S1 Data - by Haoqiang Liu (193675)

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

Pseudo Code of RBMO. by Chenyi Zhu (9383370)

Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regio... by Michael D. Cobler-Lichter (22492930)

Table_1_Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning.DOCX by Maruf A. Tamal (18947776)

Table_2_Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning.DOCX by Maruf A. Tamal (18947776)

Using BART to Perform Pareto Optimization and Quantify its Uncertainties by Akira Horiguchi (11768593)

“…The performance of our BART-based method is compared to a GP-based method using analytic test functions, demonstrating convincing advantages. Finally, our BART-based methodology is applied to a motivating engineering problem. …”

Surround Suppression mechanism. by Elnaz Nemati (21402730)

Outputs of T-test and proposed distance metrics. by Sukhvinder Kaur (20297968)

Outputs of BIC and KLD distance metrics. by Sukhvinder Kaur (20297968)

Proposed diagram of speaker segmentation system. by Sukhvinder Kaur (20297968)

Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by 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). …”

Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

Data Sheet 2_Early stroke detection through machine learning in the prehospital setting.pdf by María Ríos Delgado (22004942)

Data Sheet 1_Early stroke detection through machine learning in the prehospital setting.pdf by María Ríos Delgado (22004942)

Table 1_Early stroke detection through machine learning in the prehospital setting.xlsx by María Ríos Delgado (22004942)

Fortran & C++: design fractal-type optical diffractive element by I-Lin Ho (13768960)

“…</p> <p>(4) export geometry/optics raw data and figures for binary DOE devices.</p> <p><br></p> <p>[Wolfram Mathematica code "square_triangle_DOE.nb"]:</p> <p>read the optimized binary DOE document (after Fortran & C++ code) to calculate its diffractive fields for comparison.…”