• Journal of Industrial Technology
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• v.17
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• pp.323-330
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• 1997

In this paper, a new approach to modeling of nonlinear systems using fuzzy theory is presented. To express the various and complex behavior of nonlinear system, we combine multiple model method with hierachical prioritized structure, and the mountain clustering technique is used in partitioning of system. TSK rule structure is adopted to form the fuzzy rules, and Back propagation algorithm is used for learning parameters in consequent parts of the rules. Also we soften the paradigm of Mamdani's inference mechanism by using Yager's S-OWA operators. Computer simulations are performed to verify the effectiveness of the proposed method.

• Journal of IKEEE
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• v.16 no.3
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• pp.197-202
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• 2012

As more and more cores are integrated on a single chip, power consumption has become an important problem in system-on-a-chip (SoC) design. Multiple supply voltage (MSV) design is one of popular solutions to reduce power consumption. We propose a new method that determines voltage level of cores before floorplanning stage. Besides, our algorithm includes a new approach to optimize wire length and the number of level shifters without any significant decrease of power saving. In simulation, we achieved 40-52% power saving and a considerable improvement in runtime, whereas an increase in wire length and area is less than 8%.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.625-637
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• 2015

We develop a Bayesian clustering procedure based on a Dirichlet process prior with cluster specific random effects. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet process was implemented to calculate posterior probabilities when the number of clusters was unknown. Our approach (unlike its counterparts) provides simultaneous partitioning and parameter estimation with the computation of the classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. We find that the proposed Dirichlet process mixture model with cluster specific random effects detects clusters sensitively by combining vague edges into different clusters. Examples are given to show how these models perform on real data.

• Journal of Soil and Groundwater Environment
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• v.8 no.3
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• pp.8-12
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• 2003

The centrifuge test result on capped sediment was compared to the advection- dispersion equation proposed for one layered to predict contaminant transport parameters. The fitted contaminant transport parameters for the centrifuge test results were one to three orders of magnitude greater than the estimated parameters from the advection-dispersion equation. This indicates that the centrifuge model over estimated the contaminant transport phenomena. Thus, the centrifuge provides a non-conservative approach to modeling contaminant transport. It should be also noted that the advection-dispersion equation used in this study is a one layered model. Two layered modeling approaches are more appropriate for modeling this data since there are two layers with different partitioning coefficients. Further research is required to model the centrifuge test using two-layered advection-dispersion models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.330-333
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• 2003

Initial cluster size for clustering of partitioning methods is very important to the clustering result. In K-means algorithm, the result of cluster analysis becomes different with optimal cluster size K. Usually, the initial cluster size is determined by prior and subjective information. Sometimes this may not be optimal. Now, more objective method is needed to solve this problem. In our research, we propose a hybrid genetic algorithm, a tree induction based evolution algorithm, for determination of optimal cluster size. Initial population of this algorithm is determined by the number of terminal nodes of tree induction. From the initial population based on decision tree, our optimal cluster size is generated. The fitness function of ours is defined an inverse of dissimilarity measure. And the bagging approach is used for saying computational time cost.

• Journal of Microbiology and Biotechnology
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• v.12 no.4
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• pp.535-543
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• 2002

Although the generic implementation of aqueous two-phase systems (ATPS) processes for the recovery of biological products has been exploited for several years, this has not resulted in a wide adoption of the technique. The main reasons involve the poor understanding of the mechanism governing phase formation and the behavior of solute partitioning in ATPS processes, the cost of phase forming polymers, and the necessary extended time to optimize the technique. In this review paper, some of the practical disadvantages attributed to ATPS are addressed. The practical approach exploited to design ATPS processes, the application to achieve process integration, the extended use for the recovery of high-value products, and the recent development of new low-cost ATPS, are discussed. It is proposed that the trend of the practical application of ATPS processes for the recovery of biological products will involve the purification of new high-value bioparticulate products with medical applications. Such a trend will give new impetus to the technique, and will draw attention from industries needing to develop new, and improve existing, commercial processes.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.457-480
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• 2017

We develop a random partition procedure based on a Dirichlet process prior with Laplace distribution. Gibbs sampling of a Laplace mixture of linear mixed regressions with a Dirichlet process is implemented as a random partition model when the number of clusters is unknown. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities, unlike its counterparts. A full Gibbs-sampling algorithm is developed for an efficient Markov chain Monte Carlo posterior computation. The proposed method is illustrated with simulated data and one real data of the energy efficiency of Tsanas and Xifara (Energy and Buildings, 49, 560-567, 2012).

• Journal of the Korean Professional Engineers Association
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• v.20 no.1
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• pp.14-20
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• 1987

The development of the FHT (fast Hadamard transform) was presented and based on the derivation by Cooley-Tukey algorithm. Alternately, it can be derived by matrix partitioning or matrix factorization techniques. This paper proposes a simple sparse matrix technique by Kronecker product of successive lower Hadamard matrix. The following shows how the Kronecker product can be mathematically defined and efficiently implemented using a matrix factorization methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.891-899
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• 2015

This paper presents the robust stability condition of uncertain Takagi-Sugeno(T-S) fuzzy systems with time-varying delay. New augmented Lyapunov-Krasovskii function is constructed to ensure that the system with time-varying delay is globally asymptotically stable. Also, less conservative delay-dependent stability criteria are obtained by employing some integral inequality, reciprocally convex approach and new delay-partitioning method. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1542-1550
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• 2013

This paper presents new results on delay-dependent global exponential stability for uncertain linear systems with interval time-varying delay. Based on Lyapunov-Krasovskii functional approach, some novel delay-dependent stability criteria are derived in terms of linear matrix inequalities (LMIs) involving the minimum and maximum delay bounds. By using delay-partitioning method and the lower bound lemma, less conservative results are obtained with fewer decision variables than the existing ones. Numerical examples are given to illustrate the usefulness and effectiveness of the proposed method.