• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.107-113
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• 2001

This paper deals with speed control of DC servo motor using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm. Conventionally a PID controller has been used in the industrial control. But a PID controller should produce suitable parameters for each system. Also, variables of the PID controller should be changed according to environments, disturbances and loads. In this paper described by a experiment that contained a method using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm, we developed speed characteristics of a DC servo motor on variable loads. The parameters of the controller are determined by neural network performed on on-line system after training the neural network on off-line system.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.4
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• pp.87-94
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• 1999

This paper presents a study on the off-line handwritten Hangul (Korean) character recognition using the partially connected neural network (PCNN), which is based on partial connections between the input receptive fields and the hidden nodes. The hidden nodes of three PCNNs have ten receptive fields and different input feature sets. And we introduce modular partially connected neural network (MPCNN), The MPCNN combines three PCNNs with a merging network. The learning scheme of the proposed networks is composed of two steps: PCNN learning step and the merging step of combining three PCNN s. In the merging step, another merging PCNN network is introduced and trained by regarding the hidden output of each PCNN as a new input feature vector. The performance of the proposed classifier is verified on the recognition of 18 off-line handwritten Hangul characters widely used in business cards in Korea.

• Educational Technology International
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• v.7 no.2
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• pp.23-44
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• 2006

As the educational paradigm has shifted from the traditional knowledge oriented instruction learning to the knowledge product oriented instructional learning, the development of student's creativity becomes one of the most important educational goals, because the ability that can produce the knowledge creatively is required in the digital information knowledge based society. The purpose of this study is to make a basic direction and strategy for the instructional design to develop an on and off line blended instructional design which will help a learning community to be a more collaborative and creative learning community. This research has investigated the concept and the characteristics of collaborative creativity and creative problem solving as the theoretical basis of the design. After that, on the basis of the theories connected with the collaborative creativity theory, the direction and the strategies for the development of collaborative creativity was designed. The design was applied into the real learning community and finally proved the effectiveness of the learning model for the development of the collaborative creativity by the quantitative evaluation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.95-98
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• 2003

In this paper, an adaptive fuzzy neural control of unknown nonlinear systems based on the rapid learning algorithm is proposed for optimal parameterization. We combine the advantages of fuzzy control and neural network techniques to develop an adaptive fuzzy control system for updating nonlinear parameters of controller. The Fuzzy Neural Network(FNN), which is constructed by an equivalent four-layer connectionist network, is able to learn to control a process by updating the membership functions. The free parameters of the AFN controller are adjusted on-line according to the control law and adaptive law for the purpose of controlling the plant track a given trajectory and it's initial values are off-line preprocessing, In order to improve the convergence of the learning process, we propose a rapid learning algorithm which combines the error back-propagation algorithm with Aitken's $\delta$$\^$2/ algorithm. The heart of this approach ls to reduce the computational burden during the FNN learning process and to improve convergence speed. The simulation results for nonlinear plant demonstrate the control effectiveness of the proposed system for optimal parameterization.

• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.227-232
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• 2011

Individualized instruction only in the off-line classroom is not enough because elementary school students have various levels and tendencies. In recent years there are a lot of efforts to use online learning, and they are valuable. But the current online learning management systems are not utilized effectively in the elementary school. So this study suggests utilization plan of online learning management system through Moodle which can present and perform both learning objectives and learning contents for individualized instruction in elementary schools.

• 한국IT서비스학회:학술대회논문집
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• 2003.11a
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• pp.63-69
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• 2003

국내 교육시장은 매우 규모가 큰 사업이며 인터넷의 발달로 인해 교육시장에도 새로운 형태의 교육방식이 등장하고 있는 추세이다. e-Learning의 도입은 기존의 off-Line 교육시장에 새로운 변화를 일으키고 있다. 하지만 현재 국내에 e-Learning시장이 도입된 시기에 비해 그 발전 속도는 매우 더딘 상황이다. 따라서 본고에서는 교육시장개방을 앞두고 현재 국내 교육시장 중 사교육비 절감의 대안으로 떠오르고 있는 e-Learning시장의 현재 환경을 분석하고 e-Learning시장을 활성화 시킬 수 있는 방안을 살펴본다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.376-379
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• 2000

In this paper, this system makes use of the analog infrered rays sensor and converts the feature of fish analog signal when sensor is operating with CPU(80C196KC). Then, After signal processing, this feature is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error backpropagation is used as a learning algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long time when random initial weights are used, off-line learning is induced to decrease the progress time. We confirmed this method has better performance than somewhat outdated machines.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.464-470
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• 2018

With the introduction of the e-learning since 2000, the place of the education has not been limited to off-line, but the range of it has become broader in online. The e-learning market has evolved steadily over time. With the advent of the term "Edu-tech", which means a combination of education and technology, various IT technologies have incorporated education. Particularly, the Korean education market collects patterns by computerizing the learning history in classes taught according to curriculums. Because of that environment, various personalized learning services have been developed which maximize the effect of the learning. These services have qualitative differences depending on how many data is accumulated and algorithms are developed for the precise analysis. The purpose of this study is to recognize and data-ize OMR marking by the most suitable method to convert analog data into digital data without harming the Korean education system.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.724-729
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• 2001

This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.8
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• pp.766-771
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• 2005

In this study, PD(partial discharge) signals which occur at stator coil of traction Motor are acquired these data are used for classifying the PD sources. NN(neural network) has recently applied to classify the PD pattern. The PD data are used for the learning process to classify PD sources. The PD data come from normal specimen and defective specimens such as internal void discharges, slot discharges and surface discharges. PD distribution parameters are calculated from a set of the data, which is used to realize diagnostic algorithm. NN which applies distribution parameters is useful to classify the PD patterns of defective sources generating in stator coil of traction motor.