SCADET algorithm parameter configuration (Python implementation). by Xiaolong Zhang (470454)

Comparison of performance between our next reaction implementation and the Python library from Ref. [3]. by Samuel Cure (22250922)

“…<p>We simulate SIR epidemic processes on Watts-Strogatz networks with parameters <i>k</i>₀ = 5, <i>p</i> = 0.1 <b>(a)</b> and Barabási-Albert networks with parameter <i>m</i> = 5 <b>(b)</b> using the Python wrapper of our C++ implementation and compare its performance with the Python library from Ref. …”

Left schematic of the XOR gate implementation [11]. by Fabricio Cravo (21387854)

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Fitting a feast/famine cycle to a glycolysis model. by Paul van Lent (16876977)

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Python implementation of a wildfire propagation example using m:n-CAk over Z and R. by Pau Fonseca i Casas (9507338)

“…</p><p dir="ltr"><br></p><p dir="ltr">## Files in the Project</p><p dir="ltr"><br></p><p dir="ltr">### Python Scripts</p><p dir="ltr">- **Wildfire_on_m_n-CAk.py**: This file contains the main code for the fire cellular automaton. …”

Python Implementation of HSGAdviser Chatbot: AI model for Sustainable Education by Suha Assayed (22454038)

“…<p dir="ltr">This repository contains the Python source code and model implementation for HSGAdviser, an AI speech assistant designed to provide personalized college and career guidance for high school students through conversational AI. …”

Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... by Ziyan Jin (21021976)

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Python code for estimating parameters of an ALAAM model. by Alex Stivala (8356257)

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Multi-Version PYZ Builder Script: A Universal Python Module Creation Tool by Pavel Izosimov (20096259)

“…This tool represents a significant advancement in the realm of <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>secure code sharing</b></a>, providing a robust solution for modern Python programming challenges.…”

Representative examples of scanned intake forms. by Yojiro Umezaki (5916593)

Reproducible implementation for article: Reproducibility study of the modular and reusable model of epithelial transport in the proximal convoluted tubule by Leyla Noroozbabaee (14301173)

Source Code for the Hierarchical Key Assignment Scheme (HKAS) by Baris Celiktas (22804778)

Subjects: “…Hierarchical Key Assignment, Cryptography, Key Management, HKAS, Security Model, Python Implementation…”

System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool by Pavel Izosimov (20096259)

“…System Hardware ID Generator Script: Unique Device Identification for Enhanced Security and Licensing<p dir="ltr">The <b>System Hardware ID Generator Script</b> is a powerful Python tool developed to generate a unique Hardware ID (HWID) for the device it runs on. …”

Python implementation for image-based ERT inversion using ViT, CNN, UNet, and LDM models, and related data conversion and visualization by Huichao Yin (14589020)

“…<p dir="ltr">Python implementation for image-based ERT inversion using ViT, CNN, UNet, and LDM models, and related data conversion and visualization.…”

Segmentation module training details. by Khelina Fedorchuk (19130089)

PYTHON by Kan Jia (21666161)

Python code for hierarchical cluster analysis of detected R-strategies from rule-based NLP on 500 circular economy definitions by Zahir Barahmand (18008947)

“…</p><p dir="ltr">This Python code was optimized and debugged using ChatGPT-4o to ensure implementation efficiency, accuracy, and clarity.…”

Example change statistic implementations. by Alex Stivala (8356257)

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Data features examined for potential biases. by Harry Hochheiser (3413396)

“…<div><p><b>Objective:</b> To challenge clinicians and informaticians to learn about potential sources of bias in medical machine learning models through investigation of data and predictions from an open-source severity of illness score.…”

Analysis topics. by Harry Hochheiser (3413396)

“…<div><p><b>Objective:</b> To challenge clinicians and informaticians to learn about potential sources of bias in medical machine learning models through investigation of data and predictions from an open-source severity of illness score.…”