Cleavage time as a function of scaled fiber diameter. حسب Roukayatou R. Ouedraogo (20460980)

Median fiber cleavage time (black) and the fraction of successful runs (red) for different parameter values. حسب Roukayatou R. Ouedraogo (20460980)

Distribution of objective function values solved by three algorithms. حسب Meilin Zhu (688698)

Algorithm test with a 4mm deep. حسب Nicolas Herzig (9230425)

The performance evaluation of various image contrast enhancement approaches using test images 4. حسب Xiaowen Zhang (83669)

Functional enrichment analyses of Co-genes. حسب Qingcong Zheng (11169094)

Fig 1 - حسب Hind Sweis (18880638)

Fig 4 - حسب Hind Sweis (18880638)

Fig 2 - حسب Hind Sweis (18880638)

Fig 3 - حسب Hind Sweis (18880638)

Swarm intelligence algorithms for multi-objective max-min-ISP حسب Francisco Muñoz (9455441)

"…<p>Algorithms implemented on article "<strong>On the max-min influence spread problem: A multi-objective optimization approach</strong>"</p> <p><br></p> <p>usage: Main.py [-h] [-a] [-r] [-d D] [-t T] [-i I] [-q Q] [--shape SHAPE] [--sym] [--folder FOLDER] [--seed SEED] [--spread SPREAD] [--sum SUM] [--mh MH] [--tagsfile TAGSFILE] [--notags] [--prune] [--prunelowdeg] [--excludenodes EXCLUDENODES] [--includeindegzero] [--nodepthcriteria] [--memfile MEMFILE] file</p> <p><br></p> <p>Calculates the best Influence Spread set on a Weighted Graph using PSO</p> <p><br></p> <p>positional arguments:</p> <p>file</p> <p><br></p> <p>options:</p> <p>-h, --help: show this help message and exit</p> <p>-a: read file input contents as an Adjacency Matrix</p> <p>-r: reverse nodes order, reads (b,a,w) instead of (a,b,w)</p> <p>-d D: line separator to use on file parsing</p> <p>-t T: number of times to execute this solver</p> <p>-i I: number of metaheuristic iterations per execution</p> <p>-q Q: fixed quota, use 0 = floor(n/2)+1</p> <p>--shape SHAPE: shape functions for binarization - list of implemented shape functions: s2, s2_neg, v2, v4</p> <p>--sym: consider graph as symmetric instead of directed</p> <p>--folder FOLDER: output folder</p> <p>--seed SEED: use custom seeds for metaheuristic pseudo RNG</p> <p>--spread SPREAD: use specific influence spread model funcion - list of implemented models: LT, IC</p> <p>--sum SUM: adds an extra value to all edge's weight</p> <p>--mh MH: metaheuristic to use - list of implemented metaheuristics: 1 (Swarm3), 3 (Swarm3_W), 4 (Swarm3_L), 5 (Swarm4)</p> <p>--tagsfile TAGSFILE: use first row as node tags instead of using plurality criteria</p> <p>--notags: do not use first row as node tags, instead tags will be calculated</p> <p>--prune: nodes with (1) outdegree = 0 and indegree > 0, and (2) with outdegree = 1 and neighbor's outdegree > 0 will be excluded</p> <p>--prunelowdeg: nodes with low outdegree or degree will be excluded</p> <p>--excludenodes EXCLUDENODES: nodes to skip, must be comma separated</p> <p>--includeindegzero: forces to include nodes with indegree = 0 on all executions</p> <p>--nodepthcriteria: particles will not tie off with spread depth in case of having same fitness and spread</p> <p>--memfile MEMFILE: memory dump of other execution</p>…"

(Movie for Fig 2B) Same as S1 Movie but using a small value for the <i>r</i> parameter. حسب Toviah Moldwin (10866708)

(Movie for Fig 3C) Dynamics of synaptic clustering for a G-clusteron trained on positive-labeled input patterns from a multivariate Gaussian dataset with multiple groups of positiv... حسب Toviah Moldwin (10866708)

(Movie for Fig 3D) Same as S4 Movie, but with negative-labeled input patterns. حسب Toviah Moldwin (10866708)

(Movie for Fig 2C) Similar to S1 Movie, but trained on a negative example, with synapse locations initiated such that synapses are clustered with same-sign input values. حسب Toviah Moldwin (10866708)

(Movie for Fig 2A) Dynamics of synaptic clustering due to the G-clusteron location update rule, using a large value for the <i>r</i> parameter and trained on a single positive-labe... حسب Toviah Moldwin (10866708)

Comparison of the user-friendly graphical interfaces and functions of the single nucleotide polymorphism (SNP) analysis pipelines. حسب Dong-Jun Lee (14068673)

Robotic Prototype with Human Mimicry Abilities - 104 Algorithms (RPHMA^104a): Toward an Integrative Computational-Robotic Theory of Very Complex Skills حسب Maicon S. Aliaga Machado (20468810)

"…<p dir="ltr"><b>Abstract</b></p><p dir="ltr">This paper introduces the RPHMS^104a model (Robotic Prototype with Human Mimicry Abilities - 104 Algorithms), a framework for the progressive development of artificial systems capable of emulating human cognitive-behavioral functions. …"

Supplementary Figure S4 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Convergence curves on the functions CL4, CL11, CL13, CL14, CL18, CL19, C17F1, C17F2, and C17F4. حسب Mahmood A. Jumaah (22272371)