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Journal articles on the topic 'Mixed model method'

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Author: Grafiati

Published: 10 December 2022

Last updated: 19 February 2023

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1

Li Wei, Li Wei, and Bing-Wu Fang Li Wei. "Safety Analysis Method of Mixed Failure Model using Temporal Bayesian Network." 網際網路技術學刊 23, no. 4 (July 2022): 727–34. http://dx.doi.org/10.53106/160792642022072304008.

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<p>Dynamic Fault Tree (DFT) is used widely in the community of reliability and safety analysis of a complex system. DFT is a high-level modeling language lacking formal semantics, so we need to convert it to a mathematical model to analyze. The conventional analysis method can only solve the DFT with discrete or exponential distribution, but not the DFT with mixed distributions. To this end, we first propose a TBN framework to represent the DFT with mixed failure distribution by extending the BN and introduce Dirac delta functions and unit-step functions into the framework to represent the logical relationship and temporal relationship between the nodes, respectively. To run the standard BN inference algorithm over TBN, we fit the failure distribution of the nodes by using k-piece and n-degree polynomials. We then propose a transformation method from DFT to TBN and prove the equivalence of the transformation. Finally, the analysis of the DFT model of the X2000 avionics system shows that our approach can effectively analyze the reliability of mixed distribution failure models. Moreover, the accuracy and efficiency of the analysis are significantly better than current mainstream methods.</p> <p> </p>

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2

Sunandi, Etis, Khairil Anwar Notodiputro, and Bagus Sartono. "A STUDY OF GENERALIZED LINEAR MIXED MODEL FOR COUNT DATA USING HIERARCHICAL BAYES METHOD." MEDIA STATISTIKA 14, no. 2 (December 12, 2021): 194–205. http://dx.doi.org/10.14710/medstat.14.2.194-205.

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Poisson Log-Normal Model is one of the hierarchical mixed models that can be used for count data. Several estimation methods can be used to estimate the model parameters. The first objective of this study was to examine the performance of the parameter estimator and model built using the Hierarchical Bayes method via Markov Chain Monte Carlo (MCMC) with simulation. The second objective was applied the Poisson Log-Normal model to the West Java illiteracy Cases data which is sourced from the Susenas data on March 2019. In 2019, the incidence of illiteracy is a very rare occurrence in West Java Province. So that, it is suitable as an application case in this study. The simulation results showed that the Hierarchical Bayes parameter estimator through MCMC has the smallest Root Mean Squared Error of Prediction (RMSEP) value and the absolute bias is relatively mostly similar when compared to the Maximum Likelihood (ML) and Penalized Quasi-Likelihood (PQL) methods. Meanwhile, the empirical results showed that the fixed variable is the number of respondents who have a maximum education of elementary school have the greatest risk of illiteracy. Also, the diversity of census blocks significantly affects illiteracy cases in West Java 2019.

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3

Zhou, Tianyue. "Weighting Method for a Linear Mixed Model." Communications in Statistics - Theory and Methods 39, no. 2 (December 11, 2009): 214–27. http://dx.doi.org/10.1080/03610920802677216.

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4

Zhang, Ying. "Average Method of Mixed Sampling Distribution Bayesian Model." MATEC Web of Conferences 228 (2018): 01002. http://dx.doi.org/10.1051/matecconf/201822801002.

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Based on the study of Bayesian model average (BMA), this paper proposes to mix the prior distribution and sampling distribution to obtain the average method of the mixed sampling distribution Bayesian model overcoming the problem that traditional econometric modeling method does not explicitly consider the uncertainty of the model. If all the alternative models have the same parametric form, then the new Bayesian estimation will degenerate into the BMA estimator. The empirical results show that the method is better than Bayesian model average.

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5

Selvaganesan, N. "Mixed method of model reduction for uncertain systems." Serbian Journal of Electrical Engineering 4, no. 1 (2007): 1–12. http://dx.doi.org/10.2298/sjee0701001s.

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A mixed method for reducing a higher order uncertain system to a stable reduced order one is proposed. Interval arithmetic is used to construct a generalized Routh table for determining the denominator polynomial of the reduced system. The reduced numerator polynomial is obtained using factor division method and the steady state error is minimized using gain correction factor. The proposed method is illustrated using a numerical example.

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6

Bai, Hao, Yuan Zhong, Xin Gao, and Wei Xu. "Multivariate Mixed Response Model with Pairwise Composite-Likelihood Method." Stats 3, no. 3 (July 15, 2020): 203–20. http://dx.doi.org/10.3390/stats3030016.

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In clinical research, study outcomes usually consist of various patients’ information corresponding to the treatment. To have a better understanding of the effects of different treatments, one often needs to analyze multiple clinical outcomes simultaneously, while the data are usually mixed with both continuous and discrete variables. We propose the multivariate mixed response model to implement statistical inference based on the conditional grouped continuous model through a pairwise composite-likelihood approach. It can simplify the multivariate model by dealing with three types of bivariate models and incorporating the asymptotical properties of the composite likelihood via the Godambe information. We demonstrate the validity and the statistic power of the multivariate mixed response model through simulation studies and clinical applications. This composite-likelihood method is advantageous for statistical inference on correlated multivariate mixed outcomes.

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7

PAN, Jian-min. "ESTIMATION METHOD FOR MIXED-EFFECT COEFFICIENT SEMIPARAMETRIC REGRESSION MODEL." Journal of Zhejiang University SCIENCE 1, no. 1 (2000): 71. http://dx.doi.org/10.1631/jzus.2000.0071.

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8

Wang, Feng, Mingchao Cai, Gang Wang, and Yuping Zeng. "A mixed virtual element method for Biot's consolidation model." Computers & Mathematics with Applications 126 (November 2022): 31–42. http://dx.doi.org/10.1016/j.camwa.2022.09.005.

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9

Tao, Huageng, Mari Palta, Brian S. Yandell, and Michael A. Newton. "An Estimation Method for the Semiparametric Mixed Effects Model." Biometrics 55, no. 1 (March 1999): 102–10. http://dx.doi.org/10.1111/j.0006-341x.1999.00102.x.

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10

Pan, Hao, and Hongxing Rui. "Mixed Element Method for Two-Dimensional Darcy-Forchheimer Model." Journal of Scientific Computing 52, no. 3 (November 23, 2011): 563–87. http://dx.doi.org/10.1007/s10915-011-9558-3.

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11

Farhloul, M., and A. M. Zine. "A mixed finite element method for a Ladyzhenskaya model." Computer Methods in Applied Mechanics and Engineering 191, no. 39-40 (August 2002): 4497–510. http://dx.doi.org/10.1016/s0045-7825(02)00393-6.

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12

LIAW, C. M. "Mixed method of model reduction for linear multivariable systems." International Journal of Systems Science 20, no. 11 (November 1989): 2029–41. http://dx.doi.org/10.1080/00207728908910285.

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13

Kim, Kyunga, Shin-Jae Lee, Soo-Heang Eo, HyungJun Cho, and Jae Won Lee. "Modified partial least squares method implementing mixed-effect model." Communications for Statistical Applications and Methods 30, no. 1 (January 31, 2023): 65–73. http://dx.doi.org/10.29220/csam.2023.30.1.065.

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14

Huang, Jian, Long Chen, and Hongxing Rui. "Multigrid Methods for a Mixed Finite Element Method of the Darcy–Forchheimer Model." Journal of Scientific Computing 74, no. 1 (June 9, 2017): 396–411. http://dx.doi.org/10.1007/s10915-017-0466-z.

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15

MIGDAL, A. A. "MIXED MODEL OF INDUCED QCD." Modern Physics Letters A 08, no. 03 (January 30, 1993): 245–58. http://dx.doi.org/10.1142/s0217732393000258.

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The problems with the ZN symmetry breaking in the induced QCD are analyzed. We compute the Wilson loops in the strong coupling phase, but we do not find the ZN symmetry breaking, for arbitrary potential. We suggest to bypass this problem by adding to the model a heavy fermion field in a fundamental representation of SU(N). Remarkably, the model can still be solved exactly by the Riemann-Hilbert method, for arbitrary number of flavors, Nf. At Nf≪N→∞ there is a new regime, with two vacuum densities. The ZN symmetry breaking density satisfies the linear integral equation, with the kernel, depending on the old density. The symmetry breaking requires certain eigenvalue condition, which takes some extra parameter adjustment of the scalar potential.

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Spiridonov, Denis, Jian Huang, Maria Vasilyeva, Yunqing Huang, and Eric T. Chung. "Mixed Generalized Multiscale Finite Element Method for Darcy-Forchheimer Model." Mathematics 7, no. 12 (December 10, 2019): 1212. http://dx.doi.org/10.3390/math7121212.

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In this paper, the solution of the Darcy-Forchheimer model in high contrast heterogeneous media is studied. This problem is solved by a mixed finite element method (MFEM) on a fine grid (the reference solution), where the pressure is approximated by piecewise constant elements; meanwhile, the velocity is discretized by the lowest order Raviart-Thomas elements. The solution on a coarse grid is performed by using the mixed generalized multiscale finite element method (mixed GMsFEM). The nonlinear equation can be solved by the well known Picard iteration. Several numerical experiments are presented in a two-dimensional heterogeneous domain to show the good applicability of the proposed multiscale method.

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17

Amara, Mohamed, Daniela Capatina-Papaghiuc, and Amna Chatti. "Bending Moment Mixed Method for the Kirchhoff--Love Plate Model." SIAM Journal on Numerical Analysis 40, no. 5 (January 2002): 1632–49. http://dx.doi.org/10.1137/s0036142900379680.

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18

Zhang, Jing, and Gangtie Zheng. "A mixed model reduction method for preserving selected physical information." Mechanical Systems and Signal Processing 86 (March 2017): 224–36. http://dx.doi.org/10.1016/j.ymssp.2016.10.008.

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19

Khoramishad, H., M. Hamzenejad, and R. S. Ashofteh. "Characterizing cohesive zone model using a mixed-mode direct method." Engineering Fracture Mechanics 153 (March 2016): 175–89. http://dx.doi.org/10.1016/j.engfracmech.2015.10.045.

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20

Cai, Mingchao, and Mo Mu. "A multilevel decoupled method for a mixed Stokes/Darcy model." Journal of Computational and Applied Mathematics 236, no. 9 (March 2012): 2452–65. http://dx.doi.org/10.1016/j.cam.2011.12.003.

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21

Schmid, Q., Y. Mesri, E. Hachem, and R. Codina. "Stabilized mixed finite element method for the M1 radiation model." Computer Methods in Applied Mechanics and Engineering 335 (June 2018): 69–90. http://dx.doi.org/10.1016/j.cma.2018.01.046.

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22

Zheng, Yu, Siqi Qiu, Fei Shen, and Changpeng He. "RFID-based material delivery method for mixed-model automobile assembly." Computers & Industrial Engineering 139 (January 2020): 106023. http://dx.doi.org/10.1016/j.cie.2019.106023.

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23

Rahmani, M., M. Arashi, N. Mamode Khan, and Y. Sunecher. "Improved mixed model for longitudinal data analysis using shrinkage method." Mathematical Sciences 12, no. 4 (November 1, 2018): 305–12. http://dx.doi.org/10.1007/s40096-018-0270-4.

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24

Cao, Zhifu, Qingguo Fei, Dong Jiang, and Shaoqing Wu. "Substructure-based model updating using residual flexibility mixed-boundary method." Journal of Mechanical Science and Technology 31, no. 2 (February 2017): 759–69. http://dx.doi.org/10.1007/s12206-017-0127-z.

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25

Şeker, Şükran, Mesut Özgürler, and Mehmet Tanyaş. "A Weighted Multiobjective Optimization Method for Mixed-Model Assembly Line Problem." Journal of Applied Mathematics 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/531056.

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Mixed-model assembly line (MMAL) is a type of assembly line where several distinct models of a product are assembled. MMAL is applied in many industrial environments today because of its greater variety in demand. This paper considers the objective of minimizing the work overload (i.e., the line balancing problem) and station-to-station product flows. Generally, transportation time between stations are ignored in the literature. In this paper, Multiobjective Mixed-Integer Programming (MOMIP) model is presented to optimize these two criteria simultaneously. Also, this MOMIP model incorporates a practical constraint that allows to add parallel stations to assembly line to decrease higher station time. In the last section, MOMIP is applied to optimize the cycle time and transportation time simultaneously in mixed-model assembly line of a real consumer electronics firm in Turkey, and computational results are presented.

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26

Schulenberg, Jennifer L. "Analysing Police Decision‐Making: Assessing the Application of a Mixed‐Method/Mixed‐Model Research Design." International Journal of Social Research Methodology 10, no. 2 (April 2007): 99–119. http://dx.doi.org/10.1080/13645570701334050.

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27

Tang, Zhirong, Huaqiang Li, Fangwei Xu, Qin Shu, and Yue Jiang. "A Harmonic Impedance Estimation Method Based on the Cauchy Mixed Model." Mathematical Problems in Engineering 2020 (March 25, 2020): 1–13. http://dx.doi.org/10.1155/2020/1580475.

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In this paper, a new method without any tradition assumption to estimate the utility harmonic impedance of a point of common coupling (PCC) is proposed. But, the existing estimation methods usually are built on some assumptions, such as, the background harmonic is stable and small, the harmonic impedance of the customer side is much larger than that of utility side, and the harmonic sources of both sides are independent. However these assumptions are unpractical to modern power grid, which causes very wrong estimation. The proposed method first uses a Cauchy Mixed Model (CMM) to express the Norton equivalent circuit of the PCC because we find that the CMM can right fit the statistical distribution of the measured harmonic data for any PCC, by testing and verifying massive measured harmonic data. Also, the parameters of the CMM are determined by the expectation maximization algorithm (EM), and then the utility harmonic impedance is estimated by means of the CMM’s parameters. Compared to the existing methods, the main advantages of our method are as follows: it can obtain the accurate estimation results, but it is no longer dependent of any assumption and is only related to the measured data distribution. Finally, the effectiveness of the proposed method is verified by simulation and field cases.

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28

Ansari, Shahab U., Masroor Hussain, Sarvat M. Ahmad, Ahmar Rashid, and Suleman Mazhar. "STABILIZED MIXED FINITE ELEMENT METHOD FOR TRANSIENT DARCY FLOW." Transactions of the Canadian Society for Mechanical Engineering 41, no. 1 (March 2017): 85–97. http://dx.doi.org/10.1139/tcsme-2017-1006.

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Darcy flow is a steady-state model for laminar flow of a fluid through a porous medium. The present work proposes an extended model of laminar Darcy flow by introducing dynamic pressure and velocity to the classical formulation. The solution of the proposed time-space model is attained by discretizing the problem with a stabilized mixed Galerkin method in space and a forward Euler method in time. The resulting matrix equation is well-posed and is solved using the conjugate gradient (CG) method. The error analysis of the numerical solutions confirms convergence to the actual model.

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29

Zhou, Y., Q. Xu, S. Xing, and X. Hu. "GRAPHICS-IMAGE MIXED METHOD FOR LARGE-SCALE BUILDINGS RENDERING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 1237–41. http://dx.doi.org/10.5194/isprs-archives-xlii-2-1237-2018.

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Urban 3D model data is huge and unstructured, LOD and Out-of-core algorithm are usually used to reduce the amount of data that drawn in each frame to improve the rendering efficiency. When the scene is large enough, even the complex optimization algorithm is difficult to achieve better results. Based on the traditional study, a novel idea was developed. We propose a graphics and image mixed method for large-scale buildings rendering. Firstly, the view field is divided into several regions, the graphics-image mixed method used to render the scene on both screen and FBO, then blending the FBO with scree. The algorithm is tested on the huge CityGML model data in the urban areas of New York which contained 188195 public building models, and compared with the Cesium platform. The experiment result shows the system was running smoothly. The experimental results confirm that the algorithm can achieve more massive building scene roaming under the same hardware conditions, and can rendering the scene without vision loss.

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Prague, Mélanie, and Marc Lavielle. "SAMBA: A novel method for fast automatic model building in nonlinear mixed‐effects models." CPT: Pharmacometrics & Systems Pharmacology 11, no. 2 (February 2022): 161–72. http://dx.doi.org/10.1002/psp4.12742.

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31

Li, Chong, Mingzhao Yang, Yongting Zhang, and Khin Wee Lai. "An Intelligent Mental Health Identification Method for College Students: A Mixed-Method Study." International Journal of Environmental Research and Public Health 19, no. 22 (November 14, 2022): 14976. http://dx.doi.org/10.3390/ijerph192214976.

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Purpose: Mental health assessments that combine patients’ facial expressions and behaviors have been proven effective, but screening large-scale student populations for mental health problems is time-consuming and labor-intensive. This study aims to provide an efficient and accurate intelligent method for further psychological diagnosis and treatment, which combines artificial intelligence technologies to assist in evaluating the mental health problems of college students. Materials and Methods: We propose a mixed-method study of mental health assessment that combines psychological questionnaires with facial emotion analysis to comprehensively evaluate the mental health of students on a large scale. The Depression Anxiety and Stress Scale-21(DASS-21) is used for the psychological questionnaire. The facial emotion recognition model is implemented by transfer learning based on neural networks, and the model is pre-trained using FER2013 and CFEE datasets. Among them, the FER2013 dataset consists of 48 × 48-pixel face gray images, a total of 35,887 face images. The CFEE dataset contains 950,000 facial images with annotated action units (au). Using a random sampling strategy, we sent online questionnaires to 400 college students and received 374 responses, and the response rate was 93.5%. After pre-processing, 350 results were available, including 187 male and 153 female students. First, the facial emotion data of students were collected in an online questionnaire test. Then, a pre-trained model was used for emotion recognition. Finally, the online psychological questionnaire scores and the facial emotion recognition model scores were collated to give a comprehensive psychological evaluation score. Results: The experimental results of the facial emotion recognition model proposed to show that its classification results are broadly consistent with the mental health survey results. This model can be used to improve efficiency. In particular, the accuracy of the facial emotion recognition model proposed in this paper is higher than that of the general mental health model, which only uses the traditional single questionnaire. Furthermore, the absolute errors of this study in the three symptoms of depression, anxiety, and stress are lower than other mental health survey results and are only 0.8%, 8.1%, 3.5%, and 1.8%, respectively. Conclusion: The mixed method combining intelligent methods and scales for mental health assessment has high recognition accuracy. Therefore, it can support efficient large-scale screening of students’ psychological problems.

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Oliynyk, Viktor, Fedir Zhuravka, Tetiana Bolgar, and Olha Yevtushenko. "Optimal control of continuous life insurance model." Investment Management and Financial Innovations 14, no. 4 (December 8, 2017): 21–29. http://dx.doi.org/10.21511/imfi.14(4).2017.03.

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The problems of mixed life insurance and insurance in the case of death are considered in the article. The actuarial present value of life insurance is found by solving a system of differential equations. The cases of both constant effective interest rates and variables, depending on the time interval, are examined. The authors used the Pontryagin maximum principle method as the most efficient one, in order to solve the problem of optimal control of the mixed life insurance value. The variable effective interest rate is considered as the control parameter. Some numerical results were given.

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Qian, Feng Chen, Ning Shan, Ya Lin Ye, Yong Zhong Ma, and Xue Yan Hu. "A Model of Point Multiresolution Rendering Method." Applied Mechanics and Materials 482 (December 2013): 355–58. http://dx.doi.org/10.4028/www.scientific.net/amm.482.355.

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The paper proposed a data compression method in multiresolution structure and realized multiresolution rendering of point model by traversing the KD-tree breadth-first. It established the details control of multiresolution rendering, improved the drawing efficiency of point model. And a simulation study was carried out. Results show that the method could not only reduce the geometry data volume of point models directly, but also reduce the sampling point number without debasing the numerical precision of the model geometry data, so as to further reduce data volume of point model. In addition, the mixed rendering of geometric model point and rectangle in this method overcome the shortcoming that point model set is unsuitable for large flat surface.

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34

Yang, Yuqing, and Shongming Huang. "Comparison of different methods for fitting nonlinear mixed forest models and for making predictions." Canadian Journal of Forest Research 41, no. 8 (August 2011): 1671–86. http://dx.doi.org/10.1139/x11-071.

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Nonlinear mixed models have become popular in forestry applications, and various methods have been proposed for fitting such models. However, it is difficult or even confusing to choose which method to use, and there is not much relevant information available, especially in the forestry context. The main objective of this study was to compare three commonly used methods for fitting nonlinear mixed models: the first-order, the first-order conditional expectation, and the adaptive Gaussian quadrature methods. Both the maximum likelihood and restricted maximum likelihood parameter estimation techniques were evaluated. Three types of data common in forestry were used for model fitting and model application. It was found that the first-order conditional expectation method provided more accurate and precise predictions for two models developed from data with more observations per subject. For one model developed on data with fewer observations per subject, the first-order method provided better model predictions. All three models fitted by the first-order method produced some biologically unrealistic predictions, and the problem was more obvious on the data with fewer observations per subject. For all three models fitted by the first-order and first-order conditional expectation methods, the maximum likelihood and restricted maximum likelihood fits and the resulting model predictions were very close.

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35

Agarwal, Deepali, Priyanka Ravi, Bharathi Purohit, Diptajit Das, Upendra Singh Bhadauria, Charu Khurana, Monica Dev D. S., and Harsh Priya. "Perception Pertaining to Oral and Systemic Health: A Mixed Method Model." Journal of Pierre Fauchard Academy (India Section) 34, no. 3 (June 28, 2020): 87–93. http://dx.doi.org/10.18311/jpfa/2020/25827.

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36

Feizy, Tahereh, Alireza Moghali, Masuod Gramipour, and Reza Zare. "A Mixed Method Research for Finding a Model of Administrative Decentralization." International Journal of Asian Social Science 5, no. 8 (2015): 478–502. http://dx.doi.org/10.18488/journal.1/2015.5.8/1.8.478.502.

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37

Bao, Weimin, and Liping Zhao. "Application of Linearized Calibration Method for Vertically Mixed Runoff Model Parameters." Journal of Hydrologic Engineering 19, no. 8 (August 2014): 04014007. http://dx.doi.org/10.1061/(asce)he.1943-5584.0000984.

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38

Voormeeren, S. N., P. L. C. van der Valk, and D. J. Rixen. "A general mixed boundary model reduction method for component mode synthesis." IOP Conference Series: Materials Science and Engineering 10 (June 1, 2010): 012116. http://dx.doi.org/10.1088/1757-899x/10/1/012116.

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Jin, Mingzhou, and S. David Wu. "A new heuristic method for mixed model assembly line balancing problem." Computers & Industrial Engineering 44, no. 1 (January 2003): 159–69. http://dx.doi.org/10.1016/s0360-8352(02)00190-0.

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40

Krug, B. "Reweighted loglikelihood method in robust estimation in a mixed unbalanced model." Statistica Neerlandica 52, no. 2 (June 1998): 185–99. http://dx.doi.org/10.1111/1467-9574.00077.

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41

Zuo, Liyun, and Yanren Hou. "A two-grid decoupling method for the mixed Stokes–Darcy model." Journal of Computational and Applied Mathematics 275 (February 2015): 139–47. http://dx.doi.org/10.1016/j.cam.2014.08.008.

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42

Dong, Jietao, Linxuan Zhang, and Tianyuan Xiao. "Part supply method for mixed-model assembly lines with decentralized supermarkets." Tsinghua Science and Technology 21, no. 4 (August 2016): 426–34. http://dx.doi.org/10.1109/tst.2016.7536720.

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43

McMullen, P. R., and Peter Tarasewich. "A beam search heuristic method for mixed-model scheduling with setups." International Journal of Production Economics 96, no. 2 (May 2005): 273–83. http://dx.doi.org/10.1016/j.ijpe.2003.12.010.

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Purwandari, Septiyati, Aftina Nurul Husna, and Tawil Tawil. "Islamic Parenting Model to Increase Family Literacy: A Mixed Method Study." International Journal of Islamic Educational Psychology 3, no. 2 (December 10, 2022): progress. http://dx.doi.org/10.18196/ijiep.v3i2.14039.

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This study aims to test the effectiveness of a new model of Islamic parenting based on family religiousness to solve the low literacy issue in Muslim families. Using a mixed method with triangulation design, in Study 1, the researchers conducted action research by delivering six sessions parent training program to 10 women with children aged ±11 years old, grouped into high and low-literate families. Each session was followed with practice at home guided by facilitators. Data were collected using interviews and parents’ reflection journals and were analyzed using content analysis. In Study 2, concurrent to Study 1, we conducted quasi-experimental research using one group pre-test and post-test design to test the model’s effectiveness. Before and after the programs, we administered the Family Literacy Questionnaire to the women and the Literacy Activity Questionnaire to their children. The data were analyzed using Wilcoxon signed rank test to test differences between pre-test and post-test scores. The program was perceived as impactful and highly appreciated by the participants, who expected its continuation in the future. The Islamic parenting model effectively enhanced women’s family literacy in low literacy groups and children’s literacy activity in both groups.

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Setti, L., and S. Lefeuvre. "Model of a loaded 3D multimode cavity using a mixed method: 2D finite element method and modal analysis." IEEE Transactions on Magnetics 31, no. 3 (May 1995): 1574–77. http://dx.doi.org/10.1109/20.376332.

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46

Yang, Qing, and Yirang Yuan. "An Approximation of Three-Dimensional Semiconductor Devices by Mixed Finite Element Method and Characteristics-Mixed Finite Element Method." Numerical Mathematics: Theory, Methods and Applications 8, no. 3 (August 2015): 356–82. http://dx.doi.org/10.4208/nmtma.2015.my12031.

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AbstractThe mathematical model for semiconductor devices in three space dimensions are numerically discretized. The system consists of three quasi-linear partial differential equations about three physical variables: the electrostatic potential, the electron concentration and the hole concentration. We use standard mixed finite element method to approximate the elliptic electrostatic potential equation. For the two convection-dominated concentration equations, a characteristics-mixed finite element method is presented. The scheme is locally conservative. The optimalL2-norm error estimates are derived by the aid of a post-processing step. Finally, numerical experiments are presented to validate the theoretical analysis.

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DOUGLAS, JIM, JUAN E. SANTOS, and DONGWOO SHEEN. "A NONCONFORMING MIXED FINITE ELEMENT METHOD FOR MAXWELL'S EQUATIONS." Mathematical Models and Methods in Applied Sciences 10, no. 04 (June 2000): 593–613. http://dx.doi.org/10.1142/s021820250000032x.

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We present a nonconforming mixed finite element scheme for the approximate solution of the time-harmonic Maxwell's equations in a three-dimensional, bounded domain with absorbing boundary conditions on artificial boundaries. The numerical procedures are employed to solve the direct problem in magnetotellurics consisting in determining a scattered electromagnetic field in a model of the earth having bounded conductivity anomalies of arbitrary shapes. A domain-decomposition iterative algorithm which is naturally parallelizable and is based on a hybridization of the mixed method allows the solution of large three-dimensional models. Convergence of the approximation by the mixed method is proved, as well as the convergence of the iteration.

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Lai, Ling Hong. "Mixed-Model Flow Production Scheduling Method Based on Multi-Agent and Hybrid Genetic Algorithm." Applied Mechanics and Materials 63-64 (June 2011): 399–402. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.399.

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To solve the dynamic and complex problem of production scheduling, depending on the introduction between multi-agent and hybrid genetic algorithm in mixed-model flow production scheduling, this paper proposed a mixed-model flow production scheduling method based on multi-agent and hybrid genetic algorithm. On the basis of this model, the mixed-model flow production scheduling procedure and strategy based on multi-agent and hybrid genetic algorithm were established. Finally, mixed-model flow production scheduling simulation system based on multi-agent and hybrid genetic algorithm was demonstrated and validated by QUEST software. It has shown the proposed method can improve the benefit of production scheduling, and provide a support for adapting to complex and dynamic production scheduling in mixed-model flow production.

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Jiao, Wenjiang, Xingwu Jia, Yuetong Liu, Qun Jiang, and Ziyi Sun. "Single image mixed dehazing method based on numerical iterative model and DehazeNet." PLOS ONE 16, no. 7 (July 30, 2021): e0254664. http://dx.doi.org/10.1371/journal.pone.0254664.

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As one of the most common adverse weather phenomena, haze has caused detrimental effects on many computer vision systems. To eliminate the effect of haze, in the field of image processing, image dehazing has been studied intensively, and many advanced dehazing algorithms have been proposed. Physical model-based and deep learning-based methods are two competitive methods for single image dehazing, but it is still a challenging problem to achieve fidelity and effectively dehazing simultaneously in real hazy scenes. In this work, a mixed iterative model is proposed, which combines a physical model-based method with a learning-based method to restore high-quality clear images, and it has good performance in maintaining natural attributes and completely removing haze. Unlike previous studies, we first divide the image into different regions according to the density of haze to accurately calculate the atmospheric light for restoring haze-free images. Then, dark channel prior and DehazeNet are used to jointly estimate the transmission to promote the final clear haze-free image that is more similar to the real scene. Finally, a numerical iterative strategy is employed to further optimize the atmospheric light and transmission. Extensive experiments demonstrate that our method outperforms existing state-of-the-art methods on synthetic datasets and real-world datasets. Moreover, to indicate the universality of the proposed method, we further apply it to the remote sensing datasets, which can also produce visually satisfactory results.

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Krulikovská, T., E. Jarošová, and P. Patáková. "Evaluation of Rhodotorula growth on solid substrate via a linear mixed effects model." Czech Journal of Food Sciences 29, No. 4 (August 10, 2011): 400–410. http://dx.doi.org/10.17221/327/2009-cjfs.

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The growth of Rhodotorula glutinis and Rhodotorula mucilaginosa was studied under optimal and stress cultivation conditions at 10°C and 20°C for 14 days. The method of image analysis was used to determine the size of colonies. The linear mixed effects model implemented in the statistical program S-PLUS was applied to analyse the repeated measurements. Two-phase kinetics was confirmed and the mean growth rates in the second linear phase under various stress conditions were estimated. The results indicated a higher growth rate of R. mucilaginosa than was that of R. glutinis under all cultivation conditions. The highest growth rate of was observed during the cultivation of R. mucilaginosa in media with 2% of NaCl at 20°C. The impact of neglecting the fact that repeated data are not independent and using the classical regression model instead of the mixed effects model was demonstrated through the comparison of the confidence intervals for the parameters based on both approaches. While the point estimates of the corresponding parameters were similar, the width of the confidence intervals differed substantially.

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