• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.141-144
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• 1997

This paper presents a method of navigation sign recognition in indoor environments using a fuzzy inference for an autonomous mobile robot. In order to adapt to image deformation of a navigation sign resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The DASM is proposed to detect correct feature points among incorrect feature points. Finally sugeno-style fuzzy inference are adopted for recognizing the navigation sign.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.21-31
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• 1996

An intelligent integrated control system is designed for the active steering and the left/right traction force distribution control of electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additively utilized for the estimator to correctly find cornering forece. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.1
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• pp.76-89
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• 1993

The evaluation of the Fuzzy Expected Value (FEV) as a typical value requires complete knowledge about the domain of the evaluation, and the distribution of the population in that domain [1]. Since in many situations it is not possible to gather complete knowledge regarding the domain, it is necessary to relax some of the restrictions involving the evaluation of FEV. In this paper we discuss solutions to this problem by using the concept of the Fuzzy Expected Interval (FEI).

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.86-91
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• 2006

Companies had to be more intelligent in order to survive in the rapidly changing environments. We need to make a decision to build the Information System to support their decision making. But, how can we know the new system would be better than the old system in making us intelligent? The answer is we can do it with the concept of Intelligence Density. In this study, Intelligence Density concept will be introduced, and the way how it can be applied to the information system will be presented. I think Intelligence Density should be studiedmoretohelpmanagersmakerightdecisions.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.127-133
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• 2016

In this paper, an intelligent dimming control system is designed and implemented with the human visual response function using CDS sensor, PIR sensor and temperature sensor, etc. The proposed system is designed to detect a moving object by PIR sensor and to control the LED dimming considering the human visual response. Also, the dimming of LED light can modulate on the app, and simultaneously control dimming in real-world environments with smart phone app. A high-temperature warning or a fire hazard information is transmitted to user's smart phone according to sensor values and Data graph are provided as part of data visualization. Connecting the hardware controller, the proposed intelligent smart dimming control system is expected to contribute to the power reduction interior LED, smart grid building and saving home combining with internet of things.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.531-534
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• 2003

In this paper, the Intelligent Space (iSpace) concept is applied for helping disabled or blind persons in crowded environments such as train stations, or airports. The main contribution of this paper is a general mathematical (fuzzy-neuro) description of obstacle avoidance method (walking habit) of moving objects (human beings) in a limited area scanned by the iSpace. A mobile robot with extended functions is introduced as a Mobile Assistant Robot which is assisted by the iSpace. The Mobile Assistant Robot (MAR) can guide and protect a blind person in a crowded environment with the help of the Intelligent Space. The prototype of the Mobile Assistant Robot and simulations of some basic types of obstacle avoidance method (walking habit) are presented.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.61-69
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• 2007

In this paper, we developed not only a reliable sound localization system including a VAD(Voice Activity Detection) component using three microphones but also a face tracking system using a vision camera. Moreover, we proposed a way to integrate three systems in the human-robot interaction to compensate errors in the localization of a speaker and to reject unnecessary speech or noise signals entering from undesired directions effectively. For the purpose of verifying our system's performances, we installed the proposed audio-visual system in a prototype robot, called IROBAA(Intelligent ROBot for Active Audition), and demonstrated how to integrate the audio-visual system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.49-53
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• 2010

e-learning and m-learning have some problems that data transmission frequently discontinuously, communication cost increases, the computation speed of mass data drops, battery limitation in the mobile learning environments. In this paper, we propose the PULIMS for u-learning systems. The proposed system intellectualize the education environment using intelligent mobile agent, supports the customized education service, and helps that learners feasible access to the education information through mobile phone. We can see the fact that the efficience of proposed method is outperformed that of the conventional methods. The PULIMS is new technology that can be used to learn whenever and wherever learners want in Ubiquitous education environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.293-298
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• 2006

In this paper, a sensor fusion based robot navigation method for the autonomous control of a miniature human interaction robot is presented. The method of navigation blends the optimality of the Fuzzy Neural Network(FNN) based control algorithm with the capabilities in expressing knowledge and learning of the networked Intelligent Robotic Space(IRS). States of robot and IR space, for examples, the distance between the mobile robot and obstacles and the velocity of mobile robot, are used as the inputs of fuzzy logic controller. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a sensor fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process. Preliminary experiment and results are shown to demonstrate the merit of the introduced navigation control algorithm.