The 10 features captured by persistence fingerprint. by Yuxi Long (11024307)

Subjects:

Representative neurons and their corresponding step functions. by Reem Khalil (10898163)

Test on the remeshing algorithm with <i>N</i> = 50 points. by Ondrej Maxian (8722185)

ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space by Koushik Naskar (7510592)

“…In order to overcome such shortcoming, we develop a generalized algorithm, “ADT” to generate the nonadiabatic equations through symbolic manipulation and to construct highly accurate diabatic surfaces for molecular processes involving excited electronic states. …”

Fitness comparison on test function. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Surface Effect of Small Nanocrystals on the Accuracy of Structural Parameters Obtained by Pair Distribution Function Analysis by Merdan Batyrow (20808619)

Subjects:

Results from the performance-based assessments of hand function for PALS and the age/sex matched healthy subgroup. by Conor D. Hayden (20855587)

Simple sequence of numbers generated by the cos function. by Kiyoshiro Okada (10711332)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

“…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …”

Alignment of amino-acids sequence of nucleotide-binding domains of Ssa1 with DnaK from <i>E</i>. <i>coli</i> using the Needleman-Wunsch algorithm for global alignment. by Deepika Gaur (814560)

SP results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

MS results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

Results of human and algorithmic categorization performance. by John K. Tsotsos (7435094)

“…C: Performance of the top 3 saliency algorithms (oSALICON, eDN and DeepGaze II). The plot shows the percentage of correct responses (vertical axis) vs the percentage of the target within the parafovea.…”

Width of stripes as a function of time. by Pratik Mullick (12851011)

Fig 2 - by Alireza Rangrazjeddi (13360943)

Subjects:

In each subplot we show in yellow the (vertical) for arm-2 as a function of the number of SNPs corresponding to each -threshold (horizontal, log-scale). by Caroline C. McGrouther (5216153)

Results of the SSIM measure for all algorithms. by Chuang Zhang (2199421)

“…A levy flight strategy further improves the algorithm’s ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. …”

Results of Fridman test for all algorithms. by Chuang Zhang (2199421)

“…A levy flight strategy further improves the algorithm’s ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. …”

Results of the PSNR measure for all algorithms. by Chuang Zhang (2199421)

“…A levy flight strategy further improves the algorithm’s ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. …”

Results of the FSIM measure for all algorithms. by Chuang Zhang (2199421)

“…A levy flight strategy further improves the algorithm’s ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. …”