• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.345-365
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• 2020

At present, many machine leaning and data mining methods are used for analyzing and predicting structural response characteristics. However, the platform that combines big data analysis methods with online and offline analysis modules has not been used in actual projects. This work is dedicated to developing a multifunctional Hadoop-Spark big data platform for bridges to monitor and evaluate the serviceability based on structural health monitoring system. It realizes rapid processing, analysis and storage of collected health monitoring data. The platform contains offline computing and online analysis modules, using Hadoop-Spark environment. Hadoop provides the overall framework and storage subsystem for big data platform, while Spark is used for online computing. Finally, the big data Hadoop-Spark platform computational performance is verified through several actual analysis tasks. Experiments show the Hadoop-Spark big data platform has good fault tolerance, scalability and online analysis performance. It can meet the daily analysis requirements of 5s/time for one bridge and 40s/time for 100 bridges.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.139-145
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• 2020

Due to the rapid development of computer technology, online learning using ICT technology is already quickly settling in our lives. Music education was conducted mainly in an offline-based environment, but research is being conducted to switch to online because there is no time and space constraint of online education and interactive education led by learners is possible. In this study, we propose design and implement an adaptive learning system to enable adaptive learning online among music education. This system has the following advantages. First, by providing an LMS-based platform, one can solve the social education problem corresponding to economic and geographical factors. Second, both objective learning feedback provided automatically by the online adaptive harmony learning system and teaching feedback. Third, learners can be provided with recommended answers to given harmony exercises. The adaptive online learning system of harmony will lead professors and learners to effectively teach and study.

• Journal of Korea Game Society
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• v.5 no.4
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• pp.13-22
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• 2005

The research is a study on the effects of MMORPG (Massively Multi-player Online Role Playing Game) utilized in educational program. We investigated the possibilities of online game as an educational tool, especially in the field of economy education. Students have been taught market, price, profit, scarcity of goods etc., and then they played an online game we provided. Students manufactured cyber goods and also sold or bought various materials to maximize their profits. A experimental group was compared with a control group on measures of economic self-efficacy, motivation for economic learning, and attitude for economic learning, economic self-efficacy and motivation for economic leaning scales consist of 2 factors and attitude for economic leaning consists of 1 factor. Participants were 5th grade elementary school students(experimental group: 154, control group: 158). After the experiment, students' self-efficacy and motivations for economy learning have increased significantly. It has been found that students understand more easily the difficult economic terms such as' inflation', 'price setting', 'scarcity of goods etc. Their motivations for economy learning also increased significantly. This result indicates that online games have the potentiality that can be utilized as an educational tool.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.344-355
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• 2002

Having a variety of good characteristics against other pattern recognition techniques, Multilayer Perceptron (MLP) has been used in wide applications. But, it is known that Error Backpropagation (EBP) algorithm which MLP uses in learning has a defect that requires relatively long leaning time. Because learning data in pattern recognition contain abundant redundancies, in order to increase learning speed it is very effective to use online-based teaming methods, which update parameters of MLP pattern by pattern. Typical online EBP algorithm applies fixed learning rate for each update of parameters. Though a large amount of speedup with online EBP can be obtained by choosing an appropriate fixed rate, fixing the rate leads to the problem that the algorithm cannot respond effectively to different leaning phases as the phases change and the learning pattern areas vary. To solve this problem, this paper defines learning as three phases and proposes a Instant Learning by Varying Rate and Skipping (ILVRS) method to reflect only necessary patterns when learning phases change. The basic concept of ILVRS is as follows. To discriminate and use necessary patterns which change as learning proceeds, (1) ILVRS uses a variable learning rate which is an error calculated from each pattern and is suppressed within a proper range, and (2) ILVRS bypasses unnecessary patterns in loaming phases. In this paper, an experimentation is conducted for speaker verification as an application of pattern recognition, and the results are presented to verify the performance of ILVRS.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.989-998
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• 2013

We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.544-553
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• 2005

In this paper, the research has been done to develop the inclination test items to form the desirable online learning community in which social interaction may be maximized, dropout rate lowered and learners' feeling of isolation eliminated. Once developed, the inclination test items have been classified into homogeneous ones and heterogeneous ones. And on the basis of the results of this research, Intelligent agent based Inclination Test Grouping e-learning System(IIGS) has been developed, which can perform automatic grouping of online leaning community by intelligent agent. The results of this research with 1,000 teachers in reality by means of developing the grouping system have shown that 151 groups are automatically formed. Among them, 34% have shown very high degree of learning satisfaction and intended to maintain the groups in the future.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.368-369
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• 2011

This article suggests an online-based remote fault current mode discrimination method in order to identify the causes of the power line faults with various causes. For that, it refers to existing cause identification methods and categorizes modes by fault causes based on statistical techniques beforehand and performs the pretreatment process of fault currents by each cause acquired from the fault recorder into a topological plane in order to extract the characteristics of fault currents by each cause. After that, for the fault mode categorization, it discriminates modes by each cause using data by each cause as leaning data through utilizing RBF network based on FCM allowing self-organization in deciding the middle layer. And then it tests the validity of the suggested method as applying it to the data of the actual fault currents acquired from the fault recorder in the electric power transmission center.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.86-88
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• 2009

This article suggests an online-based remote fault current mode discrimination method in order to identify the causes of the power line faults with various causes. For that, it refers to existing cause identification methods and categorizes modes by fault causes based on statistical techniques beforehand and performs the pre-treatment process of fault currents by each cause acquired from the fault recorder into a phase space in order to extract the characteristics of fault currents by each cause. After that, for the fault mode categorization, it discriminates modes by each cause using data by each cause as leaning data through utilizing RBF network. And then it tests the validity of the suggested method as applying it to the data of the actual fault currents acquired from the fault recorder in the electric power transmission center.

• Research in Mathematical Education
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• v.15 no.2
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• pp.141-158
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• 2011

In recent years, an increasing number of viewpoints hold that students should be engaged in a learning environment where understanding and knowledge transfer take place. This study introduces Mathematics Created by You (MCY)-mentoring program, which allows students to construct artefacts that are required to learn. This program is online-based and so can be shared by several people and mathematics leaning takes place through interactions within this carefully designed environment. Also, MCY intends to provide students a series of sequential activities related to creative play, creative learning and creative inquiry based on a Constructive and interactive environment. Furthermore, a creative activity- constructing a creative product using building blocks- was presented as an example. Finally, we investigate the pedagogical implications and suggest directions for the further development.

• Educational Technology International
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• v.6 no.2
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• pp.59-67
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• 2005

The primary purposes of this study are to develop a Situated Learning Support System based on an MMORPG (Massively Multiplayer Online Role Playing Game) and to investigate applications of Situated Learning theory both hypothetically and practically. In Situated Leaning theory, cognition is interpreted as a dynamic system related to situation, context and activity. According to this theory, learning context, social interaction and personal direct experience are also emphasized. A virtual reality learning system based on an MMORPG provides context, social interaction and a learning environment able to provide direct experiences. However, such a system has been difficult for teachers to develop. This study aims to develop a support system facilitating the construction of a Situated Learning System based on an MMORPG. This study proposes new research and practical applications of Situated Learning theory using educational games.