• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.512-519
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• 2003

In this paper, we propose a neuro-fuzzy modeling to improve the performance using the hierarchical clustering and Gaussian Mixture Model(GMM). The hierarchical clustering algorithm has a property of producing unique parameters for the given data because it does not use the object function to perform the clustering. After optimizing the obtained parameters using the GMM, we apply them as initial parameters for Adaptive Network-based Fuzzy Inference System. Here, the number of fuzzy rules becomes to the cluster numbers. From this, we can improve the performance index and reduce the number of rules simultaneously. The proposed method is verified by applying to a neuro-fuzzy modeling for Box-Jenkins s gas furnace data and Sugeno's nonlinear system, which yields better results than previous oiles.

• Journal of Global Scholars of Marketing Science
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• v.13
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• pp.135-158
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• 2004

On-line consumers have some visit behavior characteristics when they visit internet-shopping mall between visit-stage and purchase-stage. Therefore, information of on-line consumers have influenced on internet-shopping mall's profitabilities at site manager's perspectives. For examples, Are any on-line consumers continuous visiting under any situations? Or are any on-line consumers purchased on any specific internet-shopping mall? Expecially in this paper, researcher tried to understand visit behavioral characteristics of on-line consumers using two-stage mixture regression analysis. Throughout this process, it could be proposed method, which could be reinforced competitiveness of internet-shopping mall by segmental decision-making method. Additionally, it is expected that visit behavioral characteristics' information could be supplied strategic implications between visit-stage and purchase-stage Throughout empirical test it could be proved two-stage decision-making process, which decision-making process of on-line consumers would be processed visit-stage and purchase-stage. In this study, researcher proposed suitable response strategy after understanding visiting behavioral characteristics of on-line consumers. This paper has some academical contributions, which visit behavioral characteristics of on-line consumers could be grasped the meaning by site stickiness and navigation pattern.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.167-176
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• 2005

This paper describes how the state tying model based on the decision tree which is one of Acoustic models used for speech recognition optimizes the model by reducing the number of mixture Gaussians of the output probability distribution. The state tying modeling uses a finite set of questions which is possible to include the phonological knowledge and the likelihood based decision criteria. And the recognition rate can be improved by increasing the number of mixture Gaussians of the output probability distribution. In this paper, we'll reduce the number of mixture Gaussians at the highest point of recognition rate by clustering the Gaussians. Bhattacharyya and Euclidean method will be used for the distance measure needed when clustering. And after calculating the mean and variance between the pair of lowest distance, the new Gaussians are created. The parameters for the new Gaussians are derived from the parameters of the Gaussians from which it is born. Experiments have been performed using the STOCKNAME (1,680) databases. And the test results show that the proposed method using Bhattacharyya distance measure maintains their recognition rate at $97.2\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. And the method using Euclidean distance measure shows that it maintains the recognition rate at $96.9\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. Then the methods can optimize the state tying model.

• Journal of Marine Life Science
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• v.4 no.2
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• pp.45-52
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• 2019

Polycyclic aromatic hydrocarbons (PAHs) are persistent and commonly detected in marine ecosystem. They coexist with a various contaminants including heavy metals in real environment, but most studies have been still focused on single effects of these contaminants to aquatic organisms. In this study, the single and combined effects of benzy[a]pyrene (B[a]P) and HgCl₂ were investigated in the brackish water flea, Diaphanosoma celebensis. For combined effect study, three mixtures A (3:7), B (5:5), and C (7:3) of benzy[a]pyrene (B[a]P) and HgCl₂ were determined by 48 h - LC₅₀ values of single exposure. Combined effects of both chemicals were estimated by concentration addition (CA) model and independent action (IA) model. As results, 48 h - LC₅₀ values of benzy[a]pyrene (B[a]P) and HgCl₂ was 25.75 ㎍ l^-1 and 3.6 ㎍ l^-1, respectively. TU values of mixture A, B, and C were 1.06, 0.83, and 0.96, respectively, indicating additive effects of mixtures using CA model. This study will be helpful as basic data for understanding the combined effects of contaminants in marine environment.

• MALSORI
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• no.50
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• pp.139-150
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• 2004

A Phonetic Tied-Mixture (PTM) model has been proposed as a way of efficient decoding in large vocabulary continuous speech recognition systems (LVCSR). It has been reported that PTM model shows better performance in decoding than triphones by sharing a set of mixture components among states of the same topological location[5]. In this paper we propose a Phonetic Tied-Mixture Syllable (PTMS) model which extends PTM technique up to syllables. The proposed PTMS model shows 13% enhancement in decoding speed than PTM. In spite of difference in context dependent modeling (PTM : cross-word context dependent modeling, PTMS : word-internal left-phone dependent modeling), the proposed model shows just less than 1% degradation in word accuracy than PTM with the same beam width. With a different beam width, it shows better word accuracy than in PTM at the same or higher speed.

• 한국연소학회:학술대회논문집
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• 2003.12a
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• pp.57-61
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• 2003

In the combustion modeling of non-premixed flames, the mixture fraction conserved scalar approach is widely utilized because reactants are mixed at the molecular level before burning and atomic elements are conserved in chemical reactions. In the mixture fraction approach, combustion process is simplified to a mixing problem and the interaction between chemistry and turbulence could be modelled by many sophisticated combustion models including the flamelet model and CMC. However, most of the mixture fraction approach is restricted to one mixture system. In this study, the flamelet model based on the two-feed system is extended to the multiple fuel-feeding systems by the two mixture fraction conserved scalar approach.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.13-20
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• 2009

Development of a dynamic engine model is essential to predict and analyze of dynamic characteristics from a natural gas engine. Reducing the harmful exhaust emissions can be accomplished by a precise air-fuel ratio control. In this paper, the dynamic engine model was proposed and included mixture formation and intake process because the dynamic characteristics can be affected by the mixture components such as an air and a gaseous fuel. The air mass flow, the partial pressure ratio, and the gas constant are changed by variations of the components in the mixture formation and intake process. The dynamic engine model is applied to the natural gas engine for validation test. Experimental results show that the dynamic engine model is effective to predict the dynamic characteristics of the natural gas engine.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.35-41
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• 2020

This study was conducted to develop the efficient system for starch hydrolysis suppression using rutin, quercetin and dietary fiber through the statistical mixture design. The three components were replaced with wheat flour at the level of 10% and the mixed gel with three components was characterized by in vitro starch digestion. The mixture design was applied by simplex-centroid experimental model. The quadratic model (R²=0.86) was well fitted and the obtained regression equation indicated that the significant positive effects was observed in the quercetin and fiber mixture. Based on the statistical results, the best mixing ratio of quercetin and fiber was 72: 28 that led to the lowest predicted glycemic index (pGI). Their interactions on the pGI of starch digestibility were clearly visualized in the 3D surface plot. These results suggested that the mixture of quercetin and fiber interact strongly with wheat flour, consequently retarding starch hydrolysis by 15%.

• Journal of computational fluids engineering
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• v.16 no.1
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• pp.60-66
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• 2011

Engineering interests of submerged bodies and turbomachinery has led researchers to study various cavitation models for decades. The governing equations used for the present work are the two-phase Navier-Stokes equations with homogeneous mixture model. The solver employed on implicit dual time preconditioning algorithm in curvilinear coordinates. Three different cavitation models were applied to two axisymmetric cylinders and compared with experiments. It is concluded that the Merkle's new cavitation model has successfully accounted for cavitating flows and well captured the re-entrant jet phenomenon over the 0-caliber cylinder.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1870-1877
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• 2012

Transient signals generally have short duration and variable length with time-varying and non-stationary characteristics. Thus frame-based pattern matching method is useful for classification of transient signals. In this paper, we propose a new method for classification of underwater transient signals using a Gaussian mixture model(GMM). We carried out classification experiments for various underwater transient signals depending upon the types of noise, signal-to-noise ratio, and number of mixtures in the GMM. Experimental results have verified that the proposed method works quite well for classification of underwater transient signals.