• Asian Journal for Public Opinion Research
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• v.5 no.3
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• pp.250-265
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• 2018

Thailand is one of the ASEAN countries and is said to be the most visited country in Southeast Asia. Despite its development, Thailand falls as one of the countries with the lowest rates of English proficiency. This article is written to describe one of the possible factors of Thailand's low English proficiency, which is the foreign language anxiety of students. This article outlines references regarding the English language anxiety of Thai students and uses them as a basis in distinguishing English language anxiety among nursing students in Boromarajonani College of Nursing Nakhon Lampang, Thailand (BCNLP). A survey was conducted using a questionnaire based on the FLCA Scale by Horwitz, Horwitz, and Cope, (1986) with a focus group consisting of 80 participants randomly selected from $1^{st}$ year to $4^{th}$ year nursing students of BCNLP. As found in the survey there were two sources of English language anxiety among nursing students: 1. Fear of negative evaluation due to unpreparedness, and feeling and thinking that others are better in language learning as the main factors; and 2. Communicating apprehension, where in speaking without preparation, speaking in the foreign language in front of other students, and self-doubt about one's ability to speak in the foreign language are the highest ranked causes of anxiety. The results indicate two main problems: unpreparedness and self-concept. Therefore, it is recommended that English Language classes should be taught with the learner-centered approach and that instructors should put importance in preparing the students during class, and encouraging them to increase a positive self-concept towards English language learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.333-342
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• 2021

The purpose of this study is to compare the differences in transfer motivation and learning self-efficacy before and after applying virtual simulation for nursing in psychiatric nursing practice, and to provide them as basic data for effective psychiatric practical education. This study was conducted from October to December 2020. The subjects were 41 people who were enrolled in the third year of a located in U city, and who had received psychiatric nursing practice education using virtual simulation for nursing. Data were analyzed by paired t-test and pearson's correlation coefficient. After practice compared to before psychiatric nursing practice with virtual simulation nursing applied, transfer motivation was significantly increased and learner self-efficacy increased, but it was not statistically significant. Therefore, It was confirmed that psychiatric nursing practice education using virtual simulation for nursing is partly an effective practice strategy.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.538-547
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• 2022

Recently introduced image classification methods using Transformers show remarkable performance improvements over conventional neural network-based methods. In order to effectively consider regional features, research has been actively conducted on how to apply transformers by dividing image areas into multiple window areas, but learning of inter-window relationships is still insufficient. In this paper, to overcome this problem, we propose a transformer structure that can reflect the relationship between windows in learning. The proposed method computes the importance of each window region through compression and a fully connected layer based on self-attention operations for each window region. The calculated importance is scaled to each window area as a learned weight of the relationship between the window areas to re-calibrate the feature value. Experimental results show that the proposed method can effectively improve the performance of existing transformer-based methods.

• Journal of Yeungnam Medical Science
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• v.40 no.2
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• pp.179-186
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• 2023

Background: This study summarizes the experience of operating a 'Medical Humanities' course, which was taught remotely to maintain activities and discussions at medical schools in Daegu, Korea during the sudden and unexpected coronavirus disease 2019 (COVID-19). Methods: The subjects of this study were 73 first- and 79 second-grade medical students who took the medical humanities (1) and (2) courses among first- and second-grade students of Yeungnam University College of Medicine in 2020. Of the 152 students who agreed to the online survey, 123 completed the survey. Self-, environmental, and program evaluations were conducted on the study subjects, and differences according to grade and gender were analyzed. Results: As a result of the study, a significant difference between self-evaluation and environmental evaluation was confirmed. Self-evaluation was determined to be higher in the first grade than in the second grade. The environmental evaluation showed that male students were more satisfied than female students and students generally had difficulties in the classroom environment. Of the applications used in class, the highest satisfaction was observed with KakaoTalk (Kakao Corp.) and Zoom (Zoom Video Communications Inc.). At the end of COVID-19, the students preferred online classes. Conclusion: If the learning environment for online classes is well prepared and systematic provisions are made, such as class operations that are suitable for the subject, effective education and learning can be achieved by taking advantage of both face-to-face and online classes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.907-917
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• 2023

Recently, a self-driving car have applied deep learning technology to advanced driver assistance system can provide convenience to drivers, but it is shown deep that learning technology is vulnerable to adversarial evasion attacks. In this paper, we performed five adversarial evasion attacks, including MI-FGSM(Momentum Iterative-Fast Gradient Sign Method), targeting the object detection algorithm YOLOv5 (You Only Look Once), and measured the object detection performance in terms of mAP(mean Average Precision). In particular, we present a method applying morphology operations for YOLO to detect objects normally by removing noise and extracting boundary. As a result of analyzing its performance through experiments, when an adversarial attack was performed, YOLO's mAP dropped by at least 7.9%. The YOLO applied our proposed method can detect objects up to 87.3% of mAP performance.

• Journal of Korean Home Economics Education Association
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• v.30 no.2
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• pp.137-147
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• 2018

The purpose of this study was to develop and examine the effects of flipped learning in ancient Mesopotamian costume history. The flipped learning class was designed to three steps(pre-class, in-class, after-class). Pre-class: Students learned the socio-cultural background of Mesopotamia by watching videos online and Mesopotamian costume with PPT. In-class: Students were evaluated for their prior learning through the quiz. After the quiz, the instructor had a supplementary mini-lecture. Then the advanced learning was progressed with the team project(Mesopotamian costume analysis) by online Louvre Museum. Students made a team presentation and the instructor provided feedback. After-class: The effectiveness of flipped learning was measured based on the students' self-reflective journals and class awareness surveys. As the results, students actively participated in flipped learning and the class was rated appropriate. Students were satisfied with the overall quality of the flipped learning class. The Effect of Flip Learning Classes in reflective journals were shown as 'related flipped learning style,' 'related online Louvre museum project,' 'understanding of cooperative learning,' and 'contents of the class'. In conclusion, the flipped learning applied to Mesopotamian costume history was positive as a learner-centered education.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.35-43
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• 2023

This study tried to find out the applicability and effectiveness of the AI-based adaptive learning system in university classes by operating an AI-based adaptive learning system on a pilot basis. To this end, an AI-based adaptive learning system was applied to analyze the operation results of 42 learners who participated in basic mathematics classes, and a survey and in-depth interviews were conducted with students and professors. As a result of the study, the use of an AI-based customized learning system improved students' academic achievement. Both instructors and learners seem to contribute to improving learning performance in basic concept learning, and through this, the AI-based adaptive learning system is expected to be an effective way to enhance self-directed learning and strengthen knowledge through concept learning. It is expected to be used as basic data related to the introduction and application of basic science subjects for AI-based adaptive learning systems. In the future, we suggest a strategy study on how to use the analyzed data and to verify the effect of linking the learning process and analyzed data provided to students in AI-based customized learning to face-to-face classes.

• Education of Primary School Mathematics
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• v.26 no.4
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• pp.333-348
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• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.

• Journal of dental hygiene science
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• v.12 no.4
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• pp.375-382
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• 2012

This research will target the Dental Hygienics students to identify the level and type of the $2{\times}2$ achievement target orientation, and will study how this achievement target orientation is related to the Self-Regulated Learning, as well as the effect on the each sub elements of the Self-Regulated Learning (SRL). Among the $2{\times}2$ achievement target orientation of all the female university students, the skillful approach was found to be highest. In case of the adjustment of the motivation following grade, intrinsic value of the 1st grader was higher than the intrinsic value of the 2nd and 3rd graders. As for the behavior adjustment, the 3rd grader's time and studying adjustment were found to be higher. Mean while, pursuit of the cooperation was found to be high compared to the time and studying adjustment of the1st and 2nd graders. Second, intrinsic value, overt goal orientation, and studying environment adjustment among the SRL's subelements, manifested significant correlation with all the sub elements of the $2{\times}2$ achievement target orientation. As for the elements that affected cognition adjustment, grade and skillful approach were found to exert significant effect on the performance adjustment. As for the element that affects behavior adjustment, grade and skillful approach exerted significant effect on the sub elements of the behavior adjustment. Analysis on the effect of the achievement target orientation and SRL implies that the direction of the students' learning goal can be modified and that they can learn effectively by using the SRL appropriately. When the two elements are factored in carefully, the key findings could serve as a base data that can motivate the students, inducing effective learning process.