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

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by Pascal Wang (10130612)

“…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …”

Simulation Results Plot of the SBW System Response: (a) Step response curve of the SBW system; (b) Sine response curve of the SBW system; (c) Steady state error curve of the SBW sy... by Honglei Pang (22693724)

Simulation Results Plot of the EMB System Response: (a) Step response curve of the EMB system; (b) Sine response curve of the EMB system; (c) Steady state error curve of the EMB sy... by Honglei Pang (22693724)

BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)

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. …”

Bespoke software controls the sorter GUI and reports on instrument status to the user. by Diane M. Wiener (1956583)

Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective by Xiangyang Jia (10026932)

Multidomain, Automated Photopatterning of DNA-functionalized Hydrogels (MAPDH). by Moshe Rubanov (7289156)

“…The algorithm incorporates a wash step between each round of patterning. …”

Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by Daniel Pérez Palau (11097348)

“…</a></p><p dir="ltr">More information:</p><ul><li><a href="https://www.hatemedia.es/" rel="nofollow" target="_blank">https://www.hatemedia.es/</a> or contact: <a href="mailto:elias.said@unir.net" target="_blank">elias.said@unir.net</a></li><li>This algorithm is related to the hate/non-hate classification algorithm, also developed by the authors: <a href="https://github.com/esaidh266/Algorithm-for-detection-of-hate-speech-in-Spanish" target="_blank">https://github.com/esaidh266/Algorithm-for-detection-of-hate-speech-in-Spanish</a></li><li>This algorithm is related to the algorithm for classifying hate expressions by intensities in Spanish, also developed by the authors: <a href="https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-intensities-in-Spanish" target="_blank">https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-intensities-in-Spanish</a></li></ul><p></p>…”

Data_Sheet_1_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).docx by Niklas Pallast (6796196)

“…Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. …”

Data_Sheet_2_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).pdf by Niklas Pallast (6796196)

“…Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. …”

Principal component analysis (PCA) of sub-layer mean intensities. by Maëlle Vilbert (17101954)

Schematic example of multiscale modelling implementation. by Robyn M. Stuart (3754000)

Presentation_1_NeuroEditor: a tool to edit and visualize neuronal morphologies.pdf by Ivan Velasco (9463019)

“…Moreover, NeuroEditor can be easily extended by users, who can program their own algorithms in Python and run them within the tool. Last, this paper includes an example showing how users can easily define a customized workflow by applying a sequence of editing operations. …”

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows by Pierre-Alexis DELAROCHE (22092572)

“…When using this data in your research, please cite: @dataset{ecological_benchmark_2025, title={An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows}, author={AlbumForge Research Team}, year={2025}, publisher={Figshare}, doi={10.6084/m9.figshare.XXXXXXX}, url={https://figshare.com/articles/dataset/XXXXXXX} } Contributing and Data Governance Issue Reporting Technical issues, data quality concerns, or methodological questions should be reported via GitHub Issues with the following template: **Issue Type**: [Bug Report / Data Quality / Methodology Question] **Hardware Configuration**: [Specify if applicable] **Dataset Version**: [e.g., v1.0.0] **Description**: [Detailed description of the issue] **Reproducibility**: [Steps to reproduce if applicable] **Expected Behavior**: [What should happen] **Actual Behavior**: [What actually happens] Data Update Protocol Dataset versioning follows semantic versioning (SemVer) principles: Major version (X.0.0): Incompatible schema changes Minor version (0.X.0): Backward-compatible feature additions Patch version (0.0.X): Backward-compatible bug fixes Technical Support and Community For advanced technical discussions, algorithmic improvements, or collaborative research opportunities, please contact: Primary Maintainer: research@albumforge.com Technical Issues: github.com/albumforge/ecological-benchmark/issues Methodology Discussions: [Academic collaboration portal] Industry Partnerships: partnerships@albumforge.com Acknowledgments: This research was conducted using computational resources provided by AlbumForge (https://albumforge.com) under the Green Computing Initiative. …”

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> by Shubham Pawar (22471285)

“…</p><h2>Table of Contents</h2><ul><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#overview" target="_blank">Overview</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#project-structure" target="_blank">Project Structure</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#prerequisites" target="_blank">Prerequisites</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#installation" target="_blank">Installation</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#usage-guide" target="_blank">Usage Guide</a></li><li><ul><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#step-1-download-street-view-images" target="_blank">Step 1: Download Street View Images</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#step-2-predict-perceptions" target="_blank">Step 2: Predict Perceptions</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#step-3-generate-neighbourhood-clusters" target="_blank">Step 3: Generate Neighbourhood Clusters</a></li></ul></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#quick-test" target="_blank">Quick Test</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#reproducing-manuscript-results" target="_blank">Reproducing Manuscript Results</a></li><li><ul><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#tables" target="_blank">Tables</a></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#figures" target="_blank">Figures</a></li></ul></li><li><a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/README.md#citation" target="_blank">Citation</a></li></ul><h2>Overview</h2><p dir="ltr">This repository contains the complete workflow for delineating perception-based urban neighbourhoods using street view imagery and deep learning. …”

Code and Data for 'Fabrication and testing of lensed fiber optic probes for distance sensing using common path low coherence interferometry' by Radu Stancu (21165068)

“…'model_example_1.py' and 'mode_example_2.py' provide examples of how to use the function to model a particular probe and to explore the parameter space, respectively.…”

Map Matching on Low Sampling Rate Trajectories Through Deep Inverse Reinforcement Learning and Multi Intention Modeling by Reza Safarzadeh (18072472)

“…</li><li>`plots`: Contains functions for generating plots.</li><li>`MIDIRL_MapMatching.ipynb`: Includes step-by-step instructions for training the model, testing it on sample data, visualizing the results, and evaluating its performance. …”

Landscape17 by Vlad Carare (22092515)

“…Transition states were located using a two-step protocol starting with a nudged elastic band (NEB) calculation. …”