Accuracy of the segmentation model. by Owen M. O’Connor (11965460)

Subjects:

Data_Sheet_1_An Open-Source Tool for Anisotropic Radiation Therapy Planning in Neuro-oncology Using DW-MRI Tractography.pdf by Kesshi Jordan (7329089)

“…We present an open-source WMPL tool, implemented in the package Diffusion Imaging in Python (DIPY), and code to convert the resulting WMPL map to anisotropic contours for RT in a commercial treatment planning system. …”

Python code for ray-tracing through Cartesian surfaces by Alberto Silva (8373543)

Reducing the size of the model to increase speed. by Owen M. O’Connor (11965460)

Subjects:

Local Python Code Protector Script: A Tool for Source Code Protection and Secure Code Sharing by Pavel Izosimov (20096259)

“…</p><h2>Key Features</h2><ul><li><a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>Code Obfuscation in Python</b></a>: Implements multi-level protection with dynamic encryption and obfuscation techniques, making it an effective <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>Python obfuscator</b></a>.…”

Training the model on segmentation with custom weight maps. by Owen M. O’Connor (11965460)

Subjects:

Impact of frame shifts on tracking model performance. by Owen M. O’Connor (11965460)

Subjects:

A Cell-Based, Dynamic Flow Direction Model (DFD Model) for Water Balance Calculations Simulating Overland Runoff through Depressions Implemented using Python and GIS by Zhentao Wang (13042179)

“…<p>A Cell-Based, Dynamic Flow Direction Model (DFD Model) for Water Balance Calculations Simulating Overland Runoff through Depressions Implemented using Python and GIS</p>…”

Parameters and units for the Microbial Consumer Resource Model. by Robert Marsland (8616483)

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

“…</li></ul><p dir="ltr"><b>Application Areas</b></p><p dir="ltr">The <b>Multi-Version PYZ Builder Script</b> can be effectively applied in various areas:</p><ul><li><b>Commercial Distribution</b>: Distribute protected Python code to clients or customers, implementing advanced <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>source code protection</b></a> for sales or rentals.…”

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

“…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. …”

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

Invert4Geom; Progress towards an open-source geometric gravity inversion with stochastic uncertainty analysis by Matt Tankersley (11769215)

“…Here, we present a preliminary inversion algorithm written in Python to perform these geometric style of gravity inversions. …”

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

PyRates—A Python framework for rate-based neural simulations by Richard Gast (8129451)

“…In this work, we present PyRates, a Python framework that provides the means to build a large variety of rate-based neural models. …”

Utilizing variable background weight maps for training the model on debris. by Owen M. O’Connor (11965460)

Subjects:

Loss history of segmentation model trained over 600 epochs. by Owen M. O’Connor (11965460)

Subjects:

Python programming code for the stochastic inference of disease interval distributions. by Günter Schneckenreither (10099380)

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.…”

Schematic showing how the tracking model uses the inputs to make predictions. by Owen M. O’Connor (11965460)

Subjects: