ABIDE dataset subject demographics. حسب Alexandria M. Jensen (6494957)

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Linear kernel: Power and Type I error for cluster evaluation metric simulations. حسب Alexandria M. Jensen (6494957)

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P-values from analysis of ABIDE dataset for binary outcome of diagnostic group. حسب Alexandria M. Jensen (6494957)

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Examples of four simulated networks and adjacency matrices. حسب Alexandria M. Jensen (6494957)

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P-values from analysis of ABIDE dataset for continuous outcome of VIQ. حسب Alexandria M. Jensen (6494957)

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Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

"…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …"

Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... حسب Ziyan Jin (21021976)

Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter. حسب Yasamin Tabatabaee (18095491)

Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm حسب Gelio Alves (51850)

"…To overcome this limitation, we implemented an expectation-maximization (EM) algorithm, along with a biological function database, within the MiCId workflow. …"

Comparison of computational cost between SBOA and MESBOA. حسب Yuqi Xiong (12343771)

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-value on CEC2022 (dim = 20). حسب Yuqi Xiong (12343771)

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Flowchart of low-light image enhancement based on MESBOA. حسب Yuqi Xiong (12343771)

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Flowchart of low-light image enhancement based on MESBOA. حسب Yuqi Xiong (12343771)

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Precision elimination strategy. حسب Yuqi Xiong (12343771)

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Results of low-light image enhancement test. حسب Yuqi Xiong (12343771)

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Evaluation metrics obtained by SBOA and MESBOA. حسب Yuqi Xiong (12343771)

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Lens imaging opposition-based learning. حسب Yuqi Xiong (12343771)

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Test functions. حسب Kejia Liu (5699651)

"…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …"

Comparison between the proposed framework with and without Fourier Loss Function for Rain100H. حسب Chaobing Zheng (20896579)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs حسب Zahir Barahmand (18008947)

"…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…"