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processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
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binary data » primary data (Expand Search), dietary data (Expand Search)
binary d » binary _ (Expand Search), binary b (Expand Search)
d while » a while (Expand Search), red while (Expand Search), de chile (Expand Search)
processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
while optimization » whale optimization (Expand Search), wolf optimization (Expand Search), phase optimization (Expand Search)
data processing » image processing (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary d » binary _ (Expand Search), binary b (Expand Search)
d while » a while (Expand Search), red while (Expand Search), de chile (Expand Search)
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101
Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF
Published 2021“…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …”
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102
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
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103
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104
Fortran & C++: design fractal-type optical diffractive element
Published 2022“…</p> <p>(2) calculate diffraction fields for fractal and/or grid-matrix (binary) phase-holograms.</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …”
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105
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
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106
Seed mix selection model
Published 2022“…The genetic algorithm then operated over 1000 iterations, applying crossover and mutation processes to optimize bee richness. …”
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107
Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
Published 2025“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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108
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…Details on the data sourcing process, prompt engineering strategies for large language model (LLM)-based extraction, and validation protocols are provided in the Supplementary Information section.…”