• Education of Primary School Mathematics
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• v.14 no.2
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• pp.135-145
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• 2011

When mathematicians solve the new problems, they present the solutions to their colleagues for getting the approval. If the solution is accepted, it will be theorems. This phenomenon also happens to classrooms in elementary and secondary school. That is main reason to emphasize mathematical communication activities in mathematics education. This study is aimed to develop teaching and learning model for the improvement of mathematical communication ability, applicate the teaching and learning model to two groups and analyze for mathematical thoughts. This study is a case study of 3rd grader's activities. Eight students, four are group applied the teaching and learning model and four are traditional group. The results have been drawn as follows: First, students in the teaching and learning model group induced richer interactions for student's understanding and investigation when we compare to those of traditional group. Second, students in the teaching and learning model group have the chance to explain their thoughts. And we can observe students to clear on their thought through speaking and discussing. This model makes students to enhance organizing, forming and clearing in their mathematical thoughts and is effective to estimate of students thought for teacher.

• Journal of radiological science and technology
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• v.30 no.3
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• pp.197-203
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• 2007

The education of radiological technology in Korea is provided lots of information but are low effectiveness of studying due to attach importance to traditional lecture preparing for the national exam of radiological technologist. With a critique about traditional education, a new method of teaching, PBL(Problem based learning) can meet with the workplace through problems and see the real world of occupation objectively taking part in a self-directed learning and cooperative discussion process. And when become a radiological technologist as a member of current society can build up solving problems and ability of communicative competence. We suggest problem-based learning for the education of radiological technologist, hope to see make for cultivating radiological technologist of ability and improve the quality of education.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2070-2079
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• 1997

In this paper, we proposed the FNCAC (fuzzy neural call admission control) scheme of the ATM networks which used the benefits of fuzzy logic controller and the learning abilities of the neural network to solve the call admission control problems. The new call in ATM networks is connected if QoS(quality of service) of the current calls is not affected due to the connection of a new call. The neural network CAC(call admission control) system is predictable system because the neural network is able to learn by the input/output pattern. We applied the fuzzy inference on the learning rate and momentum constant for improving the learning speed of the fuzzy neural network. The excellence of the proposed algorithm was verified using measurement of learning numbers in the traditional neural network method and fuzzy neural network method by simulation. We found that the learning speed of the FNCAC based on the fuzzy learning rules is 5 times faster than that of the CAC method based on the traditional neural network theory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.147-152
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• 2023

This paper is a study of a linear algebra course taught in a high school on-demand course. Compared to the regular course, flipped learning was added to the course, and applications to signal processing related problems were covered in consideration of students' career aspirations. Overall, the class was a mixture of traditional lectures and flipped learning. Flipped learning was implemented twice. The flipped class consisted of pre-class, in-class and post-class. To verify the effectiveness of the course, a survey was conducted and most of the evaluation items were above 4. The topics of the flipped learning were Markov chains and least squares problem, which are very important in the field of signal processing.

• Journal of The Korean Association For Science Education
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• v.19 no.2
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• pp.305-314
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• 1999

The effects of three teaching models were compared in this research. One of those is concept change model, another is concept change model based on students learning motivations, the other is traditional teaching method based on science textbooks. The subjects of this research were the 8th grade students of Korean middle school. They were divided into three groups, and tested learning motivations. All of the three groups improved their learning motivations and concept understanding by the classes. Especially, the group of concept change model based on students learning motivations represented most effective improvement of learning motivations. The concept change teaching model and concept change teaching model based on students learning motivations are more effective in concept understanding than traditional teaching method based on textbooks. The students who have high learning motivations improved their concept understanding by the classes of concept change model based on students learning motivations. The students who have low learning motivations improved their learning motivations by the classes of concept change model based on students learning motivations also.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1195-1202
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• 2018

Artificial neural network is widely used for its excellent performance and implementability. However, traditional neural network needs to learn the system from scratch, with the addition of new input data, the variation of the observation environment, or the change in the form of input/output data. To resolve such a problem, the technique of transfer learning has been proposed. Transfer learning constructs a newly developed target system partially updating existing system and hence provides much more efficient learning process. Until now, transfer learning is mainly studied in the field of image processing and is not yet widely employed in acoustic data processing. In this paper, focusing on the scalability of transfer learning, we apply the concept of transfer learning to the problem of guitar chord classification and evaluate its performance. For this purpose, we build a target system of convolutional neutral network (CNN) based 48 guitar chords classification system by applying the concept of transfer learning to a source system of CNN based 24 guitar chords classification system. We show that the system with transfer learning has performance similar to that of conventional system, but it requires only half the learning time.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.297-302
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• 2004

In the information-oriented society, the paradigm of education has changed from the existing traditional teaching-centered education to the learning-centered education. In the Web-based Learning System which an learning-centered educational environment using the internet, students should have responsibility of their learning as taking more opportunities to participate their learning positively, to control their process of learning and to evaluate their learning by themselves to improve self-directed loaming ability. In this paper, the Web-based Learning System with a Self-Study Plan to lead students to select own purposes and methods of the study and write a self_evaluation is developed. The Self-Study Plan is a guide to lead the process, an order to have an individualized study and a report to evaluate own study. In addition, the suggested System is designed through object-oriented method using the extension mechanism of UML to archive the improvement of reuse and maintenance.

• Journal of the Korean Society of Food Culture
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• v.26 no.3
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• pp.249-260
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• 2011

The current research aims to verify whether distance learning can be adopted in practical cooking class for Korean foods in a two-year college. The distance learning education can be a supplementary method to the traditional cooking class. The face-to-face teaching method and the distance learning method were compared in order to determine which of the one is more effective teaching method in the practical cooking class. The results of the present experimental study were analyzed based on the participant's learning expectation and satisfaction, the evaluation of the experimental process, and the academic performance. The results of this study showed that the participants in the face-to-face class evaluated their class experience higher than those in the distance learning class with respect to the participant's learning expectation and satisfaction, and the evaluation of the experimental process. On the contrary, regarding the academic performance, the participants in the distance learning class showed higher scores than those in the face-to-face class. The end result supports the claim that the distance learning method is more effective in the participants for gaining cooking knowledge.