• Journal of the Korean Society for Library and Information Science
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• v.32 no.2
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• pp.259-276
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• 1998

This study is to contribute to develop adaptive information systems meeting inside information needs as well as represented information needs, and dealing with every levels of users and user's preferences. Also, this study is to present a method of developing adaptive information system through developing user profile using machine teaming and decision tree, applying relevance feedback using merged vector, and applying user feedback.

• Journal of the Korean Institute of Educational Facilities
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• v.14 no.4
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• pp.14-24
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• 2007

Recently, there are three major trends in building school facilities by government. First trend is to reconstruct facilities that have been built for 30 years. Second is the creation of a new town, new construction demanded from the redeveloping area. Finally, third is to build educational convenience facilities such as gymnasium, auditorium and cafeteria etc. When building or reconstructing school facilities, it is important to consider the 7th Education curriculum. The purpose of this study is to propose the guide line of the planning the dimension of Science Laboratory in in elementary school, corresponding to teaming contents and method.

• Journal of the Korean School Mathematics Society
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• v.4 no.2
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• pp.125-134
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• 2001

It is necessary that at any rate we try to decrease underachievers by learning deficiency in mathematics to extreme limits under circumstances that mathematics becomes more requisite daily in the 21st century's informative society. However, the traditional teaching method causes a lot of problems in elevating the needed ability for the newly changing society. Accordingly, for the purpose of letting underachievers by learning deficiency have much interest in mathematics, seek the qualitative elevation, have the feelings of self-confidence and accomplishments, escape from desperation, and also teachers choose the activities of small groups, design teaching plans, apply those to teaching-learning activities and finally verify the effect, this researcher sets up a hypothesis as follows: 1. The teaching method through small groups will be effective for the accomplishments of underachievers in mathematics. 2. Its method will bring out the meaningful change in the emotional areas of mathematics. Therefore, so as to prove the above hypothesis, the results through the theoretical approach and practicing teaming by small groups have turned out to be positive.

• Journal of Families and Better Life
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• v.25 no.6
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• pp.71-82
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• 2007

On this research we investigated variables affecting university students' time management and verify relationship between the time management and life satisfaction. 438 students at Korea National Open University in Seoul were questioned through questionnaires composed of 47 questions. Data was analyzed by t-test, one-way ANOVA, Duncan's multiple range test and Person's correlation. The variables affecting time management were religion(those who believe in organized religion vs. those who do not), individual income, family income, teaming experiences for time management and reading books related to time management. fender, age, marriage status and occupation didn't affect the time management of students. The relationships between time management and life satisfaction showed a little positive relation. Some proposals for future researches and practices are given.

• Journal of Digital Convergence
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• v.6 no.3
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• pp.13-22
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• 2008

The purpose of this study is to explore 'Flow Experience' of those studying English speaking and listening in the e-Learning environment. The exploration of flow experience in this study is based on the literature research of Csikszentmihalyi's flow models and other studies. There have been many studies on flow experience focusing on arts, leisure and sports in accordance with Csikszentmihalyi's original theory, however, his flow theory has recently been adapted to the educational field. Nonetheless, it is in the e-learning environment, rather than the face-to-face traditional teaming environment, that there is not enough flow state measurement scale. Therefore, it is important to develop as a stepping stone a flow state scale for those who study English speaking and listening by the cyber-native-speaker on e-Learning environment to improve their satisfaction and achievement.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.284-295
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• 2003

The servo tracks of disk drives are constructed at the time of manufacture with the equipment of servo track writer. Because of the imperfection of servo track writer, disk vibrations and head fluctuations during servo track writing process, the constructed servo tracks might deviate from perfect circles and take eccentric shapes. The servo track writing error should be corrected because it might cause interference with adjacent tracks and irrecoverable operation error of disk drives. The servo track writing error is repeated every disk rotation and so is periodic time function. In this paper, we propose a new correction algorithm of servo track writing error based on iterative teaming approach. Our correction algorithm can learn iteratively the servo track writing error as accurately as is desired. Furthermore, our algorithm is robust to system model errors, is computationally simple, and has fast convergence rate. In order to demonstrate the generality and practical use of our work, we present the convergence analysis of our correction algorithm and some simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.95-104
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• 1999

In this paper we propose a fast and precise control algorithm for a mobile robot, which aims at the self-tuning control applying two multi-layered neural networks to the structure of computed torque method. Through this algorithm, the nonlinear terms of external disturbance caused by variable task environments and dynamic model errors are estimated and compensated in real time by a long term neural network which has long learning period to extract the non-linearity globally. A short term neural network which has short teaming period is also used for determining optimal gains of PID compensator in order to come over the high frequency disturbance which is not known a priori, as well as to maintain the stability. To justify the global effectiveness of this algorithm where each of the long term and short term neural networks has its own functions, simulations are peformed. This algorithm can also be utilized to come over the serious shortcoming of neural networks, i.e., inefficiency in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.12
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• pp.1023-1030
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• 2002

Since the dynamics of autonomous underwater vehicles (AUVs) are highly nonlinear and their hydrodynamic coefficients vary with different vehicle's operating conditions, high performance control systems of AUVs are needed to have the capacities of teaming and adapting to the variations of the vehicle's dynamics. In this paper, a linearly parameterized neural network (LPNN) is used to approximate the uncertainties of the vehicle dynamics, where the basis function vector of the network is constructed according to the vehicle's physical properties. The network's reconstruction errors and the disturbances in the vehicle dynamics are assumed be bounded although the bound may be unknown. To attenuate this unknown bounded uncertainty, a certain estimation scheme for this unknown bound is introduced combined with a sliding mode scheme. The proposed controller is proven to guarantee that all signals in the closed-loop system are uniformly ultimately bounded (UUB). Numerical simulation studies are performed to illustrate the effectiveness of the proposed control scheme.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.265-268
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• 2001

This paper proposes the strategy of noise injection into inputs in the Kohonen learning algorithm (KKA) to improve the local convergence problem of the KLA. Noise strengths are high in the begin of the learning and gradually lowered as the teaming proceeds. This strategy is a kind of stochastic relaxation (SR) method which is broadly used in the general optimization problems. It is convenient to implement and improves the convergence properties of the KLA with moderately increased computing time compared to the KLA. Experimental results for Gauss-Markov sources and real speech demonstrate that the proposed method can consistently provide better codebooks than the KLA.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.9-12
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• 2001

Learning vector quantization (LVQ) is a supervised learning technique that uses class information to move the vector quantizer slightly, so as to improve the quality of the classifier decision regions. In this paper we propose a selection method of initial codebook vectors for a teaming vector quantization (LVQ3) using support vector machines (SVM). The method is experimented with artificial and real design data sets and compared with conventional methods of the condensed nearest neighbor (CNN) and its modifications (mCNN). From the experiments, it is discovered that the proposed method produces higher performance than the conventional ones and then it could be used efficiently for designing nonparametric classifiers.