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. …”

(A) Sampling locations and ranges of <i>I. feisthamelii</i> (purple) and <i>I. podalirius</i> (teal) butterflies. by Sam Ebdon (21072525)

“…(B) Sampling locations of butterflies from the <i>Iphiclides</i> HZ. The dashed line represents the approximate HZ center, based on samples collected by Lafranchis et al. …”

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

“…<p><br></p><p dir="ltr">The EQN framework is a micro-emotion annotation and detection system that realizes the automatic micro-emotion annotation of text with energy level scores for the first time. The text emotion datasets it annotates are no longer simple single-label or multi-label, but macro-emotions and micro-emotions with continuous values ​​of emotion intensity. …”

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

“…In this study, we present an open-source, Python-based computational framework that unifies photon transport modeling, probe geometry optimization, and photothermal safety assessment into a single workflow. …”

Reinforcement Learning based traffic steering inOpen Radio Access Network (ORAN)- oran-ts GitHub Repository by Aaradhy Sharma (21503465)

“…It features a modular Python framework implementing various RL agents (Q-Learning, SARSA, N-Step SARSA, DQN) and a traditional baseline evaluated in a realistic cellular network environment. …”

Core data by Baoqiang Chen (21099509)

“…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

Datasets from the Programmatic Analysis of Fuel Treatments: from the landscape to the national level Joint Fire Science Project (14-5-01-1) by Douglas B. Rideout (19657906)

“…Included for each study site are individual rasters representing the fire affected resources for that study site. …”

face recognation with Flask by Muammar, SST, M.Kom (21435692)

“…Built using the <b>Flask</b> web framework (Python), this system provides a lightweight and scalable solution for implementing facial recognition capabilities in real-time or on-demand through a browser interface.…”

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

“…</p><p dir="ltr">Implemented in Python (NumPy, Matplotlib, 3D visualization), the framework is fully annotated and reproducible. …”

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)

“…The full implementation is detailed in the accompanying Python script (Imputation_Air_Pollutants_NABEL.py). …”

End-to-end example-based sim-to-real RL policy transfer based on neural stylisation with application to robotic cutting by Jamie Hathaway (10285367)

“…</p><h3>policy/</h3><p dir="ltr">This folder contains pickled trajectories, in the form of a Python list.</p><p dir="ltr">The list's elements are TrajWithRew dataclass objects from the Imitation Python library (https://imitation.readthedocs.io/en/latest/)</p><p dir="ltr">TrajWithRew contains 4 main fields</p><ul><li> obs - the (unnormalised) observations, in the form of a [WINDOW_LENGTH * NUM_CHANNELS] array</li><li> acts - the actions in the form of a [WINDOW_LENGTH - 1 * NUM_ACTS] array</li><li> infos - the info values at each timestep, as a [WINDOW_LENGTH - 1] array of dicts</li><li> terminals - boolean indicating if that trajectory segment is a terminal segment</li><li> rews - the rewards as a [WINDOW_LENGTH - 1] array</li></ul><p dir="ltr">Each TrajWithRew represents not a full episodic trajectory, as is usually the case with Imitiation - rather they represent segments of a full episodic trajectory, of length WINDOW_LENGTH. …”

Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) by Amanda Bueno de Moraes (22559249)

“…<p dir="ltr">This deposit provides the Python notebook and the input dataset used in the study “Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil).” …”

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. …”

Hierarchical Deep Learning Framework for Automated Marine Vegetation and Fauna Analysis Using ROV Video Data by Bjørn Christian Weinbach (16918707)

“…</p><ol><li><b>MaskRCNN-Segmented Objects</b>:</li></ol><p dir="ltr"> - `.jpg` files representing segmented objects detected by the MaskRCNN model.…”

Supplementary Material for: The prediction of hematoma growth in acute intracerebral hemorrhage: from 2-dimensional shape to 3-dimensional morphology by figshare admin karger (2628495)

“…We subsequently constructed the 3-dimensional morphology models, including the probability of hematoma morphology (PHM) and the probability of comprehensive model (PCM), to predict HG. …”

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><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.…”

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

“…</p><p dir="ltr">MSc Personalised Medicine is a Master’s programme that can be taken in 1 year full-time or across 2 years part-time. Both full-time and part-time programmes have two intakes and can be started in September or January.…”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…Analysis of the confusion matrix revealed a critical limitation: although the model correctly identified 785 poisonous mushrooms, it misclassified 313 as edible (false negatives), which represents an unacceptable risk in a practical application.…”

Data Sheet 1_Nationwide epidemiological study of subarachnoid hemorrhage: trends in admissions, mortality, seasonality, costs, clipping, embolization, and the impact of COVID-19.pd... by Thiago Oscar Goulart (22485604)

“…</p>Methods<p>This retrospective study analyzed secondary data from the Brazilian public health system (DataSUS) using ICD-10 code I60 for aSAH. Key metrics included the evaluation of admissions with time-series in Python, and mortality rates, procedures, and costs.…”