• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.57-69
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• 2017

Due to the development of technology even in learning and education area, many studies have begun to make a new attempts to research by using SNS, breaking away from traditional learning methods. However, the limitations of these studies are restricted only to the use of wireless Internet and writing on Web sites. This study aims to conduct a research on English learning activities that utilize various technologies such as Bigdata, Facebook, Social Network Services (SNS) and English applications. In addition, this study looks into how these modern technologies can be integrated in the classrooms and which activities can be applied in the English classroom. This research is to suggest effective English learning methods through a thorough investigation on the effectivity of various technologies based on the Web 2.0 such as Flickr, blogs, MySpace, and online discussion board within the context of the English learning. To verify the effect of the study, the subjects are divided into experimental and control group. The experiment is proceeded with pre- and post-test. The experimental group is designed to verify the effects using SNS tools such as Facebook, Bigdata, and Online Massive Learning. A survey is conducted to determine the preference of utilizing social networking sites and to analyze the effects in class. The result is that the average scores for experimental group have improved more than the average of control group. The comparison of pre and post-test of the experimental group shows that the significance of the higher and median group was statistically significant at the p<0.01.

• ETRI Journal
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• v.44 no.5
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.

• Journal of the Korean School Mathematics Society
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• v.6 no.2
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• pp.71-85
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• 2003

In this paper we study the usefulness of Maple in school calculus education. The use of computer and calculator is debated in many aspect in mathematics education. By the computer visualization of mathematical image and proper use of computer we can teach inductively and intuitively the mathematical concept and give rise to the students' interest. Maple is very popular in college but is not in middle school because of language. Maple application which is made by Maplet is very useful multimedia teaching-learning tools. We introduce the use of Maplet and some application of the calculus course which we made.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.654-656
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• 1998

This paper presents an optimal identification method of nonlinear and complex system that is based on fuzzy-neural network(FNN). The FNN used simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM Algorithm to find initial parameters of membership function. And then to obtain optimal parameters, we use the genetic algorithm. Genetic algorithm is a random search algorithm which can find the global optimum without converging to local optimum. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance of the FNN, we use the time series data for 9as furnace and the sewage treatment process.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.75-79
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• 2021

The article covered theoretical aspects use of information and communication technologies in teaching. Information and communication technologies are technologies that allow you to search, process and assimilate information from various sources, including the Internet. This is the presentation of information in electronic form, its processing and storage, the use of the computer, a variety of programs. The use of information and communication technologies in the work of a student gives an increase in motivation for learning; increased cognitive interest; evaluate their learning activities, identify the problems of their own educational activities; the formation of cognitive independence of students.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.534-540
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• 1993

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algrithms need a special perfect position sensor or a priori information about error sources, while ours does not. To our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterative learning algorithm does not have the drawbacks of the existing iterative learning control theories. To be more specific, our algorithm learns a uncertain function inself rather than its special time-trajectory and does not request the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• Journal of Engineering Education Research
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• v.25 no.5
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• pp.75-84
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• 2022

In the post-Corona era, blended learning will be one of the most important instructional strategies for successful education. The purpose of this study is to examine reliability and validity of the instrument developed in the instructional aspect so that a successful blended learning can take place. This instrument consists of 31 items to evaluate class operation, online learning environment, online contents, offline class, interaction and overall satisfaction. For this study, a survey was conducted in LMS and the responses of 164 students were used for analysis. Confirmatory factor analysis was used to evaluate validation of this instrument and this analysis was run in R studio. As a result of CFA, the standardized factor loadings of all items were 0.930~0.754 and the reliability and validity of all constructs were adequate. The results of this instrument enable universities to manage the quality of their classes and instructors can use them as self-checklist to improve future classes in terms of instructional points. Finally, this instrument can be used in a variety of learner-centered learning environments.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.91-102
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• 2018

The purpose of this study was to identify the variables that influence the intention of students to continue participating in SW education. Based on the TAM and reference to existing research on IT introduction, subjective norms, activity promotion conditions, programming related self-efficacy, perceived easy of use, and perceived usefulness were set as factors. We also tried to identify the structural causality between these factors and the intention to continue learning. The samples of this study were 204 elementary students participating in SW education. We collected our data by conducting web survey with these students for 1 month. Among the eight hypotheses set out in this study, the two hypotheses 'subjective norms will have a positive (+) effect on perceived ease of use' and 'perceived ease of use will have a positive (+) effect on Learning continuation intention' were rejected. The characteristics of the results are as follows. First, perceived ease of use indirectly influences learning intention through mediation of perceived usefulness. Second, in order to increase the intention of continuing learning, programming self-efficacy proved to be the most significant factor. The results of this study suggest that the usefulness of SW education and the programming self-efficacy of students should be improved for effective support of elementary school students' SW education.

• Journal of Gifted/Talented Education
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• v.25 no.6
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• pp.905-926
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• 2015

This study examined differences among high, medium, and low achievers' motivation, self-regulation strategy, and learning style in an online gifted program. The sample included 788 middle and high school students who participated in the 3-months online gifted program. Participants volunteerly completed 60 questions on their motivation, self-regulation strategy use, and learning style. Multivariate analysis of variance(MANOVA) was conducted for data analysis using SPSS 19.0. The results of this study showed that (1) as levels of students' achievement increased, levels of intrinsic motivation increased as well; (2) statistically significant differences also existed on the levels of elaboration strategy, effort management, and time management strategy use among three levels of achievement and (3) no significant differences in students' learning style preference were found between competitive or cooperative learning style. To sum up, high achieving students' levels of intrinsic motivation, elaboration strategy, effort management strategy, and time management strategy use were the highest compared to medium and low achieving students.

• International Journal of Costume and Fashion
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• v.17 no.1
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• pp.1-15
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• 2017

This study made use of a qualitative approach with an intrinsic case study to explore how handheld devices applications were integrated in teaching and learning in Textiles, Clothing and Design programmes. Participants of the study were purposively sampled from the Textiles and Clothing department at a selected university of Science and Technology in Zimbabwe comprising eight lecturers and thirty-two students. In-depth, focus group interviews and observations were used to gather data for the study. The findings of the study showed that participants were still at the stage of actively experimenting with very limited handheld device applications for the purposes of teaching and learning. Photoediters and digital cameras were the commonest applications used in most modules of the Textiles, Clothing and Design programmes. Though the photoediters and digital cameras were found to match the multimedia category of the Functionality framework, these were not fully utilised by students. It was recommended that there is need for the Textiles, Clothing and Design lecturers to provide opportunities for students to use a variety of applications on handheld devices for collaborative designing in practical modules of the programmes as these can encourage the development of critical skills necessary for creating innovative textiles and fashion designs.