Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”

Table_1_Bioprospecting Trichoderma: A Systematic Roadmap to Screen Genomes and Natural Products for Biocontrol Applications.XLSX by Tomás A. Rush (11440123)

The number of inactive nodes as a function of time steps at higher values of <i>P</i> and <i>α</i> in (a) a random network and (b) a scale-free network. by Waseem Al-Aqqad (14123917)

As for Fig 2, we present failure rates as a function of the cohort size (vertical axis) versus the number of distractors (horizontal axis), for the Smyth and McClave baseline algor... by Daniela Huppenkothen (9174507)

“…In the upper right, a case where the embedded cohort has uniform targets across both attributes, but the distractors added are skewed with <i>f</i>_random = 0.1. …”

Complementary cumulative distribution functions of in degree distribution and fitted power law, lognormal and truncated power law distributions. by Olga Valba (10531121)

Algorithm 1. by Muhammad Zubair Rehman (11243478)

Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>14−<i>f</i>23. by Ying Li (38224)

“…<p>Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>14−<i>f</i>23.…”

Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>8−<i>f</i>13. by Ying Li (38224)

“…<p>Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>8−<i>f</i>13.…”

Relationship between bistability and resettability. by Takashi Naka (272391)

Dataset for 'An Automated Workflow of Deep Learning Ensemble Model with Principal Component Analysis for Enhanced Material Characterisation in Energy Dispersive Spectroscopy' by Fanzhi Su (21005174)

Subject characteristics. by Dominique Vincent-Genod (20552594)

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Research data. by Dominique Vincent-Genod (20552594)

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Generated blended data using mouse brain cells and human embryonic heart cells, labeled as <i>Mix</i>[<i>a</i>,<i>b</i>,<i>c</i>], indicates the proportion of mouse brain cells fou... by Nuray Sogunmez Erdogan (21533872)

Attack and defense behaviors with the sensory–motor algorithm between a single predator and a single prey. by Hiroyuki Ichijo (13891153)

Network Gradient Descent Algorithm for Decentralized Federated Learning by Shuyuan Wu (57425)

“…This greatly enhances the reliability of the entire algorithm. Those nice properties inspire us to carefully study the NGD method both theoretically and numerically. …”

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

The process of function F in the improved Blowfish algorithm. by Sathish Kaveripakam (16940710)

MEDOC: A Fast, Scalable, and Mathematically Exact Algorithm for the Site-Specific Prediction of the Protonation Degree in Large Disordered Proteins by Martin J. Fossat (3714079)

“…While it is often convenient to assume that these residues follow their model-compound p<i>K</i>_a values, recent work has shown that local charge effects (charge regulation) can upshift or downshift side chain p<i>K</i>_a values with major consequences for molecular function. …”

Results of the PSO-Kmeans-ANMS algorithm for the Rastrigin function. by Rutinaldo Aguiar Nascimento (14259594)

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Results of the PSO-Kmeans-ANMS algorithm for the Rosenbrock function. by Rutinaldo Aguiar Nascimento (14259594)

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