• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.278-283
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• 2010

In this paper, we designed and proposed framework of extended user model to support student tailored learning in ubiquitous environment. For the purpose, existents model that is domain model, user model, adaptation model and interaction model connected to LMS(Learning Management System) and LCMS(Learning Contents Management System). Students information management process that is extended user model is in between LMS and adaptive learning system. And the process connected u-LMS to use u-learning. u-LMS and u-LCMS could support the learning contents through exchange the contents according to connect and request from the students.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.661-667
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• 2010

A lot of existence e-learning are connected SCORM and LMS. And u-learning was researching as one of the new trend. But there are few research paper to connect the existing SCORM and LMS. In this paper, we proposed u-learning framework with connect the SCORM and LMS. And we used the mobile equipment transform module and learning object reconstruction module to apply each different characteristics of mobile equipment. Especially, information of the mobile equipment was stored and managed using the meta-data of the equipment.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.130-135
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• 2006

There have been experiments dealing with the possibility of the actualization of the ANC system by means of operating the DSP adaptation filter. This filter is composed of various filters(including X-LMS algorithm, Filter-U algorithm, and Full-Feedback-Filter-U algorithm) that use ventilation fans and loudspeakers as a primary source in a circular duct as an experimental device. In this operation, the ANC system using the X - LMS algorithm was found to be more effective in reducing noise than without such system. When applying the input signal of the DSP board Full Feedback-Filtered-U algorithm system while having in mind that the additionally installed second control signal was gone through feedback and mixed into the detection microphone installed near the ventilation fan when using the first ventilation fan, the system was not emitted, but maintained stable during the operation of the control filter. At this point, noise tended to decrease at a maximum of l0dB compared to other algorithms at the frequency band of 170-250Hz.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3647-3653
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• 2012

In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.2
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• pp.146-155
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• 2012

The filtered-x LMS(FX-LMS) algorithm has been applied to the active noise control(ANC) system in an acoustic duct. This algorithm is designed based on the FIR(finite impulse response) filter, but it has a slow convergence problem because of a large number of zero coefficients. In order to improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct since the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filtered-u LMS algorithm(FU-LMS) based on infinite impulse response(IIR) is developed by considering the backward acoustic propagation. This algorithm, unfortunately, generally has a stability problem. The stability problem was improved by using an error smoothing filter. In this paper, the recursive LMS algorithm with variable step size and smoothing error filter is designed. This recursive LMS algorithm, called FU-VSSLMS algorithm, uses an IIR filter. With fast convergence and good stability, this algorithm is suitable for the ANC system in a short acoustic duct such as the intake system of an automotive. This algorithm is applied to the ANC system of a short acoustic duct. The disturbance signals used as primary noise source are a sinusoidal signal embedded in white noise and the chirp signal of which the instantaneous frequency is variable. Test results demonstrate that the FU-VSSLMS algorithm has superior convergence performance to the FX-LMS algorithm and FX-LMS algorithm. It is successfully applied to the ANC system in a short duct.

• Convergence Security Journal
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• v.5 no.4
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• pp.33-40
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• 2005

As e-learning studying is activated, learner's requirement increased. Therefore, need correct e-learning model augmented requirement of learner and new ubiquitous surrounding. In this treatise when, proposed to supplement studying contents relationship conversion service and cooperation studying service function to LMS that analyze existing e-learning model's limitation for ubiquitous environment e-learning model that can study regardless of, ubiquitously some contents and do based on SCORM ubiquitous-network and next generation sensor technology etc. Learning form conversion service senses a learner's surrounding situations and recognize his/her body condition using smart sensor technology and provides the learner with contents in the optimal form. Using sensing projects like Orestia and SOB, users can more effective collaborative learning service.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.1-7
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• 2010

Recently, interest in u-learning to pursue effective learning by using ubiquitous environment in teaching and learning activities. In u-learning environment, learners should be able to push necessary information at the right time and the right place. Also calm technology oriented to, and this means that it can recognize learners' terminal information and to provide adaptive interface. In u-learning environment, main learning terminals would be mobile terminals which support mobility. However, learning in the existing PC environment should not be excluded. Thus, by providing adaptive interface according to various learners' terminal in LMS for u-learning, learners are able to learn through consistent and natural learning interface with any computer or any network at any place and at any time. The purpose of this study is to propose the interface adaptation based on terminal information focusing on the layout transformation process in the development environment.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.2
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• pp.3-9
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• 2014

• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.76-81
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• 2012

With the spread of the various mobile devices, the studies on the learning management system based on the u-learning are actively proceeding. The u-learning-based learning management system is very convenient in that there are no restrictions on the various access devices as well as the access time and place. However, the judgments on the authentication for the user and whether learning is focused on are difficult. In this paper, the voice and user face capture interface rather than the common user event oriented interface was applied to the learning management system. When a user is accessing the learning management system, user's registered password is input and login as voice, and the user's learning attitude is judged through the response utterance of simple words during the process of learning through contents. As a result of evaluating the proposed learning management system, the user's learning achievement and concentration were improved, thus enabling the manager to monitor the user's abnormal learning attitude.

• International Journal of Contents
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• v.1 no.2
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• pp.10-12
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• 2005

Along with development of the Internet, education is achieved on-line actively. Therefore, interest about computer aided learning is growing. By a lot of advantages such as expense and time-saving side, this type of learning is widening area gradually. In this paper we discuss some of the learning technology, such as e-learning, m-learning, and u-learning.