The skeleton algorithm identifies mitochondrial density in sample images from cells. by Margarita M. Ivanova (11604141)

Detailed information of benchmark functions. by Guangwei Liu (181992)

“…In Case 1, the GJO-GWO algorithm addressed eight complex benchmark functions. …”

Schematics for gmxapi operations. by M. Eric Irrgang (4487278)

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

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Example of an application of functional safety-critical energy optimization reallocation tasks. by Zhiqun Lin (1429501)

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

APSO–WOA–CNN algorithm’s minimal fitness values modified over iterations. by Ahmed Bahaa (12887063)

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

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Algorithm parameter levels. by Peng Yao (448155)

“…Alternatively, the formulated objective functions often deviate from real-world scenarios. …”

Experimental optimization results for dimension 10 using reported competitor algorithms on the unimodal, multimodal, hybrid, and composite of CEC2022 benchmark functions. by WanRu Zhao (18980374)

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<i>S</i>_<i>c</i> of ch150, rat575 and fl1400 for algorithms of each group. by Jin Zhang (53297)

Parselmouth for bioacoustics: automated acoustic analysis in Python by Yannick Jadoul (11498813)

“…Five years ago, the Python package Parselmouth was released to provide easy and intuitive access to all functionality in the Praat software. …”

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. …”

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)

“…Whiskers show the lowest and highest values within 1.5 × <i>IQR</i> from the first and third quartiles, respectively. …”

Smoothing curve from GAM model in which the survival of smaller cluster has been modeled as a smooth function of the sample size. by Muhammad Atif (2575789)

Smoothing curve from GAM model in which the survival of smaller cluster has been modeled as a smooth function of the sample size. by Muhammad Atif (2575789)

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

Smooth functions for the GAMMs showing the influence of significant covariates on the NASC values of echo-classes 1 to 4. by Pavanee Annasawmy (14570135)

Performance of the IERWHO algorithm in 50 runs of four LAA models. by WanRu Zhao (18980374)

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