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. …”

Overview of generalized weighted averages. by Nobuhito Manome (8882084)

“…The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…”

Sonification of Warming Stripes by Christopher Harrison (9448751)

“…The sonification was produced using the STRAUSS sonification Python package.</p><p dir="ltr">Here we release:<br>1. …”

MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

“…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”

Physiotherapist-Assisted Wrist Movement Protocol for EEG-Based Corticokinematic Coherence Assessment by Fanni Kovács (21733838)

“…</li></ul><p dir="ltr"><b>Example (Python, using numpy):</b></p><pre><pre>import numpy as np, os<br><br>filename = "S113_ckc_bal_t1_01"<br><br># Read channel labels from .hed<br>channels = []<br>with open(filename + ".hed", "r") as f:<br> for line in f:<br> if line.startswith("Ch:"):<br> channels.append(line.split(":")[1].strip())<br>n_channels = len(channels)<br><br># Determine number of samples<br>filesize = os.path.getsize(filename + ".flo")<br>n_samples = filesize // (4 * n_channels)<br><br># Load EEG data<br>raweeg = np.fromfile(filename + ".flo", dtype="f4")<br>raweeg = raweeg.reshape(n_channels, n_samples)<br></pre></pre><h4><b>Notes</b></h4><ul><li>Data are organized by movement side (<code>bal</code> = left, <code>jobb</code> = right), trial (<code>t1</code>), and block repetition (01, 02).…”

Sonification of Growing Black Hole by Rose Shepherd (20328444)

“…We used the open source Python package STRAUSS to produce the sonification (Trayford and Harrison 2023). …”

Missing and Unaccounted-for People in Mexico (1960s–2025) by Montserrat Mora (20430644)

“…</li></ul><p dir="ltr"><b>Additional Materials:</b></p><ol><li><b>Python Script:</b> A Python script to generate customizable visualizations based on the dataset. …”

Thermally Activated Resonant Tunnelling in GaAs/AlGaAs Triple Barrier Heterostructures by Craig Allford (19079081)

“…Each file is named to represent the sample wafer under test, the pins used on a 20-way ceramic package into which the sample wafers were mounted and bonded, and the temperature at which the data was taken. …”

Attention and Cognitive Workload by Rui Varandas (11900993)

“…</p><p dir="ltr">The data for subject 2 do not include the 2nd part of the acquisition (python task) because the equipment stopped acquiring; subject 3 has the 1st (N-Back task and mental subtraction) and the 2nd part (python tutorial) together in the <code>First part</code> folder (file <code>D1_S3_PB_description.json</code> indicates the start and end of each task); subject 4 only has the mental subtraction task in the 1st part acquisition and in subject 8, the subtraction task data is included in the 2nd part acquisition, along with python task.…”

Related to Figs 1, 2 and S1. by Tyron Chang (9922533)

“…Sheet B, C, D, and E in S1 Table (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1012673#ppat.1012673.g002" target="_blank">Fig 2</a>): Log₂TPM (transcripts per million) RNA-Seq values and statistics for representatives from ISG subclasses ‐ 2 high, 2 low, and 5 variable ‐ across 578 human lung tissue samples (Sheet B in S1 Table), 226 human liver tissue samples (Sheet C in S1 Table), 241 human spleen tissue samples (Sheet D in S1 Table), and 755 human whole blood tissue samples (Sheet E in S1 Table). …”

Shadowed Realities: An Investigation of UI Attacks in WebXR - Research Artifacts by Chandrika Mukherjee (20576567)

“…These are implemented using Python. The entry point to the scripts is main_analysis.py. …”

Cognitive Fatigue by Rui Varandas (11900993)

“…In our analysis, the first baseline period, although not explicitly present in the dataset, was designated as representing no CF, whereas the final baseline period was designated as representing the presence of CF. …”

GameOfLife Prediction Dataset by David Towers (12857447)

“…</p><p dir="ltr">The data is stored in a channels-first format with a shape of (n, 1, 10, 10) where n is the number of samples in the corresponding set (50,000 for training, 10,000 for validation, and 10,000 for testing).…”

Metaverse Gait Authentication Dataset (MGAD) by sandeep ravikanti (20704127)

“…Data Structure & Format</b></h2><ul><li><b>File Format:</b> CSV</li><li><b>Number of Samples:</b> 5,000 users</li><li><b>Number of Features:</b> 16 gait-based features</li><li><b>Columns:</b> Each row represents a user with corresponding gait feature values</li><li><b>Size:</b> Approximately (mention size in MB/GB after upload)</li></ul><h2><b>3. …”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…Samplings were performed during solar midday and on clear sunny days. …”

<b>Code: Inferred movements of SARS-CoV-2 infections between the 25 administrative regions of Peru (Figure 3) + </b><b>International spread of four SARS-CoV-2 sub-lineages of Peruv... by Pablo Tsukayama (22614461)

“…</b> Movements of Lambda C.37, Gamma P.1.12, Omicron XBB.2.6, and Omicron DJ.1 lineages inferred from phylogeographic analysis. Arcs represent transitions between countries of sample collection, projected in Plate Carrée at a scale of 1000 km. …”

Code and parameter package for long-term mapping and object-based typing of freeze–thaw colluvial deposits (1990–2024) along the Yunnan–Tibet corridor by Hui Ye (22308559)

“…Tested with Python 3.x/ArcGIS Pro (ArcPy) and the GEE Code Editor. …”

Data Sheet 1_Feasibility of predicting next-day fatigue levels using heart rate variability and activity-sleep metrics in people with post-COVID fatigue.csv by Nana Yaw Aboagye (22637360)

“…Background<p>Post-COVID fatigue (pCF) represents a significant burden for many individuals following SARS-CoV-2 infection. …”

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

“…The analysis was conducted in a Jupyter Notebook environment, using Python and libraries such as Scikit-learn and Pandas. …”