Examples of tweets texts (English). by Sylvia Iasulaitis (8301189)

“…The process of collecting and creating the database for this study went through three major stages, subdivided into several processes: (1) A preliminary analysis of the platform and its operation; (2) Contextual analysis, creation of the conceptual model, and definition of Keywords and (3) Implementation of the Data Collection Strategy. Python algorithms were developed to model each primary collection type. …”

Users information. by Sylvia Iasulaitis (8301189)

“…The process of collecting and creating the database for this study went through three major stages, subdivided into several processes: (1) A preliminary analysis of the platform and its operation; (2) Contextual analysis, creation of the conceptual model, and definition of Keywords and (3) Implementation of the Data Collection Strategy. Python algorithms were developed to model each primary collection type. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical data sets. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical data sets. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical data sets. …”

CSMILES: A Compact, Human-Readable SMILES Extension for Conformations by James W. Furness (22319738)

“…As such, canonical CSMILES strings are invariant to atom reordering, rigid translation, and rigid rotation. A two-way conversion from three-dimensional (3D) structure to CSMILES has been implemented, and the article is accompanied by a Python code which effectuates such conversions. …”

CSMILES: A Compact, Human-Readable SMILES Extension for Conformations by James W. Furness (22319738)

“…As such, canonical CSMILES strings are invariant to atom reordering, rigid translation, and rigid rotation. A two-way conversion from three-dimensional (3D) structure to CSMILES has been implemented, and the article is accompanied by a Python code which effectuates such conversions. …”

The format of the electrode csv file by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”

The format of the simulation reports by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”

Comparison of BlueRecording with existing tools by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”

The format of the weights file by Joseph James Tharayil (21416715)

“…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”

BlueRecording simulates hippocampal LFP. by Joseph James Tharayil (21416715)

Memory monitoring recognition test workflow. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Voice recognition workflow. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Memory monitoring recognition test main screen. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Task descriptions. by Pedro C. Martínez-Suárez (21192459)

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Spherical Texture method design. by Oane Gros (20636735)

“…<b>H)</b> The <i>Spherical Texture</i> extraction is implemented as a Python package and it is directly available in <i>ilastik</i>, allowing for its adoption into the Object Classification workflow. …”

Code for High-quality Human Activity Intensity Maps in China from 2000-2020 by Wenqi Xie (18273238)

“…<p dir="ltr">Code and remote sensing images and interpretation results of the samples for uncertainty analysis for "High-quality Human Activity Intensity Maps in China from 2000-2020"</p><p dir="ltr">“Mapping_HAI.py”：We generated the HAI maps using ArcGIS 10.8, and the geoprocessing tasks were implemented using Python 2.7 with the ArcPy library (ArcGIS 10.8 + Python 2.7 environment). …”

Extending the pyAFQ software. by John Kruper (18809386)

The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" by Chongshan Wan (19247614)

“…</li></ul><h2>Codes</h2><p dir="ltr">This repository contains the following Python codes：</p><ul><li>`data_processing.py`: Contains the implementation of data processing and feature extraction. …”