RNA Velocity model simulation results. (A) Simulation results for RNA Velocity model without delay ( samples). The simulation is composed of an up-regulation phase (both production... حسب Ziyan Jin (21021976)

الموضوعات:

Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... حسب Ziyan Jin (21021976)

الموضوعات:

System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool حسب Pavel Izosimov (20096259)

"…</li><li><b>Technical Support and Troubleshooting</b>: Support teams can quickly identify devices during support requests, track support history, and automate support processes using the HWID, improving response times and customer satisfaction.</li></ul><h2>Integration with Other Tools</h2><p dir="ltr">The System Hardware ID Generator Script is part of the broader suite of tools offered by the <a href="https://xn--mxac.net/" target="_blank">Alpha Beta Network</a>, dedicated to enhancing security and performance in <a href="https://xn--mxac.net/" target="_blank">Python programming</a>.…"

Online Resource 3: Word Cloud Dataset and Code حسب Jessica Zylla (17692920)

"…This set of files are part of Online Resource 3, which allows readers to implement a Jupyter Notebook Python program to create a word cloud based on survey responses. …"

This package of Python scripts implements the proposed unsupervised sentiment analysis approach.... حسب Xiaohan Yu (7525940)

"…<p>This package of Python scripts implements the proposed unsupervised sentiment analysis approach. …"

Tracking module training details. حسب Khelina Fedorchuk (19130089)

Segmentation module training details. حسب Khelina Fedorchuk (19130089)

Five Operator Lattice Simulation حسب James McDaniel (22522571)

"…</p><p dir="ltr">Running the included file <code>five_operator_lattice_sim.py</code> (Python 3.14 + NumPy 2.1) reproduces the dynamic interactions and figures reported in Appendix A of the paper, generating time-series data that demonstrate operator balance, instability, and renewal cycles.…"

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 حسب Jordan Waters (21620558)

"…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …"

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. …"

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

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

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

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

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