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System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool
Published 2024“…</li><li><b>Cross-Platform Compatibility</b>: Designed with cross-platform functionality in mind, the script works seamlessly on Windows, macOS, Linux, Unix, and other operating systems where Python 3.6 or higher is installed.</li><li><b>Modular Design</b>: The script can be used as a standalone tool or imported as a module into other Python projects, enabling developers to easily integrate hardware identification into their applications.…”
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EthoPy: Reproducible Behavioral Neuroscience Made Simple
Published 2025“…To overcome these challenges, we developed EthoPy, an open-source, Python-based behavioral control framework that integrates stimulus presentation, hardware management, and data logging. …”
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Workflow of a typical Epydemix run.
Published 2025“…<div><p>We present Epydemix, an open-source Python package for the development and calibration of stochastic compartmental epidemic models. …”
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Efficient, Hierarchical, and Object-Oriented Electronic Structure Interfaces for Direct Nonadiabatic Dynamics Simulations
Published 2025“…We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. …”
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Soulware-Lite
Published 2025“…</p><p><br></p><p dir="ltr">The system is fully modular, built on Python + FastAPI, and integrated with Streamlit UI for visualizing alignment confidence and drift flags. …”
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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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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. …”
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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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Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series
Published 2025“…The method also successfully recovers the location and nature of changes in more traditional changepoint tasks. An implementation of our method is available in the Python package bclr.…”
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Table 1_Analysis of distribution equilibrium and influencing factors for older adult meal service facilities in mainland China.xlsx
Published 2025“…Objective<p>Analyze the distribution equilibrium of older adult meal service facilities in mainland China and explore the factors influencing their distribution.</p>Methods<p>Use Python to obtain data on older adult meal service facilities, and analyze the equity of older adult meal services using descriptive statistics, the Lorenz curve, the Gini coefficient, and the Spatial Mismatch Index (SMI). …”
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MSc Personalised Medicine at Ulster University
Published 2025“…</p><p dir="ltr">This is a flexible, modular, credit-bearing programme that can be studied to achieve a range of postgraduate qualifications.…”
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Contrast enhancement of digital images using dragonfly algorithm
Published 2024“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”
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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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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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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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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>…”