Measurement data from full-scale fire experiments of battery electric vehicles and internal combustion engine vehicles by Nathaniel G. Sauer (22463233)

“…</li><li><strong>data_heatflux.zip</strong>: ZIP archive containing 12 HDF5 files (readable via Python <code>h5py</code>). Six files (<code>T_XX</code>) record temperature and six (<code>HF_XX</code>) record incident radiative heat flux to plate sensors located along the driver and passenger sides of the vehicle. …”

Table 1_Analysis of distribution equilibrium and influencing factors for older adult meal service facilities in mainland China.xlsx by Feng Wang (44414)

“…A multiple linear regression model was applied to explore the relationships between older adult meal services and factors such as population, economy, infrastructure, geography, and policies.…”

Cognitive Fatigue by Rui Varandas (11900993)

“…<br></p><p dir="ltr"><b>HCI features</b> encompass keyboard, mouse, and screenshot data. Below is a Python code snippet for extracting screenshot files from the screenshots CSV file.…”

CNG-ARCO-RADAR.pdf by Alfonso Ladino (21447002)

“…This approach uses a suite of Python libraries, including Xarray (Xarray-Datatree), Xradar, and Zarr, to implement a hierarchical tree-like data model. …”

Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) by Tahir Bhatti (20961974)

“…<p dir="ltr">This dataset presents computational analyses of two SARS-CoV-2 BioSamples sequenced in December 2025, processed to assess the genomic presence of mutations associated with pemivibart (VYD2311) monoclonal antibody escape. …”

Trustworthy and Ethical AI for Intrusion Detection in Healthcare IoT (IoMT) Systems: An Agentic Decision Loop Framework by ibrahim adabara (22107287)

“…</p><h2>️ Repository Structure</h2><pre><pre>agentic-ethical-ids-healthcare/<br>│<br>├── src/ # Source code for model, rule engine, and agent<br>│ ├── train_agent.py<br>│ ├── ethical_engine.py<br>│ ├── detector_model.py<br>│ └── utils/<br>│<br>├── data/ # Links or sample data subsets<br>│ ├── CIC-IoMT-2024/ <br>│ └── CSE-CIC-IDS2018/<br>│<br>├── notebooks/ # Jupyter notebooks for training and analysis<br>│<br>├── models/ # Pretrained model checkpoints (.pth, .pkl)<br>│<br>├── results/ # Evaluation outputs and figures<br>│<br>├── requirements.txt # Python dependencies<br>├── LICENSE # MIT License for open research use<br>└── README.md # Project documentation<br></pre></pre><h2>⚙️ Setup and Installation</h2><p dir="ltr">Clone the repository and set up your environment:</p><pre><pre>git clone https://github.com/ibrahimadabara01/agentic-ethical-ids-healthcare.git<br>cd agentic-ethical-ids-healthcare<br>python -m venv venv<br>source venv/bin/activate # On Windows: venv\Scripts\activate<br>pip install -r requirements.txt<br></pre></pre><h2> Datasets</h2><p dir="ltr">This project uses three datasets:</p><table><tr><th><p dir="ltr">Dataset</p></th><th><p dir="ltr">Purpose</p></th><th><p dir="ltr">Source</p></th></tr><tr><td><b>CIC-IoMT 2024</b></td><td><p dir="ltr">Primary IoMT intrusion detection dataset</p></td><td><a href="https://www.unb.ca/cic/datasets/index.html" rel="noopener" target="_new">Canadian Institute for Cybersecurity</a></td></tr><tr><td><b>CSE-CIC-IDS2018</b></td><td><p dir="ltr">Domain-shift evaluation</p></td><td><a href="https://www.unb.ca/cic/datasets/ids-2018.html" rel="noopener" target="_new">CIC Dataset Portal</a></td></tr><tr><td><b>MIMIC-IV (Demo)</b></td><td><p dir="ltr">Clinical context signals</p></td><td><a href="https://physionet.org/content/mimic-iv-demo/2.2/" rel="noopener" target="_new">PhysioNet</a></td></tr></table><blockquote><p dir="ltr">⚠️ Note: All datasets are publicly available. …”

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

“…</li><li><b>4_final_models_pipeline.ipynb</b><br>The final implementation pipeline that loads the data, applies preprocessing and encoding (e.g., latency or ISI), trains the detection models, and stores performance metrics.…”

Online Resource: Reservoir Computing as a Promising Approach for False Data Injection Attack Detection in Smart Grids by Carl-Hendrik Peters (21530624)

“…</li><li><b>4_final_models_pipeline.ipynb</b><br>The final implementation pipeline that loads the data, applies preprocessing and encoding (e.g., latency or ISI), trains the detection models, and stores performance metrics.…”

Globus Compute: Federated FaaS for Integrated Research Solutions by eRNZ Admin (6438486)

“…</p><p dir="ltr">Globus Compute [2] is a Function-as-a-Service platform designed to provide a scalable, secure, and simple interface to HPC resources. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud-hosted service. …”

FORCE11: FROGS: Facilitating Reproducible Open (Geo)Science by Deborah Khider (4673140)

Monte Carlo Simulation Code for Evaluating Cognitive Biases in Penalty Shootouts Using ABAB and ABBA Formats by Raul MATSUSHITA (10276562)

“…<p dir="ltr">This Python code implements a Monte Carlo simulation to evaluate the impact of cognitive biases on penalty shootouts under two formats: ABAB (alternating shots) and ABBA (similar to tennis tiebreak format). …”

Table & Figure.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

“…Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”

Raw Data EEG.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

“…Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”

Automated Discovery of Semantic Attacks in Multi-Robot Navigation Systems - Research Artifacts by Doguhan Yeke (21498410)

“…<h4>We present the research artifacts for our USENIX Security 2025 submission. …”

Table 1_From rocks to pixels: a comprehensive framework for grain shape characterization through the image analysis of size, orientation, and form descriptors.docx by A. L. Back (20719049)

“…A total of 51 descriptors, including elongation and Fourier amplitudes, were extracted, compiled, and computed using Python. The descriptor computation code is provided as a library with this article. …”

Data Sheet 5_From rocks to pixels: a comprehensive framework for grain shape characterization through the image analysis of size, orientation, and form descriptors.csv by A. L. Back (20719049)

“…A total of 51 descriptors, including elongation and Fourier amplitudes, were extracted, compiled, and computed using Python. The descriptor computation code is provided as a library with this article. …”

Data Sheet 8_From rocks to pixels: a comprehensive framework for grain shape characterization through the image analysis of size, orientation, and form descriptors.csv by A. L. Back (20719049)

“…A total of 51 descriptors, including elongation and Fourier amplitudes, were extracted, compiled, and computed using Python. The descriptor computation code is provided as a library with this article. …”

Data Sheet 4_From rocks to pixels: a comprehensive framework for grain shape characterization through the image analysis of size, orientation, and form descriptors.csv by A. L. Back (20719049)

“…A total of 51 descriptors, including elongation and Fourier amplitudes, were extracted, compiled, and computed using Python. The descriptor computation code is provided as a library with this article. …”

Data Sheet 9_From rocks to pixels: a comprehensive framework for grain shape characterization through the image analysis of size, orientation, and form descriptors.csv by A. L. Back (20719049)

“…A total of 51 descriptors, including elongation and Fourier amplitudes, were extracted, compiled, and computed using Python. The descriptor computation code is provided as a library with this article. …”

Data Sheet 15_From rocks to pixels: a comprehensive framework for grain shape characterization through the image analysis of size, orientation, and form descriptors.csv by A. L. Back (20719049)

“…A total of 51 descriptors, including elongation and Fourier amplitudes, were extracted, compiled, and computed using Python. The descriptor computation code is provided as a library with this article. …”