• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.569-572
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• 2010

맞춤형 이러닝은 학습효과의 증진을 위한 방안으로 개인 맞춤형, 개인화 혹은 적응화 등의 개념이 제안되고 확장되었다. 본 논문에서는 초기 선호도, 흥미도 혹은 검색습관을 고려하는 방식으로부터, 특정한 학습객체를 자율 선택하여 반복 학습할 수 있도록 개념단위를 적용한 방식, 학습자의 능력을 고려한 최적 난이도 학습객체를 제공하는 방식 등 다양하게 제안되고 있는 현대적 개인 맞춤형 이러닝 체계들을 비교 분석한다. 개별 시스템에 따라 '평가'에 국한되거나 '평가'와 '학습'을 연계하는 경우가 존재하며, 이에 따른 적용에 의하여 학습환경과 맞춤형 제공방식 및 학습효과를 상호 연계할 수 있음을 밝힌다.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.53-62
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• 2013

In cloud robotics, the model to share information efficiently is still a research challenge. This paper presents an information sharing model for cloud-enabled robots to collaborate and share intelligence. To provide the efficient message dissemination, an adaptive group communication based on multi-agent is proposed. The proposed algorithm uses a weight function for the link nodes to determine the significant links. The performance evaluation showed that the proposed algorithm produced minimal message overhead and was faster to answer queries because of the significant links compared to traditional group communication methods.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.441-449
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• 2007

In video coding, motion estimation is a process to estimate the pixel of the current frame from the reference frame, which affects directly the predictive quality and the encoding time. This paper is related to AHHS(Adaptive Hierarchical Hexagon Search) using spatio-temporal motion activity for fast motion estimation. The proposed method defines the spatio-temporal motion activity of the current macroblock using the motion vectors of its spatio-temporally adjacent macroblocks, and then conventional AHS(Adaptive Hexagon Search) is performed if the spatio-temporal motion activity is lower, otherwise, hierarchical hexagon search is performed on a multi-layered hierarchical space constructed by multiple sub-images with low frequency in wavelet transform. In the paper, based on computer simulation results for multiple video sequences with different motion characteristics, the performance of the proposed method was analysed and assessed in terms of the predictive quality and the computational time. Experimental results indicate that the proposed method is both suitable for (quasi-) stationary and large motion searches. The proposed method could keep the merit of the adaptive hexagon search capable of fast estimating motion vectors and also adaptively reduce the local minima occurred in the video sequences with higher spatio-temporal motion activity.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.8
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• pp.421-431
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• 2004

This paper presents adaptive execution techniques that determine whether parallelized loops are executed in parallel or sequentially in order to maximize performance. The adaptation and performance estimation algorithms are implemented in a compiler preprocessor. The preprocessor inserts code that automatically determines at compile-time or at run-time the way the parallelized loops are executed. Using a set of standard numerical applications written in Fortran77 and running them with our techniques on a distributed shared memory multiprocessor machine (SGI Origin2000), we obtain the performance of our techniques, on average, 26%, 20%, 16%, and 10% faster than the original parallel program on 32, 16, 8, and 4 processors, respectively. One of the applications runs even more than twice faster than its original parallel version on 32 processors.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1161-1167
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• 2006

본 논문에서는 구조, 행위, 리소스, 환경의 여러 관점을 적용한 다양한 모델들을 이용하는 적응 프레임워크를 제안한다. 또한, 대상 시스템에 대해 앞에서 언급한 4 가지 모델을 위한 모델링 방법론과 각 모델링 요소들에 대한 효과적인 표기법을 제시하였다. 다양한 모델들을 통해 시스템의 구성 요소들 간의 관계 구조와 시스템의 계층적 상태와 행위 정보, 실행 환경을 구성하는 시스템 의존적인 요소 및 독립적인 요소까지의 정보들이 표현된다. 이들 모델간의 유기적인 상호 운용으로 통합적인 추론과 보다 정확한 평가가 가능하다. 이를 통해 시스템은 예상치 못한 변화에 대해 통합된 관점의 더욱 정확한 진단과 반영할 수 있다. 이를 기반으로 다양한 수준에서 적응 동작의 조절을 수행함으로써 하이브리드하고 보다 확장된 적응이 가능해진다. 논문에서 정의한 모델과 제안 프레임워크는 다른 도메인으로 재사용이 가능하다. 제안 시스템은 평가를 위해 프로토타입을 구현하여 원격 화상 회의 시스템에 적용하였으며, 그 기능과 유효성을 확인하였다.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.121-135
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• 2003

This paper proposes a web-based adaptive tutoring system based on fuzzy set that provides learning materials and questions dynamically according to students' knowledge state, and gives advices for the learning after an evaluation. For this, we design a courseware knowledge structure systematically and then construct a fuzzy level set on the basis of it considering importance of learning targets, difficulty of learning materials and relation degree between learning targets and learning materials. Using the fuzzy level set, our system offers learning materials and questions to adapt to individual students. Moreover, a result of the test is evaluated with fuzzy linguistic variable. Appling the fuzzy concept to the tutoring system could naturally consider and deal with various and uncertain items of learning environment thus could offer more flexible and effective instruction-learning methods.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.455-463
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• 2003

Adaptive noise cancellation techniques are ideally suitable for reducing spatially varying noise due to the grain structure of material in ultrasonic nondestructive evaluation. Grain noises have an un-correlation property, while flaw echoes are correlated. Thus, adaptive filtering algorithms use the correlation properties of signals to enhance the signal-to-noise ratio (SNR) of the output signal. In this paper, a multi-stage adaptive noise cancellation (MANC) method using adaptive least mean square error (LMSE) filter for enhancing flaw detection in ultrasonic signals is proposed.

• Journal of the Korea Society of Computer and Information
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• v.9 no.3
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• pp.115-120
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• 2004

As a part of working on development of the learning management system, a adaptive learning management system which is able to provide individual learner with different learning contents or paths customized to learner's learning behaviors by expanding SCORM was proposed in this dissertation. In terms of instructional technology interrelated with technology of CBI and ITS, new learning environments and learner preferences were analyzed. A related laboratory system was implemented by packaging a process on how to expand the meta data for contents and a process on how to utilize the web-based learning contents dynamically. In order to evaluate the usability of the implemented system, a sample content was provided to some selected learners and their learning achievement resulted from the new learning environment was analysed. A result of the experiment indicated that the adaptive learning management system proposed in this dissertation could provide every learner with the different content tailored to their individual learning preference and behavior. and it worked also to promote the learning performance of every learner.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2511-2520
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• 2011

This paper describes the parameter adjustment method of fuzzy membership function to improve the performance of multi-sensor fusion system using adaptive fuzzy-Kalman filter and cross-validation. The adaptive fuzzy-Kanlman filter has two input parameters, variation of accelerometer measurements and residual error of Kalman filter. The filter estimates system noise R and measurement noise Q, then changes the Kalman gain. To evaluate proposed adaptive fuzzy-Kalman filter, we make the two-axis AHRS(Attitude Heading Reference System) using fusion of an accelerometer and a gyro sensor. Then we verified its performance by comparing to NAV420CA-100 to be used in various fields of airborne, marine and land applications.

• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.33-40
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• 2008

In this paper, we propose a method to enhance adaptability in a dialogue system using the reinforcement learning that reduces response errors by trials and error-search similar to a human dialogue process. The adaptive dialogue strategy means that the dialogue system improves users' satisfaction and dialogue efficiency by loaming users' dialogue styles. To apply the reinforcement learning to the dialogue system, we use a main-dialogue span and sub-dialogue spans as the mathematic application units, and evaluate system usability by using features; success or failure, completion time, and error rate in sub-dialogue and the satisfaction in main-dialogue. In addition, we classify users' groups into beginners and experts to increase users' convenience in training steps. Then, we apply reinforcement learning policies according to users' groups. In the experiments, we evaluated the performance of the proposed method on the individual reinforcement learning policy and group's reinforcement learning policy.