PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

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)

Hist-8000 sequence similarity scores are closer to the ground truth than the corresponding Sum-of-learnt-Trigrams scores. (NW, Hist-8000) and (NW, Hist-SDM12) are both higher than... by Frixos Papadopoulos (22001664)

Frequency-dependent pre- and post- synaptic plasticity in rate-based models. by Toviah Moldwin (10866708)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs by Zahir Barahmand (18008947)

“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”

Workflow of the BOMS algorithm. by Ocima Kamboj (21533199)

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

Membership function of output for tank 2. by Tamiru Demelash Kassie (20678515)

ClaritySpectra: Raman spectra analysis tool by Aaron Celestian (9395696)

“…</li></ul><h3>PEAK FITTING </h3><ul><li>Automated background subtraction using asymmetric least squares fitting</li><li>A new suggested background feature that lets you preview the background that you like best</li><li>Interactive background fitting lets you further tune the background to perfection</li><li>Four choice of peaks: Gaussian, Lorentzian, Pseudo-Voigt, and the new Asymmetric Voigt functions</li><li>Overlapping view of how well the peaks fit with quality metrics</li><li>No need to define regions, the algorithm is smart enough to what a peak looks like.…”

ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... by G. Christopher Marais (21492084)

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

Modeling Molecularly Imprinted Nanoparticles with LNKD: A Resource Efficient Algorithm for Polymer Cross-Linking by Emma Stevens (22257358)

“…Here, we propose LNKD (Linking Nodes in KD-trees), a resource-efficient algorithm for predicting pairs of reactive atoms in pre-cross-linked 3D structures of monomers that applies not only to the modeling of MIPs, but also chemical cross-linking in other materials. …”

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

Membership function of error E2 for tank 2. by Tamiru Demelash Kassie (20678515)

Overview of mouse ovary analysis using Vizgen MERFISH data. by Ian K. Gingerich (22822222)

Spatial domain analysis of the mouse olfactory bulb using STOmics Stereo-seq data. by Ian K. Gingerich (22822222)

RASP performance across different scales in the Mouse Sagittal brain dataset. by Ian K. Gingerich (22822222)

Spatial domain analysis of human breast cancer tissue using 10x Xenium data. by Ian K. Gingerich (22822222)

Human dorsolateral prefrontal cortex (DLPFC) spatial transcriptomics analysis, 10X Visium data. by Ian K. Gingerich (22822222)

Covariate analysis (Mouse ovary dataset) for the cell type clustering case. by Ian K. Gingerich (22822222)