• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.309-313
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• 2002

This paper presents an artificial intelligent model for a soccer robot. We classified soccer robot as artificial intelligent model into three elemental groups including instinct intuition and reason. Instinct is responsible for keeping the ball, walking or rushing toward the ball. This is very simple fundamental action without regard to associates and enemies. Intuition contributes to the faster/slower moving and simple basic turning to get near to the ball and to make a goal noticing associates and enemies. Reason is the most intelligent part, the law of reason is not simple relatively with instinct and intuition. We shall expect to design the best law of reason for a soccer robot some time. We also compared nerve system and muscles of human being model with controller and motors of a physical soccer robot model individually. We had designed several algorithms and made programs to investigate effects and control soccer robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.975-978
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• 2003

This paper presents an artificial intelligent model for a soccer robot. We classified soccer robot as artificial intelligent model into three elemental groups as instinct, intuition, reason. Instinct is responsible for keeping the ball, driving or rushing toward the ball. This is very simple fundamental action without regard to associates and enemies. Intuition contributes to the fast/slow moving and simple basic turing to get near to the ball and to make a goal noticing associates and enemies. Reason is the most intelligent part. The law of reason is not simple relatively with instinct and intuition. We also compared nerve system and muscles of human being model with controller and motor of physical soccer robot model individually. We had designed several algorithms and made programs th investigate effects and control soccer robot.

• Structural Engineering and Mechanics
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• v.45 no.5
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• pp.693-702
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• 2013

Recently, artificial intelligence tools are most used for structural engineering and mechanics. In order to predict reserve prices and prices of awards, this study proposed a novel regression prediction model by the intelligent Kalman filtering method. An artificial intelligent multiple regression model was established using categorized data and then a prediction model using intelligent Kalman filtering. The rather precise construction bid price model was selected for the purpose of increasing the probability to win bids in the simulation example.

• Journal of Fisheries and Marine Sciences Education
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• v.20 no.3
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• pp.462-472
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• 2008

Education is a field that has tried to make use of the advantages of computers since they were introduced to the world. Intelligent Tutoring System and multimedia have become methods of teaching students of Computer Science, Education, Psychology, and Cognitive Science. Until now, they have been designed and produced only on the basis of a very specific domain and format. However, in the education field, most learners ask for integrated service that is practical, realizable, and sensitive to technological change. Therefore, in this study, we would like to present the technological and formal integration model as an ITS model which acknowledges changes in the fields of technology and education. As a technological integration model, the integration model of traditional Symbolic Artificial Intelligence and Artificial Neural Networks was presented. As a formal integration model, three integration models were presented according to (a) the process of learning diagnosis (b) learners' action behaviors (c) intelligence service respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.259-265
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• 2006

Learning and emotions are very important parts to implement intelligent robots. In this paper, we implement intelligent virtual character based on reinforcement learning which interacts with user and have internal emotion model. Virtual character acts autonomously in 3D virtual environment by internal state. And user can learn virtual character specific behaviors by repeated directions. Mouse gesture is used to perceive such directions based on artificial neural network. Emotion-Mood-Personality model is proposed to express emotions. And we examine the change of emotion and learning behaviors when virtual character interact with user.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.217-242
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• 2022

With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.513-516
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• 2003

In this paper, we designed a Artificial Life(AL) that acts the appropriate actions according to the user's action, environments and AL's feeling. To realize this AL, we used the Markov Model. We consisted of the chromosome by Markov Model and obtained the appropriate actions by Genetic Algorithm.

• Journal of Christian Education in Korea
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• v.66
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• pp.309-341
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• 2021

The purpose of this study is to develop an intelligent learning platform model for faith education in preparation for the post-corona era. This study reviewed artificial intelligence algorithms, research on learning platform development, and prior research related to faith education. The draft of the intelligent learning platform design model was developed by synthesizing previous studies. The developed draft model was validated by a Delphi survey targeting 5 experts. The content validity of the developed draft model was all 1. This is the validation of the draft model. Three revised opinions of experts were presented on the model. And the model was revised to reflect the opinions of experts. The modified final model consisted of three areas: learning materials, learning activities, learning data, and artificial intelligence. Each area is composed of 9 elements of curriculum, learning content additional learning resources, learner type, learning behavior, evaluation behavior, learner characteristic data, learning activity data, artificial intelligence data, and learning analysis. Each component has 29 sub-elements. In addition, 14 learning floors were formed. The biggest implication of this study is the first development of a basic model of an intelligent learning platform for faith education.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.79-89
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• 1993

This paper deals with a computer aided control of an adjustment process for the complete electronic devices by means of an application of artificial neural network and an implementation of neuro-controller for intelligent control. Multi-layer neural network model is employed as artificial neural network with the learning method of the error back propagation. Information initially available from real plant under control are the initial values of plant output, and the augmented plant input and its corresponding plant output at that time. For the intelligent control of adjustment process utilizing artificial neural network, the neural network emulator (NNE) and the neural network controller(NNC) are developed. The initial weights of each neural network are determined through off line learning for the given product and it is also employed to cope with environments of the another product by on line learning. Computer simulation, as well as the application to the real situation of proposed intelligent control system is investigated.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.90-96
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• 2004

A generalized net model of a training process with modified fuzzy marks in answers of the trained objects and their current and total modified fuzzy evaluation, tharning themes, estimation criteria and others are discussed and interpreted.