Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization by Sandeep Jagonda Patil (22048337)

Classification performance after optimization. by Amal H. Alharbi (21755906)

ANOVA test for optimization results. by Amal H. Alharbi (21755906)

Wilcoxon test results for optimization. by Amal H. Alharbi (21755906)

Supplementary file 1_Encodings of the weighted MAX k-CUT problem on qubit systems.pdf by Franz G. Fuchs (22776248)

“…This study explores encoding methods for MAX k-CUT on qubit systems by utilizing quantum approximate optimization algorithms (QAOA) and addressing the challenge of encoding integer values on quantum devices with binary variables. …”

Pressure-Stabilized Zinc Trifluoride by Shiyin Ma (5793191)

Wilcoxon test results for feature selection. by Amal H. Alharbi (21755906)

Feature selection metrics and their definitions. by Amal H. Alharbi (21755906)

Statistical summary of all models. by Amal H. Alharbi (21755906)

Feature selection results. by Amal H. Alharbi (21755906)

ANOVA test for feature selection. by Amal H. Alharbi (21755906)

Classification performance of ML and DL models. by Amal H. Alharbi (21755906)

Input features. by Nicola Lazzarini (3528197)

Baseline characteristics of patients in the study cohort. by Nicola Lazzarini (3528197)

Robustness of the optimization process in a real dataset. by Neta Ravid Tannenbaum (2940351)

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). …”

Image1_RobustTree: An adaptive, robust PCA algorithm for embedded tree structure recovery from single-cell sequencing data.pdf by Ziwei Chen (626412)

<b>Road intersections Data with branch information extracted from OSM</b> & <b>C</b><b>odes to implement the extraction </b>&<b> I</b><b>nstructions on how to </b><b>reproduce each... by Zihao Tang (19794537)

“…</p><h2><b>3. Instructions for codes</b></h2><p dir="ltr">This code repository is organized into eight folders and two files:</p><h3>(1) Folder: <b>candidateIdentify</b></h3><p dir="ltr">This folder contains code related to the identification of candidate junctions or intersections from the input data. …”

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”