• Title/Summary/Keyword: linear mixture model

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Formulation Optimization of Salad Dressing Added with Bokbunja (Rubus coreanum Miquel) Juice (복분자(Rubus coreanum Miquel) 즙을 이용한 드레싱 제조의 재료 혼합 비율의 최적화)

  • Jung, Su-Ji;Kim, Na-Young;Jang, Myung-Sook
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.37 no.4
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    • pp.497-504
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    • 2008
  • This study was conducted for the optimization of ingredients in salad dressing using Bokbunja (Rubus coreanum Miquel) juice. The experiment was designed according to the D-optimal design of mixture design, which included 14 experimental points with 4 replicates for three independent variables (Bokbunja juice $15.70\sim47.10%$, oil $23.50\sim39.20%$, vinegar $3.90\sim19.60%$). The compositional and functional properties of the prepared products were measured, and these values were applied to the mathematical models. A canonical form and trace plot showed the influence of each variable on the quality attribute of final mixture product. By the use of F-test, viscosity, color values (L, a, and b), emulsion stability and sensory characteristics (color) were expressed by a linear model, while the color values (L) and sensory characteristics (smell, taste, and overall acceptance) were by a quadratic model. The optimum formulations by numerical and graphical method were analogous: Bokbunja juice, oil and vinegar of 36.02%, 26.48%, and 12.00% by numerical method, respectively; those of 36.00%, 26.44%, and 12.06% by graphical method, respectively.

Variable Rate IMBE-LP Coding Algorithm Using Band Information (주파수대역 정보를 이용한 가변률 IMBE-LP 음성부호화 알고리즘)

  • Park, Man-Ho;Bae, Geon-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.5
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    • pp.576-582
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    • 2001
  • The Multi-Band Excitation(MBE) speech coder uses a different approach for the representation of the excitation signal. It replaces the frame-based single voiced/unvoiced classification of a classical speech coder with a set of such decision over harmonic intervals in the frequency domain. This enables each speech segment to be a mixture of voiced and unvoiced, and improves the synthetic speech quality by reducing decision errors that might occur on the frame-based single voiced and unvoiced decision process when input speech is degraded with noise. The IMBE-LP, improved version of MBE with linear prediction, represents the spectral information of MBE model with linear prediction coefficients to obtain low bit rate of 2.4 kbps. In this Paper, we proposed a variable rate IMBE-LP vocoder that has lower bit rate than IMBE-LP without degrading the synthetic speech quality. To determine the LP order, it uses the spectral band information of the MBE model that has something to do with he input speech's characteristics. Experimental results are riven with our findings and discussions.

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Effects of changing materials properties for vibration of FGM beam using integral shear deformation model

  • Mokhtar Ellali;Mashhour A. Alazwari;Mokhtar Bouazza;Mohamed A. Eltaher;Noureddine Benseddiq
    • Coupled systems mechanics
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    • v.13 no.4
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    • pp.277-291
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    • 2024
  • The objective of this work is to study the effects of the modification of material properties on the vibration of the FGM beam using an integral shear strain model. In the present theory, the rotational displacement is replaced by an integral term in the displacement fields. The use of a shear correction factor is not necessary because our model gives a parabolic description of shear stress through the thickness while satisfying the conditions of zero shear stresses on the bottom and top surfaces of the beam. The FGM beam is assumed that the beam is a mixture of metal and ceramic, and that its properties change depending on the power functions of the thickness of the beam such as: linear, quadratic, cubic and inverse quadratic. By applying Hamilton's principle, general formulas were obtained to obtain the frequencies of the FGM beam. The effects of changing compositional characteristics of materials presented by volume fraction of FGM beams with simply supported edges on free vibration and some mode shapes are investigated.

Hygrothermal Fracture Analysis in Dissimilar Materials

  • Ahn, Kook-Chan;Lee, Tae-Hwan;Bae, Kang-Yul
    • International Journal of Aeronautical and Space Sciences
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    • v.2 no.2
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    • pp.65-72
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    • 2001
  • This paper demonstrates an explicit-implicit, finite element analysis for linear as well as nonlinear hygrothermal stress problems. Additional features, such as moisture diffusion equation, crack element and virtual crack extension(VCE) method for evaluating J-integral are implemented in this program. The Linear Elastic Fracture Mechanics(LEFM) Theory is employed to estimate the crack driving force under the transient condition for an existing crack. Pores in materials are assumed to be saturated with moisture in the liquid form at the room temperature, which may vaporize as the temperature increases. The vaporization effects on the crack driving force are also studied. The ideal gas equation is employed to estimate the thermodynamic pressure due to vaporization at each time step after solving basic nodal values. A set of field equations governing the time dependent response of porous media are derived from balance laws based on the mixture theory. Darcy's law is assumed for the fluid flow through the porous media. Perzyna's viscoplastic model incorporating the Von-Mises yield criterion are implemented. The Green-Naghdi stress rate is used for the invariant of stress tensor under superposed rigid body motion. Isotropic elements are used for the spatial discretization and an iterative scheme based on the full Newton-Raphson method is used for solving the nonlinear governing equations.

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Two-Stage Experimental Design for Multiple Objectives (다수목적을 위한 2단계 실험)

  • Jang, Dae-Heung;Kim, Youngil
    • The Korean Journal of Applied Statistics
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    • v.28 no.1
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    • pp.93-102
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    • 2015
  • The D-optimal design for the nonlinear model typically depends on the unknown parameters to be estimated. Therefore, it is strongly recommended in literature to use a sequential experimental design for estimating the parameters. In this paper two stage experimental design is discussed under many different circumstances including estimating parameters. The method is so universal to be applied to any mixture of objectives for any model including linear model. A hybrid approach is suggested to handle more than 2 objectives in two-stage experimental design. The design is discussed in approximate design framework.

A comparative study on applicability and efficiency of machine learning algorithms for modeling gamma-ray shielding behaviors

  • Bilmez, Bayram;Toker, Ozan;Alp, Selcuk;Oz, Ersoy;Icelli, Orhan
    • Nuclear Engineering and Technology
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    • v.54 no.1
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    • pp.310-317
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    • 2022
  • The mass attenuation coefficient is the primary physical parameter to model narrow beam gamma-ray attenuation. A new machine learning based approach is proposed to model gamma-ray shielding behavior of composites alternative to theoretical calculations. Two fuzzy logic algorithms and a neural network algorithm were trained and tested with different mixture ratios of vanadium slag/epoxy resin/antimony in the 0.05 MeV-2 MeV energy range. Two of the algorithms showed excellent agreement with testing data after optimizing adjustable parameters, with root mean squared error (RMSE) values down to 0.0001. Those results are remarkable because mass attenuation coefficients are often presented with four significant figures. Different training data sizes were tried to determine the least number of data points required to train sufficient models. Data set size more than 1000 is seen to be required to model in above 0.05 MeV energy. Below this energy, more data points with finer energy resolution might be required. Neuro-fuzzy models were three times faster to train than neural network models, while neural network models depicted low RMSE. Fuzzy logic algorithms are overlooked in complex function approximation, yet grid partitioned fuzzy algorithms showed excellent calculation efficiency and good convergence in predicting mass attenuation coefficient.

Mixutre Optimization of Hwangdo Peach (Prunus persica L. Batsch) Dressing by Mixture Experimental Design (혼합물 실험계획법에 의한 황도복숭아 드레싱 재료혼합비의 최적화)

  • Park, Jung Eun;Kim, Yong-Sik
    • Culinary science and hospitality research
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    • v.23 no.7
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    • pp.20-30
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    • 2017
  • This study was conducted for the optimization of ingredients in salad dressing using Hwangdo peach (Prunus persica L. Batsch). The experiment was designed according to the D-optimal design of mixture design, which included 14 experimental points with 4 replicates for three independent variables (olive oil 40~65%, peach puree 27~50%, vinegar 8~20%). The linear regression models for pH, viscosity and color value and the quadratic regression models for emulsion stability, all sensory evaluation of the products were proven to be valid by the F-test for the overall significance of the regression model at a 5% level. Viscosity and pH of the products increased as olive oil content. Color value, viscosity and pH of the products increased as peach puree content. pH, viscosity, redness, and yellowness of the products decreased as vinegar content. Sensory evaluation result of the products showed that general preference for the products were increasingly affected by the increases in contents then decreased as they exceeded the optimum levels. In consequence, according to result from the first stage of the experiment, the optimum ingredients ratios of the raw materials were set in olive oil 52.43%, peach puree 35.07%, and vinegar 13.91% for ingredients of apricot dressing. These results provided the possibility that peach can be applied to the preparation of a dressing, and thereby present baseline data for the development of new dressings. This is also presumed to meet demands of customers who are always in pursuit of new products.

Optimization of Ingredient Mixing Ratio for Preparation of Steamed Cake with Mugwort (Pseudosasa japonica Makino) Powder (혼합물 실험계획법에 의한 쑥 첨가 찜 케이크의 최적화)

  • Oh, Suk-Tae;Park, Jung-Eun
    • Korean journal of food and cookery science
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    • v.28 no.1
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    • pp.67-76
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    • 2012
  • This study examined the optimal ingredient mixing ratio for the preparation of steamed cake containing mugwort (Artemisia princeps var. orientalis) powder. After preliminary studies, the following ingredient ranges were determined; 110~129% sugar, 3~8% mugwort powder, 10~25% oil. Among the different mixture designs, the D-optimal design was chosen for analysis. The results of F-test, specific gravity, viscosity, volume and color values (L, a, b), hardness decided a linear model, while the sensory characteristics (color, taste, texture and overall acceptance) decided a quadratic model. The fitness analysis results showed that in all characteristic, the probabilities were significant within 0.05%; thus, the models were accepted as appropriate. The response surface and trace plot results showed that increasing amounts of mugwort powder decreased the brightness, and increased redness and yellowness. As the level of added oil increased, the softness of the cake increased. Cake samples received low sensory evaluation scores when sugar, mugwort powder, and oil were added above their optimal levels. The optimum formulations by the numerical and graphical methods, were similar, and with the numerical method presented as: sugar, mugwort powder, and oil at 120.7%, 5.1%, and 16.2%, respectively(flour weight basis). The above results demonstrate the feasibility of adding mugwort powder to sponge cake, and therefore, the commercialization of mugwort powder cake marketed as a functional food is deemed possible.

Speech Emotion Recognition Based on GMM Using FFT and MFB Spectral Entropy (FFT와 MFB Spectral Entropy를 이용한 GMM 기반의 감정인식)

  • Lee, Woo-Seok;Roh, Yong-Wan;Hong, Hwang-Seok
    • Proceedings of the KIEE Conference
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    • 2008.04a
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    • pp.99-100
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    • 2008
  • This paper proposes a Gaussian Mixture Model (GMM) - based speech emotion recognition methods using four feature parameters; 1) Fast Fourier Transform(FFT) spectral entropy, 2) delta FFT spectral entropy, 3) Mel-frequency Filter Bank (MFB) spectral entropy, and 4) delta MFB spectral entropy. In addition, we use four emotions in a speech database including anger, sadness, happiness, and neutrality. We perform speech emotion recognition experiments using each pre-defined emotion and gender. The experimental results show that the proposed emotion recognition using FFT spectral-based entropy and MFB spectral-based entropy performs better than existing emotion recognition based on GMM using energy, Zero Crossing Rate (ZCR), Linear Prediction Coefficient (LPC), and pitch parameters. In experimental Results, we attained a maximum recognition rate of 75.1% when we used MFB spectral entropy and delta MFB spectral entropy.

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Implementation of HMM-Based Speech Recognizer Using TMS320C6711 DSP

  • Bae Hyojoon;Jung Sungyun;Bae Keunsung
    • MALSORI
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    • no.52
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    • pp.111-120
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    • 2004
  • This paper focuses on the DSP implementation of an HMM-based speech recognizer that can handle several hundred words of vocabulary size as well as speaker independency. First, we develop an HMM-based speech recognition system on the PC that operates on the frame basis with parallel processing of feature extraction and Viterbi decoding to make the processing delay as small as possible. Many techniques such as linear discriminant analysis, state-based Gaussian selection, and phonetic tied mixture model are employed for reduction of computational burden and memory size. The system is then properly optimized and compiled on the TMS320C6711 DSP for real-time operation. The implemented system uses 486kbytes of memory for data and acoustic models, and 24.5 kbytes for program code. Maximum required time of 29.2 ms for processing a frame of 32 ms of speech validates real-time operation of the implemented system.

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