<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

Activation functions: Sigmoid function and ReLU function. by Wan-Hua Zhang (21601139)

Examples of between- and within-community Beta distributions. by Alexandria M. Jensen (6494957)

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Distribution of cross correlations in functional connectivity in ABIDE sample. by Alexandria M. Jensen (6494957)

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Overview of the wavess algorithm and R package. by Narmada Sambaturu (4989539)

Reward function related parameters. by Honglei Pang (22693724)

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Analysis of ABIDE dataset: Conventional regression frameworks for optimized algorithmic value. by Alexandria M. Jensen (6494957)

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Comparison of algorithms across metrics in test problems. by Jihui Hu (19812736)

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Performance comparison of different mainstream algorithms. by Haisong Xu (141729)

Function <i>χ</i>_<i>opt</i> superimposed with the phase-field function indicating the channel geometry. by Martina Bukač (20161460)

Comparison of average precision means of different algorithms. by Haisong Xu (141729)

Algorithm comparison experiment on the RSOD dataset. by Pingping Yan (462509)

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ANOVA was performed to test the differences between the algorithms for each indicator. by Jihui Hu (19812736)

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Heatmap results from the global sensitivity analysis for the generation of villous vessels within a placentone. by Diana C. de Oliveira (9220729)

The phase-field function for three different network configurations considered in this work. by Martina Bukač (20161460)

Algorithm comparison experiment on the NWPU VHR-10 dataset. by Pingping Yan (462509)

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Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

“…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …”

Classification algorithm implemented in SPARTA. by Baptiste Ruiz (20285217)

Comparison of different algorithms. by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

Pictorial representation of isomorphically scaling down spots within a fixed field of view and corresponding imaging configuration. by Nicholas H. Vitale (20469289)