Visitor Segmentation Validation Accuracy. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

Integration of VAE and RNN Architecture. by Jing Zhang (23775)

“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”

Knowledge Graph validation using SHACL Shapes by Ángel Iglesias Préstamo (19745767)

“…Leveraging Rust’s performance and safety features, rudof provides efficient validation tools and Python bindings for integration with data science workflows. …”

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. …”

Landscape Change Monitoring System (LCMS) Conterminous United States Cause of Change (Image Service) by U.S. Forest Service (17476914)

“…Scikit-learn: Machine Learning in Python. In Journal of Machine Learning Research (Vol. 12, pp. 2825-2830).Pengra, B. …”

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. …”

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

“…The pipeline integrates established open-source tools (fastp, BWA-MEM, samtools, iVar, bcftools) and implements <b>codon-aware mutation calling</b> at five canonical RBD positions (R346, S371, K444, F456, F486) relative to NC_045512.2. …”

3D PD-Controlled Nanorobot Swarm Simulation for Targeted Cancer and BBB Therapy by Umar Tabbsum (22058780)

“…Cancer-targeting nanorobots converge rapidly, while BBB-targeting nanorobots follow more complex paths due to navigation constraints.</p><p dir="ltr">Implemented in Python (NumPy, Matplotlib, 3D visualization), the framework is fully annotated and reproducible. …”

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.…”

Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”

Elements: Streaming Molecular Dynamics Simulation Trajectories for Direct Analysis – Applications to Sub-Picosecond Dynamics in Microsecond Simulations by Matthias Heyden (17087794)

“…This eliminates the need for intermediate storage and allows immediate access to high-frequency fluctuations and vibrational signatures that would otherwise be inaccessible. We have implemented this streaming interface in the MD engines NAMD, LAMMPS, and GROMACS</p><p dir="ltr">On the client side, we developed the IMDClient Python package which receives the streamed data, stores into a custom buffer, and provides it to external tools as NumPy arrays, facilitating integration with scientific computing workflows. …”

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.…”

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. …”

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

“…[<a href="https://doi.org/10.6084/m9.figshare.27266961" rel="nofollow" target="_blank">https://doi.org/10.6084/m9.figshare.27266961</a>]</p><h2>Table of Contents</h2><ul><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#overview" target="_blank">Overview</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#requirements" target="_blank">Requirements</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#datasets" target="_blank">Datasets</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#installation" target="_blank">Installation</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#running-the-code" target="_blank">Running the Code</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#expected-results" target="_blank">Expected Results</a></li></ul><h2>Overview</h2><p dir="ltr">This repository provides the code for predicting mental health outcomes associated with Internet Gaming Disorder (IGD) and Cyberbullying using machine learning and deep learning models. Models like Logistic Regression, Random Forest, Ensemble Models, CNNs, and LSTMs are implemented to detect patterns from behavioral data.…”

MSc Personalised Medicine at Ulster University by Steven Watterson (100045)

“…This includes the economic models that underpin big pharma as well the importance of entrepreneurship and small medium enterprises in driving forward healthcare innovation.…”

Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples by Derek Lam (11944213)

“…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …”

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.…”

Mapping Policy Coherence in National UK Food Systems (2008– 2024): Analysing the Integration of Climate Change Mitigation and Adaptation Strategies, LEAP 2025 conference, Oxford by Ronja Teschner (20974180)

“…</p><p dir="ltr">Data Screening inclusion criteria followed the Food Systems Countdown Initiative (FSCI).2</p><p><br></p><p dir="ltr">diets, nutrition and health</p><p dir="ltr">diet quality, food security, food environments, policies affecting</p><p dir="ltr">food environments</p><p dir="ltr">environment and climate</p><p dir="ltr">land use, greenhouse gas emissions, water use, pollution, biosphere integrity</p><p dir="ltr">livelihoods, poverty, and equity</p><p dir="ltr">poverty and income, employment, social protection, rights</p><p dir="ltr">governance</p><p dir="ltr">shared vision, strategic planning and policies, effective implementation, accountability</p><p dir="ltr">resilience and sustainability</p><p dir="ltr">exposure to shocks, resilience capacities, agrobiodiversity, food security stability</p><p><br></p><p dir="ltr">Findings</p><p dir="ltr">o N=157 policy documents integrate climate change considerations.…”