• The Journal of Information Systems
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• v.17 no.1
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• pp.83-111
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• 2008

The purpose of this study is to identify which factors are important for learning performance and the moderating effects of self-regulated factors such as elaboration and organization between users characteristic(perceived usefulness, preparatory education, internet experience) and learning performance. To Accomplish these research purpose, this study performed a survey and 173 response were used for statistical analysis. The results of this study are as follows: First, 7 factors(ease of use, interactivity, accuracy, media richness, perceived usefulness, preparatory education, internet experience) had significant impacts on learning performance whereas reliability did not. Second, the moderating effects of self-regulated factors showed that Elaboration of self-regulated factors can be considered as a significant moderating variable between 2 factors(perceived usefulness, internet experience) and teaming performance.

• The Journal of Information Systems
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• v.17 no.3
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• pp.1-24
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• 2008

This study empirically investigated the relationships among inter-organizational contextual factors(assets specificity, long-term orientation and interdependence), information exchange between trading partners, inter-organizational loaming and trust, and inter-organizational performance. In this study, types of information exchanged between trading firms are classified into two broad kinds: transaction information and management information. from empirical results, we found that inter-organizational contextual factors have a greater positive impact on the exchange of management information. It is also observed that the exchange of information positively influences inter-organizational trust and loaming. finally, the results of this study showed that inter-organizational trust and teaming have positive effects on the improvement of inter-organizational performance. Thus, it is concluded that the amount of information exchanged according to the conditions of inter-organizational contextual factors gives rise to inter-organizational teaming and high levels of trust, and high levels of trust and learning contribute to the increase of inter-organizational performance.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.47-61
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• 2001

Lazy loaming methods including CBR have relative advantages in comparison with eager loaming methods such as artificial neural networks and decision trees. However, they are very sensitive to irrelevant features. In other words, when there are irrelevant features, larry learning methods have difficulty in comparing cases. Therefore, their performance can be degraded significantly. To overcome this disadvantage, feature weighting methods for lazy loaming methods have been studied. Most of the existing researches, however, were focused on global feature weighting. In this research, we propose a new local feature weighting method, which we shall call CBDFW. CBDFW stores classification performance of randomly generated feature weight vectors. Then, given a new query case, CBDFW retrieves the successful feature weight vectors and designs a feature weight vector fur the query case. In the test on credit evaluation domain, CBDFW showed better classification accuracy when compared to the results of previous researches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.381-384
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• 2006

Self Organizing Map(SOM) is a powerful neural network model for unsupervised loaming. In many clustering works with exploratory data analysis, it has been popularly used. But it has a weakness which is the poorly theoretical base. A lot more researches for settling the problem have been published. Also, our paper proposes a method to overcome the drawback of SOM. As compared with the presented researches, our method has a different approach to solve the problem. So, a hybrid SOM is proposed in this paper. Using Monte Carlo computing, a hybrid SOM improves the performance of clustering. We verify the improved performance of a hybrid SOM according to the experimental results using UCI machine loaming repository. In addition to, the number of clusters is determined by our hybrid SOM.

• Education of Primary School Mathematics
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• v.3 no.1
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• pp.37-45
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• 1999

This paper investigates the comparative effectiveness of two kinds of instructional methods in transfer of mathematics learning: one based on the situated cognition, ie. situated learning and the other based on traditional learning. Two classes of second graders studied the instruction about 3-digit addition and subtraction. After that, they completed two written tests and a real situation test. As a result. no significant differences were found between the two group's performance on the written test 1 and real situation test. But the situated learning group performed significantly better on the performance of story problem than traditional group. This result indicated that the situated learning made improvement in transfer of mathematic loaming. As a result of interviews with 12 children, the situated loaming group's children were able to use contextual resources in solving real situation as well as story problems.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.464-470
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• 2004

We propose an enhanced backpropagation algorithm by auto-tuning of learning rate using fuzzy control system for performance improvement of backpropagation algorithm. We propose two methods, which improve local minima and loaming times problem. First, if absolute value of difference between target and actual output value is smaller than $\varepsilon$ or the same, we define it as correctness. And if bigger than $\varepsilon$, we define it as incorrectness. Second, instead of choosing a fixed learning rate, the proposed method is used to dynamically adjust learning rate using fuzzy control system. The inputs of fuzzy control system are number of correctness and incorrectness, and the output is the Loaming rate. For the evaluation of performance of the proposed method, we applied the XOR problem and numeral patterns classification The experimentation results showed that the proposed method has improved the performance compared to the conventional backpropagatiot the backpropagation with momentum, and the Jacob's delta-bar-delta method.

• Journal of the Korean Professional Engineers Association
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• v.29 no.2
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• pp.71-79
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• 1996

This paper evaluates the clustering performance of a neural network and a statistical method. Algorithms which are used in this paper are the GLVQ(Generalized Loaming vector Quantization) for a neural method and the k -means algorithm for a statistical clustering method. For comparison of two methods, we calculate the Rand's c statistics. As a result, the mean of c value obtained with the GLVQ is higher than that obtained with the k -means algorithm, while standard deviation of c value is lower. Experimental data sets were the Fisher's IRIS data and patterns extracted from handwritten numerals.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.994-998
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• 1996

We propose an approach to integrating fuzzy logic control with RBF(Radial Basis Function) networks and show how the integrated network can be applied to multivariable self-organizing and self-learning fuzzy controller. Using the hybrid learning algorithm. To investigate its usefulness and performance, this controller is applied to a time-delayed process system. Simulation results show good control performance and fast convergency in hybrid loaming method.

• The Mathematical Education
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• v.40 no.1
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• pp.67-75
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• 2001

Since performance assessment was introduced in Korea in the middle of 1990, many problems which include its definition, characters, methods and scorings etc., raised in mathematics education worlds. Therefore this paper presents the theoretical background of performance assessment in mathematics education. Contemporary teaching and loaming theories reject stimulus-response theory which emphasizes outcome. Performance assessment emphasizes the assessment which reveal learning process and various strategies. And it bases on constructivism and socio-cultural perspective. This paper presents paradigms which guide the roles and purposes of assessment. The paradigms include conventional paradigm, constructivist paradigm and critical paradigm. There is a close correlation between constructivist paradigm and performance assessment. Assessment has to grasp the development of present and the possibility of development of future of the students. Performance assessment must be fixed the new paradigm of education for this purpose.