EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…For a RDKit molecule, it provides (i) a PNG binary string with an image of the molecule with color-highlighted functional groups; (ii) a list of sets of atom indices (idx), each set corresponding to a functional group; (iii) a list of pseudo-SMILES canonicalized strings for the full functional groups; and (iv) a list of RDKit labeled mol objects, one for each full functional group. …”

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz by Faizan Ali (21689861)

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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

<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.…”

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

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Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

Membership function of output for tank 1. by Tamiru Demelash Kassie (20678515)

Overview of the Cell2Spatial algorithm. by Huamei Li (8815955)

Membership function of error E1 for tank 1. by Tamiru Demelash Kassie (20678515)

Comprehensive Re, F1 and Pre values of FcaNet-CycleGAN model. by Xiaojun Wang (50332)

Comparison of optimization performance of six ABC algorithms. by Shuhui Yu (1535500)

Kinematic features for all patients before (PRE) and one year after surgery (P1Y) as well as all control group values. by Xavier Gasparutto (8374578)

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Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

A flow diagram to explain the algorithm named 2BDP (Biomarker Discovery Process at Binomial Decision Point) that we used to find the best fitting model to predict RRiF. by Nabarun Chakraborty (535772)

PyNoetic’s pre-processing module, which supports filtering and artifact removal, including ICA. by Gursimran Singh (575288)

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

Average function evaluation times of the three optimization algorithms. by Shuhui Yu (1535500)

Spike sorting performance dependence on pre-recording duration. by Tjitse van der Molen (20391106)

Functional Projection <i>K</i>-means by Roberto Rocci (16022201)

“…<p>A new technique for simultaneous clustering and dimensionality reduction of functional data is proposed. The observations are projected into a low-dimensional subspace and clustered by means of a functional <i>K</i>-means. …”

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