Illustration of the text transformation process before and after synonym replacement: The process begins with a sample initial text segment (Sample text before synonym replacement’... by Enock Niyonkuru (21246879)

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Schematic of the approach: This schematic illustrates the entire workflow of the project. by Enock Niyonkuru (21246879)

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Text Transformation Pipeline: An example of the multi-stage text transformation pipeline applied to a sample abstract (PMID: 30609739). by Enock Niyonkuru (21246879)

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Comparative analysis of WordNet replacement impact on data distribution. by Enock Niyonkuru (21246879)

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Comparison of window size for embedding with Wordnet synonym replacement (WN) and without (PM). While Table 1 compared the effects of different values of using a window size of 10,... by Enock Niyonkuru (21246879)

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Non-biomedical word replacement algorithm: This algorithm outlines the process for replacing non-biomedical words in a corpus using WordNet. by Enock Niyonkuru (21246879)

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Comparison of mean interconcept distance for embedding with WordNet synonym replacement (WN) and without (PM). The initial number of unique concepts in the total corpus was 3,018,9... by Enock Niyonkuru (21246879)

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Comparative analysis of WN and PM methodologies: Figure (a) displays the bar chart comparing WN and PM across five distinct concept sets (Methods), highlighting the number of conce... by Enock Niyonkuru (21246879)

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

“…Each lane includes 'geometry' and 'inter_id' attributes.</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. …”

MYTHOS: A Python Interface for Surface Crystal Structure Prediction of Organic Semiconductors by Emilio Lorini (21689822)

“…We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based on molecular mechanics and molecular dynamics simulations, and implemented in a user-friendly Python program, this method enables a sequential layer-by-layer analysis of crystalline formation, thus allowing to identify surface-induced polymorphs (SIPs) and to study the transition between surface and bulk structures. …”

MATH_code : False Data Injection Attack Detection in Smart Grids based on Reservoir Computing by Carl-Hendrik Peters (21530624)

“…</li><li><b>3_literature_analysis_and_mapping.ipynb</b><br>Contains the Python code used for executing the systematic mapping study (SMS), including automated processing of literature data and thematic clustering.…”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…<h2>A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation</h2><p><br></p><p dir="ltr">This is the implementation for the paper "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation".…”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…<h2>A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation</h2><p><br></p><p dir="ltr">This is the implementation for the paper "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation".…”

Code by Baoqiang Chen (21099509)

“…</p><p><br></p><p dir="ltr">For the 5′ UTR library, we developed a Python script to extract sequences and Unique Molecular Identifiers (UMIs) from the FASTQ files. …”

Exploring the integration of metaverse technologies in engineering education through the SAMR model by Snezhana Dineva (22444471)

“…The final deliverable is a plan for phased integration of metaverse learning into a Python programming course following this model, building on existing best practices.…”

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

“…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)

“…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. …”

SEPARATE Code Repository by Gyuri Kim (21424973)

“…<p dir="ltr">Python implementation of the SEPARATE, which enables three-dimensional multiplexed fluorescence imaging by pairing proteins based on their spatial expression patterns and computationally unmixing signals using deep learning.…”

Data&Codes.zip by Zer0 Star (20545655)

“…</p><p dir="ltr">To facilitate the widespread use of the proposed framework, we have implemented it as the <b><i>ESLocalIndi</i></b> open-source package in Python, making it easily accessible to geographers. …”

Exercises of the AAU-DA Summer School 2025 by Leire Retegui-Schiettekatte (18008506)