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. …”

Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management by Pavel Izosimov (20096259)

“…A license key is generated, allowing authorized users to access the code.bash<pre><pre>python secure_python_code_manager.py --upload -f your_script.py<br></pre></pre></li><li><b>Updating Previously Uploaded Code</b>: With the <code>--update</code> function, update your code in the cloud without needing to redistribute new files to clients, ensuring seamless code maintenance and updates.bash<pre><pre>python secure_python_code_manager.py --update -f your_script.py -l your_license_key<br></pre></pre></li><li><b>Retrieving License Information</b>: The <code>--license-info</code> function lets you retrieve detailed information about your licenses, including status, usage data, and limits.bash<pre><pre>python secure_python_code_manager.py --license-info -l your_license_key<br></pre></pre></li><li><b>Service Usage Monitoring</b>: Use the <code>--service-usage</code> function to monitor your service usage, including uploaded scripts and associated licenses, helping you keep track of your code deployment.bash<pre><pre>python secure_python_code_manager.py --service-usage<br></pre></pre></li></ol><h2>Use Cases</h2><ul><li><b>Protect Python Code</b>: If you're looking to <b>protect Python code</b> from unauthorized use, this tool provides robust protection mechanisms.…”

Online Resource 3: Word Cloud Dataset and Code by Jessica Zylla (17692920)

“…<p dir="ltr">Online Resource 3: Word Cloud Dataset and Code. This set of files are part of Online Resource 3, which allows readers to implement a Jupyter Notebook Python program to create a word cloud based on survey responses. …”

RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices by RealBench RealBench (22275393)

“…<br>The supplemented materials for Review #2570C is in the ''Response to Review #2570C.md''.<br><br><br></pre><p dir="ltr">This repository contains the implementation of **RealBench**, a comprehensive benchmark and evaluation framework for repository-level code aligned with real-world software development practices.…”

Data and code for: Automatic fish scale analysis by Christian Vogelmann (21646472)

“…</p><h3>Includeed in this repository:</h3><ul><li><b>Raw data files:</b></li><li><code>comparison_all_scales.csv</code> – comparison_all_scales.csv - manually verified vs. automated measurements of 1095 coregonid scales</li></ul><ul><li><ul><li><code>Validation_data.csv</code> – manually measured scale data under binocular</li><li><code>Parameter_correction_numeric.csv</code> – calibration data (scale radius vs. fish length/weight)</li></ul></li><li><b>Statistical results:</b></li><li><ul><li><code>comparison_stats_core_variables.csv</code> – verification statistics (bias, relative error, limits of agreement)</li><li><code>Validation_statistics.csv</code> – summary statistics and model fits (manual vs. automated)</li></ul></li><li><b>Executable script (not GUI):</b></li><li><ul><li><code>Algorithm.py</code> – core processing module for scale feature extraction<br>→ <i>Note: The complete Coregon Analyzer application (incl. …”

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by Jordan Waters (21620558)

“…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …”

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. …”

Data and some code used in the paper:<b>Expansion quantization network: A micro-emotion detection and annotation framework</b> by Zhou (20184816)

“…</p><p dir="ltr">GPU：NVIDIA GeForce RTX 3090 GPU</p><p dir="ltr">Bert-base-cased pre-trained model: https://huggingface.co/google-bert/bert-base-cased</p><p dir="ltr">python=3.7，pytorch=1.9.0，cudatoolkit=11.3.1，cudnn=8.9.7.29.…”

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" by Krishnendu Chatterjee (15367413)

“…</p><h2>Dependencies</h2><p dir="ltr">In order to run the code the following dependencies must be met:</p><pre><pre>- Python 3 should be installed. …”

adnus by Mehmet Keçeci (14301782)

“…<p dir="ltr">adnus (AdNuS): Advanced Number Systems</p><p dir="ltr">adnus is a Python library that provides an implementation of various advanced number systems. …”

The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025) by zixuan yuan (17602152)

“…</p><h3><b>Installation</b></h3><h4><b>install Dependencies</b></h4><p dir="ltr">Our artifact depends on several packages, please run the following command to install all necessary dependencies.</p><pre><pre>sudo apt-get install -y wget git build-essential python3 python python-pip python3-pip tmux cmake libtool libtool-bin automake autoconf autotools-dev m4 autopoint libboost-dev help2man gnulib bison flex texinfo zlib1g-dev libexpat1-dev libfreetype6 libfreetype6-dev libbz2-dev liblzo2-dev libtinfo-dev libssl-dev pkg-config libswscale-dev libarchive-dev liblzma-dev liblz4-dev doxygen libncurses5 vim intltool gcc-multilib sudo --fix-missing<br></pre></pre><pre><pre>pip install numpy && pip3 install numpy && pip3 install sysv_ipc<br></pre></pre><h4><b>Download the Code</b></h4><p dir="ltr">Download <b>DD4AV</b> from the Figshare website to your local machine and navigate to the project directory:</p><pre><pre>cd DD4AV<br></pre></pre><h4><b>Configure Environment and Install the Tool</b></h4><p dir="ltr">For convenience, we provide shell scripts to automate the installation process. …”

kececilayout by Mehmet Keçeci (14301782)

“…<p dir="ltr"><b>Kececi Layout (Keçeci Yerleşimi)</b>: A deterministic graph layout algorithm designed for visualizing linear or sequential structures with a characteristic "zig-zag" or "serpentine" pattern.</p><p dir="ltr"><i>Python implementation of the Keçeci layout algorithm for graph visualization.…”

Gene Editing using Transformer Architecture by Rishabh Garg (5261744)

“…</p><p dir="ltr">Once TASAG detects a deviation from a reference sequence (e.g., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…<p dir="ltr">The dataset contains:</p><ol><li>Steady_squeezing.zip <b>a)</b> data for steady squeezing data and characteraztion <b>b)</b> data for pulse RF magnetormeter</li><li>Tracking1.zip <b>a)</b> data of OU process for Deep learning <b>b)</b> data of OU-jump process for Deep learning</li><li>Tracking2.zip <b>a)</b> data of white noise process in backaction experiment <b>b) </b>data of white noise process in rearrange experiment</li><li>Code <b>a)</b> Randomly signal generating code <b>b)</b> Deep learning codec.data pre-processing code</li></ol><p dir="ltr">The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

IGD-cyberbullying-detection-AI by Bryan James (19921044)

“…</li></ul><h2>Installation</h2><ol><li>Clone the repository:<pre>git clone https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI<br>cd IGD-cyberbullying-detection-AI</pre></li><li>Install the required dependencies:<pre>pip install -r requirements.txt</pre></li></ol><h2>Running the Code</h2><ol><li><b>Cyberbullying Prediction</b>:</li><li><ul><li>Open the <code>Cyberbullying.ipynb</code> notebook and run the cells in order to train and evaluate the deep learning models on the provided datasets.…”

Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

“…Includes imputation statistics, data dictionary, and the Python imputation code (Imputation_Air_Pollutants_NABEL.py). …”