Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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<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.…”

CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20. by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

Power flow and cost optimization with Improved PSO algorithm (b). by Muhammad Ahmad Iqbal (11851338)

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CPU usage of benchmark function: (a) CPU Usage during the Execution of Benchmark Functions F21-F30, (b) CPU Usage during the Execution of Benchmark Functions F31-F40 and (c) CPU Us... by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

Iteration curve of benchmark function: (a) Convergence curves of the average best fitness for functions F21-F30, (b) Convergence curves of the average best fitness for functions F3... by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

a) FO Function, b) FI function. by Huang Jiexian (17060975)

“…The SRL32 primitive (Reconfigurable Look up Tables—RLUTs) and DPR (Dynamic Partial Reconfiguration) are employed to reconfigure single round MISTY1 / KASUMI algorithms on the run-time. The RLUT based architecture attains dynamic logic functionality without extra hardware resources by internally modifying the LUT contents. …”

Power flow and cost optimization with APSO variant-16 of APSO algorithm (b). by Muhammad Ahmad Iqbal (11851338)

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An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b>⁰ (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …”

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

An example of our color correction algorithm (with primary surface function <i>f</i>₁). by Guixiang Zhang (383795)

The specific implementation of the BioRS function in the molecular biological aspect. by Alexander V. Spirov (11302085)

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Examples of parametric 2d-spatial varying functions. by Guixiang Zhang (383795)

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Brief sketch of the quasi-attraction/alignment algorithm. by Takayuki Niizato (162226)

“…(D) A brief sketch of the avoidance algorithm. Upper: Each direction is extended to the repulsion area = {<b><i>r</i></b>||<b><i>r</i></b>| = <i>R</i>}, where is the minimal sphere cap that covers all points on . …”