the world economy driven by technological innovation, emphasizing knowledge-based processes. While the tertiary education enrolments in wealthy nations have gone up incrementally, the same cannot be said to be right about developing economies. E-Learning can streamline enrolments to higher education, in developing nations by being a cost-effective and flexible alternative. The objective of this paper is to draw attention to the similarities in the national culture of these two countries and compare students' perception on e-learning in India and Sri Lanka along eight dimensions viz., viability, dependability, flexibility, inclusivity, power, pertinence, challenge and equitability. The results reveal that e-learning is equally popular among students from both countries, and they have a high perception score towards e-learning on each of the measured eight dimensions. Hence results are indicative of an opportunity of tapping the potential of e-learning in reaching out to a broader audience of underprivileged students and onboarding them into the knowledge economy.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.89-104
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• 2010

In a rapidly changing and increasingly technological society. the use of technology should not be disregarded in issues of learning algebra. The use of technology in learning algebra raises many learning and pedagogical issues. In this article, previous research on the use of technology in learning algebra is synthesized on the basis of the four issues: conceptual understanding, skills, instrumental genesis, and transparency. Finally, suggestions for future research into technological pedagogical content knowledge (TPCK) are made.

• Journal of Gifted/Talented Education
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• v.7 no.2
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• pp.47-67
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• 1997

Fourteen Special high schools for developing talents in Science, Foreign Languages, and Arts in Seoul Metropolitan city were analyzed in terms of their educational objectives, Students screening system, curriculum, teaching-learning methods, teachers, and consistency with higher education. Special high schools in talent area were more or less similar to each other in all the above aspects. However, special high schools in different talent areas were quite different in student screening, teaching-learning methods, teachers, and consistency with higher education. Public schools were more affluent than the private ones. Special high schools in Science, arts and Sports were providing individualized, activity oriented, process-oriented teaching-learning methods, while the Foreign languages high schools excercised teacher-centered, grammar oriented, lecture-focused teaching methods more. Special high schools in arts and sports could have consistency with higher education because the university focuses on talents in the specified field rather than academic scores. In conclusion, the schools have a great deal of rooms to improve in teaching-learning methods with which students can maximize their potential development. However, the special high schools were equipped with better learning environments than regular high schools in many aspects.