• Korean Chemical Engineering Research
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• v.48 no.5
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• pp.632-637
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• 2010

Liquid-liquid equilibrium data for the quaternary system water +tetrahydrofuran + butyl acetate + isoamyl alcohol mixture were measured at 298.15 K and atmospheric pressure. Binodal curves, tie-lines, distribution, and selectivity for the quaternary system have been determined in order to investigate the effect of using binary solvents, butyl acetate and isoamyl alcohol, on extracting tetrahydrofuran from aqueous solution. In addition, these experimental tie-line data were also compared with the values predicted by the UNIFAC model. For the quaternary system, an average root-mean-square deviation for the system in 75/25, 50/50, and 25/75 mass ratios as mixed solvents are(3.35, 5.21 and 5.65) %, respectively.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.75-81
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• 2004

Gaussian selection (GS) is a popular approach in the continuous density hidden Markov model for fast decoding. It enables fast likelihood computation by reducing the number of Gaussian components calculated. In this paper, we propose a new GS method for the phonetic tied-mixture (PTM) hidden Markov models. The PTM model can represent each state of the same topological location with a shared set of Gaussian mixture components and contort dependent weights. Thus the proposed method imposes constraint on the weights as well as the number of Gaussian components to reduce the computational load. Experimental results show that the proposed method reduces the percentage of Gaussian computation to 16.41%, compared with 20-30% for the conventional GS methods, with little degradation in recognition.

• Journal of Energy Engineering
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• v.18 no.3
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• pp.203-211
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• 2009

Vapor pressure of HFC-404a and polyol ester system were measured at 56 points from 263.15 to 323.15 K and from 0 to 90 mass %polyol ester. It was found that below 273.15 K, the effect of the polyol ester on the vapor pressure was negligible up to 30 mass % polyol ester. The vapor pressure of the system significantly decreased as the mass fraction of polyol ester increased over 50 percent. Raoult's model and Flory-Huggins model were tested for data reduction. Empirical vapor pressure equations were obtained in terms of temperature and mass fraction of polyol ester.

• Applied Chemistry for Engineering
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• v.26 no.2
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• pp.184-192
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• 2015

Characteristics of Char-$CO_2$ gasification for petroleum coke, biomass and mixed fuels were compared in the temperature range of $1,100{\sim}1,400^{\circ}C$ using TGA (Thermogravimetric analyzer). Kinetic constants with respect to reaction temperature were determined by using different gas-solid reaction models. Also activation energy (Ea) and pre-exponential factors ($K_0$) in each models were calculated by using Arrhenius equation and then were compared with experimental values to determine reaction rate equation for char-$CO_2$ gasification. Reaction time for $CO_2$ gasification decreased with an increase of reaction temperature. Also, the activation energy of $CO_2$ gasification reaction for mixture with petroleum coke and biomass decreased with increasing biomass contents. This indicates that mixing with biomass could bring synergy effects on $CO_2$ gasification reaction.

• Journal of the Korea Concrete Institute
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• v.20 no.5
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• pp.627-634
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• 2008

This paper presents an optimum mixture design method for proportioning a concrete. In the proposed method, the search space is constrained as the domain defined by the minimal convex region of a database, instead of the available range of each component and the ratio composed of several components. The model for defining the search space which is expressed by the effective region is proposed. The effective region model evaluates whether a mix-proportion is effective on processing for optimization, yielding highly reliable results. Three concepts are adopted to realize the proposed methodology: A genetic algorithm for the optimization; an artificial neural network for predicting material properties; and a convex hull for evaluating the effective region. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix-proportion obtained from the proposed methodology using convex hulls is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.93-99
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• 2017

A hybrid approach using Long Short Term Memory (LSTM) Recurrent Neural Network (RNN) has showed great improvement in speech recognition accuracy. For training acoustic model based on hybrid approach, it requires forced alignment of HMM state sequence from Gaussian Mixture Model (GMM)-Hidden Markov Model (HMM). However, high computation time for training GMM-HMM is required. This paper proposes an end-to-end approach for LSTM RNN-based Korean speech recognition to improve learning speed. A Connectionist Temporal Classification (CTC) algorithm is proposed to implement this approach. The proposed method showed almost equal performance in recognition rate, while the learning speed is 1.27 times faster.

• Science of Emotion and Sensibility
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• v.8 no.2
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• pp.155-160
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• 2005

The aim of this study was to examine the effects of aqua-acupuncture a mixture of bos taurus domesticus and selenarctos thiberanus, and bos taurus domesticus, selenarctos thiberanus and Moschus moschiferus on an animal model of arthritic pain. Under halothane anesthesia, arthritic pain was induced by the injection of $2\%$ carrageenan into the left knee joint cavity of male Sprague-Dawley rats. The responses of afferents to a movement cycle were recorded before and after aqua-acupuncture. The aqua-acupuncture at acupoints reduced neural responses to noxious movement stimulation. Aqua-acupuncture at Zusanli inhibited neural responses of articular afferents to noxious stimulation more than at Hegu. These results indicate that aqua-acupuncture of a mixture of bos taurus domesticus and selenarctos thiberanus, and bos taurus domesticus, selenarctos thiberanus and Moschus moschiferusmay provide a potent strategy in relieving arthritic pain.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.311-318
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• 2013

This paper deals with a noise reduction algorithm which uses the binary masking in the time-frequency domain. To improve speech intelligibility in noise, noise-masked speech is decomposed into time-frequency units and mask "0" is assigned to masker-dominant region removing time-frequency units where noise is dominant compared to speech. In the previous research, Gaussian mixture models were used to classify the speech-dominant region and noise-dominant region which correspond to mask "1" and mask "0", respectively. In each frequency band, data were collected and trained to build the Gaussian mixture models and detection procedure is performed to the test data where each time-frequency unit belongs to speech-dominant region or noise-dominant region. In this paper, we consider the correlation of masks in the frequency domain and propose a post-processing method which exploits the Viterbi algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.12
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• pp.1605-1612
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• 2012

The distribution of a response usually depends on the distribution of the variables. When a variable shows a distribution with two different modes, the response also shows a distribution with two different modes. In this case, recently developed methods for reliability analysis assume that the distribution functions are continuous with a mode. In actual problems, however, because information is often provided in a discrete form with two or more modes, it is important to estimate the distributions for such information. In this study, we employ the finite mixture model to estimate the response distribution with two different modes, and we select the best candidate distribution through AIC. Mathematical examples are illustrated to verify the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.13-18
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• 2018

In this study, we classify Seoul metro stations according to boarding and alighting patterns using machine earning technique. The target data is the number of boarding and alighting passengers per hour every day at 233 subway stations from 2008 to 2017 provided by the public data portal. Gaussian mixture model (GMM) and K-means clustering are used as machine learning techniques in order to classify subway stations. The distribution of the boarding time and the alighting time of the passengers can be modeled by the Gaussian mixture model. K-means clustering algorithm is used for unsupervised learning based on the data obtained by GMM modeling. As a result of the research, Seoul metro stations are classified into four groups according to boarding and alighting patterns. The results of this study can be utilized as a basic knowledge for analyzing the characteristics of Seoul subway stations and analyzing it economically, socially and culturally. The method of this research can be applied to public data and big data in areas requiring clustering.