• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.225-229
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• 1998

If there is a mismatch between the controller programmed rotor time constant and the actual time constant of motor, the decoupling between the flux and torque is lost in an indirect rotor field oriented control. This paper presents a new estimation scheme for rotor time constant using artificial neural networks. The parameters of induction motor model organize 2 layer neural to be weight between neuron, which is proposed new in this paper. This method makes networks simple, so its brings not only the improvement in speed but simplification in calculation. Furthermore, it is possible to estimated rotor time constant real time through on-line learning without using off-line learning. The digital simulation and the experimental results to verify the effectiveness of the new method are described in this paper.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.406-408
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• 1997

This paper presents the new method of a nondestructive spot welding state inspection system using neural networks. The learning process of neural networks makes the inspection system to adapt the variable welding parameters. The inspecting process is working with on-line real-time after off-line learning process. This neural network based inspection system shows reliable results through the field test for variations of applied voltages, currents, and contact area of the welding electrode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.888-894
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• 2010

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase and more efficient and accurate methods have been studied. This paper proposes a bayesian algorithm for wireless fingerprinting and indoor location determination using fuzzy clustering with bayesian learning as a statistical learning theory.

• Asia pacific journal of information systems
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• v.16 no.4
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• pp.179-202
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• 2006

The objective of this study is to identify the impacts of communication reinforcement on performance of learning in Web-PBL. Communication reinforcement is defined as the combination of information sharing and co-construction. As factors facilitating communication reinforcement, we propose learner's characteristics, task characteristics, and group characteristics. Learner's characteristics are collaboration-orientation, openness, holistic approach, and online community-orientation which reflects e-learning environment. Collaboration-oriented tasks as group projects were developed and given to groups with 5-6 members. The group characteristics are categorized into 'horizontal' and 'vertical', according to the patterns of communication between a group leader and members. To verify empirically the proposed research model, an experimental design was performed to learners who took on-line and off-line courses with group projects. We found important results as follows; First, field dependence has positive impacts on information sharing, and online community-orientation has positive impacts on co-construction. These results correspond with prior studies on relationship between field dependence and collaborative learning. Second, collaboration-oriented task directly impacts on information sharing, and indirectly affects co-construction, This result implicates that information sharing is pre-requisite of co-construction. Third, 'horizontal' was identified as a factor giving positive effects on information sharing and co-construction. This result implies that horizontal communication is very important to facilitate communication reinforcement.

• School Mathematics
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• v.18 no.3
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• pp.479-501
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• 2016

This study was conducted as a learning project for 20 pre-third graders in high school by means of math textbooks, G+, and sample questions from previous CSAT as learning tools for 9 weeks from Dec. 24, 2015. The purpose of the study was to develop 'math textbook project learning(MtPL)', a mixed learning method combined on-line with off-line, and analyze the effects of MtPL on the affective domain of high school students. As a result of the study, it was found that MtPL had positive effects on self-efficacy and self-confidence of students, while the collaborative learning using a textbook and teacher's role worked as instrumental motivation in mathematics learning. The result also implies that the perception of high school students, who think to resolve more difficult math problems to succeed in CSAT, about mathematics learning method has to be modified. Furthermore, it is shown that the preparation of CSAT by utilizing textbook and the use of textbook in math learning have been worked positively for the students.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.991-1000
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• 1994

To control nonlinear systems adaptively, we improve learning speed of neural networks and present a novel control algorithm characterized by compensation of control inputs. In an error-backpropagation algorithm for tranining multilayer neural networks(MLNN's) the effect of the slope of activation functions on learning performance is investigated and the learning speed of neural networks is improved by auto-adjusting the slope of activation functions. The control system is composed of two MLNN's, one for control and the other for identification, with the weights initialized by off-line training. The control algoritm is modified by a control strategy which compensates the control error induced by the indentification error. Computer simulations show that the proposed control algorithm is efficient in controlling a nonlinear system with abruptly changing parameters.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.176-183
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• 2006

A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.214-225
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• 2001

This research deals with an off-line learning method targeted for systematically constructing negotiation strategies in automated electronic commerce. Single-issue negotiation is assumed. Variants of competitive learning and hierarchical clustering method are devised and applied to extracting negotiation strategies, given historical negotiation data set and tactics. Our research is motivated by the following fact: evidence from both theoretical analysis and observations of human interaction shows that if decision makers have prior knowledge on the behaviors of opponents from negotiation, the overall payoff would increase. Simulation-based experiments convinced us that the proposed method is more effective than human negotiation in terms of the ratio of negotiation settlement and resulting payoff.

• The Journal of Information Systems
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• v.17 no.4
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• pp.31-49
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• 2008

As the development of information technology, the biggest change in educational paradigm is apparent in the shift that the emphasis of education is layed on from teachers to learners. E-learning education service through the internet is less restricted in the respect of time and places in comparison with off-line education. Therefore e-Learning is spreaded rapidly and the educational effectiveness of that is needed to be investigated. In this study theoretical research was performed firstly and framework of the study was constructed. After establishment of hypotheses the survey data were collected by the learners of e-Learning and the hypotheses were verified by the SPSS version 12.0. The results are as follows : First, the quality of e-Learning service influences significantly to the technology acceptance of users. Secondly, perceived usability and perceived easiness of technology acceptance model influences significantly to the intention of reuse of users of e-Learning services. Lastly, the playfulness of the Flow theory influences significantly to the intention of reuse of users of e-Learning services. Although there are some limitations in the respect of the numbers of variables, parameters, or samples, this study will contribute for enhancing the effectiveness of education in e-Learning service by providing the acceptance factors of e-learners.

• Journal of Digital Contents Society
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• v.12 no.1
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• pp.123-131
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• 2011

The purpose of this study is to discover if the use of computer technologies in computer-assisted language learning, in the aspect of vocabulary learning, is both effective and useful. The technique of using multimedia lessons, using the computer, offers a variety of language learning tasks in relation to the four basic language learning skills. Korean students have been accustomed to a cramming style of education, and they utilize rote memorization for learning vocabulary. This study consisted of surveys and experiments, using specific multimedia language learning courseware exercises on three different age groups. The study explores the issues and problems that followed, and how teachers could effectively apply or enhance their vocabulary teaching through computer-assisted multimedia which is suited for a variety of levels versus the classroom off-line vocabulary learning application which is suited to one level.