Code used to run simulations and generate figures. حسب Guillaume Mestdagh (22656397)

"…<p>The archive contains the Python code to reproduce simulations presented in this paper. …"

py-rocket: A Docker image to promote cross-language (Python, R) collaboration across diverse user platforms for cloud computing in the earth sciences حسب Eli Holmes (20363193)

"…</p><p><br></p><p dir="ltr">A sturdy Docker stack relies on a solid base image. Here we present work on the py-rocket base image and illustrate how this enhances collaboration while providing familiar IDEs and environments to both R and Python users. …"

Designing an online Introduction to Programming w/GenAI (EDUC90970_2025_S2) حسب Jean Lee (20590241)

Code and data for reproducing the results in the original paper of DML-Geo حسب Pengfei CHEN (8059976)

"…<p dir="ltr">This asset provides all the code and data for reproducing the results (figures and statistics) in the original paper of DML-Geo</p><h2>Main Files:</h2><p dir="ltr"><b>main.ipynb</b>: the main notebook to generate all the figures and data presented in the paper</p><p dir="ltr"><b>data_generator.py</b>: used for generating synthetic datasets to validate the performance of different models</p><p dir="ltr"><b>dml_models.py</b>: Contains implementations of different Double Machine Learning variants used in this study.…"

PTPC-UHT bounce حسب David Parry (22169299)

"…<br>It contains the full Python implementation of the PTPC bounce model (<code>PTPC_UHT_bounce.py</code>) and representative outputs used to generate the figures in the paper. …"

Data for "A hollow fiber membrane permeance evaluation device demonstrating outside-in and inside-out performance differences" حسب Timothy Warner (20222838)

"…</li><li>Plot data derived from the above data sources.</li><li>Python code to generate figures from the plot data.…"

Data files accompanying our PLoS One publication حسب Peter Hinow (21810605)

Overview of deep learning terminology. حسب Aaron E. Maxwell (8840882)

"…Training loops are implemented with the luz package. The geodl package provides utility functions for creating raster masks or labels from vector-based geospatial data and image chips and associated masks from larger files and extents. …"

Efficient, Hierarchical, and Object-Oriented Electronic Structure Interfaces for Direct Nonadiabatic Dynamics Simulations حسب Sascha Mausenberger (22225772)

"…We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. …"

Graphical abstract of HCAP. حسب 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. …"

Recall analysis. حسب 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. …"

Convergence rate analysis. حسب 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. …"

Computational efficiency. حسب 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. …"

Analysis of IoMT data sources. حسب 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. …"

Prediction accuracy on varying attack types. حسب 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. حسب 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. حسب 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 حسب 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. حسب Asra Sarwat (22453794)

Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan) حسب Winston Yap (13771969)

"…<p dir="ltr">Supporting files to implement GNN training for Melbourne, Singapore, Washington DC, and NYC-Manhattan. …"