Showing 161 - 180 results of 230 for search '(( binary data using optimization algorithm ) OR ( binary a robust optimization algorithm ))', query time: 0.37s Refine Results
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    Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model by Getachew S. Molla (6416744)

    Published 2019
    “…Moreover, a design of experiments is included in the methodology to generate and use experimental data appropriately for model parameter regression and model validation. …”
  12. 172

    Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

    Published 2021
    “…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”
  13. 173

    A new fast filtering algorithm for a 3D point cloud based on RGB-D information by Chaochuan Jia (7256237)

    Published 2019
    “…This method aligns the color image to the depth image, and the color mapping image is converted to an HSV image. Then, the optimal segmentation threshold of the V image that is calculated by using the Otsu algorithm is applied to segment the color mapping image into a binary image, which is used to extract the valid point cloud from the original point cloud with outliers. …”
  14. 174

    Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level by Giovanni Nattino (561797)

    Published 2021
    “…Few studies, however, have used matching designs with more than two groups, due to the complexity of matching algorithms. …”
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    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes by Yu Y. (3096192)

    Published 2022
    “…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”
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    Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX by Umesh C. Sharma (10785063)

    Published 2021
    “…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …”