Algoritmo de detección de odio en español (Algorithm for detection of hate speech in Spanish) by Elias Said-Hung (10790310)

“…</li></ul><h2>Training Process</h2><h3>Pre-workout</h3><ul><li>Batch size: 16</li><li>Epochs: 5</li><li>Learning rate: 2e-5 with 10% warmup steps</li><li>Early stopping with patience=2</li></ul><h3>Fine-tuning</h3><ul><li>Batch size: 128</li><li>Epochs: 5</li><li>Learning rate: 2e-5 with 10% warmup steps</li><li>Early stopping with patience=2</li><li>Custom metrics:</li><li>Recall for non-hate class</li><li>Precision for hate class</li><li>F1-score (weighted)</li><li>AUC-PR</li><li>Recall at precision=0.9 (non-hate)</li><li>Precision at recall=0.9 (hate)</li></ul><h2>Evaluation Metrics</h2><p dir="ltr">The model is evaluated using:</p><ul><li>Macro recall, precision, and F1-score</li><li>One-vs-Rest AUC</li><li>Accuracy</li><li>Metrics by class</li><li>Confusion matrix</li></ul><h2>Requirements</h2><p dir="ltr">The following Python packages are required (see requirements.txt for the full list):</p><ul><li>TensorFlow</li><li>Transformers</li><li>scikit-learn</li><li>pandas</li><li>datasets</li><li>matplotlib</li><li>seaborn</li></ul><h2>Usage</h2><p dir="ltr">The model expects input data with the following specifications:</p><ol><li><b>Data Format</b>:</li></ol><ul><li>CSV file or Pandas DataFrame</li><li>Mandatory column name: <code>text</code> (type string)</li><li>Optional column name: <code>label</code> (type integer, 0 or 1) if available for evaluation</li></ul><ol><li><b>Text Preprocessing</b>:</li></ol><ul><li>Text will be automatically converted to lowercase during processing</li><li>Maximum length: 128 tokens (longer texts will be truncated)</li><li>Special characters, URLs, and emojis must remain in the text (the tokenizer handles these)</li></ul><ol><li><b>Label Encoding</b>:</li></ol><ul><li><code>0</code> = No hateful content (including neutral/positive content)</li><li>1 = Hate speech</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). …”

<b>DDS3 - Dataset of mosaic sputum smear microscopy images for evaluation of bacillus detection algorithms</b> by Marly G F Costa (19812192)

“…<p dir="ltr"><b>DDS3 - Dataset of mosaic sputum smear microscopy images for evaluation of bacillus detection algorithms</b></p><p dir="ltr">This data set corresponds to mosaic images that are composed of a 10x10 arrangement of patches (negatives and positives) from the DDS1 dataset, resulting in a 400x400 pixel image. …”

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). …”

Model & data for automated classification of male and female house wren song by Karan Odom (18271399)

Supplementary Material 8 by Nishitha R Kumar (19750617)

Flow diagram of the automatic animal detection and background reconstruction. by David Tadres (9120564)

“…If the identical blob that was detected in panel J (bottom) is found in any of the new subtracted binary images (cyan arrow), the animal is considered as having left its original position, and the algorithm continues. …”

WEISS Catheter Segmentation in Fluoroscopy Dataset by Evangelos Mazomenos (6761597)

Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

“…The QC pipeline included: 1) quality check of the raw sequencing data using FastQC (v 0.11.9) and MultiQC (v 1.9); 2) mapping the sequencing reads to the human genome (build 102) using HISAT2 (v 2.2.1), followed by SAMtools (v 1.12) to convert BAM (Binary Alignment Map) into SAM (Sequence Alignment Map) files; 3) assembly of RNA-seq reads into transcripts using StringTie (v 2.1.4); and 4) calculation of expression levels from read counts, producing a gene count matrix. …”

Behavioral and Eye-tracking Data for Adaptive Circuit Dynamics Across Human Cortex During Evidence Accumulation in Changing Environments by Peter Murphy (10141523)

“…The main variable in each file is a matrix called <i>Behav</i> for which each row is a trial and columns are the following:</p> <p>column 1 – the generative distribution used to draw the final sample location on each trial (and thus, the correct response)</p> <p>column 2 – the response given by the participant</p> <p>column 3 – the accuracy of the participant’s response</p> <p>column 4 – response time relative to Go cue</p> <p>column 5 – trial onset according to psychtoolbox clock</p> <p>column 6 – number of times participant broke fixation during trial, according to online detection algorithm</p> <p>Each .mat file also contains a trials*samples matrix (<i>tRefresh</i>) of the timings of monitor flips corresponding to the onsets of each sample (and made relative to trial onset), as provided by psychtoolbox.…”

HPDmobile H5 Image Zone Labels by Soumik Sarkar (2039536)

“…Contains files for each hub and day with binary zone based occupancy, indicating if a human is present in the image (1) or not (0). …”

HPDmobile H2 Image Zone Labels by Soumik Sarkar (2039536)

“…Contains files for each hub and day with binary zone based occupancy, indicating if a human is present in the image (1) or not (0). …”

HPDmobile H6 Image Zone Labels by Soumik Sarkar (2039536)

“…Contains files for each hub and day with binary zone based occupancy, indicating if a human is present in the image (1) or not (0). …”

HPDmobile H4 Image Zone Labels by Soumik Sarkar (2039536)

“…Contains files for each hub and day with binary zone based occupancy, indicating if a human is present in the image (1) or not (0). …”

HPDmobile H1 Image Zone Labels by Soumik Sarkar (2039536)

“…Contains files for each hub and day with binary zone based occupancy, indicating if a human is present in the image (1) or not (0). …”

HPDmobile H3 Image Zone Labels by Soumik Sarkar (2039536)

“…Contains files for each hub and day with binary zone based occupancy, indicating if a human is present in the image (1) or not (0). …”

Dataset for C57BL/6 mice related to "Rapid decay in fast delta following prolonged wakefulness marks a phase of wake-inertia in NREM sleep" by Jeffrey Hubbard (8782154)

“…Matlab scripts to read both file formats, a data descriptor of the programs included, as well as an algorithm for detecting slow-waves, is included. …”

Chákṣu IMAGE: A glaucoma-specific fundus image database by Harish Kumar J R (12958519)

“…The folder 5.0_OD_OC_Mean_Median_Majority_STAPLE in the Train/Test set contains the overlay, mean, median, majority, and STAPLE algorithm based gold standard binary images obtained from the binary images of doctors annotations. …”