The objective function values of scheduling schemes considering extreme scenarios. by Yuanpeng Hua (19146645)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

Genes with rare, predicted damaging variants identified by exome sequencing in multiple affected members within 19 families with left sided defects. by David M. Gordon (3259002)

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Friedman test average rankings of IFOX and competing optimization algorithms across CL, C17, C19, C21, C22, and RWPs. The “Position” column indicates the overall rank based on the... by Mahmood A. Jumaah (22272371)

The objective function value of the most economical scheme of the deterministic optimization model. by Yuanpeng Hua (19146645)

The objective function value of the most economical solution for interval optimization model. by Yuanpeng Hua (19146645)

Functional modules. by Mehrnaz Shoushtarian (6411299)

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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Python implementation from Symplectic decomposition from submatrix determinants by Jason L. Pereira (11598632)

“…Python implementation of the algorithm and demonstration of how to use the functions.…”

GraSPy: an Open Source Python Package for Statistical Connectomics by Benjamin Pedigo (6580352)

“…We developed GraSPy, an open-source Python toolkit for statistical inference on graphs. …”

Rare variants in <i>SMYD1</i> and <i>BMP10</i> identified in family 346 are functionally damaging. by David M. Gordon (3259002)

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Average Friedman test ranks (left) and pairwise average Wilcoxon signed-rank test p-values (right) for all compared optimization algorithms across CL, C17, C19, C21, C22, and RWPs. by Mahmood A. Jumaah (22272371)

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

The workflow used to analyze imbalanced and balanced sequences. by Solomon Shiferaw Beyene (9143178)

Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)

Accuracy, sensitivity, specificity and F-score. by Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)