Prediction accuracy on varying attack types. by Mohanad Faeq Ali (21354273)

“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”

<b> </b> Precision analysis. by Mohanad Faeq Ali (21354273)

“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”

Impact of cyberattack types on IoMT devices. by Mohanad Faeq Ali (21354273)

“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”

Predicting coding regions on unassembled reads, how hard can it be? - Genome Informatics 2024 by Amanda Clare (98717)

“…The locations and directions of the predictions on the reads are then combined with the information about locations and directions of the reads on the genome using Python code to produce detailed results regarding the correct, incorrect and alternative starts and stops with respect to the genome-level annotation.…”

Error reduction over time by the HOFA-SMC. by Asra Sarwat (22453794)

Code and data for evaluating oil spill amount from text-form incident information by Yiming Liu (18823387)

“…The code is written in Python and operated using Jupyter Lab and Anaconda. …”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”

Evaluation and Statistical Analysis Code for "Multi-Task Learning for Joint Fisheye Compression and Perception for Autonomous Driving" by Basem Ahmed (18127861)

“…</li></ul><p dir="ltr">These scripts are implemented in Python using the PyTorch framework and are provided to ensure the reproducibility of the experimental results presented in the manuscript.…”

Code for the HIVE Appendicitis prediction modelRepository with LLM_data_extractor_optuna for automated feature extraction by Anoeska Schipper (18513465)

“…</p><p dir="ltr"><b>LLM Data Extractor optuna repo</b> is a Python framework for generating and evaluating clinical text predictions using large language models (LLMs) like <code>qwen2.5</code>. …”

Workflow of a typical Epydemix run. by Nicolò Gozzi (8837522)

“…<div><p>We present Epydemix, an open-source Python package for the development and calibration of stochastic compartmental epidemic models. …”

Quetzal: Comprehensive Peptide Fragmentation Annotation and Visualization by Eric W. Deutsch (13887)

“…We describe how Quetzal annotates spectra using the new Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) mzPAF standard for fragment ion peak annotation, including the Python-based code, a web-service end point that provides annotation services, and a web-based application for annotating spectra and producing publication-quality figures. …”

Quetzal: Comprehensive Peptide Fragmentation Annotation and Visualization by Eric W. Deutsch (13887)

“…We describe how Quetzal annotates spectra using the new Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) mzPAF standard for fragment ion peak annotation, including the Python-based code, a web-service end point that provides annotation services, and a web-based application for annotating spectra and producing publication-quality figures. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…Concurrently, our ability to perform long-time scale molecular dynamics (MD) simulations on proteins and other materials has increased exponentially. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…Concurrently, our ability to perform long-time scale molecular dynamics (MD) simulations on proteins and other materials has increased exponentially. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…Concurrently, our ability to perform long-time scale molecular dynamics (MD) simulations on proteins and other materials has increased exponentially. …”

Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems by Lakshit Mathur (20894549)

“…The work advances national AI autonomy, real-time cognitive context modeling, and ethical human-AI integration.…”

Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection by Huichao Yin (14589020)

“…<p dir="ltr">Python image preprocessing and model implementation for research of "Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection".…”

Research Data and Code on Characteristics and Drivers of Plant Diversity in Viaduct Footprint Spaces of a Mountainous, High-Density City—A Case Study of Central Chongqing by Junjie Zhang (355622)

“…</li><li>Derived data including calculated plant diversity metrics and environmental factor data.</li><li>R and python code used for statistical analysis.</li></ul><p dir="ltr">Data collection was conducted through on-site field surveys in the central urban area of Chongqing, China, from April to October 2024.…”

Map of cumulative daily root-mean-square errors for each province in China in the test set. by Xiaoyi Wang (90589)