• Title/Summary/Keyword: intelligent approach

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PC based Open Architecture Machine Controller for Intelligent Manufacturing system (지능생산시스템을 위한 PC 기반 개방형 머신제어기)

  • Park, Kyung-Su;Choi, Kyung-Hyun;Lee, Seok-Hee
    • Proceedings of the KSME Conference
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    • 2000.04a
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    • pp.884-889
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    • 2000
  • This paper describes the design and implementation of PCOAMC(PC-based Open Architecture Machine Controller) to be flexible and independent from the vendor-oriented hardware and software structure. This openness approach is able to enhance an intelligence and integration of a manufacturing system. The development methodology of PcOAMC is an Object-Oriented approach, and all modules in PcOAMC are modelled using UML(Unified Modelling Language) that provides an easy understanding and modification. In order to demonstrate an applicability of PcOAMC, a simple test has been executed by using the Client-Server system consisting of two PcOAMCS and bus monitoring system. The good results have been obtained, so that the developed controller is expected to be embedded into IMS(Intelligent Manufacturing System) as a basic unit.

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Inter-Conversion Matrix for Transcoding Block DCT and DWT-Based Compressed Images

  • Kim, Donggyun;Lim, Sanghee;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.3
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    • pp.103-109
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    • 2014
  • This study derived the inter-conversion matrices, which can be used in heterogeneous image transcoding between the compressed images using different transforms, such as the $8{\times}8$ block discrete cosine transform (BDCT) and the one-level discrete wavelet transform (DWT). Basically, to obtain the one-level DWT coefficients from $8{\times}8$ BDCT, inverse BDCT should be performed followed by forward DWT, and vice versa. On the other hand, if the proposed interconversion approach is used, only one inter-conversion matrix multiplication makes the corresponding transcoding possible. Both theoretical and experimental analyses showed that the amount of computation of the proposed approach decreases over 20% when the inter-conversion matrices are used under specific conditions.

Current Mirror-Based Approach to the Integration of CMOS Fuzzy Logic Functions

  • Patyra, Marek J.;Lemaitre, Laurent;Mlynek, Daniel
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.785-788
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    • 1993
  • This paper presents the prototype framework for automated integration of CMOS current-mode fuzzy logic circuits using an intelligent module approach. The library of modules representing the standard fuzzy logic operators was built. These modules were finally used to synthesized sophisticated fuzzy logic units. Fuzzy unit designs were made based upon the results of a newel methodology of the current mirror-based fuzzy logic function synthesis. This methodology is actually incorporated into the presented framework. As an example, the membership function unit was synthesized, simulated, and the final layout was generated using the presented framework. Finally, the fuzzy logic controller unit (FLC) was generated using the proposed framework. Simulation as well as measurement results show unquestionable advantages of the proposed fuzzy logic function integration system over the classical design methodology with respect to the area, relative error and performance.

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A Study on Kohenen Network based on Path Determination for Efficient Moving Trajectory on Mobile Robot

  • Jin, Tae-Seok;Tack, HanHo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.2
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    • pp.101-106
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    • 2010
  • We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

Multi-classifier Fusion Based Facial Expression Recognition Approach

  • Jia, Xibin;Zhang, Yanhua;Powers, David;Ali, Humayra Binte
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.1
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    • pp.196-212
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    • 2014
  • Facial expression recognition is an important part in emotional interaction between human and machine. This paper proposes a facial expression recognition approach based on multi-classifier fusion with stacking algorithm. The kappa-error diagram is employed in base-level classifiers selection, which gains insights about which individual classifier has the better recognition performance and how diverse among them to help improve the recognition accuracy rate by fusing the complementary functions. In order to avoid the influence of the chance factor caused by guessing in algorithm evaluation and get more reliable awareness of algorithm performance, kappa and informedness besides accuracy are utilized as measure criteria in the comparison experiments. To verify the effectiveness of our approach, two public databases are used in the experiments. The experiment results show that compared with individual classifier and two other typical ensemble methods, our proposed stacked ensemble system does recognize facial expression more accurately with less standard deviation. It overcomes the individual classifier's bias and achieves more reliable recognition results.

Fuzzy Decision Making System

  • Karpovsky, Ephim Ja
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.806-809
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    • 1993
  • This paper focuses on the usage of the fuzzy set theory in decision making systems. The approach to calculation of generalized membership function, based on application of method of principal components is proposed. For solving of the problem of fuzzy forecasting the development of Bayes procedure is used. The structure of decision making system, in which following procedures are fulfilled, is discussed.

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FUZZY CHOICE IN DESIGN OF THE COMPLEX SYSTEMS.

  • Belov, Y.;Matsuoka, K.;Shafranskiy, S.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1301-1304
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    • 1993
  • The base of proposed decomposing approach is multilevel process of agregation (simplificative transformation) of the description of the project structures. The new classification of fuzzy choice operators is suggested to obtain the decomposing correlations.

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The ξ-Quality Defuzzification Method

  • Hans, Hellendoorn;Christoph, Thomas
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1159-1162
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    • 1993
  • We describe six important defuzzification methods and their respective merits and shortcomings, dependent on the rules, domains, etc. Furthermore, we present an alternative approach, the so called ξ-Quality defuzzification method, for the case that the output fuzzy sets have different shape or are asymmetric.

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