A* Path-Finding Algorithm to Determine Cell Connections حسب Max Weng (22327159)

"…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …"

Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

"…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"

Hybrid Computational Framework for Fault Detection in Coil Winding Manufacturing Process Using Knowledge Distillation حسب Izhar Escudero Ornelas (7442897)

"…</p> <p><br></p> <p>The conventional End of the Line (EoL) tests are insufficient in detecting faults during process resulting in increased manufacturing costs and lead times. …"

Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) حسب Daniel Pérez Palau (11097348)

"…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …"

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 حسب Andrew Rogers (17623239)

"…</li></ul><h3>Analysis Scripts</h3><p dir="ltr">Complete set of R scripts for reproducing all analyses:</p><ul><li><b>percent cost increase_line plot.R</b>: Creates visualizations of energy cost impacts under different conservation scenarios</li><li><b>Zonation curves.R</b>: Generates conservation performance curves and coverage statistics</li><li><b>NPV_bar_plot.R</b>: Produces economic analysis plots with Net Present Value breakdowns</li><li><b>domestic_export_map_iterations.R</b>: Creates spatial maps of renewable energy infrastructure for domestic and export scenarios</li></ul><h2>Technical Specifications</h2><h3>Data Formats</h3><ul><li><b>Spatial Data</b>: ESRI Geodatabase (.gdb), Shapefile (.shp), GeoTIFF (.tif)</li><li><b>Tabular Data</b>: CSV, Microsoft Excel (.xlsx, .xls)</li><li><b>Analysis Code</b>: R scripts (.R)</li></ul><h3>Software Requirements</h3><ul><li><b>R</b> (≥4.0.0) with packages: sf, dplyr, ggplot2, readr, readxl, tidyr, furrr, ozmaps, ggpattern</li><li><b>ESRI ArcGIS</b> or <b>QGIS</b> for geodatabase access and spatial analysis</li><li><b>Zonation</b> conservation planning software (for methodology understanding)</li></ul><h3>Hardware Recommendations</h3><ul><li><b>RAM</b>: 16GB minimum (32GB recommended for full spatial analysis)</li><li><b>Storage</b>: 15GB free space for data extraction and processing</li><li><b>CPU</b>: Multi-core processor recommended for parallel processing scripts</li></ul><h2>Detailed Description of the VRE Siting and Cost-Minimization Model</h2><p><br></p><p dir="ltr">This section provides an in-depth description of the Variable Renewable Energy (VRE) siting model, including the software, the core algorithm, and the optimisation process used to determine the least-cost, spatially constrained development trajectory for VRE infrastructure in Queensland, Australia.…"