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modular implementation » model implementation (Expand Search), world implementation (Expand Search)
python model » python tool (Expand Search), action model (Expand Search), motion model (Expand Search)
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201
MCCN Case Study 3 - Select optimal survey locality
Published 2025“…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”
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202
Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1
Published 2025“…</p><p dir="ltr">The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:</p><p dir="ltr">https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589</p><p dir="ltr">Peer-Review Reference and Proper Citation:</p><p dir="ltr">Zomer, R.J.; Xu, J.; Trabuco, A. 2022. …”
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203
Data files accompanying our PLoS One publication
Published 2025“…The videos were digitized and the positional data were saved in .xlsx or .csv format, respectively. The python codes contain the numerical implementations of our mathematical models.…”
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204
Cathode carbon block material parameters [14].
Published 2025“…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …”
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205
Sodium concentration distribution cloud map.
Published 2025“…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …”
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206
Sodium binding coefficient R.
Published 2025“…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …”
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207
Probabilistic-QSR-GeoQA
Published 2024“…<p dir="ltr">The code and data are related to the paper Mohammad Kazemi Beydokhti, Matt Duckham, Amy L. …”
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208
Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan)
Published 2025“…</p><p dir="ltr">Each zipped folder consists the following files:</p><ul><li>Graph data - City object nodes (.parquet) and COO format edges (.txt)</li><li>predictions.txt (model predictions from GraphSAGE model)</li><li>final_energy.parquet (Compiled training and validation building energy data)</li></ul><p dir="ltr">The provided files are supplementary to the code repository which provides Python notebooks stepping through the data preprocessing, GNN training, and satellite imagery download processes. …”
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Leue Modulation Coefficients (LMC): A Smooth Continuum Embedding of Bounded Arithmetic Data
Published 2025“…This Zenodo package includes: the full research paper (PDF), a complete Python implementation generating the LMC field and conductivity model, a numerical plot comparing discrete LMC values with the smoothed continuum field, a cover letter and supporting documentation. …”
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211
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Error reduction over time by the HOFA-SMC.
Published 2025“…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …”
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213
Comparison of SMC techniques.
Published 2025“…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …”
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214
Proposed HOFA-SMC with experimental validation.
Published 2025“…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …”
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215
ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
Published 2025“…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
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216
ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
Published 2025“…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
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217
Overview of generalized weighted averages.
Published 2025“…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…”
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218
Supervised Classification of Burned Areas Using Spectral Reflectance and Machine Learning
Published 2025“…Six Python scripts are provided, each implementing a distinct machine learning algorithm—Random Forest, k-Nearest Neighbors (k-NN), Multi-Layer Perceptron (MLP), Decision Tree, Naïve Bayes, and Logistic Regression. …”
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219
Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games"
Published 2024“…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…”
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220
Reinforcement Learning based traffic steering inOpen Radio Access Network (ORAN)- oran-ts GitHub Repository
Published 2025“…<p dir="ltr">This repository contains the simulation codebase for research on <b>Reinforcement Learning (RL) based Traffic Steering and Resource Allocation in Open Radio Access Networks (O-RAN)</b>. It features a modular Python framework implementing various RL agents (Q-Learning, SARSA, N-Step SARSA, DQN) and a traditional baseline evaluated in a realistic cellular network environment. …”