بدائل البحث:
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
algorithm cep » algorithm cl (توسيع البحث), algorithm co (توسيع البحث), algorithm seu (توسيع البحث)
cep function » cell function (توسيع البحث), step function (توسيع البحث), t4p function (توسيع البحث)
algorithms a » algorithms _ (توسيع البحث), algorithm a (توسيع البحث), algorithm _ (توسيع البحث)
a function » _ function (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
algorithm cep » algorithm cl (توسيع البحث), algorithm co (توسيع البحث), algorithm seu (توسيع البحث)
cep function » cell function (توسيع البحث), step function (توسيع البحث), t4p function (توسيع البحث)
algorithms a » algorithms _ (توسيع البحث), algorithm a (توسيع البحث), algorithm _ (توسيع البحث)
a function » _ function (توسيع البحث)
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a) FO Function, b) FI function.
منشور في 2023"…The SRL32 primitive (Reconfigurable Look up Tables—RLUTs) and DPR (Dynamic Partial Reconfiguration) are employed to reconfigure single round MISTY1 / KASUMI algorithms on the run-time. The RLUT based architecture attains dynamic logic functionality without extra hardware resources by internally modifying the LUT contents. …"
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149
2lpiRNApred: a two-layered integrated algorithm for identifying piRNAs and their functions based on LFE-GM feature selection
منشور في 2020"…A new feature selection algorithm, which was based on Luca fuzzy entropy and Gaussian membership function (LFE-GM), was proposed to reduce the dimensionality of the features. …"
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150
The ALO algorithm optimization flowchart.
منشور في 2024"…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …"
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The IALO algorithm solution flowchart.
منشور في 2024"…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …"
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CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages
منشور في 2024"…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …"
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CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages
منشور في 2024"…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …"
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CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages
منشور في 2024"…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …"
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Algorithm pseudocode.
منشور في 2025"…In order to improve the clarity and visual effect of product appearance design, a visual edge feature enhancement method for product appearance design images based on an improved Retinex algorithm is proposed. …"
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Efficient algorithms to discover alterations with complementary functional association in cancer
منشور في 2019"…We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. …"
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An Efficient Algorithm for Minimizing Multi Non-Smooth Component Functions
منشور في 2021"…<p>Many problems in statistics and machine learning can be formulated as an optimization problem of a finite sum of nonsmooth convex functions. We propose an algorithm to minimize this type of objective functions based on the idea of alternating linearization. …"
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