Table3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

“…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”

Table4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

“…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”

Table2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

“…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”

Image4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

“…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”

Models and Dataset by M RN (9866504)

“…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”

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). …”

Results of preliminary experiments. by Grzegorz Dudek (18239346)

Feature importance. by Grzegorz Dudek (18239346)

Comparison of ML model performances. by Grzegorz Dudek (18239346)

Hyperparameters of the ML models. by Grzegorz Dudek (18239346)

Confusion matrix for NB with features v1v3v4v5. by Grzegorz Dudek (18239346)

DT model. by Grzegorz Dudek (18239346)

Clinical characteristic of the studied group. by Grzegorz Dudek (18239346)

Seed mix selection model by Bethanne Bruninga-Socolar (10923639)

“…</p> <p>  </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”

Table_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.xlsx by Yao Gao (1420339)

“…Most of these models focus on the 2D/3D similarity of chemical structure of drug components and ignore the functional optimization space based on relationship between pathogenetic genes and drug targets. …”

Image_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.tif by Yao Gao (1420339)

“…Most of these models focus on the 2D/3D similarity of chemical structure of drug components and ignore the functional optimization space based on relationship between pathogenetic genes and drug targets. …”

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

“…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …”

Fitting single-cell data to the stochastic model. by Benjamin D. Maier (13994415)

Table_1_Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique.DOCX by Hasan Zulfiqar (12117255)

“…The obtained features were optimized by using correlation and the mRMR-based algorithm. …”