Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection by Huichao Yin (14589020)

“…<p dir="ltr">Python image preprocessing and model implementation for research of "Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection".…”

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)

“…Imputation for PM₂.₅: </i>Missing PM₂.₅ values (primarily pre-Jan 2016) were imputed using an XGBoost regression model (xgboost.XGBRegressor). …”

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

“…The pseudo-code follows standard Python syntax specifications for functions and loops and is easy to understand and implement. …”

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

“…<p dir="ltr">This dataset accompanies the publication:<br><b>"Automatic fish scale analysis: age determination, annuli and circuli detection, length and weight back-calculation of coregonid scales"</b><br></p><p dir="ltr">It provides all essential data and statistical outputs used for the <b>verification and validation</b> of the <i>Coregon Analyzer</i> – a Python-based algorithm for automated biometric fish scale measurement.…”

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. …”

Reproducible Code and Data for figures by Bonyad Ahmadi (20750327)

“…<br>✅ <b>Generated Figures</b> – High-resolution images illustrating model outputs and analytical results.<br>✅ <b>Machine Learning Models</b> – Implementation of <b>K-Nearest Neighbors (KNN) regression</b> with different distance metrics (<b>Mahalanobis, Fuzzy Mahalanobis, Euclidean</b>).…”

Curvature-Adaptive Embedding of Geographic Knowledge Graphs in Hyperbolic Space by chenchen Guo (21327470)

“…/CAH-GKGE/model/supplementary instruction.md </p>…”

Supplementary Material by Aris Shahbazian (22464325)

“…The supplementary material includes the full Python-based implementation of the AI-driven optimization framework described in the manuscript. …”

A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification by Mohammed Nasser Al-Andoli (21431681)

“…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…”

NanoDB: Research Activity Data Management System by Lorenci Gjurgjaj (19702207)

“…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”

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. …”

A Fully Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture by Nagarajan Kandasamy (8400168)

“…QUANTISENC’s software-defined hardware design methodology allows the user to train an SNN model using Python and evaluate performance of its hardware implementation, such as area, power, latency, and throughput. …”

Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas by Pedro Cabral (18947566)

“…<p dir="ltr">A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.…”

Fast, FAIR, and Scalable: Managing Big Data in HPC with Zarr by Alfonso Ladino (21447002)

“…</p><p dir="ltr">In this work, we apply the scientific datacube model to the transformation of large-scale radar datasets from Colombia and the U.S. …”

Mean Annual Habitat Quality and Its Driving Variables in China (1990–2018) by ChenXi Zhu (21374876)

“…</p><p dir="ltr">(HQ: Habitat Quality; CZ: Climate Zone; FFI: Forest Fragmentation Index; GPP: Gross Primary Productivity; Light: Nighttime Lights; PRE: Mean Annual Precipitation Sum; ASP: Aspect; RAD: Solar Radiation; SLOPE: Slope; TEMP: Mean Annual Temperature; SM: Soil Moisture)</p><p dir="ltr"><br>A Python script used for modeling habitat quality, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), and implementation of four machine learning models to predict habitat quality.…”

PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation by David Lewis Stewart Parry (22188211)

“…PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation This release provides the complete, reproducible numerical implementation of the Parry Tensional Phase Collapse (PTPC) model — the dynamic core of the Universal Heartbeat Theory (UHT/PTPC). …”

Soulware-Lite by Abhiram Gnyanijaya (21572942)

“…It supports OpenAI GPT-4, Anthropic Claude, Google Gemini, Meta LLaMA, and other open-source models.</p><p><br></p><p dir="ltr">Soulware-Lite is the first live implementation of a cognitive conscience layer, born from architectural failures in AI output hallucination and anchored by integrity principles like MAP/ARP and RDIP. …”

Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”

Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”

Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”