• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.993-1001
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• 2021

This study aims to determine the factors influencing student performance using the teaching and learning process through e-learning based on the unified theory of acceptance and use technology (UTAUT). This study also sets out to propose additional variables to expand the UTAUT model to be more suitable to use in higher education. This research conducted a literature review, expert interviews, and a self-administered survey involving 200 students at tertiary institutions in Riau province, Indonesia. The questionnaire data were analyzed using SmartPLS 2. This study shows that UTAUT constructs, namely, social influence, facility conditions, and effort expectancy have a significant influence on student behavior and performance, while the performance expectancy variable shows no significant effect. The additional variables, including lecturer characteristics, external motivation, and organizational structure, directly affect student performance. However, concerning student behavior, motivation and environment are the only variables with a significant effect. The results of this study suggest the behavior deteminant such as lecturer characteristics, motivation and environment, and organizational structure improve student performance. This study investigates factors affecting the performance of university students through the learning employing e-learning by developing the UTAUT constructs to include the lecturer characteristics, motivation and environment, and organizational structure in improving student performance.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.673-687
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• 2023

Convolutional neural network-based deep learning technology is the most commonly used in image identification, but it requires large-scale data for training. Therefore, application in specific fields in which data acquisition is limited, such as in the military, may be challenging. In particular, the identification of ground weapon systems is a very important mission, and high identification accuracy is required. Accordingly, various studies have been conducted to achieve high performance using small-scale data. Among them, the ensemble method, which achieves excellent performance through the prediction average of the pre-trained models, is the most representative method; however, it requires considerable time and effort to find the optimal combination of ensemble models. In addition, there is a performance limitation in the prediction results obtained by using an ensemble method. Furthermore, it is difficult to obtain the ensemble effect using models with imbalanced classification accuracies. In this paper, we propose a transfer learning-based feature fusion technique for heterogeneous models that extracts and fuses features of pre-trained heterogeneous models and finally, fine-tunes hyperparameters of the fully connected layer to improve the classification accuracy. The experimental results of this study indicate that it is possible to overcome the limitations of the existing ensemble methods by improving the classification accuracy through feature fusion between heterogeneous models based on transfer learning.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.245-250
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• 2005

With rapid development of Internet, new paradigm creation requirement about the education environment and method is increasing and also the e-learning to apply traditional education industry was introduced in many field of education. The research about a learner's satisfaction of the e-learning, aided by effort to spread this e-learning, have been processed much but most of these researches were intended for the enterprise and there are few for the high school. Therefore, in this study we proposed a model for evaluating the education satisfaction of the e-learning and analyzed the consciousness structure about the e-learning education satisfaction of the high school students using Fuzzy Structural Modeling method. Also, constructing an evaluation model considered the results of consciousness structure analysis, we evaluated the e-learning education satisfaction and showed a method which improved it by the sensitivity analysis.

• Journal of Korean Dental Hygiene Science
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• v.1 no.2
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• pp.21-39
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• 2018

The purpose of this study was to examine the learning competencies of students at a college from September 1 to November 30, 2017, in an effort to provide some information on how to foster learning competencies in college years, which lay the foundation for work and social lives. 1. The learning competencies of the subjects consisted of academic vision, student identity, cognitive regulation, emotional regulation, learning management and creating learning environments. Out of five points, they scored the highest in academic vision and student identity with 3.34, followed by learning management with 3.20, creating learning environments with 3.18, emotional regulation with 3.16 and cognitive regulation with 3.14. 2. There were statistically significant differences in academic vision according to age, the area of major, the academic credential of their fathers, commuting time, military service experience and career plans. 3. There were statistically significant differences in student identity and cognitive regulation according to gender, age, the area of major, the academic credential of their fathers, commuting time, military service experience and career plans. 4. There were statistically significant differences in emotional regulation according to age, the area of major, the academic credential of their fathers, commuting time, career plans and daily mean study hours. 5. There were statistically significant differences in learning management according to gender, age, the area of major, grade point average, the academic credential of their fathers, career plans and daily mean study hours. 6. There were statistically significant differences in creating learning environments according to gender, age, the area of major, the academic credential of fathers, commuting time, career plans and daily mean study hours. As they were poorest at the cognitive regulation area among the areas of learning competencies, self-directed learning programs that deal with how to study, learning process, how to take notes and arrange them, how to link different pieces of acquired knowledge and how to map out study plans should be developed to give support to students.

• Communications of Mathematical Education
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• v.27 no.4
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• pp.407-428
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• 2013

The purpose of this research is to develop an effective teaching-learning model and suggest efficient methods for improving the learning abilities in mathematics of the students of engineering college. For this purpose, we examined their learning styles and learning attitudes toward Mathematics, which are important factors in teaching-learning process, and analyzed the relation between them. As a result, we found that participants had a disposition of being dependent and highly participating, so we made an effort to develop a teaching-learning model which can make the students active and highly involved in. After applying the developed teaching-learning model to Engineering Mathematics class for one semester, we conducted survey of the participants' responses. In conclusion, we found that this model is very helpful for Engineering students to utilize a self-directed learning by diagnosing and adjusting their learning process in Meta-cognitive way. Also, it is confirmed that this model has a considerable influence in which students can actively participate in class and have positive attitude to Mathematics learning.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.135-139
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• 2001

There has been a study about the effective multimedia education using a computer following the appearance of a virtual space. Also, there has been an effort to connect the information & communication technology with education. The popular on-line lecture systems are mostly on English lecture sites. However, they just offer the VOD(Video On Demand) services ignoring students' convenience. To improve these week points, we design and implement the multimedia leaching system focusing on an efficient repeat-effect in order that students can control the Media Player by clicking a sentence on a web page. This paper presents the Editor and Player considering students' interest and the effective learning fruits. So users can easily make multimedia materials and use them to improve their English listening skill.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.1029-1034
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• 2006

In this paper, the tracking control of an automatic pipe cutting robot, called APCROM, with a magnetic binder is studied. Using magnetic force APCROM, a wheeled robot, binds itself to the pipe and executes unmanned cutting process. The gravity effect on the movement of APCROM varies as it rotates around the pipe laid in the gravitational field. In addition to the varying gravity effect other types of nonlinear disturbances including backlash in the driving system and the slip between the wheels of APCROM and the pipe also cause degradation in the cutting process. To maintain a constant velocity and consistent cutting performance, the authors adopt a repetitive learning controller (MRLC), which learns the required effort to cancel the tracking errors. An angular-position estimation method based on the MEMS-type accelerometer is also used in conjunction with MRLC to compensate the tracking error caused by slip at the wheels. Experimental results verify the effectiveness of the proposed control scheme.

• Journal of the Korean Society for Library and Information Science
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• v.5
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• pp.1-30
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• 1978

The libraries of the various learning institutes in the Yi Dynasty may be categorized into four types: 1) The Hyang-Gyo library(the public school libraries in rural districts) 2) The Sabu-Hankdang library (the public school libraries in the Capital) 3) The $S\bar{o}w\bar{o}n$ library (the libraries of private learning institutes) 4) The $Jyon-Gy\bar{o}ng-Gak$ library (the library of the Sung Kyun Kwan which was the highest learning institute in the Yi Dynasty) For the historical study of Korean libraries as well as its education and culture the Hyang-Gyo libraries hold an very important position, but undeservedly its study has been neglected. In this paper, the writer made an effort to grasp the various function of the Hyang-Gyo libraries with its historical background.

• Research in Mathematical Education
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• v.6 no.2
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• pp.159-170
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• 2002

The undergraduate curriculum in differential equations has undergone important changes in favor of the visual and numerical aspects of the course primarily because of recent technological advances. Yet, research findings that have analyzed students' thinking and understanding in a reformed setting are still lacking. This paper discusses an ongoing developmental research effort to adapt the instructional design perspective of Realistic Mathematics Education (RME) to the teaching and learning of differential equations at Ewha Womans University. The RME theory based on the design heuristic using context problems and modeling was developed for primary school mathematics. However, the analysis of this study indicates that a RME design for a differential equations course can be successfully adapted to the university level.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.