• Title/Summary/Keyword: linear mixture model

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Evaluation of Structure Development of Xanthan and Carob Bean Gum Mixture Using Non-Isothermal Kinetic Model

  • Yoon, Won-Byong;Gunasekaran, Sundaram
    • Food Science and Biotechnology
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    • v.16 no.6
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    • pp.954-957
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    • 2007
  • Gelation mechanism of xanthan-carob mixture (X/C) was investigated based on thermorheological behavior. Three X/C ratios (1:3, 1:1, and 3:1) were studied. Small amplitude oscillatory shear tests were performed to measure linear viscoelastic behavior during gelation. Temperature sweep ($-1^{\circ}C/min$) experiments were conducted. Using a non-isothermal kinetic model, activation energy (Ea) during gelation was calculated. At 1% total concentration, the Ea for xanthan fraction (${\phi}_x$)=0.25, 0.5, and 0.75 were 178, 159, and 123 kJ/mol, respectively. However, a discontinuity was observed in the activation energy plots. Based on this, two gelation mechanisms were presumed-association of xanthan and carob molecules and aggregation of polymer strands. The association process is the primary mechanism to form 3-D networks in the initial stage of gelation and the aggregation of polymer strands played a major role in the later stage.

Enhancing prediction accuracy of concrete compressive strength using stacking ensemble machine learning

  • Yunpeng Zhao;Dimitrios Goulias;Setare Saremi
    • Computers and Concrete
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    • v.32 no.3
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    • pp.233-246
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    • 2023
  • Accurate prediction of concrete compressive strength can minimize the need for extensive, time-consuming, and costly mixture optimization testing and analysis. This study attempts to enhance the prediction accuracy of compressive strength using stacking ensemble machine learning (ML) with feature engineering techniques. Seven alternative ML models of increasing complexity were implemented and compared, including linear regression, SVM, decision tree, multiple layer perceptron, random forest, Xgboost and Adaboost. To further improve the prediction accuracy, a ML pipeline was proposed in which the feature engineering technique was implemented, and a two-layer stacked model was developed. The k-fold cross-validation approach was employed to optimize model parameters and train the stacked model. The stacked model showed superior performance in predicting concrete compressive strength with a correlation of determination (R2) of 0.985. Feature (i.e., variable) importance was determined to demonstrate how useful the synthetic features are in prediction and provide better interpretability of the data and the model. The methodology in this study promotes a more thorough assessment of alternative ML algorithms and rather than focusing on any single ML model type for concrete compressive strength prediction.

An Experimental Investigation of Heat Transfer in Forced Convective Boiling of R 134a, R 123 and R 134a/R 123 in a Horizontal Tube

  • Lim, Tae-Woo;Kim, Jun-Hyo
    • Journal of Mechanical Science and Technology
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    • v.18 no.3
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    • pp.513-525
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    • 2004
  • This paper reports an experimental study on flow boiling of pure refrigerants R l34a and R l23 and their mixtures in a uniformly heated horizontal tube. The flow pattern was observed through tubular sight glasses with an internal diameter of 10㎜ located at the inlet and outlet of the test section. Tests were run at a pressure of 0.6 MPa in the heat flux ranges of 5-50㎾/㎡, vapor quality 0-100 percent and mass velocity of 150-600㎏/㎡s. Both in the nucleate boiling-dominant region at low quality and in the two-phase convective evaporation region at higher quality where nucleation is supposed to be fully suppressed, the heat transfer coefficient for the mixture was lower than that for an equivalent pure component with the same physical properties as the mixture. The reduction of the heat transfer coefficient in mixture is explained by such mechanisms as mass transfer resistance and non-linear variation in physical properties etc. In this study, the contribution of convective evaporation, which is obtained for pure refrigerants under the suppression of nucleate boiling, is multiplied by the composition factor by Singal et al. (1984). On the basis of Chen's superposition model, a new correlation is presented for heat transfer coefficients of mixture.

Quality Characteristics of Surimi-Based Product with Sea Tangle Single Cell Detritus (SCD) (다시마 Single Cell Detritus(SCD)를 첨가하여 제조한 수산연제품의 품질특성)

  • Bang, Sang-Jin;Shin, Il-Shik;Chung, Dong-Hwa;Kim, Sang-Moo
    • Korean Journal of Food Science and Technology
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    • v.38 no.3
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    • pp.337-341
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    • 2006
  • The quality characteristics of a surimi-based product with sea tangle single cell detritus (SCD) were studied in order to utilize SCD from sea tangle as a food additive. Mixture design and regression models were applied to optimize the processing conditions and to investigate the interaction between surimi and the other ingredients. Surimi and SCD decreased hardness and cohesiveness of surimi gels, and then increased them. Water increased hardness and then decreased it, whereas cohesiveness was reversed. Surimi and water increased gumminess and brittleness of surimi gels, but SCD decreased them. SCD increased water retention ability (WRA) and whiteness of surimi gels, whereas water decreased it. Hardness and cohesiveness fitted nonlinear models by ANOVA, but gumminess, brittleness, WRA and whiteness fitted linear models. The response constraint coefficient showed that surimi influenced hardness and whitenessmore than water and SCD, whereas water influenced WRA more than surimi and SCD. Moreover, SCD influenced cohesiveness, gumminess and brittleness more than surimi and water. Hardness and cohesiveness fitted nonlinear models with interaction terms for surimi-SCD and surimi-water, respectively. Optimum mixed ratio values of surimi, water, and SCD were 36.80, 57.07 and 4.14%, respectively, by mixture model.

Least Cost and Optimum Mixing Programming by Yulmu Mixture Noddle (율무국수를 이용한 최소가격/최적배합 프로그래밍)

  • Kim, Sang-Soo;Kim, Byung-Yong;Hahm, Young-Tae;Shin, Dong-Hoon
    • Korean Journal of Food Science and Technology
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    • v.31 no.2
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    • pp.385-390
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    • 1999
  • Noodle was made using a combination of yulmu, wheat and water through mixture design. Statistical models of yulmu noodle were shown by analysing tensile stress and color $(L^{*})$, and sensory evaluation with other constraints. Analysing the linear and non-linear model, the linearity in the values of tensile stress, lightness $(L^{*})$ and sensory evaluation showed that each component worked separately without interactions. In studying the component effect on the response by trace plot, the result indicated that the increase in the amount of yulmu enhanced tensile stress of noodle while degrading $L^{*}$ value and sensory evaluation score. In the range of satisfying the conditions of noodle in every tensile stress, $L^{*}$ value and sensory evaluation point, the optimum mixture ratio of yulmu : wheat : water was 2.27% : 66.28% : 28.45% based on least cost linear programming. In this calculation, the least cost was 9.924 and estimated potential results of the response for tensile stress was 2.234 N and those for $L^{*}$ was 82.39. Finally, the potential response results affected by mixture ratio of yulmu, wheat and water were screened using Excel.

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Dilutant flow characteristics model of coarse particle suspensions with uniform size distribution

  • Ookawara, Shinichi;Ogawa, Kohei
    • Korea-Australia Rheology Journal
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    • v.15 no.1
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    • pp.35-41
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    • 2003
  • It is expected that particle size distribution of any portion obtained through screening, is of more uniform than that of the original mixture, typically following such as log-normal, Rosin-Rammler distributions and so on. In this study, therefore, a new relation between parameters of the uniform distribution and flow characteristics of the coarse particle suspensions is derived based on the continuous polydisperse model (Ookawara and Ogawa, 2002b), which is derived from the discrete polydisperse model (Ookawara and Ogawa,2002a). The derived model equation predicts a linear increase of viscosity with shear rate, viz., dilutant flow characteristics. Further, the increase of viscosity is expected to be proportional to the square of volume fraction of particles, and to show the linear dependency on density and average diameter of particles. It is also shown that the uniform distribution model includes additional term that expresses the effect of distribution width. For verification of the model, the experimental results of Clarke (1967) are cited as well as in our previous work for the monodisperse model (Ookawara and Ogawa,2000) since most parameters were varied independently in his work. It is suggested that the newly introduced term expands the applicable range compared with the monodisperse model.

ON PREDCTION OF CONCENTRATION OF LIQUID FOOD BY ACOUSTIC NON-LINEAR PARAMETER B/A

  • Nishizu, Takahisa;Ikeda, Yoshio
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1993.10a
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    • pp.344-352
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    • 1993
  • The purpose of this study is to investigate the possibility of the non-destructive quality evaluation for food by the acoustic non-linear parameter B/A which is a measure of the non-linearity of the state equation of the medium in terms of pressure and density. The B/A of water, corn oil O/W(oil in water) emulsion and milk were measured by using a sound velocity measuring system. The B/A value of water was measured for ascertaining reliability of our experimental system. Corn oil W/W emulsion was prepared as a model of milk . It was proved that the B/A value of O/W emulsion was related to the oil concentration by a law of mixture. We applied this result to milk and obtained satisfactory results for predicting the milk fat concentration.

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Effective Combination of Temporal Information and Linear Transformation of Feature Vector in Speaker Verification (화자확인에서 특징벡터의 순시 정보와 선형 변환의 효과적인 적용)

  • Seo, Chang-Woo;Zhao, Mei-Hua;Lim, Young-Hwan;Jeon, Sung-Chae
    • Phonetics and Speech Sciences
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    • v.1 no.4
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    • pp.127-132
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    • 2009
  • The feature vectors which are used in conventional speaker recognition (SR) systems may have many correlations between their neighbors. To improve the performance of the SR, many researchers adopted linear transformation method like principal component analysis (PCA). In general, the linear transformation of the feature vectors is based on concatenated form of the static features and their dynamic features. However, the linear transformation which based on both the static features and their dynamic features is more complex than that based on the static features alone due to the high order of the features. To overcome these problems, we propose an efficient method that applies linear transformation and temporal information of the features to reduce complexity and improve the performance in speaker verification (SV). The proposed method first performs a linear transformation by PCA coefficients. The delta parameters for temporal information are then obtained from the transformed features. The proposed method only requires 1/4 in the size of the covariance matrix compared with adding the static and their dynamic features for PCA coefficients. Also, the delta parameters are extracted from the linearly transformed features after the reduction of dimension in the static features. Compared with the PCA and conventional methods in terms of equal error rate (EER) in SV, the proposed method shows better performance while requiring less storage space and complexity.

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SHADOW EXTRACTION FROM ASTER IMAGE USING MIXED PIXEL ANALYSIS

  • Kikuchi, Yuki;Takeshi, Miyata;Masataka, Takagi
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.727-731
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    • 2003
  • ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

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Human-Content Interface : A Friction-Based Interface Model for Efficient Interaction with Android App and Web-Based Contents

  • Kim, Jong-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.55-62
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    • 2021
  • In this paper, we propose a human-content interface that allows users to quickly and efficiently search data through friction-based scrolling with ROI(Regions of interests). Our approach, conceived from the behavior of finding information or content of interest to users, efficiently calculates ROI for a given content. Based on the kernel developed by conceiving from GMM(Gaussian mixture model), information is searched by moving the screen smoothly and quickly to the location of the information of interest to the user. In this paper, linear interpolation is applied to make one softer inertia, and this is applied to scrolls. As a result, unlike the existing approach in which information is searched according to the user's input, our method can more easily and intuitively find information or content that the user is interested in through friction-based scrolling. For this reason, the user can save search time.